Girl Geek X Clover Lighting Talks & Panel (Video + Transcript)

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Mary Uslander, Ellen Linardi, Rachel Ramsay, Meghana Randad and Bao Chau Nguyen speaking

Clover girl geeks: Mary Uslander, Ellen Linardi, Rachel Ramsay, Meghana Randad and Bao Chau Nguyen speak on a panel at Clover Girl Geek Dinner in Sunnyvale, California.   Erica Kawamoto Hsu / Girl Geek X

Transcript of Clover Girl Geek Dinner – Lightning Talks & Panel:

Gretchen DeKnikker: Hi, I’m Gretchen, I’m with Girl Geek X. Welcome. How many of you guys, this is your first event? Oh wow, that’s so many. We’ve been doing these for about 11 years. We’ve done over 200 of them. We do them almost every week, up and down the peninsula, so hopefully you should be on our … That’s all right, I can definitely talk over that. We do them every week and you should come because you get to see amazing women, you get to meet amazing women, and you get to feel inspired so that you can go back and fight the good fight every single day, right? Yes.

Gretchen DeKnikker: We do a podcast also, if you want to check it out. We take like little clips from these events, and then we chitchat around them. So, there’s like finding a mentor, and what’s the right way to use the word intersectionality, and all sorts of really important life skill things. Definitely find it, rate it, keep it, and tell us if it’s any good, because we’ve never done a podcast before so we’re still figuring it out. Then finally, we just launched a store on Zazzle with all of our cute little Pixie things. You guys haven’t seen a lot of them because they weren’t on the branding for this, but it’s super cute.

Gretchen DeKnikker: Can I borrow you because I love your hair? Can you hold this for a second? I love her. We have this cute fanny packs and a little bag that you could put cosmetics, but you could also put Sharpies or something less female in, and water bottles. All sorts of stuff, and they have our little Pixie characters, they say, “Lift as you climb.” That’s it, we’re good. That’s all the things that are in my bag. You were an awesome assistant, everyone give her a hand.

Gretchen DeKnikker: This space is awesome. I’m so excited for the content because everything that we’ve experienced thus far has been really amazing, right? Yes, you ate, you had your… They’re not quite awake yet, but we’re going to get them there. I am not a good warm up for this, apparently. Without further ado, please welcome Jennifer Oswald from Clover, who’s the head of People Operations.

Jennifer Oswald

Head of People Jennifer Oswald welcomes the sold-out crowd at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Jennifer Oswald: Hi, everyone, I’m going to try and navigate a lot of different technology while I’m up here. I’m Jen Oswald, and it’s my pleasure to have you all here to kick off our collaboration with Girl Geek X. This is an event on unconscious bias. I’d like to thank you for attending and I can’t wait to hear what takeaways you have from this event. We know that events like these can impact your lives and have a lasting effect on not only your professional life, but also your personal life.

Jennifer Oswald: Our agenda this evening is as follows. First, me, I’m your introduction and welcome. Then we’re going to look at what we do. We’re proud to showcase a bit on what we do here at Clover. You’ll also be meeting our CEO, who will talk you through that. We’ll have lightning talks as well that will show you a little bit more about our product. Next we’ll be featuring our panel discussion on unconscious bias, and then lastly, we want to make sure you still have time to network, and don’t forget your swag.

Jennifer Oswald: Maybe a silly question, but who is confused by me being up here today introducing unconscious bias? You don’t have to raise your hand, you can just think it if you want. Would it surprise you to know that I grew up identifying as two races, Native American and Caucasian? That was before a DNA test. More to come about that later. When biases come to mind, what did you think when you saw my picture before this event? What did you think when I came up here? That is unconscious bias, it’s bias happening in our brains making incredibly quick judgments and assessments of people and situations without us even realizing.

Jennifer Oswald: They can be influenced by our background, our cultural environment and personal experiences, and resolving feelings and attitudes towards others based on race, ethnicity, age, appearance, accent, et cetera. Also termed as implicit social cognition, this includes both favorable and unfavorable responses and assessments activated without an individual’s awareness, or intentional control.

Jennifer Oswald: How did I get here? That’s little baby Jen and that’s my mom. As you can probably see, she was a very, very young mom. She had me at a young age, she worked the night shift and we lived in the projects aka, subsidized housing. That’s a picture of Iowa City, Iowa. We were on food stamps and we struggled to get by. Even at a young age, I knew what it was like to struggle. Then the classic story, mom meets dad, he adopted me at about age six and life was a little more middle class and a little more in the middle of nowhere.

Jennifer Oswald: I grew up in Palmer, Iowa. This is a picture of our downtown. That is the one gas station, right next to it was the grocery store/where everybody went to have coffee in the morning. I was in a town of 256 people, so how diverse do you think that was? Here I am, I’m the only adopted person in the whole town, mixed, left-handed, and female. How many do you think were college grads? I was supposed to get married, raise three to five kids, maybe have a job after I took care of the kids and at the very least, I should be a great cook and make sure that everyone is well fed. So, what do I have? I have a college degree, an almost masters, zero kids except for my fur babies, zero husband, and I just moved from the Silicon Hills, Austin, Texas, to Silicon Valley.

Jennifer Oswald: My unconscious biases tell me that men should have a career, women should stay home and raise a family. Being adopted means you don’t really have a family like others. Men should make the money, women should tend to the family. Once poor, always poor. You should write with your right hand because everyone else does. Men are better at math and science. Yet here we are at a tech company with a panel of amazing females to tell you about their experiences and biases they’ve encountered, and how they proved many of my own unconscious biases wrong.

Jennifer Oswald: We all have unconscious biases. It comes from our culture, it comes from our families, it comes from our family’s families, yet once recognized, we can overcome them. So here I am, a place I shouldn’t even tried to get to, kicking off an event for an amazing company that says FU bias, and we’re working to overcome and support diversity and inclusion. No matter what the package looks like on the outside. We hire the book, not the cover. On that note, I want to introduce the person responsible for creating such a great place for like-minded people to come together. In fact, in 2019 he was nominated for two awards, Best CEO for Women, and Best CEO for Diversity, and we just think he’s the best. I’d like to welcome John Beatty, our Clover CEO.

John Beatty speaking at Clover Girl Geek Dinner

CEO John Beatty talks about the change that needs to happen in the world at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

John Beatty: Thanks, Jen. Welcome everyone to Girl Geek X. You know, I get the opportunity, of course I have to promote my own company. There could be no better promotion of Clover than what you just saw with Jen. She’s our new Head of People, and I think she’s absolutely amazing. Really excited to grow our people function here, so thank you very much, Jen.

John Beatty: First I’m going to just tell you a little bit about what we do here. You’ve probably encountered a device that looks very much like this. We are all across America, we’re also in a number of other countries. Thank you. We build absolutely beautiful cloud based point of sale hardware and software and systems. I’ll tell you the reason why we did this, this is going back, we started Clover about eight years ago. What we saw was a bunch of really ugly, really insecure, really closed systems and there was … on the counter at all these restaurants and retailers and services companies. We were trying to bring some innovations into that market and just ran into a bunch of brick walls.

John Beatty: We started talking to business owners and we realized they absolutely hate their systems, they keep having data breaches, the systems really don’t help them run or grow their businesses very efficiently. We thought that was a very interesting problem to solve. We love small businesses and recognize that a lot of small business owners are just trying to do what they love and they need technology to support them. We have many, many … We’ve manufactured over 1 million devices. The US is our largest market, so you have almost certainly encountered one of our devices.

John Beatty: On the consumer side, we have a very engaging consumer experience. First, the consumer journey starts off typically signing up for a loyalty program. You’ve probably seen one of these as well, you just type in your phone number and then we extend that consumer journey–if we could could go to the next slide, all all the way to the mobile phone. We have a very highly rated mobile app as well. It starts off with loyalty, but of course we also have Bluetooth beacon enabled payments. You can walk into a store, you don’t even take it out of your pocket. They know you’re there, they know what you like. You don’t even have to pay. You just say, “I’d like to pay with Clover,” and you walk out. It’s a very magical experience.

John Beatty: On the other side of the counter, they have a Clover device. Your profile picture will show up there, a little bit about your history, how often you’ve been there and what you like. We’re really building an absolutely fantastic end-to-end experience both for the merchant and the consumer.

John Beatty: Now, we also have an app marketplace that helps businesses run and grow their businesses. We take a lot of the … We make a lot of the mundane, very simple. We have a number of partners in categories like payroll. If you want to make your life very easy as a business owner and get all the employee information and get it into your payroll system, we make that very seamless. We work with best-of-breed other companies and we partner with many of them here in the market.

John Beatty: That is enough about Clover. I know I get a few minutes here of corporate shilling, so thanks for bearing with me. First, I want to talk a little bit about, what does it take to win one of these awards? Let me just tell you, when I first saw the news that I’d won these awards, I had two thoughts. The first is, “Well, that’s really cool. I’m very proud of that.” Then the second is like, “How did that happen?” To be completely honest. So first, to talk just a little bit about the pride that I felt. These middle meant a lot to me, both personally and professionally.

John Beatty: Personally, I have a–I have a wife. My wife is right here in the front row. She’s a scientist who’s now in business development. Very accomplished in her field. I also have a six year old daughter, and I also have two boys, four and two. I’m not going to go into any details. Let’s say, my wife has run into some professional situations that are absolutely outrageously unacceptable. I think the world has made a tremendous amount of progress in being more fair and just over the last 50 years, but there’s a lot of work left to do. And with all of my kids, both my girl and my boys, I’m very … When they grow up and they see that I’ve done things like this, I’m very proud that I can say I helped make the world more fair and just. That means a lot to me personally.

John Beatty: I asked the question, what does it take to win one of those awards? Honestly the answer is, not enough. The bar is actually just too low. I will say we try very hard at Clover on diversity and inclusion, but we are a small company. Just a short number of years ago, we were a very small startup just trying to survive. Most of your thoughts on, how do I not die, not, how do I create the world’s best culture?

John Beatty: Now that we’ve grown up a little bit, now we are very focused on building out those programs. We’re out of the almost dying category and into the very successful category. I’m very proud that we’re doing events like this tonight. But, this is very recent for us to actually build these institutions. We have a Women in Tech Group here at Clover, and that’s a very grassroots effort. It’s building and it’s building, and we’re really getting a lot of great programs here.

John Beatty: I could win this award with honestly not doing that much proactively, just avoiding the unforced errors and making sure we squash any bad behavior that we see, it means the bar’s probably too low. That’s the Clover story. If you could just jump of course, I’m going to show one more time. We have recruiters standing by. Alicia, John, they are waving at you right there. They would love to talk to you and of course, Clover.com/careers.

John Beatty: I’m going to introduce Rachel. Rachel, why don’t you come on up? Rachel is on our software engineering team on our Payment Terminal API and she will tell you a little bit more about what she does in a lightning talk.

Rachel Antion speaking

Software Engineer Rachel Antion gives a talk on semi-integrations and how it fits into the business at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X  

Rachel Antion: Hi, my name is Rachel Antion and I’m a software engineer here at Clover on the semi-integrations team, which is our internal name for the Payment Terminal API so if I use them interchangeably, that’s why. Overall, we make about 2 billion card transactions every year, which amounts to be about $100 billion on over 1 million devices sold in seven countries, and we are approaching 5% of Visa and MasterCard volume worldwide, which I think is pretty impressive considering we’re only in seven countries right now. Of that, 2.5% of those transactions are processed via the Payment Terminal API, which might not sound like a lot until you think that it’s about $2.5 billion, and it’s growing every year.

Rachel Antion: Can you click it? Some of those transactions are coming from integrators that you probably recognize like Amazon, the Las Vegas Convention Center, the stadiums of the Philadelphia Eagles, the Seattle Seahawks, and the New York Mets. All of these integrators created their own solution customized to their individual business needs. Here is a specific example of a solution built with the Payments Terminal API. This is a beautiful point of sale created by Hy-Vee that’s totally customized to their individual business needs. But in order to appreciate just how awesome this is, you might need to know a little bit more about the Payment Terminal API, where it came from, and how it works.

Rachel Antion: People have been taking payments for pretty much as long as people have been around and as we progress, the way that we take payments also has to progress. When credit cards were first introduced, there was not a lot of security, but as the age of the internet progressed, so did the need for that security. Older point of sales basically consisted of some kind of UI attached to a magstripe reader that would send unencrypted data to the point of sale, which might make all of you uncomfortable because it led to things like the data breaches that started in 2010.

Rachel Antion: Clover knew that there had to be a better way to take secured payments without making companies throw away all the hard work they put into developing their point of sale systems. That solution was the Payments Terminal API, which allows you to use a Clover device as an external payment device. Your point of sale gets a Clover payments API, and Clover provides the PCI compliance. Basically, you make the point of sale and Clover takes care of the rest. All the point of sale needs to worry about is creating the order and making sure the right amount gets sent to the Clover device.

Rachel Antion: We have two different flavors, if you will, of the Payments Terminal API. We have Native or takeover that lets you create your own app that runs directly on the Clover device, and we have Remote that lets you run it on pretty much any device. We have SDKs and Android, iOS, Windows, and JavaScript so the possibilities are pretty endless. That beautiful point of sale I showed you earlier is actually an example of a takeover model. You can see it here running on our Clover station.

Rachel Antion: Who exactly is the Payment Terminal API for? Its for someone who has an existing point of sale. Maybe everybody’s already trained, they know how to use it and it works just fine, but they want to use a Clover device to take payments because it’s faster. It’s someone with a specific business case, a hotel, a restaurant, a mom and pop shop. They’re all going to have different payment needs and it makes sense that they might want different apps. It’s for someone who wants more control over the process. It’s possible that you need different payment flows, even within the same business.

Rachel Antion: For example, at salon, how you pay for a service and just a product might be different. You probably don’t need a tip and signature if you’re just buying a bottle of shampoo, but you do when you’re buying your snazzy new haircut. Or, it’s someone who just wants to build their own app. If you think this might be you or you have any other questions, I’d be happy to chat with you after. I’m going to turn this over to Wako who’s going to talk to you about empathy here at Clover.

Wako Takayama speaking

User Research Lead Wako Takayama gives a talk on fostering customer empathy at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Wako Takayama: Hi everyone, my name is Wako Takayama and I lead the user research group here at Clover. John and Rachel introduced you to our product and the technology, so I am going to focus on the people who use our products and services here. Business owners like Thomas, who runs Poorboy’s Cajun Kitchen, which is just a few miles from here. You may have been there, very good food. And, Olivia from Theory Salon, which is in Woodstock, Georgia.

Wako Takayama: As with a lot of companies, we at Clover, we face the challenge that we build products for people who do jobs that we don’t do. These small business owners like Thomas and Olivia, they have a lot of things on their plate, they’re juggling a lot of things. They make all the decisions about their business, where are they going to open their store? What’s their product? What’s the price they’re going to sell things at? They have to hire, they have to fire.

Wako Takayama: Here we have one of our local businessmen. He needs to set up his own Clover system. He takes orders, he delivers food, he’s checking inventory, and then he has to call the vendor to make sure that he has stuff to sell, so a lot of stuff. This is just what we call front of house. Then there’s back of house. It’s all the office management stuff, lots of stuff that these business owners have to do.

Wako Takayama: For us to do our jobs as designers, engineers, marketers, we really need to know a lot about what these people do. We need to know that because that’s what we base our work on, the building, the designing that we do. The user research team, my colleagues and I, we help by doing formal research studies and, we work on fostering company empathy across the whole company.

Wako Takayama: But first, what is empathy? I’m going to read this to you, the ability to step into the shoes of another person aiming to understand their feelings and perspectives, and to use that understanding to guide our actions. The key here is that empathy allows us to get beyond our biases. One way we’re doing this, I’ll tell you quickly, is that we foster empathy at Clover starting on day one at the company. If you were to join Clover, you’d join the Merchant Empathy Program. This is a way to step into the shoes of a new Clover merchant. During the first week, you would work with your fellow new hires to dream up a business, set up a Clover system. You can see one of our designers really went over the top and he created this beautiful menu, and then take orders and payments.

Wako Takayama: I’m a researcher, so of course I send out surveys after things. I found out that this program has had a really great impact. One engineer said, “There were a couple of issues I worked on as I joined the team and due to my knowledge of the system from the session I was able to figure out a couple of issues easily.” That’s fantastic, right? Another engineer said, “It has helped me feel more connected to the customer and the company, and has helped me feel a little closer to the customer.” That’s really the key. We want to all feel closer to the customer, that we understand them, that we are serving them.

Wako Takayama: Imagine what stepping into the shoes of the user of your product or service could look like. How can you foster empathy for the person who’s using the product that you’re working so hard to build? If you’d like to brainstorm with … If you’d like me to brainstorm with you about some ideas, I’d be happy to do that, just come find me afterward. And, if you haven’t already had a chance to touch and step into the shoes of our Clover merchants, you can do that over there to get your schwag, and also just to play around with our product. Thank you.

Wako Takayama: Now I’d like to introduce Kejun Xu.

Kejun Xu speaking

Product Design Manager Kejun Xu gives a talk on thinking like a designer at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Kejun Xu: Thank you, Wako. Let me see if I can make this magical work somehow. Let me give it a try. Nope, doesn’t like me. All right, hi, everyone. My name is Kejun Xu. I’m a Product Design Manager here in Clover. I want to talk about how we design at Clover today, and you don’t have to be a designer to think design. You may ask, well … Next please. What is design thinking?

Kejun Xu: Actually, first of all, let me start with some numbers. It’s quite interesting. A few years ago, a team of researchers looked at how design impacted the organizations across S&P 500 companies. What they found was that of the top 20 companies, including Apple and Coca-Cola, who made it to the list, who are considered as design-centric, their stocks performed 211% over S&P 500 Index. This is compelling data.

Kejun Xu: You may ask, well, what is design thinking? Fortunately, we didn’t invent the term. You can search tons of information and technology out there. But basically, it’s a framework to foster innovation and collaboration. It starts from empathizing with your target audiences all the way to testing and evaluation. Wako talked a lot about merchant empathy. A lot of us joined at Clover without any knowledge about restaurant or SMBs, including myself, so we would go out for day trips and we’d go talk to the restaurant owners and managers. We’ll learn about their lives and their challenges. We also would go and shadow them and see how they would ring up an order on the Clover station, or how they would take payments …

Kejun Xu: Oh, it works? Can I have it? I’ll try it. This was a trip that my product manager, my researcher, and I went out and shadowed the merchants and see how they would take payments at the table. Still doesn’t like me. Sometimes when things are disconnected, we’ll go out and talk to them and see how much the pain point was. There are also other insights and data that we just couldn’t get by sitting here at our cubicles or in the office. By looking at this sheet of paper, the restaurant owner would know exactly what’s going on with this restaurant. It’s actually a pizza restaurant out there in Sunnyvale called Tasty Pizza.

Kejun Xu: That owner would know exactly what their customers ordered, where’s the order coming from, is Uber Eats or is it from DoorDash, was it paid or not? With all that forward data … I’m going to just do it myself, we’ll come back to the office and sit down as a team and really scope the problem. I’m really proud to say that every sticky note out there that you see our team put up, it connects to a real world problem. Then we’ll also sit down with the team to sketch the ideas all together. Like I said, you don’t have to be a designer in order to design. One of the sketches that got the most [inaudible] vote on is actually from one of our engineers.

Kejun Xu: This is where the design team will come into play. We would turn the ideas and all the concepts and sketches into clickable prototypes. We would then present the prototypes and we’ll do usability testing around it. Some of the testing that we’ve done are in house. We will invite merchants to our office and give them a tour and in the meantime, help us usability test or prototype. Sometimes we’ll go back to the restaurant, and we’ll go back and talk to them and test the prototype in their natural environment. A lot of times, we also do our usability testing remotely in remote sessions through GoToMeeting or Google Meet because we know that we live in this place called a bubble of Silicon Valley.

Kejun Xu: Well, design apparently doesn’t stop here. We shepherd through the entire development process. What this really enables us is that design get to sit at the forefront of the conversation and everyone get to sit at the forefront of the conversation. It allows product managers, engineers, marketers, researchers, designers, and everyone on the team and cross functionally align our goals, and that’s a recipe for high performing teams. You have to add a very special flavor to how we make design here at Clover, and it’s really that we make this a fun process to work on and if you haven’t noticed, we have an open bar at that corner. What’s more fun than sipping on a glass of Mimosa, then sketching your next product idea? Thank you.

Kejun Xu: Next up, I want to introduce our lovely panel for tonight with a topic of navigating conscious and unconscious bias and I want to introduce our moderator for tonight, our engineering director Bao Chau Nguyen. Welcome.

Bao Chau Nguyen speaking

Director of Engineering Bao Chau Nguyen introduces the panel of Clover leaders at Clover Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Bao Chau Nguyen: Good evening everyone. My name is Bao Chau Nguyen and I lead several engineering teams here at Clover, the Clover mobile apps point of sale and the app market web apps. The topic of conscious and unconscious bias had never been more prevalent than right now. From the current political landscape to the social movements, we are immersed in this topic, sometimes not by choice. We’ve come a long way in identifying biases, but we’re not close to eliminating or overcoming them consistently.

Bao Chau Nguyen: I want to show you a research study that I ran across on this topic. Imagine a fake company having a 1% performance bias towards gender. The impact of this 1%, they’re starting out with 50:50 men-women distribution across all career levels and this company rates women from one to 100, and men from one to 101. Over 20 simulations, the company is now skewed with fewer women at top levels. Now imagine running more simulations, the number is going to be a bigger gap.

Bao Chau Nguyen: We know this is a fake company, but we also know 1% bias is not realistic. Having been a young immigrant to America, I faced many biases over the years in all aspects, from classrooms, to just vacationing outside of California, to workplaces. I wanted to make sure that tonight’s panel will have a heart to heart conversation with you and whether you have experienced a bias or not, you can walk away with more awareness and some learnings on how we can become allies to one another. You want to speak up when you see these microaggressions and stand up for each other, because together we are stronger.

Bao Chau Nguyen: With that, I’d like to introduce our panelists, Mary Uslander, Ellen Linardi, Rachel Ramsay, and Meghana Randad. Let’s start ladies, welcome. Would you talk a little bit about your role here and, what was your initial reaction when you were invited on this talk?

Mary Uslander: Yes. Hi, everyone. My name is Mary Uslander. I’m actually from our New York office and I lead commercialization, client experience and work closely with the Clover team. I’m actually part of Fiserv, the parent company. For me, the topic was really around inclusivity and how you use it to an advantage, to really build diverse teams for success. I’m really excited to talk more about that.

Ellen Linardi: Hi, Ellen Linardi. I head the product team here at Clover. When Bao Chau approached me about being in the panel, it was interesting. I think I’ve always had a very interesting relationship with bias, both having seen a lot of it and we’ll chat more about that a little bit later, but also how it made me feel, then how I reacted to it and how I find what you do with the bias that is ultimately always going to be there leads a lot to the outcome. Hopefully we get to chat a little bit about that and we find it valuable. Excited to be here.

Rachel Ramsay: Hi, my name is Rachel Ramsay. I’m a developer advocate here at Clover. I also work very closely with our data analytics team. When you invited me to be on this panel, I was excited because up until I was 25, I thought I was going to be a sociologist, so I feel that I bring a more structural perspective than a lot of people have.

Meghana Randad: Hi, I’m Meghana Randad and I am a software engineer on the payments team here. When I was first invited to talk about this topic by Bao Chau, I was really excited and very happy because this is one of the topics which is very close to my heart. I have always been an advocate for women against inequality, against bias, and a lot of things we are going to talk here. Just coming from a very different background of being an immigrant and a woman and just an engineer, I face it every day, so thank you for having me. Honored to be here.

Bao Chau Nguyen: Great. Where can I start? This is a question for all of you. Would you share a time or a setting where you experienced a gender or an affiliation bias? How did that make you feel and how did you overcome that? We can start with you.

Meghana Randad: When I was growing up, the part of the world that I grew up in, in India, it was a norm and it was also common that women should get a college degree to find a better husband, not to find a better job, and then run the home. People often ask me, “Why do you want to work so hard? Why do you want to have a career when all you can do is support your husband, be home so he can really focus on his work?” A very fundamental assumption that women cannot, are not really so capable to work outside home and can’t have a career was very upsetting.

Meghana Randad: I had to overcome that many times in my life. To me, the key really is to believe in yourself. Sometimes you have to do what you have to do. If you want to get something, if you have a goal that you need to achieve, you have to be persistent and sometimes it could mean challenging the status quo. I was the first woman engineer in my family, and the first one to travel abroad, come to a new country all alone to pursue my career. It’s very easy when you have a defined path, but it’s really hard when you know where you want to be, but nobody to guide you or mentor you, so really all you can do is to believe in yourself.

Bao Chau Nguyen: I really can relate to that. My parents came here and had to start their career all over. They were teachers and then they came here, they had to go to back to school for a different degree and different occupations, so I applaud you, Meghana. Rachel?

Rachel Ramsay: Yeah. I’m an older millennial. I say that because I feel like a lot of women my age, when we were in middle school and when we were in high school, we were learning HTML, we were learning CSS, we were learning JavaScript because we were making our own websites back in the web 1.0 days, yet of all my friends and I who did that, no one was like, “That’s front end web design. You can make a lot of money doing that.” No one else was like, “There are other programming languages that you might enjoy.”

Rachel Ramsay: Out of my friends, none of us ended up pursuing it in college or as a career. I sort of backed into tech by going to a boot camp. But even once you get your foot in the door, once you’re the diversity in D&I, it can be hard to stay technical. Because people say, “You have such great people skills, maybe you want to go into management,” or “You’re a great communicator, have you thought about technical writing?” So, it can be very hard to say, “My North Star is,” whatever it is for you. I want to be a principal engineer and stay on that, stay in technical working with your manager to say, “I want to get the promotion, what do I have to do? Where are the opportunities?” You really do have to run your own career sometimes.

Ellen Linardi: I think from my perspective, a lot of the stuff that Meghana and Rachel both talked about are certainly true. I grew up in Indonesia, in a town not very different than what Jen showed. We had seven, about 7-Eleven looking thing and if I get in trouble at school, by the time I get home my mom knows about it. I don’t know how, but it’s a very small town. It was similar expectation with Meghana was saying, grow up, get married, make sure the man takes care of you.

Ellen Linardi: While I have a lot of stories I think on on biases that I’ve seen, what I wanted to share was probably an experience I had early in my career when I was in Intuit. I started out as an engineer there and loved coding. I was a keyboard hogger. When someone’s coding or trying to solve a problem too long, I get anxious and it’s like, “Let me try, let me try.” I knew I was very comfortable, I enjoyed that a lot.

Ellen Linardi: The other thing that was quite interesting, and I think this is something a lot of females can identify with, I was a good communicator, I like to organize, I pay a lot of attention on how everybody else feels so I kind of try to make it a team decision, make sure everyone’s included. So, one day one of my colleague came to me and told me, it was like, “You know, you’re an okay developer, but it’s all because you’re a good talker.”

Ellen Linardi: It was meant as a dig and I think the thing that I really wanted to share here is, at that point you have a decision. You could take it as a dig, or you could take it as a compliment. I chose to take it as a compliment at the time and I said, “Thank you very much. It is a skill so if you ever need help, I’ll be happy to help you in that area.” The thing I wanted to share there is that we are all going to run into bias, especially unconscious bias, and it’s called unconscious for that reason.

Ellen Linardi: It is going to be there, and I think we’re going to have a lot of opportunity to decide what you do with it. You either let it drive you and change the decision you have, to the point of focusing on where you want to go. Take it how you want it, and the bias folks have are not always bad. If someone say, “You’re Asian, you must be good in math,” maybe you are, you’re like, “Yes I am, thank you.” I just think that one of the way that I’ve approached some of the biases is not always negative, it’s simply a perception people have had going to that interaction with you and their experience of how they thought you should be.

Bao Chau Nguyen: Did you remember some of the responses after your-

Ellen Linardi: I never heard that line again after and I could tell you, certainly being a good communicator has gotten me to where I am. It hasn’t held me back, so I suggest that if you guys have felt biases or people saying things that you know, you’re female, you must be good in this, just say, “Thank you, that’s awesome. I’m good in that and this.”

Mary Uslander: I wanted to share more … First of all, having conversations like this is critically important and I’m just thrilled that everybody’s here. I think this is a conversation that we have to keep having. From my perspective, what I try to do is constantly make people aware that maybe they’re thinking about things a certain way, because of some unconscious bias. Whether it’s working with my male colleagues if we’re in the middle of merging with a new company, and people are making their decisions or judgments about individuals. It’s always interesting about how they talk about the women versus how they talk about the men.

Mary Uslander: When they’re senior women who are very strong, and very powerful, and very opinionated, and very inquisitive and are asking hard questions, there’s always a different value judgment on that individual versus if John was sitting down and really asked all those hard questions, “Why did you think about it this way? Why are you doing that?” That’s part of what you do. It’s really important to–in a right way, but just say, did you think about … Are you judging this person differently because they are a woman?

Mary Uslander: It’s really being aware of that and personally, I try very hard within my own team and I can see it as well. I have two young analysts, there’s a male and a female and they’re both incredibly smart and very talented. She works her butt off and puts her head down quietly and just gets things done. The young gentleman, he’s great too but he’s constantly putting time on the calendar and just showing me what he’s done. Not in a bad way, but I encourage her to do the same. I think it’s just being aware each other as well, and really trying to keep the conversation going, and how do you use it in a positive way?

Bao Chau Nguyen: Thank you Mary, just hold on to that. I wanted to ask you a follow up question. Having so much experience and leading big teams, in your … What have you noticed in your observations on diversity and how it impacts business outcomes?

Mary Uslander: I would say it’s really important to have different people on your team that do different things, but also come with a different perspective. You want someone like Kejun who’d have a design perspective, somebody who’s going to have a different perspective on, let’s say the merchant or empathy, analytical skills, detail oriented, big picture, creative. But, it’s really the power of that diversity of thought that really helps you get better outcomes.

Mary Uslander: What you also want to have is the commonality of you want people to have similar core values, to be ethical, to be honest, to work hard, to be smart and talented, so you really want to … You want to build your team based on skills and based on talent, but you want that talent to have a very diverse perspective. That really helps you achieve much better goals, because people are challenging you in different ways and arriving in problem solving in unique ways to get a much better result.

Bao Chau Nguyen: Thank you, I love that. Ellen, going back to what you were saying, coming from Indonesia and having that cultural bias of certain things that women have to do, and I know you have two daughters. Are they here?

Ellen Linardi: Wondering around here somewhere.

Bao Chau Nguyen: They’re just being great kids. I wanted to ask you, knowing that cultural bias exists and having daughters, does that impact how you raise them?

Ellen Linardi: I think what actually impact how I raise my kids has a lot to do with how I was raised actually. The interesting thing is while I grew up in a very traditional Asian town, I would say my parents were probably pretty progressive, not very conventional. Partly, my sister and I always … I have one sibling, so we are two sisters as well. My dad never had a son. I think he poured it all into us. He basically told us, “Whatever you want to do, pursue it. If you don’t like something, question it.”

Ellen Linardi: I think it drove my mother crazy somehow because when she told us, “Because I told you so,” we were like, “That’s not a reason.” We were brought up to really question the assumption and I think that was unusual. I think that was unusual in my town, that might be unusual for some of you, but I think questioning the bias and assumption and take it as an opinion at face value, and then deciding for yourself. It’s really a matter of choice. Running a home is not a bad choice.

Ellen Linardi: I think that’s one of the tricky thing, is that a lot of times you could see, your mom’s giving you the value she knew, and she knew how to run a home. That’s the life she could envision for you. To be able to understand the intent behind it and realize the impact that it has but not take it as face value, and be able to insert your own thoughts and your own desire to it, I think that is what I was taught.

Ellen Linardi: For me, I told my parents all the time I grew up to become who I am because of what I think the upbringing that I had and I try to do the same with my kids. I hope to be half as good of a parent as my parents was, but it’s the same thing and I think part of it is that it’s slightly uncomfortable. You tell them to question things, I tell them, “Because mommy told you so,” and before I say it I’m like, “They’re going to tell me it’s not a reason.” But, it’s ensuring that you understand why you’re doing things, and it is for a reason that you accept and you’re aligned with.

Ellen Linardi: It’s not because someone told you, it’s not because you’re scared, it’s not because society expect you to do so, it’s because you want to. I think having that as a compass is what I try to instill in my kids. That’s helped me, hopefully it helps others as well.

Bao Chau Nguyen: Certainly I grew up and my mom expected me to help her in the kitchen, and I always ran off and go do something else. Having two kids, a boy and a girl, I try to be as equal, whether by chores, it’s like, “Both of you clean up your rooms, both of you fold away your own laundry, both of you wash your own dishes.” So, not guiding them towards anything that is specific to their gender that they have to do. Just growing up here and seeing that world, it really helped me raise my kids to.

Ellen Linardi: It was actually what the interesting thing when I first came to the States, and I came after high school, actually. I always thought I was different when I was back home, but my parents kept telling me it was okay to be different. I was also a sick kid, so there was a lot of reason to be different. But when I came here, I realized I was different, but everyone felt a lot more different and being different was okay. I’m like, “That’s awesome, I’m never going back.” Here I am like 20 years later.

Bao Chau Nguyen: Now Rachel, being a lesbian you have twice the potential for bias from gender to sexual orientation. What changes or suggestions would you like to see in an organization to combat these biases?

Rachel Ramsay: Well, it’s easier to be a lesbian in the Bay Area than it was in North Carolina. I do want to call out the ways in which I am privileged, which allowed me to come here. I’m a white woman, I come from an upper middle class background, I’m a cis woman. When I decided like, “The Bay Area is really expensive, I need to get one of those tech jobs,” I was able to say, “I can get a loan to go to the boot camp, but dad, I’m going to be out of work for three months. Can you give me a loan from bank of dad?” Which he did. The question is…

Bao Chau Nguyen: Thank your dad for us.

Rachel Ramsay: Yes, I’ll tell him that. So, how do we create a world where everyone is safe is a really big question, bigger than the question you asked me, so I will limit myself. But, I’m really excited by what Jen is planning, our new head of people ops to include more of a diversity and inclusion training as part of our onboarding, similar to the program that we established for merchant empathy. But it’s not just about new hires, it’s across the company. Every year I get to sit through some trainings that are like, don’t bribe people, don’t sexually harass people.

Rachel Ramsay: I would love to also have a mandatory training like, don’t misgender your colleagues. It’s not just about education, it’s also the policies and the material support that we can provide to our colleagues. Whether that’s little simple steps like normalizing doing your pronouns when you get introduced, whether that’s having a gender neutral bathroom that’s just like a place for non-binary folks. And of course, making trans healthcare accessible. It has to be part of your health coverage and you also have to pair it with a supportive medical leave policy.

Bao Chau Nguyen: Hear that, Jen? She’s working on it. Meghana, you have two little kids. Describe to me balancing work and life, and not having the choices to stay late to work on a project or going out to a team dinner for team bonding. How did that impact you, or how do you feel like it impact you or your career?

Meghana Randad: Most of us feel that 24 hours in the day is not enough. I feel when you have young kids, even 48 hours are not enough. It’s just a lot of physically, emotionally sleepless nights, and being present at work and to be productive at what you do. When my team goes out for happy hours, and happy hours I feel are staying, working late together as a team are ways to bond, are ways to network. Sometimes you talk about things which are not related to work. You talk about your passions, we are in this space together and we are all motivated towards similar goals. You form a sense of community, you feel you belong here.

Meghana Randad: I felt when that happens, the team that I worked in was much more productive. Then being a young mom, being a young mom is incredibly hard. It’s very hard to create that harmonious balance between work and family. I do have to put definitely much more effort for working or even sometimes to just bond with my colleagues. For example, there has been times I had a four year old boy, a five month old baby, I’m on call for production, there’s a fire and I have to deal with it, I have to debug the issue.

Meghana Randad: My sick kid is now refusing to eat, some I’m sitting at the table, trying to get him to eat, a laptop in front of me Slacking and trying to look at all the graphs and debugging our code to figure out what’s wrong, to make sure we don’t fall apart as Clover. At the same time, holding my five month old in another hand and breastfeeding her. She was happy sucking away.

Bao Chau Nguyen: Multitasking to the next level.

Meghana Randad: And all moms have it. It’s not just me. But, I feel very grateful. I have an incredible partner who supports me when you have to stay late at work. For example, today he’s babysitting. I feel equally happy to work for a company, which supports its employees through various life phases. It’s just not flexible hours or maternity perks, it’s more than that. It’s a thinking that’s ingrained in culture here at Clover.

Meghana Randad: In my first week actually, we had happy hour on a Thursday and John Beatty, our CEO, he came up to me and he told me, “Hey, I know you’ve been a new mom and I know how hard it can be because I’m a new parent myself. I understand it’s hard, and I’m here to support you, so let me know if you need anything.” That itself is, that comes back to me every time I feel I’m struggling, and it’s very reassuring to have that support, just not at home, but also at work. I feel happy and cared for.

Bao Chau Nguyen: Wow, that’s a great story. Thank you, John. One last question before we open up to Q&A for everyone. How would you challenge stereotypes, provide some advice to your audience and promote sensitivity and inclusion?

Meghana Randad: As Jen said, we all have unconscious bias. We have amazing unconscious mind, which helps us navigate through a lot of decisions that we make every day. But unfortunately, this unconscious bias that we have against people could lead to make some wrong assumptions about people. Every time I make assumptions about someone, I try to ask myself, why? Why have I made that … Why do I think that way? Do I have enough data to support that? Has that person, does he have skills to do what he needs to do or she needs to do?

Meghana Randad: For me to challenge stereotypes, the keys to keep asking yourself and be really mindful, and be conscious about your biases. Once you’re aware, I think that’s the very first step towards tackling those and to create a very diverse and inclusive environment. It’s very important to have a diverse team, because most people learn from their experiences. To me personally, experiences are most powerful, that’s how I learn.

Meghana Randad: When you create those diverse teams, it can be gender, it can be number of experience, your background, many other things, right? Then people when they interact with each other, their assumptions are challenged a lot of times and they understand perspective of other people. That helps improve the whole culture of inclusion. I feel when you’re creating such diverse teams in workplace, the most important thing is to create a safe place where people can really share their differences and don’t feel that they have to conform to a norm. Really getting that richness in workplace would be the key I guess.

Bao Chau Nguyen: Well said. Rachel?

Rachel Ramsay: I think getting people in the door is not enough, hiring is not enough. You have to be bringing them into an environment that is truly inclusive, truly safe, where they can show up with their whole self and do good work, and come home feeling only the normal amount of exhaustion that you feel. How do you do that? I do think it requires a C suite level buy-in, it requires a buy-in from managers. I’m not a manager, I’m an individual contributor. As an IC, one thing that we can do for each other is we can look out for each other, we can have each other’s backs.

Rachel Ramsay: One time I was in a meeting and whenever I notice like, who gets cut off, who gets assigned the note taking, who gets chosen. You don’t want to white knight for people because it’s their career, but it’s easy to stand up for someone else, probably easier than standing up for yourself. So, there’s always an opportunity to call in a co-worker, to call in a manager.

Ellen Linardi: Let’s see, where do we start here? I think that ultimately, the interesting thing for me, at least from my experience on unconscious bias, is that we all have it. In some ways I say we have unconscious bias to the people that we think have unconscious bias. When certain people approach you in a particular way, you react to them. One of my biggest learning over the years professionally and personally really … I’m a divorced mom as well, so I’ve gone through various life experiences.

Ellen Linardi: Well, in that area is to decouple the impact and intent. The minute you couple the two because of the way someone makes you feel and you start reacting to that personally, emotionally, the conversation really isn’t going to go anywhere. The biggest thing that I really try to do is, I’m like, “Take the impact,” like, “Ouch, that hurt,” and then decouple it and say, “I know you didn’t mean to do that because when you say at the intent it sounds completely bad,” and then even if they mean to so it they’ll be like, “No, no, that was not what I meant to do.”

Ellen Linardi: Everyone take the higher road, but give people a chance to take the higher road. Because, when you tell someone, “I know you’re bad,” they’ll be bad, but when you say, “I know you’re actually good, but what you did was bad,” it gives them a chance to make different choices. I think that’s the first thing, is be aware of how you’re reacting to the unconscious bias. If you react to the unconscious bias by providing your own unconscious bias, it’s like regurgitating the same cycle and it doesn’t really get anywhere.

Ellen Linardi: I think the second thing is when it comes down to bias, the best thing I’ve ever find throughout my career of changing that is by changing the experience that the individual or the people or group in front of you have with whoever you represent. Sometimes I represent an epileptic person, sometimes I represent a divorced mom, sometimes I’m an immigrant, sometimes I’m a female leader, but in whatever context, you have an opportunity to recreate what it meant to interact with who you represent.

Ellen Linardi: When you change that experience, that change perception, that change bias because it is very hard to tell someone, “Change your unconscious bias.” It starts from the experience because that’s where it comes from. I think we all have an opportunity to slowly change that up, both by, I think, providing programs, having structures, and policies and everything that encourages it and making sure people are more aware, but each of us individually also have a chance, I think, on every interaction, to, I think, not continue that bias cycle and try to break it as well.

Bao Chau Nguyen: Yeah, I think we can all be allies. We can always find something that we can ally for each other.

Mary Uslander: A couple of things. One, I try and it’s very hard to do, is listen more. So much with unconscious bias, your brain is going, you’re looking at someone, you’re making a snap judgment. But then if you stop and you actually listen to what they’re saying, it’s overwhelming like, “Oh my God, this person’s amazing and what they’re saying is incredible.” I think for all of us to just stop and really listen, hear, and just try to incorporate that skill into everything you do. That would be one thing I work on every day.

Mary Uslander: I think the other is if you’re either managing people, be aware of always going to the same person. It’s easier said than done because a lot of times you have deadlines, and you need to get things done, and Ellen is the one who can always deliver like that or whomever. But you have to really give other people a chance, and also coach and help them right. Mentoring is another thing we haven’t talked about as much here, but we all know how important mentoring is, and mentoring is everywhere. It’s tonight, right? It’s listening to these amazing women and hearing about John and others, you look around you.

Mary Uslander: Every day, you should look forward and see, what could I take from someone? Whether it’s the person at the front desk or whether it’s the person who’s bringing the coffee, there’s always something to learn. Then if there’s someone who you really admire or respect and you want to spend some time with them, seek them out, ask them if they’d be willing to have a cup of coffee with you. It’s listening, it’s being aware, it’s trying to spread the love around and really help each other out. We as women here have to really continue to help each other and help the men, because sometimes they need a little help and understanding, probably more so than most, but I think it’s our job and responsibility to keep doing and keep advocating.

Bao Chau Nguyen: I know that you are part of many women organizations as well, you’re a big advocate for women. Can you talk a little bit about that?

Mary Uslander: Wnet is another women’s organization. Girl Geek X is amazing, but Wnet is another organization for women in the payment industry. Audrey Blackmon is in the back and she’s one of my fellow board members at Wnet. We really try to do all kinds of advocacy, education, training, webinars. I encourage you to take a look at wnet.org if you’re interested in joining. What we’re going to do is more … We’ll probably do an event here as well, but, any women’s organization or have a lunch and learn in your company. Get people together, have conversations. I think that’s really what we are trying to do here.

Mary Uslander: I just personally want to say about Jen and all of you, thank you. I feel like I’m an honorary Clover member because I’m part of the other side of the company, but I am so honored personally just to be here and to be part of this amazing group. Thank you for having me.

Bao Chau Nguyen: At this time, we’ve wrapped up the panel questionnaire and open up for Q&A.

Natalia: Thank you. I actually thought of not using maybe a microphone because it was so far away. Well, thank you for this. My name is Natalia, and thank you for sharing all the stories and feedback. Unfortunately, unconscious bias is something that affects many people, whoever brings any kind of diversity. I’m really curious about the feedback that you might actually hear from male colleagues, maybe your partners, maybe your husbands, maybe your brothers or fathers. Do they also see that unconscious bias impact them and most importantly, how they deal with it?

Ellen Linardi: I can get that started, I think. I actually am in a lot of rooms where I’m the only female. John knows this and we’ve talked about it. Recently we had a senior leader session with someone of the top product leader in the organization and I walked into a room, I opened the door, I was a little bit late. I opened the door and the room gasped. There was about 50 men in the room, and I was the only female. The guy who set up the meeting looked in the room, he looked at me, we all looked at each other and he’s like … And nobody noticed until I walked in, but–

Mary Uslander: They were all guys.

Ellen Linardi: Yeah, but they were all guys. Then he looked at me and he’s like, “That’s not good.” I think sometimes people don’t realize it’s happening, so I think being there representing it is one thing. A lot of situation, those interactions, I think, once it happens, allows you to highlight and have the discussion about how being present and having different personality from various points where I actually can deliver different values. I do think just the general climate and awareness is helping bring those conversation to the surface, so at least on the …

Ellen Linardi: Even if people don’t notice it all the time, the desire and willingness to have more inclusivity, I feel the tide is changing and it’s there. And the ability for us to actually engage in those conversation in an open way, in a non-biased way on our own and say, “I know we didn’t mean it, but this is just how it looks like right now. What do we do about it?” I think the ability to be inclusive of the solution and to not pass judgment on how we got to where we are today, I think allows everybody to take the high road and look forward on what it needs to look like in the future.

Ellen Linardi: The biggest suggestion I would say in, how do you engage in a discussion about somebody’s bias is to be very, very kind about what their intent is. Even if you’ve felt it multiple times, even if you’re like, “God, that’s so unfair,” the minute you put them in an area where they don’t have a chance to say, “I didn’t mean to do that,” you get a very different reaction and that’s true, like I said, from a personal basis, whether it’s international with your partners or your friends or different community member, all the way to in a professional environment.

Bao Chau Nguyen: I’d like to add on since you mentioned whether our male partners or husband experience bias as well. I think everyone experience it in some form, like it’s a segment that you belong to, that you’re different. Men experience it with race, as well as if men have kids, there’s unconscious bias with men who have kids versus single men. Everyone, everyone experience it and we need to have that open conversation and be receptive to that, that they do feel it to. Anyone else?

Audience Member: You spoke a little bit about being the only, help me understand your perspective on oftentimes being the only person in the room, in my case, the only person of color, sometimes the youngest person in the room, sometimes the person with the highest EQ in the room.

Bao Chau Nguyen: Good for you.

Audience Member: Help me understand your thoughts on being the only and representing all of those people. You spoke about representing all the different aspects, representing all those people while still trying to be yourself and bring your 100% self in that situation or in that room.

Ellen Linardi: I think two things. I’m going to say the first is, it’s important to know who you are, what you are and what you’re not. The best way you can represent whoever you present, whether that’s color, ethnicity, age, or what, it’s still a version of you. It doesn’t make everybody else who’s Asian or female be like me, but it allows people to understand that no matter your color, your gender or your age, the individuality and the differences and the diversity is where it matters.

Ellen Linardi: Really a lot of the things that we talked about on biases, it’s not about, it can’t be all men, or it can’t be all white or anything, it’s that the lack of diversity impact outcome. I think being able to demonstrate how that diverse opinion and approach can change the outcome is important one. That’s number one.

Ellen Linardi: The second thing I would say is, it does come down to choice. Just because sometimes it worked, doesn’t mean it always works. You’ll find yourself sometimes in an environment where you bring your true self, and they don’t want you. That’s not what they want, and that’s a call to action. If you’re being you, and you’re not acting or behaving because you’re afraid of what people’s expectations are, or perceptions or because someone told you so, and you’re just being truthfully your value, your belief, and your talent and your skill and they’re not interested, I guarantee you someone else is. You’re wasting their time and they’re wasting your time.

Ellen Linardi: I would say if you run into a situation where you’re being your true self and that’s not being valued, there’s a better place for you out there. I’ve made multiple choices, both personally and professionally where I was being myself and that, it wasn’t right. It doesn’t make them bad, but it wasn’t right. I think at that point, you have to make the choice of whether you continue in that environment, which is your choice to stay there.

Ellen Linardi: It’s hard to make that choice and say, “Well, they’re not accepting me.” Well, you know that so what are you going to do about it? I think making the choice when you’ve tried and it’s not working is another important one I would say. When you find yourself being the only one who’s represent in whatever group it is, sometimes it’s welcomed, sometime it’s not.

Mary Uslander: I would just add to that. This is a great conversation to. I also think you just … A lot of it is competence and confidence. I can imagine you in a room with all these men even if they’re all white, but just smart, articulate, talented, and once you start talking, I think instead of looking at your exterior, they’re going to start thinking about what you have to say and say, “Oh my God, that’s really great.” I would encourage all of us, right, to say you have to be confident, you have to know your stuff, you have to be prepared. Sometimes we have to be more prepared than others and so do your homework, but just be yourself and try not to get tripped up about that. Just go in with the objective at hand and be yourself.

Meghana Randad: And as Ellen said earlier, sometimes even if you are all of that, all of your authentic self, you’re still not accepted. There will be times. You have to go back and think, how does it affect you? What is your goal here? Does it affect you so negatively that it’s not taking you to your goal, or is there something that you can overcome this resistant by doing something differently and it still be you?

Meghana Randad: If it’s actually hurting your goal and hurting what you want to do, then I would say definitely, as she said, there is a better place for you. Maybe this is not the right place. You just have to sit back and think, is that right for me and does that align with who I am and where I want to be? You can be at a certain place, there can be various paths, so this might not be it.

Audience Member: Hi, I’m [inaudible]. I’ve been in the tech industry almost 20 years now. Started in engineering, went to business school. After that, worked overseas and back here and I find like and back in ’98 sometimes, that it’s been over 20 years and the progress hasn’t happened personally for me. I look at myself as a fresh engineer arriving here in Silicon Valley. The thing that I have realized, and so it’s a comment and I agree with 100% everything that you guys have said, because it’s not just here in Silicon Valley. I’ve seen it in APAC, Singapore, Malaysia, name it which country, I’ve seen it. There’s multiple layers of biases when you work abroad. Switzerland, yes. I left a business school because I didn’t like how they treated women, and this is Switzerland. Right, so it’s all over.

Audience Member: My thing that I have come to a conclusion and I don’t know, I’m opening it up here, is that fundamentally the way–I’m trying to understand neuroscience also here–if fundamentally we were designed with unconscious bias, that’s not fundamentally going to change because it’s like 1,000 years of how the brain was wired to protect us from … To keep us safe. That’s where fundamentally, some of these reactions are. I think what we as women need to learn and some of it, I think Ellen beautifully put it there is, how do we communicate much more effectively as individuals?

Audience Member: Understanding that as the other person has bias, we carry our own biases as well on how we perceive and judge other people and it comes from that fundamental sense of safety and security. That’s my add on I wanted to contribute, is to fundamentally learn ourselves and also most importantly, teach our kids. I have a five year old girl and I want at least in the next 20 years, things to be different for her, what I didn’t have. I want to make sure that we also talk about how we raise the next generation on effective communications because the bias is not going to disappear.

Bao Chau Nguyen: Right, and I think when you catch yourself doing that bias, you can always correct and apologize. That’s the best way, “I didn’t mean that,” or, “I phrased it wrong, let me rephrase that.”

Mary Uslander: And to that point. I do think though, part of what the action has to be is there needs to be more women at the top of the house because if you have more executive and C suite women, they’re going to be more inclined to have less of those unconscious biases and have more women like themselves be part of it. We saw the stats of the 1%, but if you look at the Fortune 500 companies, maybe there’s one or two women CEO. The unconsciousness is, I’m just going to go, we’re going to go to play golf or, I’m going to go down to so and so’s office.

Mary Uslander: It’s just, people are more comfortable with people like themselves, and therefore have the tendency to then promote people like themselves. What we have to do is start changing that, and it’s up to us in our companies to really push leadership to have the training, people like Jen, to make sure our CEOs are aware of this phenomena. We have to start getting more women in leadership positions, we have to get them more on boards. I mean, there’s a whole ‘nother conversation we can have and should have.

Ellen Linardi: I was going to say the other thing that I feel like if you guys are, whether you’re manager or in leadership, is model behavior. Those of my colleague at Clover and Fiserv [inaudible] would know, I’m like unbashfully mommy. I think a lot of times to the point of being the only person in the room, you try to look like everybody else. Whether it’s if everyone go drinking, you go drinking or everyone go golfing, you go golfing or if everyone shows up at seven, you shows at seven, that actually doesn’t help the diversity. Because what it does, it creates a perception that in order to be there, you wake up at seven, you leave at six.

Ellen Linardi: I made a rule that between seven and eight, my kids at home and like I said, I’m co-parenting, there’s time where … I don’t have my parents here. They’re in Indonesia, so I’m on my own. I got to drop off, I get them ready to go to school and if we have a Thursday night and it’s my turn with the kids, they’re right there. So, I think the … Be authentically you, because then you can actually represent the diversity. It’s a little bit unsettling and people will look at you funny, but someone looking at you funny doesn’t actually hurt you.

Ellen Linardi: I think being able to actually represent the diversity and not try to be in the room and try to look like everybody else, is the responsibility that all of us have here. Because I think historically, everybody says the female get to the leadership level and they try to look like everybody else. That doesn’t help. That’s what I would say, I guess.

Audience Member: Hi, thank you very much for sharing your personal stories. My question is about change management. I was wondering if you could give an example at Clover of things within the system that was broken that you got to fix. So, a system that accidentally had unconscious bias embedded in it and affected people of color, women, other marginalized groups, and you were able to address it, because I believe that it is the system we got to fix and not the women because we’re not broken.

Meghana Randad: It’s not my story, it’s a story of my colleague. Last year when I had my baby, another colleague of mine did too. I was lucky to have a manager who was understanding and could support me to that, but she was not as fortunate, so often, she used to get interrupted during her mommy duty times and she was scared, she did not want to bring it up. She was not a leadership level, she was not a manager, she was an individual contributor at a very early stage in her career.

Meghana Randad: But then, we talked about it often. We talked about it in mother’s room and she gathered the courage. I’m very, very, very proud of her to do that and she brought it up to the management. She brought it up to John, I guess. John took action in one day and it was corrected for her. The leadership which created all that discomfort, did not value her as a mother, as a female, and did not support her was corrected right then. This is a story I know very personally for someone.

Bao Chau Nguyen: That concludes our panel for tonight. We still have plenty of networking and swag left to pick up, so enjoy the rest of your evening. Thank you for coming to Clover.


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Girl Geek X LiveRamp Lightning Talks (Video + Transcript)

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Akshaya Aradhya, Angie Chang speaking

Angie Chang, founder of Girl Geek X, welcomes sold-out crowd to LiveRamp Girl Geek Dinner in San Francisco, California.  Erica Kawamoto Hsu / Girl Geek X

Transcript of LiveRamp Girl Geek Dinner – Lightning Talks:

Angie Chang: Thank you for coming out to the Girl Geek X Dinner at LiveRamp. My name is Angie Chang. I’m the founder of Girl Geek X. We’ve been hosting dinners like this for 10 years up and down San Francisco, San Jose. And I’m really excited to be here tonight to hear from these amazing women and to meet each other over dinner, drinks, and conversation.

Gretchen DeKnikker: So, we also have a podcast, if you guys want to check it out. Check it out, read it, give us feedback. Let us know, we have mentorship, intersectionality, finding career transitions, all of these things. So, definitely go and check it out. And this is Sukrutha.

Sukrutha Bhadouria: Hi, that was Gretchen. She didn’t introduce herself. Yeah, so we started off with dinners, we talked about podcast, and then we made it happen. In the meantime, we started to do virtual conferences, which we’ve had now one every year in the last two years. And fun fact, we now have what is…a Zazzle store with our amazing branded, cool swag, I don’t fit into the T-shirt that I ordered.

Sukrutha Bhadouria: But you could get tote bags, you could get cell phone covers, so it’s really cute. Or somewhere in the back, maybe, you’ll see what our pixie characters look like that up. But if you go to the invite for tonight, you’ll see these little characters that we have represented and we try to be as inclusive as well possible. So, all of our branding is very inclusive. Please share on social media, everything that you hear tonight from our amazing speakers. Use the hashtag Girl Geek X LiveRamp. And we will follow you and retweet and re share, so thank you so much for coming and thank you to LiveRamp.

Allison Metcalf speaking

GM of TV Allison Metcalf gives a talk on how LiveRamp got into the TV game at LiiveRamp Girl Geek Dinner.   Erica Kawamoto Hsu / Girl Geek X

Allison Metcalfe: Hi guys, I get to go first. So my name is Allison Metcalfe. I am the GM of LiveRamp’s TV business. So just for context, what that means, LiveRamp, a couple years ago, we moved away from functional leadership 100%, where I was actually previously the VP of Customer Success. I’ve been here almost six years. I started customer success, I was patient zero A long time ago, and I will never do that again.

Allison Metcalfe: So a couple years ago–LiveRamp has historically been really, we really focus on the digital ecosystem and the cookie ecosystem. And there’s been a lot of changes in the industry that suddenly made TV a very, very compelling opportunity. And so, we launched a TV business that I run. And so, what I’m going to talk to you about now is kind of why we’re in this business and what the opportunity is and why it’s super cool. It’s really fun to be working in TV right now. And hopefully, we’ll get a couple converters from it.

Allison Metcalfe: So, TV is so crazy. Nothing has changed in the world of television in terms of how it was bought, measured, I need a timer here, sorry, in 70 years. So, literally like the way people measured TV and bought TV and demonstrated the success of TV up until a couple years ago was the same as it was 70 years ago, which is a little bit insane.

Allison Metcalfe: As you probably know, you think about yourselves, you are not watching Seinfeld at seven o’clock on NBC anymore. It’s not appointment viewing anymore, you’re streaming it, you’re watching TV really whenever and wherever you want, every single screen that you have, is a TV today, which is really great for us as consumers. Like TV has become very, very consumer friendly. But it’s caused a lot of problems for the industry.

Allison Metcalfe: So number one, is the way we’re measuring it, ratings is really hard to track now, right. Nielsen is the incumbent measure that would say this is how many people watched Seinfeld last night. They were able to do that because of a pretty archaic panel that they had and pretty archaic methodology. But it was accepted. And it worked for a long time. But now, the network–so it’s like NBC is, they’re putting all their money on This Is Us, right? And Nielsen is saying, “This is how many people watched This Is Us last night.” And NBC doesn’t believe them. Because they’re like, “What about all the people that watched it on video on demand? And what about the people that watched it on Hulu and Roku and all these other places where they could be streaming that versus just on appointment viewing, linear television?”

Allison Metcalfe: So, the audience fragmentation is making the networks feel like they are not getting enough credit for the viewership that they are actually driving that translate to they are losing money. And they don’t like that, right. The device fragmentation is also causing problems for brands, because the brands, all they want to do is reach you, right? If they are trying to reach young parents who are in the market for a minivan, they don’t really care where you are. They just want to make sure they’re reaching you.

Allison Metcalfe: TV used to be the easiest way to get phenomenal reach within one buy, right, because everybody was watching Seinfeld at seven o’clock and we knew who they were. Now, we’re all over the place, this creates a big problem. If you’re a brand. You’re like, “Oh my gosh, how much money do I spend on Hulu versus Roku? How much do I put on linear television? How much do I, what other devices,” there’s so many I can’t even think of them all. So, it’s a really big problem for the industry. But it’s good, right? Because change is good. And again, it’s very consumer friendly.

Allison Metcalfe: So what we call advanced TV, is the process of anytime we are using data and automation to buy and sell TV, which again, really was not done before, that sits under the umbrella of advanced TV. This is a roughly $80 billion industry–that’s the TAM in the United States. Historically, for LiveRamp, we made zero dollars from the television industry up until about two years ago.

Allison Metcalfe: So it was a whole new TAM for us, which is very, very exciting. Of that $80 billion that used to be bought and sold in the traditional way up until advanced TV came, now, we’re seeing projections of $3 billion being spent in addressable, which I will explain, close to 8 billion in OTT which is anytime you are watching television, due to your internet connection. It doesn’t matter if it’s on your phone, or your computer or your Smart TV. But if you’re watching it, because of the Internet, and not because of your set top box, right, that’s OTT.

Allison Metcalfe: And then, we’re also seeing a lot of companies like a really interesting trend is a lot of the direct to consumer. Companies like Stitch Fix or Peloton that are 100% digital companies are starting to spend a lot of dollars on television as more advanced strategies are becoming available to them. The other thing that’s happening here, guys, it’s really, really important. Facebook and Google are coming after TV hard, right. They’re like, “We want to keep growing at the rate we’re growing. But we already have like 80 or 90% of the entire digital ecosystem. So how do we keep growing, we’re going to steal money from TV, that’s what we need to do. And we’re going to do that by saying we have all the eyeballs that TV has anyways.”

Allison Metcalfe: And so, that’s another reason that the industry has to change to combat, Facebook and Google. And I think the demise of television is very overblown, as you can see by these numbers here. So, we power the future of advanced TV, when we talk about advanced TV, we’re talking about all of these things. So, addressable TV is literally the idea that you are getting a different ad, than your neighbor, right, Rachel here is big camper, I am not. You shouldn’t waste your dollars showing me commercials for camping equipment, but you should show it to Rachel. So addressable TV is meaning Rachel’s going to get the camping commercial, I’m not, based on my set top box, we power that.

Allison Metcalfe: Data driven linear TV is the idea of, if you have a target audience of say young families in the market for a minivan, we will match that against a viewership data asset so that the buyer can understand that young families in a market for minivans are over indexing to This Is Us and what’s another TV show? Modern Family, and they’re really not watching The Voice, or whatever it may be. So you’re still buying TV in the traditional way, you’re not targeting a household, you are still buying based on content, but you’re buying that content, because you are much more data informed.

Allison Metcalfe: I talked about OTT, digital video, this is clips, this is, Jimmy Kimmel had a great show last night, and there’s a clip of him and his funny joke and we might want to see, you’re all being forced to watch an ad. Before you can see that clip, as you probably all know. And then, probably the most important exciting thing is measurement. So historically, the way TV has been measured has been brand lift awareness, surveys, and reach.

Allison Metcalfe: Now, given the fact that LiveRamp and we have a couple other companies that can do this, too. We recently made an acquisition of a company called Data Plus Math, we can marry viewership data that’s ad exposure data to outcomes. So now Peloton, for example, can say, “Aha, my investment on This Is Us drove this many people to my website, that was a good investment for me. And I’m going to crank it up on This Is Us,” for example. LiveRamp plays in all of these places, a lot of companies that are getting into the TV game usually are only in one or two of these areas.

Allison Metcalfe: So it’s really exciting. I’m going to wrap it up there because we are a little bit crunched for time. And I’m not going to bore you with this. But I hope that was somewhat valuable and interesting to you. And thanks for coming. Thanks.

Tina Arantes speaking

Product Leader of Global Data Partnerships Tina Arantes gives a talk on finding product/market fit at LiveRamp Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Tina Arantes: Okay, Hey, everybody, my name is Tina Arantes, and I’m on the product team at LiveRamp. Been here about five years, so not as long as Allison, but enough to see us go from like 70 people in a little office in the mission to like, mission on mission to three floors here and like over 800 people. So it’s been a crazy ride and on products, we’ve learned a lot.

Tina Arantes: So I’m here to share with you some of the learnings from my product experience here. And primarily, the learning that listening to your customers is the first step in creating awesome products. So this may sound very obvious, like everyone’s probably like, “Duh, how else would you do it?” But when I’m out there like talking to other product managers through interviews, and other ways, it turns out a lot of people aren’t talking to their customers. And it’s actually super important because especially in the B2B business, like I’m selling into marketers, and I’m not a marketer.

Tina Arantes: So if I don’t know, if I’m not my own customer, the only way to figure out and empathize with them is to actually get out there and listen to them. So, I’m also a big fan of design thinking, right? So the only way you can create a product that your customer is going to want to buy is if you first empathize with them, define the problem you want to tackle, ideate to come up with solutions on how to solve it, and then prototype and test. So, the empathize part is actually like the part I’ll focus on first, which is like, how do you get out there and discover what are the problems your customers are actually facing?

Tina Arantes: So let’s jump right into it. How do you actually listen to your customers? The first step is actually just showing up. It sounds simple, but you’d be surprised how many times like you’ll have someone on Allison’s customer success team reached out and be like, “Hey, can you answer this question for this customer about this thing?” And the first thought most teams have is like, “I could, but how about that person does it because I have other important things to do with my engineers.” But actually, a lot of the times, it’s sometimes useful to take advantage of the opportunity to get out there and just meet the user, and start to establish trust with them. So you can ask them your own questions and get to know them better later on.

Tina Arantes: So step one is like just show up, make time in your calendar to find customers that are representative of your user base, and get to know them. So once you’re there, and you’re in the conversation, you can’t just jump right in with the hard hitting questions, right, you have to establish like base of trust. So warm them up, buy them a cup of coffee, introduce yourself, ask them about them a little bit. The way we do this, actually on a larger scale at LiveRamp is through customer advisory boards, where we actually organize getting some of our best customers together into a room, take them off site, somewhere that they can actually spend a few days with us, give us feedback on the roadmap and tell us about some of the biggest problems they’re facing.

Tina Arantes: And that’s been actually one of the really big sources of customer input and feedback that we’ve gotten. So you can do it on a small scale with a cup of coffee or organize like a whole event to get out there and start talking to your users. Okay, so once you have the customer, you warm them up. Don’t again, just jump in there with what you want to say, start listening to what they have to say, I don’t know how many times I’ve just been blown away by like being like, “Okay, what’s keeping you up at night? Like, what are your biggest goals? What can you not solve? Like, how can, how can we help you?” And they come up with all kinds of ideas I would never think of, sitting at my desk trying to imagine what they might want to do.

Tina Arantes: So be an active listener, listen to what they have to say. And don’t try to lead them to the solution you have in your mind. Because you know, you’re so smart, and you know how to solve their problem. But you also should ask juicy questions as well. So once you’ve given them a chance to talk, then you should have done your research and know who you’re talking to and know what kind of questions you can ask to really get at the heart of what you’re trying to solve.

Tina Arantes: So these could be like discovery questions, asking about what areas of problems they’re having to like, help you come up with solutions later on, that could be products. Or if you’re in a stage where maybe you’ve talked to a lot of customers, and you have an idea of a problem you can solve is like throwing it, putting it in front of them and seeing how they react to it. Do they get excited and be like, “Where do I sign? And can I buy this tomorrow?” Or they’re like, “Okay, that’s interesting, like, not that important to me right now.” So yes, you can ask your questions as well, after you’ve done your share of listening.

Tina Arantes: Okay, and after the interview, or after you talk to your customers, what happens next. Now the hard part happens where you have to map it back to everything you’ve heard from every other customer you’ve ever talked to. So definitely write these things down, keep them somewhere, like, I sometimes find notes from customers from five years ago, and I’m like, “Okay, that problem still exists, maybe we should solve it.” And then you start to look for trends, right? You want to see, is it a problem multiple customers are having, like, can I identify 20 customers that are having the same problem? How urgent is it for them?”

Tina Arantes: So people have all kinds of problems, but is it in the top three? Or is it like number 20? And they’re like, “You can solve it for me, but it’s not really going to matter.” And then the important part, like what are they willing to pay for it? You can ask like, “Hey, I have this next month, would you buy it?” And people will let you know, yes or no, there.

Tina Arantes: But let’s get real too, so earlier, I said like a lot of people don’t actually end up talking to their customers for various reasons. Of course, like time is always an issue as a product manager, because you’re running around crazy with your engineering team, like trying to keep sales happy, lots of internal squeaky wheels to keep from driving you crazy. But like you do need to make time to talk to customers. And even once you have the time, like I know, as a PM, all of these thoughts popped into my head, right? Like, what if they don’t want to talk to me? Who am I to like, go knock on the door of a Fortune 500 company and be like, “Can I have an hour of your time?”

Tina Arantes: But like, it turns out, most of the customers really do love talking to product and love providing their input in hopes that it will impact the roadmap and asking their questions to you as well. You can turn it into like a value exchange, like offer your thoughts on the vision of the product in exchange for their input as well. This one’s one of my favorite, like, what if they say bad things about my product? I know like, you get very attached to your work, right, and you don’t want to show up to a customer and they’re just like, “Yeah, no, I hate it. Your baby is really ugly.” Like, no one wants to hear that. Right? It’s terrible.

Tina Arantes: But it’s better to hear it so that you don’t walk around thinking your product is like, the best thing ever, when really like, there are some things you can improve. So, it will happen, like people will say bad things, you just have to deal with it and take the feedback as a gift. And then this one also comes up. I know a lot of product managers are like, “I don’t really want to get on the call. What if they asked me something, that I don’t know the answer to?” It’s like, that will also happen, like every single call, but it’s okay. You just have to be like, “I will find you the answer to that and pull in someone who does know the answer for the next call.”

Tina Arantes: So there’s a lot of resistance to getting out there and talking to your customers, but you got to do it. So what does it actually, what does success look like when you do this right? And when you don’t do this right? So maybe starting with like when you don’t do this right. Definitely over the past few years, I’ve made tons of mistakes, not vetting things carefully enough with customers. One standout in particular where we had a project and we’re like, “Oh, we’ll just make this product go much faster.” Because we had a few customers who were like, “Yeah, that would be great.” Jeff’s laughing back there, because he’s the engineer who built it.

Tina Arantes: So we built it, we launched it, and then no one wanted to buy it. And we were like, “What?” And it turns out, it was a problem for people, but it wasn’t something they were willing to pay for. So now, we always check like, “Oh, great, is the problem like how much would you pay for it at the end?” And it does work sometimes as well. So like we’re working on another product now that we actually got the idea from talking to our customers, different customer advisory boards, they’re like, “How can you help us share data between two partners? And we’re like, “Well, that’s an interesting idea, maybe we could help you there.”

Tina Arantes: And it’s turning out to be more successful and more people are willing to pay for it. Because of the hard work we put in, checking with a really large client base that this is going to be interesting or an urgent problem to solve and something they’re willing to pay for. So that is why I think listening to your customers, as a product manager is one of the most valuable things you can do. And the first step in creating products like people actually want to buy. So yeah. And we’re also hiring on our product team here. Definitely engineering team here. So if you want to chat later about any of this, I’m happy to talk more.

Eloise Dietz speaking

Software Enginere Eloise Dietz gives a talk on lessons learned from becoming CCPA compliant at LiveRamp Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Eloise Dietz: Hi, everyone. My name is Eloise Dietz, and I’m a software engineer here at LiveRamp. I’ve worked here for about two years. And I’m currently on the data stewardship team. Our team is responsible for ensuring that LiveRamp systems use personal and company data ethically. And right now that means working to make sure our systems are privacy compliant. If your company works in personal data, you’ve probably heard of them, GDPR, CCPA. So I’m going to talk a little bit about what this privacy compliance looks like and why it’s relevant to software engineers.

Eloise Dietz: So first, a little bit of background. LiveRamp takes data privacy very seriously, partly because we think it can be a competitive advantage. We work in data onboarding, which means that we help companies advertise to their users online, which means that they can better personalize their ads online. Studies show that consumers actually really prefer this ad personalization and a more of a customized experience. And it can be a guarantee, or it has a higher likelihood of a higher return on investment. However, there’s also losing, people are losing trust in technology companies. And research shows a majority of people worry about how tech companies are using their personal data.

Eloise Dietz: In fact, one study found that 80% of people will leave a brand if they think that they are using their data without their knowledge. So companies in ad tech, like LiveRamp have to deal with this dichotomy. And they need a way to resolve this problem and gain trust back in their users. And I think that GDPR is a really important step in this direction. So, GDPR is a data privacy law that aims to regulate data in the EU, and it took place on May 25th of this year. So CCPA is kind of the California equivalent to this GDPR. And though it has many differences, it also incorporates a lot of the same ideas. It will take effect January 1st of next year.

Eloise Dietz: So a lot of other states are following California’s example, and also have privacy bills in the process. A lot of other countries are also inspired by GDPR around the world and are going through the process of introducing their own privacy laws. More are expected to follow. So as you can see, GDPR is kind of inspiring an overall shift in regulation of data privacy. And in the US alone, 68% of multinational companies have spent between 1 million and 10 million getting ready for GDPR. As CCPA approaches, only 14% of US companies say they are fully compliant despite its similarities to GDPR. They plan to spend another 100000 to $1 million becoming compliant.

Eloise Dietz: So we can see that these laws are really causing a big shift in how companies think about data. And the reason that is, or we can look into why that is by looking at some of the key GDPR requirements. Obviously, GDPR incorporates a lot more than this, but I thought that these were some of the most relevant to software engineers. So, the first is data minimization. Or the idea that we should only collect the data on users that we need to solve a certain task and then delete that data as soon as the task is accomplished.

Eloise Dietz: The next is that data subjects or individuals have certain rights to interact with their data. So they have the right to access the data or retrieve all the data a company has on them, they have the right to restrict processing of that data or opt out, they have the right to delete that data. And they even have the right to rectify the data if they think it is incorrect. Then finally, users have the right to be notified of data collection and the use, that data is going to serve. And if you got a ton of updated privacy policies this year, it was probably from this part of GDPR.

Eloise Dietz: So you seem kind of like standard practices. But they fundamentally change how a lot of companies think about data, the companies in a data graph mode, they might not even realize what personal data they have on people, nonetheless, what it’s useless for and how to collect it and return it to an individual if they asked for it. So this is what data privacy does not look like and what data privacy actually looks like is constantly asking yourself these questions as you build systems.

Eloise Dietz: So the first step is understanding what personal information that you have, and that your system processes. Or associating with that data, why it was collected, where it was collected, and what use it’s going to serve. Data minimization is probably one of the most relevant to software engineers. It means reviewing your data and deleting it, when it is no longer needed. But this also means not logging, personally identifiable information, it means when you store it, not storing it raw, storing it pseudo anonymized, means restricting access to that data to only those who are required to use it.

Eloise Dietz: And it means not using real data in your dev and staging environments. And finally, also automating user rights for deletion, restriction, processing and access. And so at LiveRamp, as we kind of went through this checklist of how to make our systems privacy compliant, we realized that there are some cases where we even need to go beyond the law, beyond GDPR and CCPA, in order to design for the privacy of the end user, not just designed to make our systems compliant by these privacy laws.

Eloise Dietz: So the first one of those instances was reading a privacy vision to hedge against the many data privacy laws that are expected to come out. So, for example, these laws are going to differ. CCPA and GDPR differ in many ways, and sometimes, even completely contradict each other. One example of when they differ, is this right to opt out. So CCPA says people have a right to opt out of data processing, whereas GDPR says people need to actually give their consent and opt in before data is allowed to be collected.

Eloise Dietz: I think that for users, understanding the way that you can opt out. So many different privacy laws is an undue burden on the users. So, LiveRamp decided to have a global opt out repository, where we, if someone wants to opt out an identifier, say a mobile ID, cookie, or email, we pseudo anonymize that information and store it in a global repository. This means that deployments in the EU as well as nationally in the US can check to ensure that they’re not processing data over any identifier that is in this global repository. So going beyond the laws and having a clear privacy vision that opt outs will apply globally not only made our LiveRamp systems more straightforward, but also ensures that the end user is actually receiving the privacy that they’re expecting.

Eloise Dietz: Second, never let privacy come at the expense of security. So in the effort to make users be able to better understand what data companies have on them, laws like CCPA and GDPR may actually be opening up this data to bad actors and more vulnerabilities. For example, the right to access their own data means that someone could make a fake this request and maybe receive another person’s data. So I think users may not understand that this security is at the risk of privacy. And it’s up to the, this privacy comes with the risk of security and it’s up to companies to make sure that this does not happen.

Eloise Dietz: So finally, embedding privacy into the user experience I think is an important place companies can improve on. So especially the ad tech ecosystem is incredibly complicated. This infographic shows the number of ad tech players has increased significantly over the years. Users shouldn’t have to understand how all 7000 players interact in order to understand their data privacy rights. A survey went out after GDPR that asked users what their biggest complaints were and the study found that most people’s biggest complaint was the long overcomplicated privacy regulations.

Eloise Dietz: And though these may be required, sorry, privacy policies. And then though these policies may be required by law, I think that the system should be designed to incorporate the end users privacy in mind, and make it easier to work with the systems in order to find the best privacy policy. So this doesn’t necessarily mean having a accept all or opt out of all policy that often doesn’t work with like most people’s privacy. And it also doesn’t mean having so many different privacy settings where you really have to understand the privacy law in order to understand what you want. It means designing for the end user and creating a concise, intelligible, transparent and easily accessible way of working with the privacy, working with your own privacy settings for that company.

Eloise Dietz: So my end takeaway is to take GDPR and CCPA as a way to rethink your data usage, but also looking beyond these privacy laws and consider the end user when designing your systems in order to truly protect their data privacy.

LiveRamp Girl Geek Dinner

After bites and drinks, girl geeks enjoyed lightning talks from women in various parts of the org at LiveRamp Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Akshaya Aradhya: Now, that the first half of our session is over, does anybody have any questions for the speakers?

Audience Member: Quick question for you. I actually didn’t realize data minimization [inaudible] example because [inaudible] users [inaudible] out [inaudible] that even an option [inaudible] data minimization?

Eloise Dietz: A user opts out, as in the fact that we’re still maybe storing like a pseudo anonymized identifier?

Audience Member: Mm-hmm (affirmative).

Eloise Dietz: So the idea is that personally identifiable information, I think this is right. The idea is personally identifiable information needs to be minimized. But when you pseudo anonymize an identifier, it no longer counts as personally identifiable. So by storing that anonymized version, it no longer kind of counts as the process, I believe, is for opt outs.

Erin Friesen speaking

Software Engineer Erin Friesen gives a talk on destroying an entire build ecosystem to leading the engineering wide initiative to protect and improve that very same system.  Erica Kawamoto Hsu / Girl Geek X

Erin Friesen: Hello, I’m Erin. I’m a software engineer on the infrastructure Platoon, I’m working [inaudible] DevOps. And I have an obsession with making builds easy. It’s absurd. All the engineers here can say that I’ve authored them with everything. So I’m going to talk about how I got to that point, and a lot of the mistakes I made along the way. So next time, you have to do a migration, you don’t have to do them.

Erin Friesen: First off, I’m going to be talking about Jenkins. Jenkins is my best friend. If you don’t–anyone here know what Jenkins is. Yeah. So Jenkins is basically a tool to get servers to do what you want them to do. If you’re like, “I want to deploy this, send it here. I want you to set a cron job, do this, I want you to build this do this.” That’s what it should be. So we start our journey with a horrible Slack message. I snapshoted the wrong thing. And I don’t have a backup, and we don’t have our configurations. We’ve lost our builds.

Erin Friesen: As you can see, Jenkins is on fire there. And our last backup had been 10 months previously, record everything on the master server. And we had just demolished that. So we panicked, we figured it out, we got our builds back, but realizing that we are storing our configurations, the core thing that we need to do to deploy on the thing that if it goes down, it breaks it, not the best situation. So, we came up with a solution, Jenkins files. So basically, it’s codified builds, you put a Jenkins file into your git repository, it lives there, you can take Jenkins down in a heartbeat. I almost did that as a demo. But I didn’t want all those users to panic.

Erin Friesen: And instead of storing your configs in a UI like this, you get seven to eight lines of code. And that’s your entire build configuration, which is pretty awesome. And it’s very replicable. You can version your code, you can pick a library, it’s so much more control over your environment. So previously, these are my steps to get there. Let me say this was one of my first larger, like known visible projects that I’ve ever lead. Here are my steps. I create a product, I just have the teams do it themselves. And then I’m done. Easy, right? Not quite.

Erin Friesen: So first off, I skipped over scoping out the size of the migration. I didn’t realize how large the project was and how different it was. I’ll give you a scope. We have over 250 Java repositories, you have over 150 Ruby on Rails builds. All of these builds have PRs and master builds. So if you do the math, that roughly puts the 700 things that you have to migrate, that you can’t break because if production breaks, you can’t deploy a fix, you’re in trouble. So I didn’t scope out the size of the project. It led to some very troubling times.

Erin Friesen: And the second was, I did not ask for input from engineering team until I was well into development, a lot of about listening to your stakeholders. I didn’t know what they needed, or what they actually wanted from their builds. But I was like, I know better. I’ve seen a Java build. You’ve seen one Java build, you seen them all, right? No, that’s definitely not the case. And lastly, I didn’t ask anyone for help about their experiences with it, what they’d done to actually build it, other people had experienced Jenkins, but I sort of ventured on my own thinking I could plow my own path.

Erin Friesen: That didn’t work out too well, either. And so, a lot of this boils down to I didn’t communicate with people. I didn’t ask them, and I broke a lot of things. And I’m still very sorry, you guys are watching this later. And I think lastly, I assumed that the teams would do the work. Like, I assumed that if I presented the seven lines that I needed to do, everyone would adopt it, everything would work, and everyone would go in the same direction at the same time, and it would be fine. That’s not it. Because guess what, everyone’s builds are different. They’re unique. And they’re just different and unique.

Erin Friesen: And I assumed they would do that. I also didn’t assume that they didn’t want what they had, they wanted something better. Like, you want to build your own solution. And you want to have power over how you deploy and where you deploy. And I didn’t listen to any of that. I mean, I didn’t listen. I also pushed changes without telling people because I didn’t version at first, it was, I didn’t listen, and I didn’t communicate with the team. So that was like the biggest thing if you to take away anything from migration over communicate and like, talk to everyone, and I mean everyone.

Erin Friesen: So these are my steps to a new successful migration. Do your research. I didn’t. So, I didn’t break down my problem. I didn’t even figure out where my share was like, what? Where should I be living? Like, what needs to get done, and what’s broken? What can stay broken? And talking to everyone, I just didn’t think about it. Didn’t break down the problem into injectable sizes. And I couldn’t get the iterative feedback because I didn’t check. I was like, “I’m going to roll into this. And it’ll work.” Which leads into break up the project into bite size. Because if you know what you’re getting into, believe it or not, you can break it up into smaller parts.

Erin Friesen: I’m a rock climber. And so, whenever I go outdoors, I go, and I look at the mountain. I’m like, “Cool, what do I need? I need to be able to solve this section of the climb and the section of the climb.” And this is how I get to every single portion. And I always break it down into bite sized steps because you’re like, “Oh, it’s only one reach, or two reaches or I don’t know, a high knee, like pick a move.” And it works a lot better to get to the top.

Erin Friesen: And if I haven’t said it enough, communicate, just communicate with everyone. I didn’t get feedback early enough. I didn’t iterate on feedback. And I created a doc, a roadmap for it. When I’d already been working on the project for four months, like that wasn’t the efficient way to do it. I got excellent feedback from stakeholders. But it took me too long to get to that point of starting a feedback cycle.

Erin Friesen: The next two come hand in hand. Rollout gradually. And at one point in time, I had 355 PRs open, various repositories, so I created a script to create a PR to inject my one size fits all Jenkins file. And there was no back out, like it’s hard to rewrite those. And it was broken, it was hard because I didn’t version it, I didn’t have an interface. And so, if I had to make a change to a function, I had to make 355 individual commits to everything, they’re starting to get customized. So I didn’t have a rollout plan, which means I also didn’t have a backup plan. If I needed to roll back what I was doing.

Erin Friesen: So, successfully, you need to have backup, you need to be able to bail if a rollout goes bad. And finally, you just iterate and repeat over and over and over and over again. And if you keep these steps in mind, the best thing is, everyone wins. Everyone gets the product they want. You don’t waste cycles on trying to build something that they don’t want. And you actually get help along the way and it speeds it up. So that was me about how to migrate way better than me.

Akshaya Aradhya: Questions for Erin?

Erin Friesen: Part of it, the story, oh, it didn’t have the date on it. It was 2018. November, 2000–no, November, 2017, it was right at the end.

Akshaya Aradhya: Before Thanksgiving, okay. Any other questions? All right.

Rachel Wolan speaking

VP of Product Rachel Wolan gives a talk on the evolution of privacy, discuss what it means to build products intended to protect consumer privacy globally, and the design decisions we make along the way.   Erica Kawamoto Hsu / Girl Geek X 

Rachel Wolan: Hey, everyone, my name is Rachel Wolan. And I’m the VP of Applications for product. And I’ll echo what Tina says, we’re hiring. I’ve been here about five months. And I think Eloise did a great job of kind of helping everyone understand a lot about the regulations of privacy. Today, I’m going to talk a little bit about, like the history of privacy. So I will kick this off by telling you a very private story.

Rachel Wolan: So maybe over Christmas, I got engaged. And before I asked my partner to marry me, said yes, I had to get through her parents. And I was way, way more nervous about this stuff than talking to her. I’ll tell you a little bit about her parents. They’re from Singapore, they’re native Chinese. And I’d met them twice. I had a lot of things going for me. So, I sit down with her parents. And I’ve managed to, it’s Christmas. And I got all the kids out of the house, like they went to the bathroom, is great. I had like 15 minute window.

Rachel Wolan: And I was really looking for, not permission, but their blessing. So I sit down with them. And I say, “Hey, I’d really like to ask your daughter to marry me.” And mom’s like, “Hey, I’m going to sharpen my pencil.” She like, basically pulls out a list of like, 20 questions that she wants to ask me. Just asking me what were your past relationships like, what, like, do you have kids? I’m like, “No, no kids,” “Do you want kids? When are you going to have kids?” Like, all these questions.

Rachel Wolan: And like I think I’m doing a really good job. And this whole time, she’s actually translating in Cantonese to Mr. Chia. And I think, okay, I’m like, her mom’s like holding my hand, things are going really well. And I’m like, “Okay, this is over. She’s about to give me a blessing.” And then all of a sudden, Mr. Chia’s English gets really good. He looks at me, and he says, “What do you do for a living? How much money do you make?” And this is not something that like even I talk to my parents about. And it kind of struck me that privacy is really contextual.

Rachel Wolan: And I tell this story because privacy isn’t like one thing. It’s not something that is just regulated by one country or a group of countries, it’s something that is very meaningful to each individual. It’s different based on your race, your age, your gender, your socioeconomic status, your sexual orientation, where you live, where you’re from, like what religion you grew up in, really everything. And privacy is, each person’s privacy might even change over time.

Rachel Wolan: And, what I think is also, like, an important context about privacy is it’s a relatively new concept. So I’m going to show you guys some really cool technology that has helped evolve privacy. So the first is the printing press. The silent reading was really, one of the first forms of privacy, where people kind of had like, internal thoughts that they weren’t there, maybe they were writing them down, maybe they weren’t writing them down. And that really took like, 500 years to evolve.

Rachel Wolan: Internal walls were huge for privacy. Previously, it had been like, kind of that one room house where people lived, and they kind of all slept in the same bed for a long time in the entire house, and, like, fast forward to the 1900s. And the camera came around. And the concept of the right to privacy actually came to being. And what I think is interesting about this is that we didn’t really even put laws into place around privacy until post Watergate, right, like 1974.

Rachel Wolan: And then fast forward to today, AT&T, is, like, you can pay AT&T 30 bucks to opt out of ad tracking, but most people don’t do that. It’s really, the concept of privacy has evolved. And, I think, really, you have to think about privacy from like the standpoint that there’s a value associated with privacy and people are willing to trade privacy, there is a currency. And how many Millennials are in the room. If I offered you a pizza for three of your friends’ email addresses, would you… That’s what I thought.

Rachel Wolan: And so, I just spent a couple of weeks in China. And if you go to almost any street corner in China, you will see these cameras. And what they’re basically doing is tracking, what do citizens do? Did they walk across the street, did they jaywalk? I jaywalked, like this morning. So my social score will go down. Did they go through a red light, and all of these characteristics are being collected as part of a social privacy score, right, a social credit score. And so, really, in this case, one of the reasons why China introduced a social credit score is because in 2011, I think I saw some stat, two out of three people were unbanked in China, they really wanted to accelerate, people getting credit and being able to buy houses.

Rachel Wolan: And so in 2015, they actually made their data, their privacy data available to eight companies, including like Ant Financial, which is owned by Alibaba. And so today, I was talking to one of my co workers about his social credit score, and he was saying, “Well, I definitely don’t yell at my neighbors, I don’t park in a parking spot that’s not mine. Because that’s going to ding me and I want to, use the whatever the version of TSA Pre check is, right, if you have a high social credit score, you get a better line at the airport, there’s a different car on the train, there’s even a different–you can like skip the line at the hospital.” So there’s a lot of benefits. And, really like privacy can be traded for societal value.

Rachel Wolan: So, then the question is, I did a lot about design in our product org. How many people here have designed apps for Android or products for Android? So you know it’s really freaking hard. And I would say designing privacy is a 10X problem of them. And so, this is actually was a pizza study, where people were, there are 3000 people that were asked to trade their friends’ email addresses for pizza. Like 95% of them did. And that’s kind of like what I think is interesting here, because Tina aptly said, like, ask your customers what they want.

Rachel Wolan: But the most interesting thing about the study is customers actually said, “Oh, no, I would never do that.” Like the people in the study said, “I would never get my private information.” And then they target those same people. And they all did. So, this is one of those situations where you really have to actually think–was anybody in here familiar with privacy by design? Cool. So privacy by design is, it is a framework that you can use in order to start thinking about, does my product really protect the privacy of… So you can think about it at the very beginning and discovery and start asking questions, to try to understand the needs of your users. And look at it as kind of like a review process. We have a data ethics team at LiveRamp. We have what’s called a cake process where you can actually start to think about like, a probe through right before you even start building. Does this match our privacy standards?

Rachel Wolan: And then, I think a lot of the government laws that have been put into place, right, from the perspective that it raised our awareness of–around privacy, but it’s really our responsibility. And so, I’ll leave you with one final thought. So, this is actually privacy. Our phones are just like spraying our private information at all times. And so, like, try this, like brief experiment, turn off location services on Google. Does it still work? So I did this for like two weeks, and it kind of drove me crazy. And what’s interesting about this is, I actually had to go into a separate set of settings to completely turn off location services.

Rachel Wolan: And the cynics may say, “Oh, it’s because Google wants to track you. They want like all your data so they can sell your data, blah, blah.” And I actually think that this was really a design decision. Because they knew that you actually want that blue dot. And you want that blue dot, because you get value from it. You’re willing to trade your value, and maybe even go and kind of look and see. Like maybe you don’t want to trade all of your location data, but maybe some of it, for that value exchange. So, in conclusion, treat data like it’s your own, and make privacy happen by design. Thank you.

Akshaya Aradhya speaking

Senior Engineering Manager Akshaya Aradhya gives a talk on managing a geographically distributed engineering team at LiveRamp Girl Geek Dinner.   Erica Kawamoto Hsu / Girl Geek X

Akshaya Aradhya: Hello, everyone. My name is Akshaya. I’m the IT manager for the integrations group. And I work with people like Jeff, Sean or head of engineering, Andrew, who’s our biggest women ally, here. He has three daughters. And when I told him we are hosting a Girl Geek X event, he’s like, “Woo-hoo.” So, that’s Andrew right there. And Jacob, who’s in my team, he’s awesome. And he’s supporting all of us. And I work with all these people every day. And I want to talk about how I manage distributed teams. And my of champagne.

Akshaya Aradhya: That I want to give a glimpse of how many offices we have globally. So these are camping experience. We have social, there’s a doctor in the office. We have a lot of fun [inaudible]. Our New York office, we’re on Fifth Avenue where all the shopping malls are. Philadelphia. Seattle. Burlington. Arkansas. Erin Bodkins was supposed to be here. But she had another commitment. Paris. There is a lot of French people in my team. London. Asia, Pacific, China [inaudible].

Akshaya Aradhya: Because I knew how loud they were. So, let’s talk about all these teams that you just saw, right? So I manage two teams, I’ll soon be managing four teams. And most of the, like both the teams that I manage are currently in within United States right now, but may spread out to China. So this is the headquarters where most of my team sits, but not all of them. There are some people out there in the New York office. And there’s one in Philadelphia, and, I also talk to the people in Arkansas, because I like them, you saw how fun they were.

Akshaya Aradhya: Some of my team members, like I said, are French and they like going back to France to meet their family and sometimes work out of their homes. And is that normal for LiveRamp? Yes. But you don’t necessarily need to be French to work out of your home. So what do I do first thing as a manager, whenever I, start managing any team, I do it inside, listen first, so I kind of ask them, what are their preferences? Do they have any time commitments? Some people have kids, they need to leave at certain times, some people have soccer practice, some people need to work out for health reasons or for any other reasons.

Akshaya Aradhya: And some people, like not having meetings at a certain time, and we chat a lot during our one on ones. Jacob is nodding his head. He knows why. And so, we have all these preferences. And East Coast people have their preferences. So, how do I manage the priorities? Like how do we all deliver against this shared vision? So, I can go back and make notes. And I’m like, so if we have dedicated set of meetings for the team to talk to each other, that’s number one. You’re all one team. You all need to get along, whether you like it or not. And you need to talk. And how do you establish that, right?

Akshaya Aradhya: Before I started working for LiveRamp, I was working for a company called McKinsey right across the street. And before that, Intuit, and it’s like, each company has its own culture. 

Akshaya Aradhya: At that time, I was married, but I didn’t have kids. So just a piece of cake, right. And then I got pregnant, and then they flew me to Canada, ask me that went. My feet swelled so badly, I couldn’t fit in my shoe. And not that… And I sent a picture to my husband, once I, or two different shoes. And I couldn’t even see it. You know? And I was like, “Yeah, yeah, sure, right. The time difference, just wake up when you’re pregnant, you love waking up when you’re, like then and you like everyone you meet when you wake up. Right?”

Akshaya Aradhya: So that’s how that went. 

Akshaya Aradhya: The culture doesn’t mandate you to go and sit with someone to be productive. You could as well be on blue jeans. You can, like I made my son’s appointment after joining LiveRamp. And then I could come back can take meetings, take knowledge transfers, talk to people, be productive.

Akshaya Aradhya: You’re not judged based on where you work from. Okay, that’s number one. Second thing, as a woman who went through all of this, I kind of make sure that I don’t step on other people’s toes or schedule meetings when somebody has an important thing, okay. And if you’re working with East Coast people, I tell all my teams, you better have those meetings, before 2:00 p.m., Pacific, otherwise don’t have shared meetings. And if you do want to have shared meetings, ask that person, if it’s okay, get the Slack message saying yes, and then you’re going to have that meeting. And, make sure that you don’t keep it as a recurring one. So that’s one thing, coordination.

Akshaya Aradhya: And following the right tools, I mean, you need to, whether you follow Agile or [inaudible], whatever it is, or whatever form of Agile your company follows. I know, Agile means different things for different people. But you need to get your message across to the team, everybody needs to talk, at least for like 10 minutes a day, and share what they’re doing. And, like, after sharing work related things, you want to share anything personal, or any, anything that you want our team to know, like you are engaged or you have a baby or whatever it is right, you can now share it.

Akshaya Aradhya: And, in one of my teams, I tell people, right, just because you’re working out of San Francisco doesn’t mean that you need to sit here till I leave, or sit here till 6:00 to make a point. You’re going to work on flexible time. And I need to see what progress you made. And you’re not blocking anyone and you’re out, right. It’s value to your personal space and time while being productive and accountable. That’s what you need.

Akshaya Aradhya: Again, I’m going to share my version of what works and what doesn’t. So you can as will be micromanaging, go to each person’s desk. Or like you could start off by not asking questions, or over communicating, assuming things and get the wrong thing. And then pass it on to your team, you lose that trust, you lose that trust with, it’s so easy to lose trust when you’re managing distributed teams, then micromanaging. Who loves these people in this room? That’s what I thought. And then people start leaving, and you wonder why and the cycle repeats, if you’re not listening, if you’re not watching your team, the cycle repeats. What works?

Akshaya Aradhya: Get the wrong thing. But you learn and adapt. People make mistakes. It’s okay, as long as you’re not consistently making them, you’re okay, you’re going to learn. And you’re going to share what you learn. Sharing is not on the screen because I run out of space, but you got to share what you learn with your teams, and communicate closer. Talk to them drop. Messages on Slack or whatever messaging service you use, add any relevant process. Relevant process, not process for the sake of process. And relevant process that works for you and whoever you’re working with. Are you peer programming? Are you a software engineer? Does this process work for you? Fine. If you’re in product, maybe you’re talking to customers, there’s a different process that Tina or Rachel may use, I don’t know.

Akshaya Aradhya: But as engineers, especially here in the valley, or New York or all the places that you work, whatever works for you is the best process. That’s what I tell teams and effective collaboration, effective collaboration. Destructive feedback is not effective collaboration. Rambling is not effective collaboration. Putting down others, sarcasm, you’re maybe the best, most intelligent person. But if you’re not nice, you’re out, that’s good as that. So play nice. And teamwork. Teamwork is success according to me. If you don’t work as a team, you work in silo, you may be the best person in the world. But if your team doesn’t see what you do, or if your team doesn’t find value in what you do, you don’t have any business value with the work you’re doing or you don’t grow, you don’t let others grow, you don’t help anybody or mentor people. That’s all contributing to bad culture.

Akshaya Aradhya: One of the things that I really like at LiveRamp when somebody spoke, during my onboarding, was that if somebody sends you an email, you respond quite quickly. It’s–in other companies that I worked at, response right away meant that you’re supposed to work or respond back at some time, right? So now studying at Wharton, Sean, our head of engineering. At his level, or Andrew or even Jacob or who, or Jeff, if you send a message to them, and I work from 1:00 a.m. to 4:00 a.m. because I need to study when my son is sleeping. Some of you may resonate with that. So if you don’t, you can judge and I’m crazy, partly.

Akshaya Aradhya: But that’s my time when both my dogs are asleep, and my son is asleep. That’s my time. Okay, so what do I do? I catch up on all the emails and I told my team, “If I send you a message on Slack, or an email, do not respond to me outside office hours, unless it’s really urgent.” There have been nothing really urgent that needs a response. And I was surprised when I sent a message to Sean one day, and he just responded at 2:00 a.m., I’m like, “What did I see? Did I a response?” And I’m like, “Thank you for messaging.”

Akshaya Aradhya: And it’s like, you may choose to do that. But it’s such your own volition, you’re not forced. And I think I tell all my teams that, “If you see it, ignore it. If you don’t want to, like if you’re sleeping do not wake up, because of me. Snooze your notifications.” Yeah. And basically, there’s a saying, right, you don’t go to work when, something you really like, then you enjoy what you’re doing. It’s not really work or something like that.

Akshaya Aradhya: And I think when you join a company that values your personal space, your ambitions and offers you opportunity to grow. And you love what you’re doing. There was recently a job satisfaction survey at Wharton, where I’m studying, part-time. It’s like, in my group, and when I say group, it’s about seventy people in one section. People did a job satisfaction survey based on so many different metrics. And they were talking about organizational stuff, and how do you grow your teams? What is effective, what’s not, somewhere on this, but in a more lectury fashion.

Akshaya Aradhya: And I took a survey of my past job and this job. And it was one among the top five. And I’m thinking, “Huh, I did that, I think, right?” When you love what you do, your stress goes down, you’re happier, your kid kind of sees you really happy, right? You don’t go crazy. And you can actually do what you want to do, study, pick up a hobby, rock climbing, or do a side project on Android, I don’t know, on whatever you want to do. Don’t do that. So yeah, it’s like, the last thing I want to leave this room with, is like this.

Akshaya Aradhya: Professionally, you set an example for your team. You don’t need to be a manager, each person can be an individual. You set an example for your team. And if you overburden yourself or you don’t enjoy what you’re doing, your team can see it and your productivity goes down. So make sure wherever you choose to work or whoever you choose to work with. Hopefully at LiveRamp, because we have opening, you should choose something that will allow you to grow and be happy at the same time. And that’s what the whole talk was about and what all the speakers and organizers want. And hopefully, after this presentation, you come by and say hi to all of us and hang out with us, ask us questions, learn about us and connect with us. We would love to keep in touch, any case. Thank you.


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Girl Geek X Aurora Lightning Talks & Panel (Video + Transcript)

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Aurora garage girl geeks

A self-driving car remains in the garage as the Aurora Girl Geek Dinner kicks off with drinks and networking after hours in San Francisco, California.  Erica Kawamoto Hsu / Girl Geek X

Speakers:
Jessica Smith / Software Engineer / Aurora
Haley Sherwood-Coombs / Technical Operations Specialist / Aurora
Elizabeth Dreimiller / Mapping Operations Lead / Aurora
Khobi Brooklyn / VP of Communications / Aurora
Chethana Bhasham / Technical Program Manager / Aurora
Lia Theodosiou-Pisanelli / Head of Partnerships Products and Programs / Aurora
Catherine Tornabene / Head of Intellectual Property / Aurora
Angie Chang / CEO & Founder / Girl Geek X
Gretchen DeKnikker / COO / Girl Geek X

Transcript of Aurora Girl Geek Dinner – Lightning Talks & Panel:

Angie Chang: Okay. Thank you all for coming out tonight to Aurora. My name is Angie Chang, I’m the founder of Girl Geek X. We’ve been hosting these events in the San Francisco Bay area from San Francisco to San Jose for the last 11-plus years, and every week we really love coming out and meeting other girl geeks at different tech companies and hearing them give tech talks that we’re going to be hearing tonight, as well as hearing from them on how they’ve accelerated their careers.

Gretchen DeKnikker: Hey, I’m Gretchen, also with Girl Geek. So, whose first time at a Girl Geek Dinner? Oh. A lot. Cool. Well you should keep coming because they’re awesome. Like Angie said, we do them every week. We also have a podcast that we’d love your feedback on, and we’d love for you to rate it and all sorts of things. We cover mentorship, career transitions, imposter syndrome, getting the definition of intersectionality right, a whole bunch of stuff. So check it out and let us know.

Gretchen DeKnikker: Okay, and then we also just opened a swag store, and it’s a bittersweet story. So we have some really, really cute awesome stuff, and then we have this stuff, which is kind of cute, but poorly printed, so we’re going to find a different place. But in the interim, you can check out these really cool things. Okay, Angie, hold them up. Man, one-armed.

Gretchen DeKnikker: Okay. Water bottle. Cute, right? The little pixie girls? Okay. Notebook. That’s me on the notebook, by the way. That’s my pixie, so if you want to put me in your pocket, that’s the way you take me with you everywhere. And then the fanny pack, which I’m way too old for, but it is so cute. Everybody needs this fanny pack. Oh, and then there’s a little zipper bag. That’s my favorite thing, that’s why we have to show it to them. Look at the little zipper pouch for your pencils and you Sharpies and your Post-Its. Oh, we have Post-Its.

Gretchen DeKnikker: Okay, and iPhone cases. All this crap. Anyway, check it out because we put a whole bunch of work into it and we would love for people to have the stuff that they said they wanted. Okay. So without further ado, so we have got the CEO, his name is Chris Urmson, you can also call him Dr. Chris or Mr. Woke AF, so please join me in welcoming him.

Angie Chang: Oh, and really quickly, this is … okay, really quickly, this is a sold out event, so if you are liking this event, please help us tweet. The hashtag is Girl Geek X Aurora. If there’s something great that he says or any of the girl geek speakers to follow, please help us tweet and share the word that this amazing company is doing really interesting things. Okay do that thing again.

Chris Urmson: Thank you. After that introduction, I feel like I can only fall on my face. So first, thank you for Girl Geek partnering with us to pull this off tonight. Thank you all for coming tonight. This is my first Girl Geek event, and we’re just thrilled to have you here. We’re building something exciting in Aurora, we have this mission of delivering the benefits of self-driving technology safely, quickly, and broadly. We’d love to share that with you.

Chris Urmson: What I’m really excited about is, a lot of time in the press, what you hear about around our company is our founders and about the technology, and I’m proud as hell that we get to show off some of our awesome people today. And I was told I’m allowed to be just blunt about this, we are hiring like crazy, and we are looking for awesome people. So if you enjoy talking to these people and hearing from them, and seeing the work that they’re doing, please come join us. I think you’d love it here, and we would love to have you.

Chris Urmson: So without further ado, I’m going to invite Jessie to come talk about cool stuff.

Jessica Smith speaking simulation

Software Engineer Jessica Smith gives a talk on what her simulation team is working on at Aurora Girl Geek Dinner. Erica Kawamoto Hsu / Girl Geek X

Jessica Smith: I have a mic. So I don’t think I need that mic. Is my other mic on? All right. Sorry. Hi, I am Jessie Smith. I am on the simulation team at Aurora. And we’re going to find out if my clicker works.

Jessica Smith: So a little bit about me is my background is, I’m from Nevada, I’m from Reno, Nevada. I got a master’s degree from UNR in high-performance computing, that weird animation thing is a forest fire simulation, which is what I did my thesis in. I have some other experience in autonomous systems, mainly autonomous drones in grad school, and then on to Uber’s advanced technology group working on simulation, and now at Aurora working on simulation.

Jessica Smith: So I’m going to talk a little bit about what is simulation, and we have three main things that we do on the sim team. We are a developer tool, we do regression testing, and we do problem space exploration. So for developer tool, we build custom tests for developers to help enhance what they do on a day-to-day basis and make them faster at developing the self-driving car software.

Jessica Smith: And then as soon as they land these new features, we go out to make sure, just like every other regression test, that when you land a new one, you don’t break all the old ones. So we also do regression testing. And what I’ll talk about today is problem space exploration, which I think is one of the most interesting things that we get to do at Aurora on the sim team.

Jessica Smith: So, this video here is going to be an example of a log video, and you can see this pedestrian kind of walks into a car, opens the car door, and disappears inside of the car. And so what we’ve done in simulation is extracted the information about the spirit of the scene, and what we can do in sim, which is really, really powerful, is take this interesting encounter, where a man walked in front of the car, and instead say, “What if it’s a mother and a stroller?” And, “What if it’s a person with a bicycle?” And you can actually explore the problem space and make sure that the self-driving car does the right thing, given the insane variation of the inputs to the system.

Jessica Smith: So another example is, we can vary the behavior of the other actors in the scene just based on things like velocity or position, and so you can make sure that the car is capable of making a lane change, when it should lane change in front of another car, between two cars, or behind them, given the state of the other vehicles and what is the safest thing to do.

Jessica Smith: We can also do some sensor simulation, which helps us determine what are the capabilities that our sensors need to have, and what is the fidelity that we need to have of those sensors? Like, do we need to be able to detect … you can’t really see it in this picture because it’s tiny, but you can detect the tiny individual bike spokes on this bicyclist in this sensor simulation. So what we get to build moving forward, and what my team is hiring for, is scaling out simulation. We need thousands and thousands of these tests, and we want to build realistic world modeling, and that’s better act of behaviors in the scene, but also better 3D representation of the world.

Jessica Smith: And then we want to crank the fidelity way up and do really interesting high-fidelity camera simulation. And this image on the far left here is purely synthetic, but I certainly can’t tell the difference.

Jessica Smith: So now I’m going to hand it over to Haley to learn a little bit more.

Haley Sherwood-Coombs speaking

Technical Operations Specialist Haley Sherwood-Coombs talks about machine learning datasets and the perception platform at Aurora Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Haley Sherwood-Coombs: Hey there, I’m Haley, I’m going to talk about machine learning datasets, and our tricks here at Aurora. A bit about me, so I’m in technical operations here and I work under perception platform. I have a background in operations management and information systems from Santa Clara University, and I’ve been here at Aurora since April of 2018.

Haley Sherwood-Coombs: So our team mission is to provide abundant, high quality machine learning datasets to fuel machine learning. And I want to pause on the word fuel. At Aurora, we talk a lot about fueling rockets, which [inaudible] off the saying, “Don’t try to build a ladder to the moon.” What this is getting at is that building a ladder makes very small progress. Small progress which is gratifying to see, but will never practically reach the goal.

Haley Sherwood-Coombs: At Aurora, we believe the way to actually get there is to build a rocket. It will initially appear to make little visible progress, but once carefully built and tested, it will cross the quarter million miles in a matter of days.

Haley Sherwood-Coombs: So how does this fit into the scheme of perception platform, and where I do most of my work in machine learning datasets? So the machine learning datasets are the rocket fuel for our rocket. The metrics are the launch pad, and the models are the engine. So in the machine learning datasets, it’s the creation of meaningful data. So what can we do to input the best data into our models? Metrics is the offline assessment of perception, so making sure and double-checking that the machine learning datasets are going to be great for our models, and accurately assessing these models and having value identification on these.

Haley Sherwood-Coombs: And the models is real time. It’s our Aurora driver. It’s real time action machine learning. So jumping into machine learning datasets. In order to get this data, we have to look at cameras, radar, and LIDAR, and this is where we get the returns for these labels. Our sensors are strategically placed all around our cars to eliminate blind spots and optimize our field of view. Most of the times, we put these so that we never have any blind spots.

Haley Sherwood-Coombs: So looking into data curation a bit more. Our tools allow us to collect high quality annotations, and we care more about high quality and fewer, within a larger amount of lower quality annotations. To curate the best data, we align across our organization. We look across teams, and also organization-wide to see what is feasible, and what will provide the most impact.

Haley Sherwood-Coombs: Diving into a bit of the models here. So here are two examples of our Aurora perception system. Right here on the left, you can see our car. Well when it rolls again, it will then yield to a pedestrian right here. It’s able to track it, stop, and yield, and wait until it passes, and safely drive again. You can also see that it then starts picking up all these other cars that a normal human driver wouldn’t be able to see until it was like mid-way.

Haley Sherwood-Coombs: On the right here, our perception system is tracking cyclists 360 degrees around the car. Normally if you were driving, you would have blind spots and wouldn’t be able to see your cyclist here or here, but having an autonomous system, it’s able to do that.

Haley Sherwood-Coombs: Metrics. This is the quantitative language that binds everything together. So we have our models, we have our data, now we need to make sure that these are doing the best they can. So we look at the impact that every single piece of data has on these models in the machine learning, and identify confusion and what changes need to be made. If something’s right, if something’s wrong, we go back and run another model on it.

Haley Sherwood-Coombs: So finally, where we culminate is the Aurora Driver. As you guys know, it’s our goal to put self-driving cars on the road safely, quickly. Here we go. Thank you. Next up is Elizabeth.

Elizabeth Dreimiller speaking

Mapping Operations Lead Elizabeth Dreimiller talks about the work of the mapping teams at Aurora Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Elizabeth Dreimiller: Hey everyone. So I’m going to be talking a little … pretty briefly about Aurora’s work with high-definition mapping. So a little bit of background around me. I grew up in Ohio, and as a kid, I absolutely loved maps. So whenever I got the opportunity to go to a park or go to a different state, I would just grab a paper map and literally would go home and put it on my wall. And the funny thing about this is, I actually never had a map of Ohio, because it’s so flat and boring, there’s no reason to.

Elizabeth Dreimiller: So that kind of led me on my career trajectory today. I went to school for GIS, geographic information systems in Pennsylvania. And then after school, I went and worked with the mapping team over at Uber before moving on to Aurora.

Elizabeth Dreimiller: So here, you can actually see our mapping software in work. You can see the operator is placing down points, and they’re going to be drawing lines that show the curve placement, where are the paint lines that we need to be paying attention to? So that’s the yellow center divider down the middle. And you’ll see as this image goes on, they’ll be placing lanes that our car pays attention to.

Elizabeth Dreimiller: And a lot of people, when they think about maps, they simply think of how to get from point A to point B. Our maps are that, but also a lot more. Our Aurora Driver needs our maps to understand how it works, or how it relates to the world around it, what it needs to pay attention to. So we’re placing traffic lights and a ton of rich information.

Elizabeth Dreimiller: So a little bit of breakdown about our team. Our mapping team is broken down into two different core teams. We have our engineering team, and they kind of work on making sure the logic is in place, that the Aurora Driver can understand and actually create the tooling that we use. So in the image to the right, you can see an operator moving a lane around to make sure that the trajectory of the lane is appropriate for the vehicle.

Elizabeth Dreimiller: On the other side is our operations team. And operations team is pretty neat. A lot of people think that it’s just creating the map content you see. And you can see all the different rich layers that we have. So we have the ground data, that’s actually LIDAR-processed data. And then we go into traffic lights and all the different lanes and paths. And then finishing off with remissions logic. A lot of rich information.

Elizabeth Dreimiller: But not only are we producing that, but we’re also coordinating all of the collection of this data. We’re making sure we’re running through quality assurance as well as maintaining hundreds of miles of map, and making sure they never go stale.

Elizabeth Dreimiller: So a brief overview of the challenges we face. I’m not going to over all of these, there’s a lot. I’m going to focus on three. So the first one is safety. So we’re producing all of these miles, how do we know that what we’re producing is of quality? And that’s when automatic validation comes into play. So our engineering team and our operations team is working on making sure we have a very good set of validations in place, both automatic and human in the loop, to make sure we’re catching everything.

Elizabeth Dreimiller: So second is quality, and with that comes speed. We want to make sure these hundreds of miles, obviously, are the highest quality, if possible. But also with that, we want to make sure we’re not sacrificing speed. So we want to make sure we’re creating tools and processes that allow us to speed up while maintaining that bar of quality.

Elizabeth Dreimiller: And lastly, policy. As you know if you’ve driven outside the state of California, every state kind of requires a little bit different interaction from their drivers. There’s laws. So we focus on trying to understand how we can create a broad policy on a highway map to fit a large geographic region. And at the essence of it, safely, safely, quickly, and broadly, is all about Aurora. We work on [inaudible] maps.

Khobi Brooklyn: How about now? Oh great. I’m Khobi Brooklyn, I’m on the communications team here at Aurora, so now in the technical part of the business, but in the part of the business that does a lot of work to reach out to folks like you and make sure that you know all the good work we’re doing here at Aurora.

Khobi Brooklyn: So I’m going to bring up a panel of Aurora women who come from all parts of the business, and we’re going to talk a little bit about brand, which is something I know a lot about. That’s what I think a lot about. But the reality is, every single one of us has a brand, and it has a huge impact on our career and how we show up at work.

Khobi Brooklyn: So I’d like to bring on some Aurora folks. We’re getting mic’d up, so it might take just a minute.

Khobi Brooklyn: Okay. All right.

Chethana Bhasha: I can get you … oh, yeah. I’m on.

Khobi Brooklyn: Is that pretty good?

Chethana Bhasha: I think so.

Khobi Brooklyn speaking

VP of Communications Khobi Brooklyn talks about personal brands, citing examples like Beyonce, Alexandria Cortez-Ocasio, and Nancy Pelosi, at Aurora Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Khobi Brooklyn: Okay, cool. So we’re going to talk a little bit about brand and building a personal brand, and what that means, and how that can have an impact on your career. And I think what’s interesting is, a lot of us have a brand, but maybe we don’t think about it because what is a brand? Right? We often think about companies and what a brand is at a company, but the reality is is that we all show up in some way, and so really, when it comes down to it, it’s how you show up.

Khobi Brooklyn: So here are three women that have incredibly strong brands, right? Beyonce is perfection, many would say. Alexandria Cortez-Ocasio, I think, is really real, right? She tells us all that she makes mistakes, but she also is unapologetic. And Nancy Pelosi is a great example of, I’d say, in the last year, she’s done a lot of work to reshape her brand. To be a boss, I would say.

Khobi Brooklyn: But we’re not here to talk about them, we’re here to talk about them. So we’re going to start with … well, and then a woman is really anything she wants to be. So at the end of the day, your brand is whatever you want it to be, and I thought that we could start by talking to these four women, and hear about who they are, and how they think about their brand. And ultimately how, as they’ve shaped their brand through their career, it’s helped them end up at Aurora, and helped them end up in the careers that they’ve had. All of them have really interesting work experience, and have taken very different paths to get to Aurora. So Chethana, we’ll start with you.

Chethana Bhasha: Sounds good. Thanks Khobi. Hello everyone, and welcome to our Aurora space, and then into this space where exciting things happen, as you can see one of the products right there.

Chethana Bhasha: Me, my brand, I should say, if you see me, I’m walking around the whole office talking with cross-functional people, interacting and then building things. I’ve been always curious, I wanted to know where, when I’m building some items, where it ends. So I want to see the end product. So that said, being a controls background engineer, I have worked on many products. And building those products, so I’ve been in the auto industry for the last … or a decade, I should say. And I’ve seen different transformations in the technology, and it’s still transforming, and this is right here. Like me here at Aurora, because we are building the self-driving technology, the Aurora Driver.

Chethana Bhasha: So here, the company, the best part is it’s sort of like an institution, as I’m passionate about learning more and more new things, exploring new spaces, and then be part of the technology, that is what Aurora has provided me. And I’m so excited to be here because, as I said, you can see me everywhere. I’m in packing, and then I have got so many opportunities in my role as a TPM or assistant engineer, or call me anything, I wear different hats every day, every hour, and it’s pretty good to learn things, be challenged, and then make it happen safely, quickly, and broadly. So thanks for that.

Khobi Brooklyn: Cool. Jessie, what’s your brand?

Jessica Smith: So you all heard a little bit about my background. I love simulation. I was kind of bitten by the bug, if you will, in grad school, and I work a lot in a semi-social role at Aurora and in my professional life. But when I go home at night, I usually have to decompress and not talk to another human being, because I’m pretty introverted in general. And so I wear a much more social hat at work, and I do a lot of work in trying to make sure that my team is communicating effectively with our customers who are the motion planning or the perception team. And that isn’t necessarily something that comes incredibly naturally to me, but it’s a role that I fill really well at work.

Jessica Smith: And then I do have to go home and only talk to my dog for a couple hours. So I think that what drew me to Aurora was that we have a lot of opportunity for people to really be themselves and to thrive in whatever environment that they thrive in. And you can find a niche here no matter what your personal brand is or your strengths are.

Khobi Brooklyn: Thank you. And Lia, you had an interesting career. Maybe we could even say you’ve reinvented your brand throughout your career? It’s a leading question.

Lia Theodosiou-Pisanelli: Sure. Oh boy. I don’t know if I’m prepared for that one. Yeah. So I … let’s see, what is my brand? I think one thing that I’ve always been really fixated on is making sure that I am authentic, and true to who I am. And in some cases, that can be a bit serious in the workplace, and I hold myself and everybody to a pretty high standard. But I also make sure that we don’t take ourselves too seriously.

Lia Theodosiou-Pisanelli: And another piece of that is also, I think that it’s really important throughout your career to focus on getting to know people as people. And a big way of doing that is … or, a big benefit of being able to do that is ending, is being in multiple roles where you kind of straddle a line between very different organizations, between very different sort of jurisdictions in some cases in my career between very different countries or political parties. And it’s really kind of evolved over time from when I was in government to when I’ve been doing product and a variety of different companies and scenarios. But the thing that’s tied it together is really being able to connect with people and translating between different worlds. And so that’s what led me here. I had an incredible opportunity to sit at the nexus between, between business and product and technology and to be able to build out a team and a function to really kind of bring all of those pieces together. And so even though I’ve had a lot of different pieces of my career and experiences, all of that has kind of come together to be able to really deliver, I think, something pretty effective here at work.

Khobi Brooklyn: Thank you. And Catherine, you have a very interesting career in spending some time on the engineering side and now on the legal side. And how have you thought about your brand as you’ve changed and evolved?

Khobi Brooklyn, Chethana Bhasha, Jessica Smith, Lia Theodosiou-Pisanelli, Catherine Tornabene speaking

Aurora girl geeks: Khobi Brooklyn, Chethana Bhasha, Jessica Smith, Lia Theodosiou-Pisanelli and Catherine Tornabene speaking on “How to Accelerate Your Career and Increase Your Impact” at Aurora Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X

Catherine Tornabene: So, hi, I’m Catherine, my role here is head of intellectual property and the legal team, but it should be mentioned the, I started my career in engineering. In fact, I was a software engineer back at Netscape back in the day and then went to law school and also obviously worked as a lawyer. And you know, when Khobi asked me this question, my first thought was, well I don’t even remember my Twitter handle. Like I don’t have a brand. And, but you know, thanks to talking with Khobi and her team, I realized, well actually I do. And that there’s really not a lot of people who have, it’s out of a niche expertise. There’s not a lot of people who have the background I do. And so my brand really is that I have a background in engineering and in law and I use both of them really every day in my job. And so it was very interesting. I appreciate Khobi even bringing the question forward cause I think it’s a very interesting question to think about. You know, I encourage you all to think about it. I thought it was a good thought exercise.

Khobi Brooklyn: Well I think building on that often, you know, part of what a brand is, is an emotional connection, right? So it’s how you’re perceived. It’s how we’re perceived in the workplace. And I would say as a woman in business and as a woman and often at tech companies, a lot of, we get conventional methods, right? We get [inaudible] whoa, sorry about that. You know, you’re either too nice or you’re too aggressive or you’re too mean or you’re too sloppy or you’re too proper or whatever, right? The list can go on and on. And I think for me at least, and I think for a lot of us up here throughout our career, we’ve found a way to find that balance of how can we show up at work in a way to to be super effective and so that people listen and we can do really good work. And how do we stay true to who we are? Right. I think, I’ll give you one personal example. I spent the first part of my life being an athlete and every coach I ever had said, you need to be really serious. You’re here to win, put your head down and win. And I literally was told not to smile because it would waste too much energy and I needed to be putting that energy into winning the race.

Khobi Brooklyn: And so that’s how I shaped my brand in the beginning. You know, I was very serious. I never smiled. I was heads down. I was there to win. And then I got into communications and I ended up in meetings with other people and I got feedback that I was way too serious and then I needed to smile. In fact, I was literally told I needed to be a ray of sunshine in every meeting. And I thought to myself like, I’m not a ray of sunshine, that’s not who I am. Like of course I don’t want to be bitchy, but I’m also like, I’m not the sunshine at the table. And it was conflicting. Right? It was super challenging for me to find out how can I be true to who I am, but clearly I need to smile more if I’m going to be effective in the workplace.

Khobi Brooklyn: And I think that’s just one example. I’m sure everybody in this room has some anecdote of a time where they felt they got conflicting messages or they weren’t quite sure like how do I show up in this meeting? Everybody else in this meeting is in sweatshirts, but I love to wear floral prints or you know, seriously or you know, everybody else in this meeting is, is super serious and I like to crack a joke every so often. Is that okay? And so I think that’s something that we all think about. Have any of you ever had conflicting messages and how you work through that?

Chethana Bhasha: I think I can just speak as Khobi just said, I mean she, I’m too serious. Like, and for me like it’s quite opposite. It always worked. I mean keep laughing maybe and get things done. That’s my mantra. But if it needs to be done, I mean it needs to be done. And it’s sometimes like I’m in in the workplace, being like a person. I mean I feel like I need to be straightforward and open, communicate, but the opposite person might not perceive it in a good way probably. But so I have been given an advice from my superiors at my previous company that “Hey, you’re doing a very good job, you get things done but make sure you are a little bit peaceful when talking with people.” And get, okay. So I’ve tried to balance that and then try to balance those emotions and then tried to read and then get at the end, make everyone happy and then work at that same place where you see each other, talk to each other. And that’s that. That has been working so far.

Lia Theodosiou-Pisanelli: Yeah, I’ve definitely gotten that conflicting advice as well. It’s interesting. So I started out my career as a negotiator for the government and I made the mistake of sending an email to a foreign negotiating counterpart that had an exclamation mark in it. And immediately my boss came into my office and said, never put an exclamation mark in an email, you will not be taken seriously. Do not show emotion. You should never have emotion on your face unless it is intentional for the objective you’re trying to get across. Right. And so that was very different from then coming out here to tech. And it’s funny. So I was kind of chiseled into this very aggressive and intense negotiator, which I’m sure none of you can imagine given how effervescent I am right now. But all of the people who work with me, you probably definitely know that I have that in me. But it’s so funny because then I started in tech and one of my first bosses in tech, maybe a month in, sat me down and said, hey, you should really think about like smiley faces, exclamation points, just to soften your tone a little bit because it kind of overwhelms people.

Lia Theodosiou-Pisanelli: And so it’s this funny like, Oh, okay, that is what success is here. And so I think what I keep kind of going back to is what is true to myself as, yeah, I’ll say different days, there’s, there’s a lot of balance that we all have to strike. But I just try to keep coming back to being authentic and being okay with the fact that that version of myself might not be what people expect of me and definitely might not be what people expect of a woman. And so it’s really important to just be OK with the fact that you’re different and not necessarily try to blend in. And so that’s what I’ve tried to hold, hold true to.

Khobi Brooklyn: And speaking of attributes, all of you are building teams and so as you build a team and you meet new people and new candidates, what do you look for? Like what kind of brand are you looking for? Catherine?

Catherine Tornabene: You know, I think, Oh, a lot of my personal career has been driven by that. That sounds really cool. And I look for that. I think intellectual curiosity is wonderful. I love when I get people who are really interested in the world around them and who are interested in how they can have an impact on the world. You know, one of the things I love about Aurora is that we are very mission driven here and that’s something that I look for and that’s some, a lot of people who care about the world around them, it is part of a personal brand and that is something I personally look for and that I enjoy very much in my teammates. We’re lucky to have that here.

Lia Theodosiou-Pisanelli: Yeah. Similar on a similar note, I would say really people who have a growth mindset, you’re not always going to find somebody who has the exact experience and fit for the tasks that you plan to have. But really having somebody who wants to grow and to learn and is willing to challenge themselves, not just in work but who also kind of shows that they want to be better. And it’s okay that maybe some things haven’t done, they haven’t done well in the past. And it’s not that they haven’t done them well, it’s just that things didn’t work out. But they learned from that. I think that’s a really important trait in somebody on the team.

Khobi Brooklyn: Jessie?

Jessica Smith: Yeah, I think, I mean for software we focus a lot on can you program, can you program, can you program? But I also really appreciate it when I ask a candidate something and they don’t know the answer if they’re just honest about like, I don’t know what that is. And then I think it provides an interesting opportunity in an interview to work through a problem together and you get to see a little bit more about is this person teachable and can we actually have a good back and forth? And if I give you a, like a hint or put you on the right path, can you actually go and ask for enough guidance to get to the right answer? So I think I really appreciate honesty in, in the interview environment.

Khobi Brooklyn: And maybe just generally.

Jessica Smith: And generally, yeah.

Khobi Brooklyn: Cool. Chethana?

Chethana Bhasha: So on the same lines, it’s person’s willingness to learn and then also at the same time contribute because it’s on both sides, right? Like you bring your own expertise. Yes you are not expert in all but you are trying to learn more but at the same time you are trying to contribute. So that that’s what most of the time we as a team look forward for like, hey the candidate is willing to learn, have the confidence, but at the same time I mean can contribute what they have learned in their past. Bring those lessons learned. So that’s what we are looking for more to build this awesome product. Yeah.

Khobi Brooklyn: Great. I’ll just add in one for myself. You know, not working in the kind of tech space. Sometimes it’s a little different what we look for, but I would say presence is really important. It’s something that I definitely try to pick up when I meet somebody new. Presence and self awareness. And I think in the tech industry broadly, we’re all doing something new, right? We don’t know the answers to everything. And so there’s a lot of mistakes. So there’s a lot of like, Ooh, we need to rethink that. And I think that takes incredible presence to have the confidence to say “I didn’t do that quite right and I need to do it better.” Or “I think I can do it differently.” And, and I think that that can be a hard skill to build because, it’s intimidating, right? It’s, it sucks to be wrong, but the more that you can get comfortable with it and use it in a positive way, I think makes us even more valuable. We’re gonna open this up to you all, but one more thing before we do is I wanted to ask each of you to share a piece of advice, either a great piece of advice that you’ve received in your career that’s really helped you along the way, or a piece of advice that you’d love to share with this group. Who wants to start? Chethana, go ahead.

Chethana Bhasha: I think what I’ve learned from like in the past was like the, or the mantra. What I usually follow is do the things, do the things in the right way, do it takes time or you face some failures, but at the end you know every single detail of it because if so if you are building a new product then you know, oh it’s the similar lines what I did in the past, this could come up and then there is mistake but that’s fine. I can do it. So that’s one thing which I would like to just as a my, my piece of advice is whatever you are doing, be confident and do it in the right way. Do I take some amount of time and failures.

Khobi Brooklyn: Yeah. Jessie.

Jessica Smith: I think the best piece of advice that someone gave me when I was thinking about a career transition was I was trying to decide should I, what should my next thing be? And it’s really hard to look at where you should go next. And a product manager that I worked with told me you shouldn’t think about your next job. You should think about your next, next job and what jobs do you need to get your next, next job. So you look a little bit further ahead and it’s actually easier to build a roadmap to where you want to be. You know, when your next next job. And so that’s really helped me build out a much more clear picture of where I want to go.

Khobi Brooklyn: Lia.

Lia Theodosiou-Pisanelli: Now I’m going to change [inaudible] ripping it. In terms of kind of looking for next jobs actually and this was, good advice for me as I was thinking about coming here. You know, you can think about is the work interesting and can I make an impact and what will this look like on my resume and all of these things. And all of those are important. But one big thing that is really important is thinking about who are you spending the majority of your waking hours with, right? We’re spending a lot of time together and so think about the people and the culture and the environment and are you going to learn from these people? Are these people going to let you be that authentic self? Are you going to be better? And when things don’t go well, do you feel like these people are going to support you and find the right solution? And so I hadn’t always focused on that. It was important, but I was always kind of blinded by the what is the most interesting, best stuff. Good news is Aurora has all of those things. So it just so happens that the people piece was like the cherry on top. But, no, really, I think, I think the people pieces is really, is really important and that, that was good advice that I received before coming here.

Khobi Brooklyn: Catherine.

Catherine Tornabene: So I think that, I think in this one, one of the most important pieces of career advice I received was once you start down a path, that doesn’t mean you’re fixed on it forever. And sometimes those meanderings that you take along the way actually turned out to be very valuable. So if you want to, if you’re debating a choice in your career or your job, you can always give yourself the choice of saying, you know, I’ll try this and if it doesn’t work out, I’ll try something else. Because I think a lot of the times we feel often like, oh my gosh, if I do this I am down this path and I am never stopping and I’m never off that route. But that’s actually not really how things generally work out. There are very few career paths that are absolutely fixed and you can generally take another route and sometimes you might find that the meandering part is the best fit.

Khobi Brooklyn: Thank you. So we’d love to hear from you all. So if anybody has any questions, please raise your hand. We’ve got mikes I believe around, so maybe you could stand up and just introduce yourself. You want to? Hi.

Aurora Girl Geek Dinner in Aurora garage

Claudia in the Aurora Girl Geek Dinner audience asks for book recommendations for women looking to accelerate their careers.  Erica Kawamoto Hsu / Girl Geek X

Claudia: Hi, I’m Claudia. Claudia [inaudible] and I have a question related to books that you guys have have read in the past that are really impactful. I’m a sucker to to learn more about what you guys have in mind around books that will help career growth.

Khobi Brooklyn: Anybody? Top of your head?

Lia Theodosiou-Pisanelli: I just read a book called The Growth Mindset, which might influence the fact that I look for people with a growth mindset. I found it to be really interesting. Actually. I’m going to be honest, I didn’t read it. I listened to it at a very fast rate. But I found that to be really interesting because it was kind of a way of describing different frames of mind of different people, which helped me to think about how I interact with others. What is my way of approaching things and being open to the fact that I can change that, so that’s a good one.

Khobi Brooklyn: Cool. Anybody else?

Catherine Tornabene: I read a ton, but very few career books.

Chethana Bhasha: That’s what I was going to say too.

Catherine Tornabene: I actually, in a sense. My answer, quite frankly, my answer is that the books that I often finance inspiration from are stories of fiction or I actually pretty much read everything, except I really don’t like brutal murder mystery. But beyond that, and so stories that I’ve read recently have been like for instance stories about, I’ve read a series of stories about Vietnamese immigrants who come to the United States or I actually read recently a story about you know, a mom who gave her child up for adoption. I like just getting in someone else’s mind for a while, I think actually is very good for teaching you mental flexibility in general. So my general advice is not actually a specific book but that the exercise of reading something that describes and gets you into someone else’s life experience is very good.

Khobi Brooklyn: Great.

Shavani: Hi, my name’s Shavani. I just had a quick question about, we talked a bit about all of your brands and what your brands are today, but you know, as you guys mentioned, you come from various backgrounds. How do you guys continue to build your brand? ‘Cause as we all know, it keeps changing every day. So if you guys like, you know, networking or any tips or bits of advice for that?

Chethana Bhasha: Yep. Yep. So, good question. So it’s again as we said, right? Like it’s you who you are. Like I’m in the more, you know, over the years that’s how you know, you get to know yourself like, Hey, who am I or what, what finds yourself like I mean, have your happy. So that kind of, I mean it’s sort of exploration and at one stage you find that Hey, this is me and this is where I have to do. Like for my example, like I started my career, as I graduated from a controls background, I started in the auto industry working on the diesel engines on a small center. But now I’m building the whole vehicle by itself. So because that tended like, I mean, Hey, who am I? Because I’m curious. I want to learn more and then I want to pick, put things together. I want to know where the end product is. So I got to know who I am. So say I’m a system architect or an engineer, now I know like that’s my basis. So that’s what I do, I interact with and collaborate with different stakeholders too because I like it. And then I want to build a product so now I know who I am and what is my passionate. So over time that gets you right there on your path like you know you’ll be happy in what you would be doing.

Khobi Brooklyn: Yep. I think go ahead.

Jessica Smith: That also helps. One of the things that I always find is that if I’m, if I’m too comfortable, I don’t really, I stagnate a little bit and I get, not bored, but I get too used to everything and I have to find something that pushes me out of my comfort zone. And so I will usually target something that I am kind of interested in but like really scares the crap out of me. And then I will go for it and add something to my plate that is completely outside of my comfort zone. And that really has forced me into a lot of situations I never thought I would be in. And it’s made me find out things about myself in terms of what do I want from my career. And the answer has surprised me quite a few times.

Khobi Brooklyn: Yep, absolutely.

Xantha Bruso speaking

Xantha Bruso asks the Aurora Girl Geek Dinner panel a forward-thinking question about the future of jobs.  Erica Kawamoto Hsu / Girl Geek X

Xantha Bruso: Hi, my name is Xantha Bruso. The autonomous vehicle industry didn’t exist that much longer before. And some of you have experience in other autonomous vehicle companies, but some of you didn’t. So how did you leverage the experience you had to enter this industry when in the future? You also know that the jobs in the future that you may have may also not exist currently. And how can you also stay relevant with what you’re doing now for those future jobs?

Catherine Tornabene: Well, I think that, I think that at the end of the day, being able to be comfortable learning things that are outside your comfort zone is really important. And when I look at my career spanned a lot of, I was at Google, I was at Netscape, there’s a lot of, I was often in situations where I didn’t actually know the, I didn’t have an expertise necessarily. And so I think that my general answer to that is that you just have to be comfortable with learning and being comfortable with saying like, you know, I don’t know the answer here, but I can figure it out. And that, you know.

Catherine Tornabene: I think the thing is in the AV space is there’s a great opportunity to learn and it’s developing very quickly. So I think that my answer to that is that I think taking a step back and looking less at the oh, the specific thing is not something you know. And more at, well, you know what? This is a thing I think I can learn. Is how I would approach it at least.

Khobi Brooklyn: Yeah. I think to build on that, I think part of what’s exciting about being in an industry that’s just shaping up and being at a company that is young and growing and shaping is that it’s less about saying, I know exactly how to do this one thing and I do it this way and I’m on this line doing this one thing. But these are my strengths. Here’s what I’m really good at. Here’s the value I can bring and different perspectives that I can bring. And together all of these different experiences and perspectives are shaping a company and helping to shape an industry. And I think that it will continue to evolve. Which one, keeps it super interesting for all of us or anybody in the industry. But also you find new ways to apply your strengths, right? And I think that that’s what’s super exciting about this industry is that you get to think differently all the time.

Chethana Bhasha: Yeah. And just to add, I think I can give my example clearly because I’m coming from a conventional automotive industry. I’ve worked on trucks and on highway and off highway which is completely a conventional [inaudible] was part of it now interspace where we are building the technology to do integrate in those platforms. So I get to see both the sides because I know how it works in the [inaudible] space and which is the technology we are building and how we integrate. So I get my own strength from the industry. At the same time I’m learning like what this technology does and how can we integrate together to have a great product. Yeah.

Audience Member: Oh, social media. Do you do that? What do you do? How cognizant of it are you? What’s your kind of strategy on developing your brand on social media? Thank you.

Khobi Brooklyn: This may sound weird coming from the comms person, but I don’t think you need social media to build a brand. I mean, I think if you want to build a big public presence brand, yeah, you should have a voice and you should find some channels to get your voice out there. But I think you can do a lot of really important work around building your reputation and being known in lots of different ways. I think it’s everything from how you show up to a meeting to what’s your tone over email to going to networking events and meeting people and sharing your thoughts and hearing new people’s thoughts.

Khobi Brooklyn: I think social media is really cool and a whole other conversation, but I think when we think about building our brand, that’s one way to share your brand, but it’s not necessarily fundamental to having a strong brand is my perspective. I don’t know if any of you have big social media presences.

Lia Theodosiou-Pisanelli: I think I tweeted this.

Audience Member: Thank you.

Khobi Brooklyn: And there we have… yeah.

Audience Member: I guess I have more of a practical question. How do you get feedback on if you’re presenting the right brand? Because I found out I’m like a very nice person, but I’m introverted so when people meet me they’re like, she doesn’t like me.

Khobi Brooklyn: I think that’s a great question. I would love to hear how any of you have received feedback. I think, yeah. Let’s hear from you guys first.

Lia Theodosiou-Pisanelli: Trial and error. This is really where it is. It’s like something’s not going well here and I think just really trying very hard to put yourself in somebody else’s shoes and to be aware of how different people are reacting to you. Right? And trying to kind of read the room or read the reaction and realize that, okay, that didn’t feel like it went well. Either I can ask why it didn’t go well or I can just try it a little bit differently this time. Right? So it depends on kind of what your comfort level is. But I think there is no silver bullet here. We all just learn as we go and, you know, that’s my take.

Khobi Brooklyn: Yeah, just to build on that. Kind of paraphrasing what you said, but a lot of it is self awareness, right? And being intentional, right? If you’re like, I’m going to think about how I show up, this matters to me. You start to realize that and pay attention. The way I acted with this person, is it resonating? Am I bringing them along in the way I wanted them to or what have you? I think is a really important thing to pay attention to. I’m sure we’ve all received advice. I know I’ve received tons of feedback on my brand and some of it has been great and some of it I’ve completely disagreed with, right? And so I’ve always had to come back with like, well, what’s true to who I am? What feels right?

Catherine Tornabene: I think the build on that, the piece of that I think is listen to people’s feedback but also have the confidence to say like, no that’s not for me. Because there’s a lot of people who will give feedback that you know, not right for you. I have an example. I remember being told, this is years ago, well you should never as a woman have a picture of your kids on your desk. I remember I took that and I listened… I had a picture of my kids on my desk. I took that and then later I was like, you know, no. That doesn’t work for me. That’s not who I am. I’m not going to do that. So I think be open to it, hear it, but also be true to yourself and say like, no, that’s not who I am. And I’m not going to listen to that.

Lia Theodosiou-Pisanelli: And don’t apologize for who you are.

Khobi Brooklyn: I think we had a question right over here…

Chico: Oh, hi. I’m Chico. And I think my question’s more about like have you ever had imposter syndrome or things like when you get disillusioned with your job because there’s some stressful scenario going on, something like that. So how do you deal with those scenarios and just get over that realize like, okay no I’m actually good at this thing and I can do the thing. So just trying to get over that big hump.

Lia Theodosiou-Pisanelli: What’s imposter syndrome? I’ve never heard that. I don’t think any of us have had that.

Lia Theodosiou-Pisanelli: I think like best advice there for me is assume everybody around you is holding kittens. No, I’m just kidding. Actually somebody did give me that advice and it was great. So I imagine that of you guys sometimes. What I would say is nobody knows everything and you know who you are and you know your experience and what you’ve learned throughout your life better than anybody else and that has made you into who you are. Right? So if I think of everything that’s happened in any of our lives, good or bad, failures, like sometimes we just do things really wrong, right? But that chisels you into who you are and you’re better for it. Right? So think of yourself as like this combination of all the experiences that you’ve had that only you know what those are, right? So nobody gets to say what you’re good at and what you’re not good at and just go for it.

Jessica Smith: I think it also takes a single catastrophic breaking of everything to realize that like, Oh, they didn’t fire me, it’s okay. I’m still breathing, the world still turns. I ruined everything for everybody for a little while, but it’s still all right. And it’s like a learning experience and… not that that ever happened to me in my early, early career, but it made me realize that like it’s going to be okay. Like even if something terrible happens and if you mess up and fall on your face, it’s really going to be okay and it’s okay to make mistakes because everyone does.

Chethana Bhasha: And as Catherine and Jessica and Lia mentioned it’s getting out of your comfort zone, right? Like if you don’t know yourself, like what you are good at or what you can do more. You have to do that. Like, I mean like as, yeah, sure, you didn’t get fired, but like you had to be like present a report in front of the upper management. Own it and then fix it so that builds your confidence.

Khobi Brooklyn: I think also somebody once told me, if you’re in the room, you belong in the room, you know? And I think it’s important to remember. If you’re sitting at the table, if you’re part of that project, you’re there for a reason. So own it and you belong there and somebody else thought you belonged there too. And so it’s just about kind of having that confidence again and just saying like, yeah, I’m here and I belong here. And being there.

Audience Member: I have a question. I guess sort of referring back to the question before this one, which is parsing through feedback, right? You get all sorts of feedback. Someone told Lia to put smiley faces in her email, things like that.

Audience Member: And this is kind of, I guess a tough subject because I think about this a lot. But as a woman, right? We’ve all heard that women get the whole, you’re aggressive feedback or you’re this way. You need to smile more. That type of feedback way, way more like the statistics show that that’s what happens. But sometimes there may be some validity to it. Right? It’s possible. And I think in my head I have that question a lot. If I’m getting the feedback that I’m too aggressive, is that real? Do I actually need to change my behavior? How do I think about this? How do I actually take that advice because it’s showed up in my performance review, so clearly I got to do something there, right? What do I do? And if I suspect that maybe it’s gendered, what do I do about that? Like how do I navigate that? That’s something that I would love to hear how you guys handle.

Jessica Smith: I have also received, “You’re really mean in code reviews.”

Chethana Bhasha: Yeah I think all of us. Yeah, yeah.

Jessica Smith: So I think my strategy for dealing with it is look at the people that I really respect in the company and who I would like to emulate and how do they give feedback and how do I maybe model my feedback on what they do in code review or in any of the communication that you’ve received feedback on and try and find ways to understand that your impact on other people might not be perceived in the way you expect it to be. And whether that’s from you know, a gender reason or you know, an experience level reason. I think that I’ve found success in changing the way that I speak to people by modeling it off of really successful communicators elsewhere in the company and it’s definitely helped me with this exact same problem. And you know, maybe giving like a little bit of positive feedback where you see… if you’re only ever writing like this is broken, this is broken, fix this thing. But you’re never saying like, wow, that was a really clever bit of code. If you have those thoughts, you can also share those thoughts and share the positivity, which helps make it so that you’re not being aggressive all the time.

Khobi Brooklyn: And I would say adding onto that is digging in a little bit. You know, like if you get feedback that you’re too aggressive, then ask why. Like, why? What’s happening or what’s not happening because of that? I think because at the end of the day, to be a good team player, to be a good part of your company and your team is to be effective. And if you’re doing something that’s not effective and maybe people like to call it being too aggressive, there is still something to fix, right? So maybe it’s the wrong label, maybe it’s sort of an offensive label because we women who sort of hear it all the time and it gets annoying. But at the end of the day, if there’s something that’s not working with the people you’re working with, then that’s fair. And that’s probably something to work on, you know? And so I think it’s a little bit of self awareness and ego and being like, okay, something’s not working I need to improve. But maybe pushing whoever you’re getting that feedback from on, well let’s talk more about that. Like let’s talk more about what it is that you’re really saying. I don’t know. That’s something that I have done.

Catherine Tornabene: I think that the other thing I would say is that I think it never hurts to assume positive intent when people are giving you feedback and assume that they actually really are trying to help you and maybe the words aren’t coming out right and maybe someone’s not really skilled at saying it or writing it or whatever. You know, nobody’s a perfect communicator and nobody can always say the right thing at the right time all the time. So sometimes, and of course there’s more career, you do wonder occasionally, you wonder, do you get feedback as a gender? But I think taking a step past and saying like, okay, well what’s the intent here? I’m assuming it’s positive and maybe there’s something here I can grow from and maybe it’s not the thing that was said to me. I mean it’s entirely possible that I’ll go in an entirely different direction.

Catherine Tornabene: But there is something there. And I mean, I don’t know, maybe I think I’m an optimist at heart, but mostly I think people want to help and they mean well and I think thinking in those terms can help you identify the thing that perhaps you want to take from it.

Lia Theodosiou-Pisanelli: One other thing I’d add is collect data, right? So similarly it’s like understand more where that person’s coming from, but then think, okay, if this is in my performance review, then maybe this came from multiple people. Maybe I should talk to a few people and not say, “Hey somebody wrote I was aggressive. Can you tell me if you agree or disagree?” But more along the lines of, “Hey, how do you feel like our dynamic is and are there ways that we could interact better?” Or things like that. And I think by having that with a few people and particularly people who you respect a lot, that will give you more context on something that’s more actionable than just kind of reading into what does this one sentence mean for me? Right?

Khobi Brooklyn: Yeah. Thank you. I think we have time for one more question, but then we have time for lots of questions just over drinks. So I think yes, you, go ahead.

Audience Member: First of all, thank you very much for all of your sharing, your experience and your perspective. It was really great to hear. Several of you here came from really different backgrounds and then transitioned into a new role and you talked a little bit about making those transitions and how your skills carried over and how you brought your backgrounds to your new roles. And I think it’s really great that Aurora is a company that values that and that sees that.

Audience Member: But I was wondering kind of from a branding perspective, if you guys could talk a little bit more about how you repositioned yourself when you made that transition. Because, as you said, you know your skills and your experience, but how do you reposition yourself to reframe that in a way, with your new role.

Khobi Brooklyn: I feel like you two should start.

Lia Theodosiou-Pisanelli: What? I think one way to go about it is to try to understand, okay, where do you want to go and what are the things that you want to do? Right? And then from there it’s trying to understand, okay, well what types of roles are interesting to you in that world.

Lia Theodosiou-Pisanelli: And then the next step, this is my thought process… And then the next step is, okay, well what makes somebody really successful in that role? And that’s usually how I start a lot of conversations because that way you can understand, okay, what are the attributes of a person? What are the things that they can do that mean success for either somebody who’s hiring or even just somebody generally who works at a company that’s interesting or in an industry that’s interesting. And then I think, okay, do I do things like that or do I have experience that can contribute to that? And how can I provide examples of things I’ve done in my past that translate into that. Right?

Lia Theodosiou-Pisanelli: And so I think one of the things about being in the self-driving space, is it hasn’t existed for that long. Right? And there is a finite number of people who have done this before. We have a lot of them here. But what I will say is there really is that openness to finding others because you… But finding people who have experiences that will help us to think about it in a different way. So that’s something Chris focuses on a lot is, how do we have a diversity of viewpoints? And so if you can think about, okay, yes, my perspective is different, but it adds value to whatever problem they’re trying to solve. Think about kind of explaining it in that way. That’s how I’ve thought about it.

Catherine Tornabene: You know, I think in some ways I would pivot it. And I think that the skills, obviously as I switched from engineering into law they’re sort of a different practical skillset.

Catherine Tornabene: But a lot of who I am is still the same. I mean, as a lawyer I’m not really all that different than as I was as a software engineer. And I think that rather than sort of focus on the external concept of necessarily rebranding, I think that I would view all of your collective experiences as you grow as part of your brand. And it’s just additive and it just adds onto your experience and who you are.

Catherine Tornabene: But who you are is you know, core to you and it kind of in a sense like which job you have. It’s just one facet of that. So I think that for me, I can’t say I thought all that much about necessarily repackaging myself as a lawyer. I just actually thought it was kind of interesting, which is how I ended up in law school. Then I thought that like this particular law job was kind of interesting. But in the end, like it’s always been like, oh, this is pretty interesting, but I’m still really the same person. And I think that the idea of brand is quite core to identity and who you are and your job is a big part of that, but there’s a lot more to you. So focusing necessarily, focusing on that will tell your story, I think.

Khobi Brooklyn: Well, thank you so much for coming. It’s been really great to have you and we would love to talk to you more. So stick around for another drink and maybe there’s even some desserts. I’m not sure. But thanks again for coming. We loved having you. And we will talk to you soon.

Khobi Brooklyn at Aurora Girl Geek Dinner

VP of Communications Khobi Brooklyn stays to mingle after the panel discussion at Aurora Girl Geek Dinner.  Erica Kawamoto Hsu / Girl Geek X


Our mission-aligned Girl Geek X partners are hiring!

Girl Geek X Zendesk Lightning Talks & Panel (Video + Transcript)

Like what you see here? Our mission-aligned Girl Geek X partners are hiring!

Gretchen DeKnikker, Sukrutha Bhadouria

Girl Geek X team: Gretchen DeKnikker and Sukrutha Bhadouria welcome the crowd to Zendesk Girl Geek Dinner in San Francisco, California. 

Speakers:
Shawna Wolverton / SVP, Product Management / Zendesk
Swati Krishnan / Software Engineer / Zendesk
Erin McKeown / Director, Engineering Risk Management / Zendesk
Alethea Power / Staff Software Engineer, Site Reliability / Zendesk
Eleanor Stribling / Group Product Manager / Zendesk
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X
Gretchen DeKnikker / COO / Girl Geek X

Transcript of Zendesk Girl Geek Dinner – Lightning Talks & Panel:

Sukrutha Bhadouria: Welcome to the Zendesk sponsored Girl Geek dinner tonight. I’m Sukrutha. This is Gretchen. Thanks for joining us. I love all the color around. I love your hair, lovely lady. Anyway, a little bit … you also, all of you. I quickly want to recap what Girl Geek X is. So why you see that up there, Girl Geek X is an organization with Angie, Gretchen, and I working to make it easier for women and people who identify as women or anything you want to identify yourself as, anyone, to come and network outside of work, find out more about other companies that have a great culture and have really, really innovative products, such as Zendesk. At dinners like these, you have the first and the third hour reserved for networking, so I hope you’ve been chatting away and making connections so when you actually want to work at the company or apply there, it makes it easier. It’s like you have inside information.

Sukrutha Bhadouria: Zendesk has sponsored a few times before so they’ve been such a great ally and with Shawna working here now. We used to work together before. Not directly but in my head we did work directly. So when she reached out to us we were super excited that we’d have another Zendesk dinner coming up. Today, we do not just dinners. Once we hit the 10 year mark with Girl Geek X, we started doing virtual conferences, which we’ve had two so far. We also have a podcast so search for Girl Geek X and we’re looking for more ideas on topics so listen to what we have and suggest topics. Sign up for our mailing list through our website, girlgeek.io. We also launched our swag store today so–

Gretchen DeKnikker: Did you guys see it?

Sukrutha Bhadouria: You did?

Gretchen DeKnikker: That’s so cute. It’s one of these little guys.

Sukrutha Bhadouria: Yeah, so Gretchen’s nicknamed those characters pixies because they’re pixelated.

Gretchen DeKnikker: It’s a great name so it’s not just that I nicknamed [inaudible].

Sukrutha Bhadouria: So please share on social media tonight everything that you see here, eat, listen to, learn. The hashtag for tonight is Girl Geek X Zendesk and that’s enough from me. This is Gretchen, like I said.

Gretchen DeKnikker: Okay, Sukrutha said everything we always say except for, please join me in welcoming the amazing Shawna Wolverton.

Shawna Wolverton: Thank you. I am just so incredibly impressed with what these women have built over 10 years. I was looking at their site today. Over 200 dinners. This is an amazing organization and we’re incredibly honored to host tonight. A little food, a little networking and hopefully, maybe, you’ll even learn a few things. We have an agenda because this is what we do at Zendesk. Everything starts with an agenda. We have checked in. That’s good. We ate. We all successfully avoided the caution tape, so it’s a classy establishment here at Zendesk. And we’re going to do some lightning talks and then stick around, we’re going to do a big group picture and then, there’s a whole other hour after we talk at you for a while with dessert and some more chatting.

Shawna Wolverton speaking

SVP of Product Management Shawna Wolverton emcees Zendesk Girl Geek Dinner, stating “it’s amazing to get a seat at the table and to look around and see people who look like you.”

Shawna Wolverton: I am Shawna Wolverton. I am the SVP of Product here at Zendesk. I joined about six months ago and it has been an amazing six months. I feel sort of corny a lot. People ask me all the time, how’s the new job? How’s the new job? I feel like a little bit of a Hallmark card. Like it’s so great. But what’s been amazing and I really just sort of figured this out is that I was trusted right out of the gate, right? I was able to go out and be competent. At week 2, I was on stage. In month 3, I’m in front of investors and in front of the press. And it’s just been so amazing to be given that trust. And I was incredibly lucky to join Zendesk in a cohort of women executives. We hired a CIO, as well as our chief customer officer, onto the executive board when I joined and then I looked up and we already had women in our CFO seats as well as in the head of people.

Shawna Wolverton: And it’s amazing to get a seat at the table and to look around and see people who look like you. So you did not, though, come here to listen to me jabber around on about how much I love my job. But we have four incredibly accomplished speakers tonight and we’re going to start with Swati who’s going to talk to us about metaprogramming. At the end, we’ll have some time for Q&A so definitely stick around for that. Swati.

Swati Krishnan

Software Engineer Swati Krishnan gives a talk on “Code that writes code: Metaprogramming at Zendesk” at Zendesk Girl Geek Dinner.

Swati Krishnan: Hi, everyone. Hi, everyone. I’m Swati. And today I’m going to be talking about code that writes code or metaprogramming here at Zendesk. So first, a little bit about me. I’ve been a software engineer in the code services organization at Zendesk for around two and a half years now. In this time, I have learned and contributed to many projects. But of the cooler and fun things that I got to learn here was metaprogramming and I hope that I can share it with all of you out here.

Swati Krishnan: So first of all, what do you mean by metaprogramming? Well, most programs are built on language constructs. These language constructs could be classes, methods, objects, et cera. Metaprogramming, basically, allows you to manipulate these language constructs at run-time. So why is Ruby as a language particularly suited to metaprogramming? Well, that’s because Ruby’s a dynamically typed language. What this means is that it allows you to access and manipulate these language constructs at run-time. This is a difference from what statically typed languages would let you do normally.

Swati Krishnan: So how do we leverage metaprogramming here at Zendesk? So Zendesk is like a Rails shop. So this basically means that we have a lot of products and apps that are built on Rails. For those of you that don’t know, Rails is a Ruby based web framework. Web frameworks have to be pretty flexible so this means that a lot of modules and libraries in Rails such as Active Support, Active Record, et cera, heavily leverage metaprogramming. So by using Rails, Zendesk by proxy, uses a lot of heavy lifting that comes from metaprogramming.

Swati Krishnan: This talk is not going to be about rails. This talk is about account feature flags at Zendesk and how we use a bit of metaprogramming magic to add some more fun and color to them. So before I launch into that, what exactly do you mean by account feature flags? Here at Zendesk, when a developer ship new code, we do so behind … I don’t know why this is so … okay. So whenever developers … that’s better. I’m just going to leave it. So here at Zendesk, whenever developers ship new code, we do that behind something called feature flags. So whenever a feature flag is down to 0%, that basically means that that feature is not available on any accounts. Is this fine? Are you sure? Okay. When it’s done to 100%, that means that it’s available on all accounts.

Swati Krishnan: So this basically gives you mechanism to roll out a feature slowly so it can go from 0 to 100% and you could also roll it back quickly so that if things go wrong, if there’s a bug in the code or if customers aren’t really appreciative of the features–which doesn’t happen. It doesn’t happen, but there’s a slight possibility so you should always [inaudible]. So basically this feature flag framework allows developers to ship code in a more reliable way.

Swati Krishnan: So the way that this is built, it basically means that developers now have a method called has feature name question mark available on the account object. So that whenever they’re trying to ship this new feature, they can just basically go if your account object has … they can basically just go that if and say that if your account object has this part of the feature turned on, that means that we can now execute the new feature’s specific code. If it doesn’t have the feature turned on, that means that we can just fall back to our old non feature specific code or just execute old code.

Swati Krishnan: So how can we simplify the existing account class structure so that we can basically add this feature so that developers can by proxy enable new feature specific code? So one way to do that would be basically to just open the account class to add your has whatever your feature name is, question mark, method inside that. All that this method would be doing would just be checking the database to see if the feature flag is turned on for the specific account or not.

Swati Krishnan: So when a developer has a new feature to add, what they’ll basically do is just go into this account class, add a method called def has feature XYZ question mark and it’ll do the exact same thing, which means that it’ll basically call the database and check if the feature flag is turned on for the account.

Swati Krishnan: But there are also several problems with this sort of an approach and you should not be doing this. And that’s because it encourages repetition a lot so whenever a developer wants to add their own feature, they’d basically be like going to this class, adding their method, making that database call to check if the feature flag is turned on. In coding and in Ruby in general, we try to discourage repetition, because if there’s a way to get something done with as few lines of code and concisely as possible, then it should definitely be trying to use that.

Swati Krishnan: The other kind of obvious disadvantages that means that every developer, whenever they want to write this particular has their own feature method on an account object. But how could I get [inaudible] implementation off fetching from the database so this is just encouraging reinventing the wheel, which is something that we don’t want developers to do because that’ll just add potential for more bugs. Because if everyone gets to write their own implementation, then you can have more bugs pop up from that.

Swati Krishnan: And last but not least, why should we do it in this brute force driven way when metaprogramming gives you more cleaner, elegant ways to solve the same problem? So the metaprogramming solution to this is basically just adding list of features. So over here I added a couple of features, but you can increase this with how many ever features you want. And then in these six magical lines, we’ll just be iterating over this features list. And we’ll be calling the Ruby metaprogramming magical method … actually the Ruby magical dynamic generation spell which is basically just going to define a new method based on that item that it’s picked from the list. It’ll just interpolate that in the method name and then, voila. I don’t know if I said that correctly. And then you basically get a method which will then make that database call with what it’s picked up from the features list.

Swati Krishnan: So this basically means that all that a developer now has to do to get the has feature available method is to just add their feature name to this features list and then whenever the Ruby app will boot up and start, it’ll automatically create the has their feature name available method on the account object so they don’t have to write their own implementation. They don’t have to repeat themselves. They don’t have to do anything much.

Swati Krishnan: So this was just one of the benefits and applications of metaprogramming. There are several others, such as the open class implementation, which will basically let you add your own functionality over any method in the class. So you basically even go and open up like the [inaudible] method in the ink class which is a code Ruby library class. And you can add your own functionality, like logging or benchmarking, to it. Another kind of interesting one would be the Active Record library in Rails. So Active Record for those of that don’t know is object relation and mapping. So basically if you have something like user dot name in your code or user dot name equal to Swati in your code, Active Record will magically figure out that this call response to the user’s table in your database. If that user’s table has a column called name, then it’ll automatically create the [inaudible] methods for you so user dot name and user dot name equal to will already be created for you so you don’t have to define it yourself.

Swati Krishnan: So yeah. These [inaudible] the applications of metaprogramming. This is just a glimpse of all that it can do. But I hope that you found this informative and will probably use it in your own work. Thank you.

Erin McKeown speaking

Director of Engineering Risk Management Erin McKeown gives a talk on “Staying Cool Under Pressure – Lessons from Incident Management” at Zendesk Girl Geek Dinner.

Erin McKeown: Hello, everybody. My name is Erin McKeown. I just want to first say welcome. I’m so excited that Zendesk is hosting this event. I’m even more excited to share with you guys a couple of lessons I’ve learned through managing incidents throughout my career. To quickly introduce myself, like I said, my name is Erin McKeown. I’m the director of engineering risk management here at Zendesk. I have the great pleasure of leading a team of–a group of teams, actually, that I like to think of in three different categories, which is really our first line of defense, threat prevention, and recovery. When I say the first line of defense, we have what we call our Zendesk Network Operation Center. We actually have Kim Smith here with us who leads the ZNOC. Hello, Kim. Everybody say hi. She’s visiting from Madison. So Kim has the pleasure of running a very, very awesome team that takes–monitors and takes care of our systems 24/7 365 a year. Like I said, they do all kinds of monitoring. They put out fires. They escalate to different engineering teams when there’s something that is a little bit larger that they need help with.

Erin McKeown: In addition to our ZNOC, we also have our incident management team. They partner very closely with our ZNOC, and they’re responsible for running all of our response and coordination of any service incident that we have here at Zendesk. On the other side of that, we have our business continuity and disaster recovery. These are really the areas of which we focus on planning for training employees and testing on how we can recover from business disruptions. So that can be anything from a natural disaster that impacts one of our office facilities to a natural disaster that may actually take out an entire AWS region. Everyone cross your fingers that that does not happen.

Erin McKeown: So this is one of my favorite quotes. It’s a little nerdy, but Franklin Roosevelt said, “A smooth sea never made a skilled sailor.” Disclaimer, I’m not a sailor, but stick with me here. I think what Frank is trying to get at here is that no matter what, there’s always going to be challenges that come up and we are going to have to deal with adversity and we can plan and we can do all kinds of things to get prepared for events to take place but at the same time, we need to take these as an opportunity to continue to learn and to grow. And so, I’m just going to share with you guys two events that I’ve actually been a part of and two important lessons I’ve learned from them. I really wanted to dig in and give you guys a real technical incident type of conversation but I didn’t want you to fall asleep.

Erin McKeown: So the first event that I’m going to talk about is from 2011. Back in 2011, there was a 9.1 earthquake off the coast of Japan and it actually was a mega underwater earthquake that took place. As a result of that, there was a tsunami that then hit a nuclear power plant and caused a meltdown of the Fukushima power plant. This is considered the second biggest radioactive event accident to have happened to Chernobyl. I don’t know if you guys are watching the HBO series, but kind of along those lines.

Erin McKeown: So a very, very devastating event. We actually had an office in Tokyo with 250 employees on the 50th floor of a high rise building when the earthquake happened. You can imagine how scary that would really be. That was the first wave of it. And then the tsunami hit and there was devastation across the entire the eastern side of Japan. And then this huge threat of radioactivity that was potentially threatening Tokyo. These employees went through the ringer. I mean it took us about a week and a half to confirm where all of our employees were, make sure that they were safe, make sure that their families were safe, that they had what they needed. All the work that was going on in Tokyo completely stopped. It’s fine. There was other people that picked it up and things to do.

Erin McKeown: I think that what we learn from this type of an event is no matter what, people are our most important asset. As a company, you consider it family and I think one of the challenges that companies do have is really understanding that line between responsibility and just doing the right thing for their employees. In this particular event, we actually considered chartering planes to get our employees out. We didn’t have to do that because it turned out everything was going to be okay, but, yeah. So bottom line from this experience, to highlight that despite the fact that the office was unoperationable for weeks at that point, everything was fine business wise. All we cared about was the employees being safe and their families being safe.

Erin McKeown: So this is another event that took place in 2012. Hurricane Sandy. It actually impacted the eastern seaboard, caused over an estimated $70,000,000,000 dollars worth of damage. Another very, very human wise devastating event. I’m not going to talk about that one. Part of this in this one, a startup that became … well, I wasn’t working there but partnered with them on some things. I wasn’t responsible for their DR. They actually had their data center in downtown Manhattan. I don’t know if you guys know that there’s data centers in downtown Manhattan but from a risk standpoint, I would not be having my data center downtown Manhattan.

Erin McKeown: Anyway, they completely lost power. They lost backup generator power. They didn’t have a disaster recovery plan. They didn’t have their data backed up. So they were pretty much dead in the water. They had to sit there and wait and see if everything would come back or if it wouldn’t. So the big lesson from them here is luckily, the services came back. They were able to continue their operations, but they quickly implemented a disaster recovery and backup data … sorry. Data backup policy.

Erin McKeown: So I think one of the things from this experience is really understanding again, first and foremost, the people aspect is the most important, but when you start thinking on the business side of things. Especially for a company like Zendesk, that our data is our bread and butter, that’s where you want to be putting some focus and making sure that you’re considering that and making plans for it. So yep. Just kind of the takeaway from that is we do consider people. Again, I think about it from a Zendesk standpoint because like Shawna, I absolutely love it here. I’ve been here for four years. They’re going to have to drag me out kicking and screaming. Again, I do believe that we’re a company that … you know, people first. We do believe that also our data’s pretty important too. So thank you so much.

Staff Software Engineer, Site Reliability, Alethea Power gives a talk on “Computer, Heal Thyself: Automating Oncall, So You Can Sleep Through It” at Zendesk Girl Geek Dinner.

Alethea Power: Hi. This is my talk. Computer heal thyself: automating oncall. So you can sleep through it. My name is Alethea Power. I’ve worked in auto-remediation, which is what I’m going to cover, and I’ll explain that term in a minute. I’ve worked in auto-remediation for about 10 years. I built one of the world’s first and largest auto-remediation services. And now I’m building an auto-remediation service in conjunction with Kim and the ZNOC team here at Zendesk.

Alethea Power: So what is the purpose of auto-remediation? Well, tech companies have been finding through the dev ops revolution, not revelation. I mean I guess it’s kind of a revelation. Over the past number of years, that they can get better product quality, faster product development velocity, and higher service reliability if they give product engineering teams both the responsibility and the authority to manage the full life cycle of the software that they’re writing. So that means not just writing code but the engineers who write the code also push the code out to production. They operate the code in production. And they respond when there are outages in production.

Alethea Power: So this causes a virtuous tight loop. The engineers who are writing the code are best equipped to solve problems when they occur and when those problems occur, it gives those engineers a lot of extremely useful information about how to change that code or repair it. So quality goes up, speed goes up, et cera, et cera. But this introduces a whole new set of responsibilities for software engineers that they have not traditionally had to take care of which means we have to provide them with tools to make these jobs easier so that they can focus on the part they understand and not have to worry about lots of things that distract them from the focus of the code.

Alethea Power: So auto-remediation is meant to be a tool to help address with your mediation of outages. And I’m not talking about the Fukishimas of the world. I’m talking about much more frequent outages. The kind that happen 20 times a day. The kind that happen at 4 A.M. and at 4:45 and at 6 and at 5:30 A.M. So what does this look like in practice? Traditionally, you have a monitoring system that detects when you have outages in your infrastructure with your services. That monitoring system gives alerts to engineers. Now this could be in the form of engineers sitting in front of a dashboard of alerts 24/7 watching it. It can be in the form of alerts paging engineers in the middle of the night and waking them up. Yeah, et cera, et cera.

Alethea Power: And then engineers take their own knowledge and documentation recorded in what’s frequently called runbooks to execute various commands in the production environment to try and solve these problems. So these commands can be things like, if you have an application that’s wedged, maybe you’ll restart it. If you have a hard drive that’s full and maybe it’s full because there’s a bunch of errors spewing into a log. Then maybe you truncate that log. If you’re in the middle of being attacked. If you’re in the middle of a DDoS attack. Maybe you changed some routing rules to black hole incoming requests.

Alethea Power: So these are the kinds of things I’m talking about. So in auto-remediation service replaces these two components. The engineer gets replaced with a service and the runbooks get replaced with remediation code. So instead of having human readable documentation about what to do, you have blocks of code. And the auto-remediation service goes and executes this code in response to alerts in the monitoring system. And then engineers can sleep through the night. Their talents are better used for, for instance, instead of waking up to restart a service that has a memory leak, they can be well rested in the morning and figure out why it has a memory leak and fix that.

Alethea Power: And in general, we can take better advantage of the knowledge that we have across all of our engineers. The engineers that are being woken up and the engineers that are watching these dashboards. We’ve got a lot of really knowledgeable, talented, intelligent people. And we want them to be able to use their skills in the most sophisticated and interesting ways possible. So we’re trying to automate as much as we can.

Alethea Power: So I’m going to look at an example here. This is a configuration file for the auto-remediation service that we’re building. I tried to design the configuration language to be as simple as possible while also being flexible enough for what we’re trying to accomplish. So let’s walk through it. This file says if you have this issue on these hosts, then it should run this job in response but don’t run it more often than that. So specifically if the osquery agent is busted, web servers in us-west-1, then you want to run this block of remediation code but don’t do it more than five times per hour per cluster. Make sense?

Alethea Power: So let’s go look at this thing right here so we can understand how that looks. So we’re also building an SDK, mostly built by engineers on Kim’s team. And this SDK includes a lot of convenience objects and convenience methods so that the people writing remediations can focus just on the logic that they care about and they don’t have to worry about things like SSH authentication and properly rotating keys and how do they get authentication into AWS so they can reboot EC2 hosts and stuff like that. We abstract all that away for them and we do it in ways that make our security compliance team happy. Every remediation uses a different SSH key magically.

Alethea Power: So this remediation you can see in four lines of code. It could fix this problem. So let’s walk through these lines. First, you import our SDK so you get all of these convenience objects and methods. Then you subclass our remediation class and override the run method and inside of that, you get this convenience object. If it’s an alert on a host, you get self.host. The remediation doesn’t even have to know what host it’s working on. It can if it wants self.host.name. We’ll tell you a host name but you don’t have to. And you get this method, self.host.run, which magically does lots of SSH things in the background and can run this command to go restart that service.

Alethea Power: So it’s that straightforward. We’re trying to make it as simple as possible for our engineers. It’s pretty complicated on the backside. Here’s a pretty simplified picture of what the backside looks like. So, Swati, you did a magic thing with a dot. I don’t know how to do it so I’m just going to go point. So that thing, the alert mapper, pulls in alerts from PagerDuty. That’s who we use for monitoring or where we consolidate our alerts. And it runs those alerts through the configuration like the configuration files we were just seeing and calculates what remediation jobs to run, inserts those jobs into the database, and then that thing, the job launcher, pulls the jobs from the database, hands them as config files to Kubernetes and Kubernetes executes them inside of containers. We’re running them in containers because I’ve built this before and engineers make jobs that take 100 gigs of ram and all the CPU you can use so we don’t want any job to choke out the others. And lastly, since we have this nice infrastructure in place already with a beautiful SDK, we’re giving people the ability to launch proactive jobs using a CLI to do things like kernel upgrades and other stuff that’s not necessarily responding to alerts. All right. Thank you.

Eleanor Stribling speaking

Group Product Manager Eleanor Stribling gives a talk on “ML in Support: Infusing a flagship product with innovative new features” at Zendesk Girl Geek Dinner.

Eleanor Stribling: Hi, everyone. My name’s Eleanor Stribling. I’m a group product manager here at Zendesk. What that means is I manage other product managers. And what I wanted to tell you about today was how we’re using machine learning in Support, our largest, oldest product. A little bit about me. I would also say that Zendesk is really the best place I’ve worked in in tech. I’ve been here a year. Before that, I’ve been in all kinds of companies ranging from a company that’s like a 100,000 people all the way to a teeny, tiny social impact startup and this experience overall has been just amazing. I work with obviously lots of really smart people, so definitely encourage you to explore this if it’s of interest to you.

Eleanor Stribling: One of the reasons I really like Zendesk and I like working on this product is … well, it’s not evil. But also, it really helps people do their jobs and do them well and that’s why I’m so excited about this particular project. Putting machine learning in Support, because like I said, this is the product that a lot of our customers use. Use it a lot. They’re in it everyday. And we want to help them do their jobs better and more efficiently. So machine learning is a great way to do that.

Eleanor Stribling: I want to do a little bit of clarification of terms. So when I say Support, I might mean something different than what you imagine it to mean. So most people when they say, most normal people who don’t work here, when they say support, they mean calling support like I need to call support because I’ve got a question. That kind of usage. What I’m going to talk about is the product Support. So Support, as I mentioned, is our oldest product. Until recently, it was Zendesk. And basically it’s a system for creating tickets or issues, moving them through a system, making sure the right people see them at the right time and then resolving them. And that’s kind of the core of what we offer. So it’s a really cool place to work because we have huge impact on a lot of users.

Eleanor Stribling: So a pause here and then zoom up a little bit. When you think of machine learning as part of customer service or customer support, what do you think of? What do you sort of imagine? Chances are, you imagine something like this. So this is one of our products. This is AnswerBot. And it is exactly what the name connotes. It is a bot that answers questions for people in chat. So in this example, you’re connecting to a chat. You’re asking some basic questions. AnswerBot looks at the text and predicts a response and then serves it to you. If the prediction is strong enough and if it doesn’t, as you can see right here, it’s going to escalate it to an agent. That went by really fast but trust me, that’s what it did.

Eleanor Stribling: So that’s usually how we think about customer support with ML, right? Bot answers your questions. I think this is a great product and it does lots of great things. Among them, it means that customers don’t always have to talk to a person. So I definitely have my moments. I think we all do when we really don’t want to talk to a person and in these circumstances, it’s great. But the problem with answer bots, generally, not just ours, is that people do want human connection. So it’s great for deflecting some issues but sometimes when you call support, you just want to talk to a person. How do I get to a person, you might scream into the void.

Eleanor Stribling: So really the question that we have now as a very customer centric company building a product that’s supposed to help you build relationships, is how do we help people inject that humanity that customers want, they want to experience. How do we help them do more of that? How can we help them be more efficient? And I think we started looking at machine learning as a way to do that in Support. This is also, I think, important kind of context. We do this really cool report every year about customer experience trends. So if you’re interested in customer experience, generally, if you’re a data person, definitely check this out because I think it gives you good perspective or if you want to apply for a job, just saying, it will give you really good perspective into the landscape.

Eleanor Stribling: So there’s a lot going on here but basically people expect answers fast. They want it on every channel that you have. They expect you to be on every channel. They really want you to be proactive but you’re probably not doing that so there’s a lot of pressure right now on these customer support organizations. So in this environment of I just want a person but I also want a person with all this other stuff, how do you manage that? So when we first looked at taking this approach of we got this giant product people know and love. It’s like where they spend their whole day in a lot of cases at work. We first started with the question, how can we use machine learning to help customers manage complexity. Because we are going up market. We’ve got more and more customers who have huge agent teams. Like about 40% of our annual revenue comes from customers that have over 100 agents. So these are not small companies. There’s a lot of complexities.

Eleanor Stribling: So we kind of started there, but then realized pretty quickly as a customer centric company that really, what we were asking is how can we use machine learning to make our customers even better at their jobs? And really even beyond that, how can we help them make their jobs less stressful? If you imagine being an agent or a manager of support agents or even an administrator of a system like this, there’s a lot riding on you. There’s a ton of stress. People are calling you stressed out, saying I’ve been trying to talk to a person for however long. It’s often not pleasant and so, I think, to make jobs for these folks easier is one of the reasons I joined Zendesk, because again, it’s something that’s actually improving people’s lives and it’s definitely not evil.

Eleanor Stribling: So what we wanted to do was figure out, how do we add little things to this so that it won’t blow you away, like the machines aren’t taking your job, but we’re giving you little tools to do everything that much better, that much faster. So again, being a customer centric company, we looked at the main groups of customers that use our product, which you see across the top there. Agents, managers, administrators. And then we thought about, for each of them, as you can see down the side there, what their goals are and then we thought about what we could use ML to do for them. How could we help them do their jobs with this rich set of data that we have for each customer?

Eleanor Stribling: So first of all, agents. So they really need to get happy customers. Like if you’re finally getting that touch of humanity in your support experience, you want your customer to leave happy, right? It satisfies them. It satisfies the customer. Everyone’s incentives are aligned. So the plan here is because agents are often working in complex environments, they can be very high turnover environments, we wanted to figure out a plan to–and what we’re working now, actually–is essentially crowdsourcing agent responses. So we can start suggesting next steps for people as they’re working on a ticket. And that’s really huge. Again, in somewhere that’s really fast paced, maybe you’re working on something you’re not familiar with, we’re kind of there to lend them a helping hand and help them be a little bit faster and more efficient and give people more relevant answers.

Eleanor Stribling: For managers, so managers are leading a team of agents and they really need these agents to be efficient and make people happy and they care about CSAP. Part of that is making sure you got the right number of people, the right people and the right number, in the right place to answer questions. So here we’re looking at grouping relevant data together. So for example, if you have a ticket that comes in and it’s one of a hundred tickets about the same topic, we want to surface that in a really clear and simple way for managers so they can respond effectively. Either by getting agents with the right skills. Maybe they figured out a response they want to communicate to their team. That kind of thing so that they can get on top of it. Another thing that we’re working on managers that I think will really help is predicting surges. So we can look at the agent staffing that they’ve had at any given time. Maybe it’s a time of it’s really busy like around Christmas for example or maybe it’s just every Wednesday. What do I need? The other thing we’re working on here is figuring out how to surface that intelligence so managers can do their job better so we’re giving them a little boost.

Eleanor Stribling: And then finally, administrators. So these are the folks that set up Zendesk and maintain Zendesk. And so their main thing is that no ticket, no issue kind of gets undealt with. And I think that there’s kind of a constant stress that they have that something will not be answered because they somehow messed up the settings. So the great thing about administrators from a data science perspective is they kindly label a lot of data for us. We don’t want them to stop doing that but what we can do is learn from how they label data for us. And what that means is we can help make sure that no ticket goes unanswered. That if they don’t assign something that makes sense, we can provide suggestions, updates for them, but also for managers in real time so that they can change the routing. So there’s a lot of really cool things we can do that would really have real time impact in small ways on our customers to, again, make their job better, make it easier and less stressful. And really, that’s one of the reasons I work in tech. Because I want people’s lives to be made better through it.

Eleanor Stribling: And finally, if you follow me on Medium or Twitter, you know I’ve got kind of this weird thing about Harry Potter and I had studied language in Harry Potter. But to me, this project is kind of like that. It’s like we’re taking something that’s everyday that people are used to staring at for hours on end and we’re adding little things that are unexpected and kind of cool. And so that’s why I think that this is such a great space to be in. Because we’re having like huge impact by making little and also extremely cool changes to the experience. We are also hiring in that team. Shameless plug. We’re hiring in that team for a data science engineer and a data scientist and I’m also hiring for a product manager, so if you’re interested in any of those, definitely come see me after. Thank you.

Shawna Wolverton: All right. Thank you to our amazing speakers. Why don’t you guys actually all come back up and we can do a little Q&A. I think there’s going to be some folks out with mics wandering around. Maybe. There you go. We don’t need all the mics. So we got about ten minutes for Q&A if anyone has questions about the talks or Zendesk or you know, we know a lot of things. Trust us. It’s fun. No? Careful, we’ll ask you … oh, great. Right … oh, you’re close but then we got one up here.

Shawna Wolverton, Swati Krishnan, Erin McKeown, Alethea Power, Eleanor Stribling

Zendesk girl geeks: Shawna Wolverton, Swati Krishnan, Erin McKeown, Alethea Power and Eleanor Stribling answer audience questions at Zendesk Girl Geek Dinner.

Audience Member: Hi. Alethea, I really enjoyed yours as someone who’s been woken up so many times from PagerDuty. Like God bless you. Can you talk more about the code behind what makes all that wonderful magic run?

Alethea Power: Yes, but there’s so much of it. Maybe it’s better to go into details after the Q&A?

Audience Member: I will find you. Thank you.

Shawna Wolverton: I have a feeling–

Alethea Power: I guess I could give you like a 30 second. It’s all written in Python. We use Aurora on the backside for the database. Like I said, we put containers into Kubernetes. I don’t know. That’s a very quick, quick, quick. It looked like you frowned when I said Python.

Audience Member: Oh no.

Alethea Power: Okay, so don’t find me afterwards. No, no, seriously. Totally come ask.

Audience Member Thank you.

Shawna Wolverton: Heard one up here.

Audience Member Hi. This is a question for Swati. You mentioned metaprogramming and I’m actually really interested in dynamic programming languages, such as Python, but you mentioned you mostly work with Ruby. So I was just curious if you ever worked with other languages, such as Python, for instance?

Shawna Wolverton: Lovers and haters of Python.

Swati Krishnan: Thanks for the question. My internship project here was in Python. So yes, I’ve worked with Python before. That was dealing with, I don’t know if you’ve heard about [inaudible], but that’s like a graph database implementation in Python. So I worked in that quite a bit and yeah, Ruby and Python are very similar, interchangeable somewhat. Yeah. Any more questions about the?

Audience Member: Talk to me more about it.

Swati Krishnan: Sure, catch me and then I can talk to you about my Python work. Sure.

Shawna Wolverton: Question.

Audience Member: Hi. I have a question for Alethea. So no doubt that it’s great that you’re not woken up at 4 A.M. or on call. Agreed with that. But I’m curious, one of the philosophies of DevOps is that when engineers feel the pain of the alerts, they’re more motivated to fix it. And so do you find that maybe the engineers aren’t as motivated to fix it and if so, is that actually a problem?

Alethea Power: That is such a good question. So this service is in the process of being built right now, but like I said, I built this in the past and had years of experience running it in the past. That’s why we surface very public metrics from it. So rather than feel the pain in a way that makes them bleary eyed and less capable of doing their jobs, they feel the pain in the sense of error budgets and visible metrics and things like this. So, yeah.

Shawna Wolverton: For the record, blameless accountability.

Alethea Power: This is true. I’m actually a big fan of blameless accountability.

Audience Member: I’m also just curious as to how many engineers helped you to build this and how long it typically takes?

Alethea Power: So it’s me and two engineers on Kim’s team. We spent a while designing because there were some security compliance constraints we had to hit and also, we’ve purchased a number of companies, so we have to be able to work with a wide variety of infrastructural decisions. So it took us a few months to figure out high level, how to design the system so that it would do all of that. And once we knew roughly what we were doing, I don’t know, what would you say? We’ve got about 80% of the code written in two months. Something like that.

Audience Member: [inaudible].

Alethea Power: Yeah. We’re cranking right now.

Audience Member: Hi. I have a question for Eleanor. So, I don’t know anything about your product, Support, but I’m assuming there’s a dashboard so when the customers come to open a ticket, is there a knowledge base? I was going to ask you, are you using machine learning to help the customer before they open a ticket.

Eleanor Stribling: Yes. So we’ve got a product called Guide, which is basically a help center. It’s a really easy use, out of the box kind of help center. So yeah, we’ve got that product. We also have AnswerBot, which I mentioned, which helps people before they even reach out to a person to try and resolve their issue before that. And we also have a bunch of tools for people who administer help centers to help them figure out what to write articles about so from those three dimensions, we try to take care of them before they need to reach out.

Audience Member: Got it. Thank you.

Shawna Wolverton: Going once. Oh, one more. [inaudible].

Audience MemberI have a question for Erin McKeown. She and Kim Smith and I actually started Zendesk on the same day, a little more than four years ago. But Erin, when you started, you were the first person to work in business continuity and disaster recovery here, and now you’ve built out quite a practice. I’m just wondering if you have any sort of quick tidbits, lessons learned, insights on that experience over the last four years?

Erin McKeown: Yeah. Well, that’s a really good question. Yeah, I started out as business continuity disaster recovery program manager and that kind of scope grew quite a bit. We had a lot of activity on our intimate management so we built out an entire team that is really churning now and doing amazing work. And so, been switching focus a little bit to prioritize different things and build out different teams. I’m actually, right now, hiring a disaster recovery manager who then will hire three analysts under them so I’m really excited about the progress that’s being made there. But I think what I tried to do was focus on what I could actually manage and actually what I could take on and be honest with myself about that. Because I think I started out of the gate being like oh, I’m going to do all of these things and quickly was like, oh gosh. Got to pace it back a little bit.

Erin McKeown: Again, having very supportive upper management and with that whole perspective has really helped us get progressively down the line, but, yeah, it’s been a fun journey over the four years for sure.

Shawna Wolverton: One in the back.

Audience Member: Hi. This question’s for Eleanor. I was just curious, and it seems that the product you’re thinking about might not be as mature. How do you deal with customer questions around validation of the algorithm or you mentioned you’re going to forecast demand search. How do you deal with where they’re like, well, how is this true or how do I know you’re giving me the right guidance because I don’t trust the machine or the model?

Eleanor Stribling: Yeah, that’s a great question. I actually saw a really … this influenced me a lot. A talk by someone from PagerDuty at a conference a little while ago. And I talked to him about it after because we were thinking about doing some similar things and he was saying that really the biggest challenge was getting people to adopt the ML because they didn’t trust it. And so I think the approach that we’re taking is very much opt in, we’re going to validate all of these algorithms we’re writing. We’re going to validate them all with customers before we start and make those early validation customers EAP customers, we hope, to sign them up so they can sort of see it in action and be part of making sure it works the way they need it to. So I think that that’s one tack.

Eleanor Stribling: But I think it’s also the reason behind the strategy that we’re not going to suddenly say oh, we’re going to use ML to route all of your tickets. Like trust us, it works. We’re not going to do that. We’re going to very gradually introduce little things that help people a little bit. And they don’t even have to take the suggestion if they don’t want to. But the hope is that over time, they begin to trust it. It doesn’t replace them. It doesn’t replace necessarily even huge amounts of their workflow. It just makes it a little bit better for them and I think that that’s definitely going to have to be the first phase of how we approach this. And then we’ll see.

Shawna Wolverton: I think one more question. Yeah? But we’ll all be here afterwards. Feel free to find us.

Audience MemberHi. I have a question for Eleanor, too.

Eleanor Stribling: Sure.

Audience MemberIt’s a continuation to what she asked. So with every customer that opt ins with you, do you retrain your model and then how do you know, how good is your model?

Eleanor Stribling: Yeah, so, great question. So we are doing individual customer models. I think that that’s really because each customer’s quite different and we definitely have customers with a ton of data and we want to make sure that we customize the solution to them. I think that’s how we’re going to get the best result. In terms of validating it, I think that, again, we’re going to need to do a couple of steps. I think with some of our biggest customers, we have some customers who are already really interested in this. So I think that there’s an opportunity there to get them on board. Have them help us test it effectively. I think we will be gating some of these things, so we’ll give them options to roll it out to portions of their organization. We have a lot of customers who deploy it in multiple areas in the organization. So do that gradually. Make sure they’ve got some training around it. But I think, again, really the strategy needs to be we’re going to get some customers who we know it works for them and they can help us evangelize it, because otherwise, I don’t think people won’t necessarily trust it. [inaudible] own data. Does that answer your question?

Audience Member: Yeah, yeah, yeah.

Eleanor Stribling: Great.

Shawna Wolverton: All right. Thank you lovely speakers. We fed and watered you. We educated you a little bit. And in exchange, you get to learn why it would be so amazing and awesome to work here. I want to introduce Lauren from our recruiting team.

Lauren Taft: Hi, everyone. Thanks so much for coming. I’m Lauren Taft, manager of recruiting for technical and university recruiting and Stephanie, who’s over there, who’s our senior tech recruiter. Just wanted to tell you a little bit more about Zendesk. We have 145,000 customers, 2,600 employees. Our headquarters is here in San Francisco. We have 16 global offices. Our product is in 160 countries. It touches 60 languages. And we have 1.4 billion yearly interactions processed.

Lauren Taft: So a little bit about Zendesk recruiting. We’re growing at scale. There’s tons of opportunity and with opportunity comes impact. And then a little bit more about what our values are here. We practice empathy, focus on relationships, and be humbledent, which is humble and confident together that we made as one word. Kind of a fun little spin. We thought it’d be great to show you a video. Oops. I should pause this for a second. We made this for International Women’s Day and it’s a little bit of what it feels like to be a female here at Zendesk.

Video Speaker: Oh okay, one word.

Video Speaker: One word to describe her? Badass.

Video Speaker: Oh, I would totally call her a badass.

Video Speaker: Badass.

Video Speaker: Is badass one word?

Video Speaker: Okay, two words. She’s amazing, but she is also a badass, which is pretty cool. She has a special way of like seeing things within you that you might still be trying to grasp or shore up and she’s like no, you’re there. You’re ready.

Video Speaker: Any time she gives me feedback, it’s often very direct, and sometimes a little shockingly direct, but it never upsets me because I know that it’s coming from a place in her heart where she wants to be my best self.

Video Speaker: She had a really genuine talk with me, which I really appreciated. It was kind of like a big sister talk and it was a talk that I’ve never gotten from anyone at work. She just did it in such a genuine, motherly way. The way that she approached the situation, I really respected, and I realized why she deserves to be in a leadership position.

Video Speaker: Wow. She said all that? Trying to put into words the emotions that are there around it. It’s wonderful to feel recognized. I feel like that’s something a lot of women don’t ask for or expect. I had women like that in my own life, and it is super meaningful to me in terms of just being a person in this world to be able to affect somebody like that, so.

Video Speaker: She’s really helped me to push myself outside my comfort zone. To own those aspects of being a woman that at times can appear or make us feel a little bit more limited. I think her favorite word was, use that emotion and passion for good. To help get things done. To help drive what’s important to your team and your organization and that’s the first time I’ve really looked at it that way. How do I take that crazy wild but super passionate part of me and put that in a place and use that in a way that can get good things done?

Video Speaker: I really love it when women have a conviction or a boldness to put themselves out there and say this is a thing that I want and then to go get it. And it’s been so cool to see her succeed and push herself and push others and grow Zendesk over the past couple of years.

Video Speaker: We would talk about what we’d like, what we didn’t like about our jobs and what we wanted and she took the steps to communicate, make it clear what her goals were, but she didn’t just wait for things to happen. And that’s what is mostly inspiring is that she took her destiny into her own hands. She went and took classes outside of work and was able to move her career in the direction that she wanted to.

Video Speaker: I would say that she’s helped me by demonstrating that you … it’s always easier to take responsibility for your current situation and how to get to where you want to be. She’s shown me that it’s good to not necessarily wait for opportunities to show up, but to go after them aggressively. Even if you’re not sure how they’re going to pan out and even if sometimes other people are telling you not to go after the thing, that if your gut is telling you to go after the thing, you should do it.

Video Speaker: I’m actually surprised at how many strong, powerful, motivated, intelligent women that I’ve met since I’ve been here. More than I’ve ever met in my life. It helps me to drive myself to be better, but it’s also just a really good support network.

Video Speaker: We’re hoping we can spread the joy.

Video Speaker: You are definitely spreading the joy. If there was like one moment this week that I needed this most of all, it was like right now, today.

Video Speaker: I’m so glad to hear that.

Video Speaker: So, thank you.

Lauren Taft: Uh oh. I don’t know what’s going on. There we go. So I hope you guys enjoyed that video. Just gives you a good sense of what it’s like to be here. If you’re interested, come chat with us. It was a pleasure hosting you all. We had a bit of swag snafu so check your inboxes for an Amazon gift card. We’re very appreciative that you’re here, and we are going to take a group picture.

Zendesk Girl Geek Dinner group picture

Zendesk Girl Geek Dinner group picture – thanks for coming out and joining us!


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Girl Geek X Poshmark Lightning Talks & Panel (Video + Transcript)

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Tracy Sun speaking

Co-Founder and SVP of New Markets Tracy Sun welcomes the crowd to the Poshmark Girl Geek Dinner in Redwood City, California. The stylish evening’s theme: “people-powered innovation”.

Speakers:
Tracy Sun / Co-Founder & Senior Vice President of New Markets / Poshmark
Barkha Saxena / Chief Data Officer / Poshmark
Vanessa Wong / Senior Director, Product Management / Poshmark
Angela Buckmaster / Associate Director, Community Operations / Poshmark
Camille Forde / Senior Manager, New Markets / Poshmark
Adrienne Hamrah / Software Engineer, Cloud Platform / Poshmark

Transcript of Poshmark Girl Geek Dinner – Lightning Talks & Panel:

Tracy Sun: So I’m here, I get to kick us off. And so after welcoming you, welcome again. What I’m going to do is tell you a little bit about me. I’ll do that pretty fast and then share what people-powered innovation means and why we chose that to be the theme of the evening. And then we’ll just kick it out to all of the amazing speakers that you’ll hear tonight. I believe there’s six women that will talk to you tonight about who they are, what they do.

Tracy Sun: When we talked to the panels, everyone wanted to share a tip that they’ve done or something they’ve done in their career that they really wanted to share with the group. So we’ll talk a little bit about tips and try to have a whole bunch of fun doing so. So to kick it off. My name’s Tracy. I’m one of the co-founders and I head up a new department at Poshmark we’re calling New Markets.

Tracy Sun: My background, I grew up in the East Coast. I’m still kind of an East Coast person, but getting more and more West Coast as the years go by. I started in science. I was a science geek. I loved reading about brain and behavior. I moved into fashion pretty early on because I loved building brands and obviously now, I’m in technology. So my one thing I wanted to share with all of you is you can switch industries. I get this question a lot. It’s hard. So you have to really want to do it, but if you want to do it, you can do it. And I’m happy to answer questions later about some tips on how.

Tracy Sun: But the first I’d say is you can do it and you have to believe in yourself. And I’ve done it twice and who knows what happens to me. I’m still pretty young and have a lot to look forward to. So now about the theme of the evening, people-powered innovation. The reason that this is the theme is this is Poshmark’s superpower. What I mean by this is this is the one thing we do that we think we do better than anyone else.

Tracy Sun: And we wanted to share with you how we’re thinking about it and what we mean by it. Because I think that maybe you can take some of that into your own lives or into your own careers or how you think about innovation. It might inspire you a little bit. So that’s why we’re choosing the theme is just really talk about our strengths and the things that we’re really proud of. So people-powered innovation to us means three things.

Tracy Sun: The first is, and then video kind of alludes to all three of them. The first is we built our entire business off of people. We call ourselves a social commerce platform. And what that means is we take people and we insert them into all the important parts of commerce. We think that all of us have stories to tell. We tell them differently. That’s part of the beauty of photos and words and stories. So we want to put that back into commerce. We think that there’s more to selling a dress than seeing it on a hanger at a store. So how did she style it? How did she feel when she was wearing it? Things like that. We think that’s really important.

Tracy Sun: So we put people back into the conversation of commerce and then we build an entire platform around this so that people, anyone, any one of you, it sounds like we have some poshers in the room, but really anyone in the world can become a seller, no matter what your experience, how much money you have, whether you’ve done it before or not. All those things are irrelevant. Anyone can be a seller. And so what we see now is we have 40 million registered users. About 6 million of them have become sellers. Meaning we’re one of the largest selling networks in the world.

Tracy Sun: So raise your hand if you’re a Poshmark seller here. Congratulations. You’re one of 6 million people in the US that are selling on Poshmark, including a lot of us here. So congratulations. So that’s number one. The second thing is you can’t build a people-powered platform without the people. So the second thing we did is we built a community. And what that means is we focused day one on really taking a look at our users and doing everything we can to support them and so saying, we are behind you to help you build your business and we encourage our community to talk to one another in case we can’t be there to support you, support each other.

Tracy Sun: And so not only does that happen in physical venues like this, but it happens in events that we hold like in our app. So a mobile event and it happens in the conversations when you’re on Poshmark and then it happens offline as well. So a lot of times we’ll see Poshmark users talk to one another, they met on the app and then they talk to one another in real life. And that to me is one of the most beautiful things about why I love coming to work every day. It also reflects in a lot of our business metrics too.

Tracy Sun: So, for example, every day a Poshmark user spends 30 minutes on Poshmark. And for those of you in commerce who think about these kinds of metrics and maybe some of you are not in commerce that think about these kinds of metrics, that’s unheard of for commerce. People don’t spend 30 minutes talking about shopping elsewhere and maybe nowhere. So people are not just talking about transactions on Poshmark, they’re also talking to each other as human beings. And that’s where we like to spend our time. That’s how we find extra minutes in the day when we’ve had a long day is to have a human connection.

Tracy Sun: And so, in so many ways, we feel like we’ve built a really large marketplace and a really large platform but also a really large place for people to come and to connect with people, either that they know really well or that they’re meeting for the first time. So that’s the second piece. And then the third is Team Posh. So there’s some of us here tonight. Team Posh is really all we have. We don’t hold any inventory. It’s all people. And then a lot of code that happens and a lot of packages shipped around but there’s 400 or so people that are part of Poshmark that really make everything go round.

Tracy Sun: So we spent a lot of time thinking about how we can innovate in this realm and really keep people happy and motivated, creative. And eight years into the business still feel like they’re learning new things every day. And so I’m really excited to kick this off. We have five people coming up to share their story, get into some specifics about the innovation that they’re seeing and the stories that they have. So with that, I’d like to bring up our next speaker. Can I go ahead? I’m going to go ahead and do it. Okay. So our next speaker is Barkha and she’s our Chief Data Officer here and officially one of the coolest women at Poshmark.

Barkha Saxena speaking

Chief Data Officer Barkha Saxena talks about being a data geek, and working with mobile, social, and commerce data, at Poshmark Girl Geek Dinner.

Barkha Saxena: Thank you, Tracy. Hi, everyone. Is everyone having fun? I was telling Tracy that I’m always bummed when I go after her. She’s such a fascinating speaker. So I’m basically making sure that nobody has very high expectation. I’m going after Tracy. So just about a little bit about myself. I’m Barkha Saxena. I’m Chief Data Officer at Poshmark. I’ve been here for five years. But somebody was asking me, I was talking to them, hey, this whole data thing didn’t exist 10 years ago so what did you do then? I was like, yeah, it’s true. This whole world data service didn’t exist but I had been literally doing this. This was my first job out of college.

Barkha Saxena: I studied statistics. Numbers is what I have known my entire life. I spent my first 10 years at a company named FICO. I was a data scientist there. I started as an individual contributor, moved into management role and then I spent some time in product management, sales, and corporate strategy. After that, I spent a couple of years in advertising industry, still focused on the data, building data products for advertising. And then I had my second child and I thought I would take a little bit break. And like in two weeks break time, my husband, someday one day comes and he says, hey, I heard about this really cool startup. They had these virtual parties which is called posh party and I think you should go and meet with them.

Barkha Saxena: And I was like, okay, it doesn’t hurt to meet. So I found a connection to Manish and I met with Manish and Manish said we had some conversation and then he said, “Hey, you should come and meet with Tracy.” You just met with Tracy. Once you talked to Tracy. There is no going back. So here I am, five and a half years ago, I joined Poshmark, still here and having a lot of fun. When I joined Poshmark, it was really the driving factor was people. I met with Manish, Tracy, Chetan, Gautam, our founding team. And honestly, it had been a long time.

Barkha Saxena: Like being in the tech sector, I had not met so many smart but super humble people. And then from being a data geek, this aspect of I’m going to be working with mobile, social, and commerce data. It can’t get any better than that. What I didn’t understand at that time was when you are putting this social and the commerce together, it’s a totally different beast than just thinking about the social network and just thinking about the commerce. So Tracy explained the social commerce from the vision perspective but I’m a data person. So I have to understand it from the data angle.

Barkha Saxena: So how did I understand the social commerce? And how I started to understand it’s really not putting two plus two, four. Really getting them together is we are making two plus two, seven. And the way it works is from the data perspective, when you are selling, what are your goals? You want to acquire users who will come and buy stuff. So at Poshmark, you build your follower network, you follow people, they follow you. And by that way, you are basically finding out the impact, the people who are going to see your merchandise.

Barkha Saxena: Then how do you market inventory? So there is a whole aspect of sharing which happens in the platform. Everyone who is successful in selling at Poshmark knows that you cannot be successful if you’re not sharing. So you’re engaged in sharing, not just your item but you also share other people’s items. Because when you share somebody else, they will share yours and you are basically just expanding the network of the people with whom you’re sharing your item. So you market your items, but then after that, you have to close the deal. How do you close the deal?

Barkha Saxena: You have to engage with your buyers in conversations. So their conversations happen in their platform around fit, style, color, and then Poshmark has built all these tools in the service of community to which you send out offers in a very personal, personalized manner to all these buyers. And that’s how you close the deal. So sellers are very vested in being social in the platform because at Poshmark that gives them an advantage to drive the more social you are, the more successful you will be. Now from the buyer’s perspective, the reason you want to be so socially engaged because when you follow people, it’s exposing you to a larger and larger merchandise which means you are looking at so many items from where you can buy.

Barkha Saxena: So you are getting exposed to the styles of different people. You engage with the seller because you want to be able to understand the merchandise beyond what just the description is telling. If you think of the reason the whole social commerce exists because just in reflecting back, the 15–people who are a little bit older. If you think of the way the commerce was done like 15, 20 years ago. I grew up in India and a lot of time when we went for shopping, we will just go back to those limited number of shops. But it was fine to go because you will go and talk to the person who is selling and that person will know which grade you are in, what you’re doing, what’s happening at your home. And it was fun in those conversations.

Barkha Saxena: As commerce became very efficient with the e-commerce and access a lot of inventory and fast shipping. It was all very efficient but it took the fun away of that personal conversation. And what we have learned at Poshmark is people actually like to connect and talk to each other. So buyers, when they engage with sellers in the conversation on hey, will this dress look good on me or like because the same dress size can be different in different [inaudible]. How do you figure it out it really fits you? So you engage in that conversation and you’re figuring out.

Barkha Saxena: Buyers do a lot of liking activity in the platform and that’s because by doing like you are creating this sort of your wishlist of the items you want to buy. By doing the activity, you’re also building the connections with the seller. So when seller is ready to make an offer, there is a way for seller to reach out to you. So that’s how like when I started looking at social commerce and the numbers started to explain why the social is truly driving the commerce. It wasn’t just hey, we got a commerce, they come less to the social. This is the genius of the founding team who built this amazing platform.

Barkha Saxena: Social is so integrated with the commerce that the two actually drive each other and that is what has gained given us such a unique advantage that we didn’t just try to bring the two pieces together. We built them interlinked from the day one and then you build that kind of platform with the types of numbers Tracy was sharing, like 40 million users and 5-6 million sellers stylist, 18 million shares per day. Think of the amount of data we are collecting. Like we have 30 plus terabytes of data, 400 plus million events logged every day. You leave a data team in that kind of environment. It’s like the wonderland for people.

Barkha Saxena: So my team is so excited. It’s a cross-functional thing. We work with multiple teams and we are solving problems that cross the aisle. From working with the marketing team on different types of users. That question problem. Working with Leanne’s team and helping out how we can serve our community better. Working with Tracy’s team and figuring out how can we help them launch market. There’s so many problems teams are solving, they get to work with humongous amount of data. They get to use different types of data technology and the tools to build out the solutions which creates business value for our community.

Barkha Saxena: And just to bring it back to I’m very lucky to have such a fantastic team which is just building all these awesome solutions. But the reason all of us are so engaged in doing all this wonderful work, going back to what Tracy said, this is just a wonderful place to be. The people are–I don’t know how many have notice our core values. I have worked at multiple places. This is the first place where I would say we actually live by our cultural value. We focus on people, truly on people. You heard Tracy. The whole conversation is started on people. We lead with love. We trust each other. We believe in supporting each other.

Barkha Saxena: We embrace all the weirdness. That is one of the core value. Honestly, even I use it in my personal life. Like when you start to accept people for what they are, life just becomes simple. And then together we go. So we are so vested in each other’s goal that it just makes this place, this beautiful place. With that, let me invite… Can I invite? More wonderful people that you guys can meet with. Okay, thank you.

Tracy Sun, Adrienne Hamrah, Camille Ford, Vanessa Wong, Angela Buckmaster

Poshmark girl geeks: Tracy Sun (speaking, right) moderates a panel discussion with Adrienne Hamrah, Camille Ford, Vanessa Wong, and Angela Buckmaster introducing themselves at Poshmark Girl Geek Dinner.

Tracy Sun: Sorry, I’m just trying to make them nervous. We’re just going to get excited, get loose. Let’s go. So first question, can you introduce yourself a little bit about what you do at Poshmark? So everyone has context of all the amazing things you’re going to say after that.

Angela Buckmaster: Yes. Microphone on. Okay. Hi, I am Angela. And as Claire mentioned, I am the Associate Community Operations Director. And so my team works under the Community umbrella and what we do is actually support all other areas of the community team through data analytics, product knowledge, and training.

Vanessa Wong: Hi, I’m Vanessa. I’m senior director in the product team and I run the core experiences team. And when I say core experience, what it means is the buying, the selling, the social interaction, working with our power sellers, our new sellers, any international expansion. And then also like market expansion as well.

Camille Ford: Hi, everyone. My name is Camille Ford. I work on the new markets team and the markets team is really focused on driving expansion into new business areas. So what that looks like could be developing a new category, launching multiple markets within the product alongside Vanessa’s team or expanding into new departments as well.

Adrienne Hamrah speaking

Software Engineer Adrienne Hamrah talks about innovation at Poshmark Girl Geek Dinner.

Adrienne Hamrah: Hi, everyone. I’m Adrienne. I’m a software engineer on the growth team. What does that mean? I basically work on projects to bring in new users to our platform. Whether that’s like an influencer project or just any like fun new things, new features.

Tracy Sun: So I know it was pretty fun to hear from me and Barkha but these ladies have the real stories that you want to hear about. As I was hearing earlier about what you guys wanted to share. I just thought it was great content to share with this group here. So no pressure. So we talked a lot about… Sorry, I’m being really goofy. It was a crazy day today. We talked a lot about innovation. And I kind of talked about it at high level, Barkha talked about it at high level. Can you guys really bring it home? Like what does innovation look like to your day to day?

Tracy Sun: Is there an example of something you’ve done recently, for example, that you think it was just a really cool project to work on because it involved innovation and, or something around people? I think that would be great for everyone to hear. Who wants to go first? Adrienne, you want to go? We’ll go backwards.

Adrienne Hamrah: So a good example of innovation was we basically wanted to bring the influencers I work with on Instagram, Facebook, YouTube, etcetera. We wanted to bring them onto our own platform rather than going through a third party. So that was my first project, starting from helping the product manager all the way to doing the tech spec and actually executing on the code. And one example of innovation is in order to like see the level of influence someone has, we have to have some sort of metric so we know how much to pay them for, for posting on Instagram, for example.

Adrienne Hamrah: And instead of going through their API because there was a lot of stuff going on Instagram and they’re saying they were taking away their API, we decided to actually just use the HTML code and get their stats that way. So I think that was a really fun example. Because the first thing, if you’re familiar with software, the first thing you usually do when you talk to different companies, is you go through their API. And we decided to just bypass that completely.

Camille Forde speaking

Senior Manager of New Markets Camille Forde talks about markets and using technology and social as tools at Poshmark Girl Geek Dinner.

Camille Ford: So the innovation question’s interesting because I feel like throughout my career I’ve always tried to think about how can I do something different? But at Poshmark, I feel like that question gets tipped a little bit. It’s how can we do things differently using social as a tool, using a technology as a tool. And so I feel like working on markets for the past six months is a really good example of that. And so markets themselves are just easy experiences within the product that make it easier for people to connect, sell, and shop by what’s important to them.

Camille Ford: And in many ways, it’s just a layer on top of Poshmark’s existing platform, but really digs into the social piece, which is, brings it back to people, I think at the end of the day. And so for me, even working on markets and figuring out like how can we get people to shopping experiences that are relevant? It’s almost like this backwards thing where through markets we’re now enabling people to shop the way that they used to shop.

Camille Ford: So if I only wanted to shop luxury and I want to go into a luxury store and I want that like real-time feedback on a certain thing, I can get that through the luxury market on Poshmark. And so to me, this is like an interesting full circle view of innovation around how can we use the tools that we have to kind of bring it back to its core. And so just working on launching markets over the past six months, I think now we have roughly 25-ish markets has been an interesting experience for me with regards to innovation.

Vanessa Wong: So, many years ago, we launched a feature called Offer. And what that feature is, I don’t know if any of you… Has anyone used it? Raise your hand if you’ve used that feature on Poshmark? So it really mimics normal behavior. You’re there like, think about the olden times. You’d go barter and negotiate. And we kind of bring that to life in the app. So what we did last year is we launched a feature called Offer to Liker. Has anyone ever liked an item on Poshmark? Has anyone had a listing and gotten likes on Poshmark? Yeah.

Vanessa Wong: So it’s an amazing feeling. You know that these people are really interested in your product. And so you’re getting all this love for this product. And so we thought why don’t we use that energy to the seller and help them. So what we launched is Offer to Liker and where you can give a private discount to the people that like your item. And that’s been amazingly successful for us. We’ve just used kind of normal behavior and we’ve used that organic behavior and we’ve amplified that through our product.

Angela Buckmaster: Awesome. So I’m kind of echoing some of the things that you’ve heard. Poshmark is a social commerce platform. And so on the app, people are commenting and communicating with each other on listings. They’re liking. They’re communicating and building bonds with each other through buying and selling. And so from the very early days of Poshmark, we actually saw that these users, these poshers, were, as Tracy mentioned, getting together outside of the app, as well, very organically and just meeting up.

Angela Buckmaster: There’s actually a term that has been coined for someone that’s a friend that you meet on Poshmark that is PFF which is Posh Friend Forever. And so, as you can tell, these bonds are lifelong. And so we saw this and we thought, okay, this is really, again, the lifeblood of Poshmark. We are all about the people and spreading the love. And that’s the only reason all of us are here today. So we came up with a type of event called a Posh N Sip. And the Posh N Sip is a posher-led event.

Angela Buckmaster: And these poshers are finding the venues. They are inviting their friends, their family, their PFFs, to get together and not only talk about Poshmark but also just build upon these bonds. And make more connections and really grow and empower each other. And so I think, to me, that’s something that’s super exciting because we get to see them meet all over the country and just get together and just kind of continue what they have on the app but in the physical world as well.

Tracy Sun: Okay, great. So we talked a lot about innovation and if you guys want any more, feel free to ask. They’ve all agreed to stay for the Q&A so you can’t leave. We’re doing a Q&A right here and then after if you have questions that you want to do in private. Now I want to talk about you as people. You have so much experience that I think is so interesting. It was really interesting to me to hear it. I think it’d be really interesting to everyone else in the room mostly because we’re all so different. Our stories are all so different.

Tracy Sun: And so can you share a little bit about how you got to Poshmark and if there is, and with that, is there anything you did along the way that kind of helped you get into the role or any tip you have? I imagine anyone, here either now or in the future, might be looking to make a change in their job, for example. So if you have any tips on that or you might want to have a job. So if you have a job are they any tips on how to be successful. It’s just you are four really successful women. And then I think I’d like to give a little bit of the floor to that. You want to start, Angela?

Angela Buckmaster: Yeah. Awesome. So I actually have been at Poshmark for a little over six years now. And so I found Poshmark through a friend who still works here. We were friends through middle school and high school, and she heard that I had graduated college and was looking for my first big girl job. And she was on a community team here and said, hey, you should come interview. So I did. And at the time, we had basically one role, which was community associate. And through that, we wore a lot of different hats, as is typical at a startup. And from there, we kind of started to build into different teams.

Angela Buckmaster: And so from there, I moved into the support team. It’s still under the community umbrella and I did some management for a couple of years. And through that, I noticed that I started having and more of an interest in our KPIs and our SLAs. And I wanted to know why are they the way they are. How can we make them better and to really understand them on a deeper level. And so I started speaking to my manager and Leanne, our SVP, and just letting them know I’m really interested in this. I would love to move into more of a data-driven role.

Angela Buckmaster: The time wasn’t right, right at that moment. But I kept telling them and I kept trying to get into projects that I could kind of dip my toes into the analytics area until the day came when Leanne approached me and she said, “Okay, the role’s here, let’s do it.” So I happily went to that more of an analytics role on the community team which was awesome. I got to stay with my community family and did that for about a year.

Angela Buckmaster: And then Leanne approached me with another opportunity and said, “Hey, let’s build out this team.” So now I have the three areas. I have a data analytics team, a product knowledge team, and a training team. And so I’ve learned a lot over six years. I’ve learned that you can’t just keep your dreams to yourself. I think something I really believe is whatever you think about and you talk about all the time is what you are or what you will become. And so I was very open and I kept telling people about my dream and I truly believe that that’s why it happened. Because if you don’t speak up, no one knows. So if that’s my little tip, I would encourage you all to just be very open about your passions and your dreams.

Tracy Sun: That’s so amazing that, Angela, you knew your dream and then went and told your boss. That’s so vulnerable. It’s so scary. Has anyone here done that? Told your boss you want a different job or you want a different you know. Anyone who wants to do that? Just kidding. I love my job. I was just trying to get people… So if you’re one of the people raising your hand, come talk to her. Because she did it and sounds like it worked out for her. So, Vanessa, you want to go?

Vanessa Wong speaking

Senior Director of Product Management Vanessa Wong talks about her journey in product management, and moving on up, at Poshmark Girl Geek Dinner.

Vanessa Wong: Cool. So when I graduated college, the economy wasn’t great and I was just applying jobs everywhere. I was hanging out with my unemployed friends. It was really fun, but my parents were like you need a job. And me being a geek, like many of you guys, I saw a job posting. I don’t know if you guys have heard of CNET? They review electronics and I love electronics. They do a lot of cool tech stuff. It’s in San Francisco. Super fun. And I got a job there. Just amazing. And it’s at a big company. It’s like, “Wow, that’s really cool.”

Vanessa Wong: But I started my job and I was really bored. It was just something, yeah, it was a job, but it wasn’t something fulfilling. But then I got immersed and started talking to people and I got involved in helping building tools for that team with engineering. I was kind of doing product management for the backend tools but I wanted something more. So like Angela, I actually went up to my VP and very–more like a “Hey, this is something I’m already doing. What can I do next?” Like, “How do I prepare myself? Do you have advice for me? Do you have input?”

Vanessa Wong: And he was very open and receptive and pretty much immediately he was like, let’s craft a role for you, which was amazing. I did not expect that. I came to kind of talk to him, building a case, not sure what would happen. I definitely was really scared, but he was very receptive and I got the role as a project manager to help build internal tools. But deep down, I really wanted to work on the user side. So I was building tools for the shopping team. So that was my kind of first step into shopping which kind of leads to where I am at now.

Vanessa Wong: And so then I was in that role for maybe about a year and then internal opening opened to be a PM for CNET shopping and CNETshopper.com and I applied. And what was great about the people at CNET is that they were so supportive. My manager was like, “Hey, yeah, go, go talk to that hiring manager.” And we were able to work through and I was able to transfer into that role. And then I was there for several years and then it kind of leads me to Poshmark where my then boyfriend was like, “Hey, there’s this job opening at this company called Kaboodle.”

Vanessa Wong: And Kaboodle is our CEO, Manish Chandra’s, first company that he started. And I just applied. I was like, okay, this seems pretty cool. I’m already doing something in shopping. This is social shopping. This is pretty new then. And then I applied and I wasn’t sure about this whole thing because it was still pretty new. Social shopping was a pretty new concept back in the day. And then I applied and then worked there for several years. I went on with my journey in product management to many different companies.

Vanessa Wong: And then I had kept a close relationship with Manish and he’s always been my mentor. And then one day he’s like, “Hey, what about joining Poshmark?” And I was like, “Yeah, of course.” This seems natural to work with people you really trust and you really admire. But coming full circle back to my role now, just a couple of weeks ago, someone on my team, she came up to me and she kind of did the same thing that me and Angela did.

Vanessa Wong: She’s like, “Hey, I love what I’m doing but I want more. Can I talk to you about it?” I’m like, “Yes.” She’s like, so the first thing she said was, “Sorry, if I’m being aggressive,” and I stopped her right there. I was like, “You’re not being aggressive at all.” Like, “I welcome this. Please, please feel that you can do this any time. I’m here to help you fulfill your dreams.” So we’ve started this conversation and we’re really helping her where we’re going to really help chart her to her dream.

Tracy Sun: That’s amazing.

Camille Ford: I’m going to cry.

Tracy Sun: Yeah.

Camille Ford: Sitting next to her. So there really are some interesting themes here. I also graduated when the economy wasn’t doing so hot and I felt like, what is the responsible thing to do now? Go be an accountant. And so my team teases me now because I call myself a recovering accountant because that’s exactly what I am. But I started my career about 10 years ago at PWC. It felt like that was the right thing to do. That was the safe thing to do. I had student debt, but it was like not the right thing for me at all. In about a couple of years into doing that, after I felt like I had a good foundation around financial services. I was auditing at the time, mainly VC funds and private equity funds.

Camille Ford: I also then went to my boss and said, I’m not happy. Like, I like it here. I like the people, I like the culture, but I don’t like the work that I’m doing. And I feel like there’s a part of my brain that’s withering away because I’m not doing anything creative. And they helped me, they helped me find a new role. And so I moved into a marketing function where I felt like I could get some different functional expertise in something that felt like I would be able to still use the analytic side of my brain but also use the more creative side of my brain as well.

Camille Ford: And it was a really great learning experience. But after a little while, it also felt like, okay, what’s next? This isn’t quite enough. And so I made the decision to move from the East Coast. I was in Boston at the time, go Bruins, and I moved to the West Coast to attend business school. And I was really intentional about my time during the MBA to just like, one, unlearn all the stuff that I didn’t feel like was for me. Because I told myself, “You are an accountant. You are only the analytical person. Who are you to think that you can be creative? Who are you to think that you can find both of those things in one job and be happy? Who are you to think you can work in fashion at all?” And really opened myself up to the possibilities of what could be.

Camille Ford: And so I spent those two years just doing a lot of internships in fashion tech and just retail and trying to just learn everything I felt like I didn’t know. Interestingly enough, I had been a user of Poshmark for several years. Actually, before I moved for business school, I sold all my stuff on Poshmark, moving across the country. And it was right before I was about to graduate. I look around and a lot of my classmates have these fancy jobs. They’re all set. They’re enjoying all this traveling and here I am still recruiting up until the day of graduation.

Camille Ford: I’m looking at Danny back there because I got a call from the Poshmark recruiter on the day, the morning of my MBA graduation and I thought he was going to say, Camille, we have an offer for you. He didn’t. Instead, he’s like, “Camille, we don’t have something for you right now. But like we still want to stay in touch.” And that was a little heartbreaking, to be honest, going into graduation, but still stayed the course. And a week later which actually was on my 31st birthday got a call from Danny again and this time it was like Tracy’s ready to make you an offer.

Camille Ford: And I share that level of detail only to say that what got me through like, one, switching these functions, kind of keeping the momentum up when I felt like I wasn’t necessarily getting to the place that I wanted to be in the time that I wanted to be at, to get there, rather, is just this layer of tenacity. And just going after it and knowing that like you are totally worthy of whatever it is that you think that you can get. Because the opportunity might not present itself right now but it definitely will.

Camille Ford: And so just staying the course that you feel like is true and natural to you and not being nervous that like, “Hey, I’ve invested all these years in like financial services.” Like that’s what I’m an expert in. No, like, now I’m an expert in social commerce. Or I’m going to get there. So just being really honest with yourself and not giving up on yourself would be my best advice.

Adrienne Hamrah: That was amazing. So like everyone else, I also had a career change. I actually had four. So 10 years ago, I was in school. I was in structural engineering and undergrad and while I really liked like calculating forces and making sure things don’t fall down in buildings I ended up getting–

Tracy Sun: Me too, by the way.

Adrienne Hamrah: Yeah, it’s still like every time I drive over a bridge I’m like, I hope this bridge like doesn’t shake. That’s always in the back of my head. So I ended up actually taking a job in civil engineering with the city of San Francisco, interned there for public works. Really, really boring. I worked on sewers and sewers are very, very boring. They like fall apart every 100 years. There’s not much thinking involved. So I went back to school, got a masters in engineering management because I wanted to learn more about the business side, the people side of things.

Adrienne Hamrah: And then after that, I actually went to Verizon. I did a four-year rotation program and that was really, really cool. I got to do four different jobs in four years. Got really great training with executives, seeing how they run a really large company. But telecom was also very boring to me. It’s like there’s only so many cell phone towers I can design. They all look the same and not very challenging.

Adrienne Hamrah: So I shifted again, I decided to become a product manager, and luckily, a girl from high school was the recruiter at a really small startup of 55 people at the time. It was in the cancer research clinical trials space. And so that was really interesting to me because I actually was pre-med for a hot minute in college. So I was like, I’m going to go back to healthcare. As a PM, though, I was doing internal tools and I don’t think that was the right fit for me. And also, the management there was just a disaster.

Adrienne Hamrah: And I think the most important thing I learned out of that is it doesn’t matter how cool the space is or how cool you think the product is. If the people, if they’re not the right fit for you, then go. Because you’ll find someplace else better. So after going through that experience and even though I was like this is such a cool like company, I was like, this is not the right thing for me. So I walked away and then I decided to go into software, so I did a boot camp.

Adrienne Hamrah: It was a three-month boot camp, 100 hours every week of coding. It was the hardest thing I’ve had to do. Harder than structural engineering undergrad because it was all crammed into one. But I came out of it absolutely loving it. I met up with a girl at a new restaurant opening. She’s actually there, Christina. Because we do food influencing on the side. And so she was like, I work at this company called Poshmark. We’re always hiring. I’m sure we have software engineer openings. Why don’t you like look?

Adrienne Hamrah: And so I took a look. I decided to apply. She referred me and I just absolutely fell in love with the culture, the people first, and then it happens that the product is also something I love and I use as well. So it’s like best of both worlds. So I think my tip is, first, if it’s not the right fit for you, don’t be scared to move. For me, I moved four times, four different companies. But just don’t settle and just go for it.

Tracy Sun: Thank you for sharing your stories. You guys, can you give them all just a… Yeah. Amazing. So I’m going to ask one more question and then I think we’re going to open up to Q&A. So those of you who know me and there’s a lot of you in the room, I’m a huge believer in superpowers. So I just gave Poshmark a superpower, which is people-powered innovation. And what I mean by a superpower is that there’s typically one thing that you can do that you know you do better than everybody else. And if you’re lucky, it’s useful in your personal life or career, but it doesn’t have to be.

Tracy Sun: And so I think it’s really–sometimes you don’t know what it is and sometimes it can change but I think it’s really helpful to have that conversation with yourself. Like, what is my superpower? So that you can carry that with you and just know, no matter what, I can do one thing better than everybody else. And I think that’s great for confidence. So I wanted to–this is one of the questions I snuck in there so I’m not going to call on anyone. But if you want to volunteer and share with us your superpower, my hope is that if we share then if you don’t know what yours is maybe we can help pull it out of you by sharing what ours is.

Tracy Sun: So I’ll just start. I didn’t know this until a few years ago but I think one of my superpowers is that I’m really good at telling stories if I care. And I’m really bad at telling stories if I don’t care. And so going back to like career stuff, I have to do things that I care about because then I do my best work. So I think my superpower is, I’m a good storyteller. Anyone want to share?

Adrienne Hamrah: I don’t know if this is a superpower, but I can literally talk about food forever, which is like it’s how I got this job. It’s how I got the job before this one. It’s great because like this company loves food too. So it just worked out and I’m like a supertaster. So I’m just very sensitive to like ingredients as well. So I’m the kind of person sitting at the table and like asking the waiter like, “What exactly do you put in here?” “Oh, yeah, yeah, I did taste that.”

Camille Ford: That’s funny. My superpower? I would say that I’m really good at building relationships with people. Not like massive amounts of people, but if I like find my group, I can really build deep relationships with them and it certainly served me at work, given that the markets team needs a lot of other people to get things done. But it just played a big role in my life to be able to like put myself in other people’s shoes.

Camille Ford: And it’s funny because my friends tell me I’m a good listener. My mom tells me I was the worst listener as a child. So I’m not exactly sure how to reconcile that. But other than kind of going this back to this point around caring. For the people that are around me, I care a lot, and building relationships has been something that I found I’m pretty good at it.

Vanessa Wong: So for me, I don’t know if this is a superpower, but I think this applies to–how many moms are out there? Yeah. So I’m a mom to three young children. I have three girls. They’re all under the age of five so I have to multitask like crazy. My husband has a really busy job too and so I think that carries on into my work life and personal life. I became super efficient after I had my first child. I don’t know if that applies to you other moms too. So I would say a superpower that I have is just being able to manage multiple things, switching context here and there and just being able to switch gears on the fly and just to readjust and reassess and prioritize accordingly. So, yeah.

Angela Buckmaster: So I think my superpower is actually something that other people knew about me before I knew it about myself and that is that I will and can support anyone in anything they want to do. So when I was a kid, I was the kid in elementary school who would get put in groups with like the trouble kids because I’d be so patient and supportive but I could like help the group get to the group project and get through it. And so for a lot of years though, I didn’t really realize this about myself and people are like, you should be a teacher, you should do this, you should do that.

Angela Buckmaster: And I always was like, “Oh, what’s my skill? What’s my thing?” And then actually being here at Poshmark and noticing kind of the roles I drifted towards and the people that I drifted towards, I kind of drifted towards the natural leaders because I wanted to support them and empower them. And I found eventually by spending a lot of time looking inside that that’s actually something I enjoy and I’m really good at. So I would say that’s my, my superpower.

Tracy Sun: Thank you guys for sharing. Let’s open it up for Q&A. If you have questions, I don’t know what to do. If you have questions, the mic is coming around. Raise your hand. Barkha, do you want to come up here? You’re fair game for questions. Thank you.

Speaker 12: Thank you. Thank you for sharing. I have two questions, so you can answer either or. One question I have is just about how you try to maintain the company culture as you grow into a larger company eventually over time? The other question I’m curious about is how you use innovation to stay ahead of your competitors? Who are your competitors?

Tracy Sun: Angela, you want to take those questions?

Angela Buckmaster: Yeah. So the first question about culture. I think for us, like you said, we’re scaling so much, so rapidly, not only internally, but externally. And so we have to think about both. And tying back into something I said earlier, I think that the way that we make sure that we continue to scale our culture is to make sure our culture is top of mind. Because again, if you think about it, if you talk about it, if you embrace it, it’s only going to get better. And you can never forget about it. So doing things like making sure we stay in touch with both our internal and external community all the time. Even at the company here.

Angela Buckmaster: So when I started six years ago, we were in one room and I knew everyone, I knew what they ate for dinner the night before. And now that we’re spread out and we’re on two different floors, it is a little bit harder, but you have to remember that we are all working together towards the same goals. So we talk to each other a lot. I can still go up to anyone in the company and talk to them about anything that’s happening inside or outside of the app. So I think again, just keeping it top of mind and always trying to think of how can we do this better has made us be able to scale our culture with the company.

Vanessa Wong: Yeah. Actually, I’ll do the first one too and I could go a little into the second one. So for our product features whenever we build something, we look at what our values are and we always make sure they’re rooted in there. So our CEO is really into love. I don’t know if you’ve guys have… You should catch some of his videos on YouTube but he always says something where you lead with love and with love comes money. And we use that a lot in our product thinking. We have a like, which is a heart, but we don’t have like a hate or dislike. Like how Facebook has different reactions.

Vanessa Wong: We always–everything is really positive. Everything is really transparent. And that goes along with a lot of our company culture as well. Everything is transparent. You can voice your opinion. You know what’s going on at our all hands–all the information is kind of disseminated into everyone. So that’s kind of how we look at when we’re developing products. As far as our competitors, yeah, we’re always checking them out. They’re always doing cool and unique things.

Vanessa Wong: But again, I think because we’re so different. We have like the largest community, social community out there. We have to take a little different angle. We can’t be like an eBay. They’re very different than us and whatever–let’s say we do something similar to them, it may not work for us. So we’re always on the lookout, but we always search within of like what would really help our sellers stylists? As people, they’ve started their own businesses on Poshmark. How can we empower them and how can we help them grow? You’ll be good…

Tracy Sun: No, no, no, no. She’s all right. I was going to echo.

Speaker: Do you have another question? Otherwise, we can keep going. All right there. Is there a mic?

Audience Member: Hi. I have a question about user feedback. How do you gather that and how do you incorporate that into the product development and innovation?

Angela Buckmaster: You can maybe onto that.

Vanessa Wong: So I actually work with people like Angela and we meet with the community team very often. I look at our Facebook groups and we talk to our users. We go to Posh Fest and we’re very connected to our users and we hear what’s going on and we incorporate that into our product roadmap. There are things that our users may request but they may not fit in. They might think that that is the solutions for them. But when we internally talk about these things, we think one step further is like, is that really helping? That might be one thing but we have a larger plan and larger vision for them.

Vanessa Wong: And I think one of the coolest things that I’ve done at Poshmark is each year, we have an annual get-together with our seller stylists called Posh Fest. And I’ve been very fortunate the last couple of years to kind of announce what we did for our hackathon. And so what we did is we had users submit things that they’ve want in the app and we get like, I don’t know, thousands and thousands of requests. And they’re like the spreadsheet is crazy.

Vanessa Wong: But I love looking at it each year because I’m like, “Oh, this is what they’re interested. This is what they’re passionate about.” And so, for example, last year we were able to rehaul our newsfeed and this is something that the users have wanted for so long and they were so excited about it. Another killer feature that we launched was they’d been always wanting a draft listing and so we were able to launch that. So that was really amazing.

Speaker: I think we have a question over here.

Audience Member: Thank you, everybody. I’m actually a Poshmark buyer, especially. I’ve been seller but buying more than selling. And so a question I have for you that I’ve noticed is that there is a very distinct culture within Poshmark. And I was wondering, how do you ensure that positive culture and thinking when like cybersecurity issues or bullying issues and things like that online considering there’s 40 million users, how do you use data or how do you think about the product or how do you build the communities to be able to continue that very specific type of culture that’s already been there? And especially around Cybersecurity anti-bullying.

Tracy Sun: So I’ll start and then Barkha, if you have anything to add, let me know. So we get this form of question quite a bit. And the first thing I’d say is it’s really hard to fake a value. So when you talk about the values that are our unique community, I’d say that comes from what we want and it’s a little bit of the world that we wish we had before we had Poshmark. We live it here at headquarters and it’s, we intentionally said let’s also build it into the user experience and also to our community.

Tracy Sun: And it’s really hard to fake that because you almost have to be a little bit crazy about it and not know you’re crazy. And in that way then you just naturally start to act in a way that’s according to your values and it becomes stronger and stronger. So what we did is we talked a lot to Angela’s point. We knew people were important to us. We knew culture is important to not just culture here, culture in our app, in our community. So we had that top of mind and built everything with that in mind.

Tracy Sun: And there are some times where we said this would make sense to make more money. But this doesn’t make sense if we want to be empowering to our sellers. And so we had our North Star and we chose that path. And so if you know what your North Star is and for us, it’s our people, then it’s easier to make those decisions when those crazy moments happen and you’re panicked and you don’t know exactly what to do. I don’t know if I can answer anything about cybersecurity. Can you? Where is Chetan?

Barkha Saxena: Or Gautam.

Tracy Sun: Or Gautam?

Barkha Saxena: Well, the only thing I would say is we also rely on our community to help with that. That’s the power of this community who is very passionate. For them, Poshmark is not just a product. It’s their own thing. So they really help us with that too. Like there’s lot of comment reporting, a lot of reporting that happens which goes to Angela team and of course, you have to look at it like the… You can report anything. But that’s where their team has the expertise in knowing like how to do it. But I think it’s our community who is actually allowing us to scale more than I would say the data in this case.

Speaker: We’ll take a few more questions.

Audience Member:  Thank you. And thank you guys so much for volunteering your time to talk to us today. My question is around branding, especially when starting a company and starting a venture, especially social like Poshmart. How did you decide your values and how did you decide what kind of brand you wanted to put forward?

Tracy Sun: So I touched a little bit before… I’ll take, okay. I touched a little bit before about our values and just to recap, I think it comes from what you deeply care about and the founders and the founding team, we have a lot of things in common but I think one of the strongest things we have in common is just a belief in the way we want the world to be. So it’s almost outside of business and it’s not just a company value. It’s like our personal values. So it comes from there.

Tracy Sun: In terms of branding, I think that’s a really interesting one for us. And when it came time to really formalize our thoughts around brand, we were a little bit confused because we’re a company that wants to empower other people. And so if you create a really strong traditional brand, likely you will alienate some people. So I come from the fashion background. So my first thought was, “Ooh, we’re going to create a really cool logo and all of our messaging and all of our images are going to look chic and sophisticated.” Things that you had imagined at like Net-a-porter, for example, or just another cool brand. But we’re like, “Yeah, but 80% of America doesn’t want to see that. So what do we do then?”

Tracy Sun: And plus all of our sellers, they have their own story. How can we possibly create a brand around our story? And this is where those core values come into play. And one of our core values in terms of how we prioritize our time is to get behind our sellers, get behind our community, and make sure that we’re empowering them. And so when we think about brand, our brand became empowering sellers. And so when you see some of our videos or you see where we put our energy into things that might be called brand. We usually don’t put our faces, we put your faces right and we celebrate your wins. We don’t really celebrate our wins because if you or the community’s winning, we know we’re winning. So a lot of our brand is around community, honestly.

Speaker: Last question.

Audience Member: Thank you all so much for taking the time to speak with us today. I was wondering if you have an example of a challenge that you’re facing as a company right now or maybe in the recent past. And I’m interested in hearing about what kind of problem-solving methodology you use in a fast-paced environment like Poshmark.

Vanessa Wong: So I think one of the problems is scaling. We’re getting larger. Our app has a lot of different things in there. We want to introduce new features, but I think the core thing is keeping it simple. We don’t want it to be complicated. We don’t want a million steps in the listing flow. We don’t want to make buying complicated. But we do want to introduce new things that are useful for everyone. So I think one thing we’ve introduced within the last couple of years and we’ve introduced a concept of a metamodel.

Vanessa Wong: And what it is, is it’s basically a core set of principles that you kind of adhere to when you’re building a feature and really mapping it back to those. So if I’m going to create this button, like does it really adhere to what we’re trying to do? So really sticking that and it really gets the team aligned, as well. So let’s say we have a team of like 10 engineers working on it. That helps us really stay focused and make sure that we’re reaching our North Star.

Tracy Sun: Just to add one thing to what Vanessa said. The metamodel is a great one. But really that the problem that we’re facing that led that to be the solution is that we used to be a team that would sit around the table and design the product and then we grew to 400 plus people. And what we found is conversations were happening all over the place about the same project in different offices. We have three other offices around the world, and we had trouble–We would always try to communicate but things would always slip between the cracks.

Tracy Sun: And so that’s a challenge of scale that we had is we were not talking to each other in a way that — we weren’t communicating. We were talking and not communicating. So what the metamodel does, and you can call it what you want, but it gives guidelines. Here’s the core values. Here is what when we’re doing a feature, when we’re doing a project, we’re doing a campaign, here’s what it should do. And so double check yourself so that we don’t have to. We can be more nimble as a smaller team.

Speaker: All right. Thank you so much. Let’s give them a big round of applause here.

Tracy Sun, Claire Berkley

Technical Recruiter Claire Berkley passes the mic to SVP of New Markets and Co-Founder Tracy Sun to deliver opening remarks at Poshmark Girl Geek Dinner.


Our mission-aligned Girl Geek X partners are hiring!

Girl Geek X Palo Alto Networks Lightning Talks (Video + Transcript)

Like what you see here? Our mission-aligned Girl Geek X partners are hiring!

Gretchen DeKnikker, Angie Chang

Girl Geek X team: Gretchen DeKnikker and Angie Chang share their excitement for Palo Alto Networks Girl Geek Dinner in Santa Clara, California. There was a photo booth for making girl geek flipbooks!

Speakers:
Varun Badhwar / SVP of Products and Engineering / Palo Alto Networks
Liane Hornsey / Chief People Officer / Palo Alto Networks
Nir Zuk / Founder & CTO / Palo Alto Networks
Citlalli Solano / Director, Engineering / Palo Alto Networks
Meghana Dwarakanath / Manager, SQA Engineering / Palo Alto Networks
Archana Muralidharan / Principal Risk Analyst / Palo Alto Networks
Paddy Narasimha Murthy / Senior Product Manager / Palo Alto Networks
Angie Chang / CEO & Founder / Girl Geek X
Gretchen DeKnikker / COO / Girl Geek X

Transcript of Palo Alto Networks Girl Geek Dinner – Lightning Talks:

Angie Chang: My name is Angie Chang, founder of Girl Geek X. I want to thank you all so much for coming out tonight to this beautiful… Thank you so much to the Palo Alto Networks for sponsoring. I’ve never been here and the campus is amazing. This space is beautiful. We’ve had so much fun meeting people here, checking out the demos, eating delicious food and drink. Now we’re really excited tonight to meet some of the people who work here, talking about their expertise.

Gretchen DeKnikker: Angie was going to tell you this part but I’m going to tell you. Okay, did you guys see all the cool stuff? There’s a photo booth here, over there and you can do that. Then you can make a little flip book where you move and then they’ll make you a little flip book on the spot.

Gretchen DeKnikker: There’s demos back there, which seem to be fabulously popular. Got the little cards. There are recruiters all over so if it seems awesome here, and it seems pretty awesome, the food’s awesome, everything’s awesome so far, right? Yes?

Audience: Yes.

Gretchen DeKnikker: Yes. Okay, so if you want to work here, they’re also hiring. Then you can work with some of these amazing women that you see here tonight. Girl Geek, we do these every week. Who’s their first time here?

Gretchen DeKnikker: Okay, cool. We’ve been doing these for about 10 years. We’ve done over 200 of them. We do them every week now up and down the Peninsula, in San Francisco. If this is fun, make sure you’re on the mailing list and come to the next ones.

Gretchen DeKnikker: We also got a podcast, we just got going. I think we’re on episode eight. What was it about? Tech stayers. Yes. Don’t leave. Tech stayers. But there’s ones on impostor syndrome and mentorship and career transitions and learning styles and just like, so check it out, it’s on all of your usual podcasting places, and then let us know if you like it or what we could do to improve it because we’re not podcasters, we have no idea what we’re doing. We’re just talking, like I am right now.

Gretchen DeKnikker: Without further ado, thank you guys so much for coming tonight and I don’t know who I’m turning this over to.

Varun Badhwar: I’ll take it.

Gretchen DeKnikker: Okay. Let’s welcome the man to the stage.

Varun Badhwar speaking

SVP of Products and Engineering Varun Badhwar warms up the crowd at Palo Alto Networks Girl Geek Dinner for talks on secure development, secure design, how security is just such a core part of development life cycles.

Varun Badhwar: Thank you. Privilege to be here. Good evening, everyone. Really an honor to have all of you here. My name is Varun Badhwar. Figured I’d just spend a few minutes sharing a little bit of my story. I’m six months or so new into Palo Alto Networks. Came in through an acquisition, actually. We recently, Palo Alto Networks acquired a company called RedLock. I was a founder CEO of that company. As a startup, one of the biggest things that makes you successful, brings the teams together is really the culture, right?

Varun Badhwar: A lot of people, there’s no product, there’s very little salary we can pay people, the office isn’t as nice as this, but ultimately we join companies for the people who are going to work with and really a grand vision of a problem we’re going to solve. That problem for us was securing the cloud. As you’re doing that and as you’re building… For those of you who are not familiar with cybersecurity, there’s normally in this industry, if you’re successful, you likely end up getting acquired by just potentially six or seven companies that can do that.

Varun Badhwar: For me, a lot of people have said, we were only three years into building RedLock, sort of how we ended up here? Why did we make that decision? Ultimately, Palo Alto Networks, for those of you not very familiar with the company, has always been at the very top of that list for us for a couple of reasons.

Varun Badhwar: One, is you’re going to hear from our founder, Nir and the team. Just incredible pace at which Palo Alto Networks has disrupted the market, has taken a leadership position, now is the largest pure play cybersecurity company in the planet.

Varun Badhwar: More importantly, all of that has been done with only 6,000 people in the company, right? Larger companies in security have 80, 100,000 people. For us, it’s been fantastic. You come in, you get the best of feeling like a startup operating really rapidly yet having a culture, and having values that are very startup like. Everything from empowerment for the teams, empowerment down to individuals working in this company to–

Varun Badhwar: I’ve just been fascinated with how important diversity has been to this company. Obviously this is one small commitment towards that. But as I can come in here and I’m asked to go work towards our annual conference, which is Ignite that’s happening next month. From the number of attendees, our customers that are coming and tracking diversity statistics there to how many speakers we’re bringing to the table, have these advanced diversity there, diversity in hiring. and diversity obviously is is about professional backgrounds–

Varun Badhwar: Maybe, heck, if you look at our CEO, he never worked in cybersecurity before this, he came from Google, right? He’s first timer in cybersecurity, so for those of you say, “This feels like too geeky of a space.” Not really. I think we really appreciate diversity. Whether you’re coming from a consumer background, enterprise background, you get race, ethnicities, values as well.

Varun Badhwar: I don’t want to take up too much time here. Just articulating a couple of things. One, phenomenal company. We’ve loved the last six months. My teams tell me we are working harder than we did at a startup and having a lot more fun. The fact that the values are so aligned to–what I think a lot of us love probably the companies we’ve worked for. The intersection of just cybersecurity, and specifically for my part, cloud is just so fascinating. It’s a cat and mouse game, security. You’re never done building products that work well. You’re always against forces that are from–Maybe Nir will touch on, it’s a good topic for him.

Varun Badhwar: There’s people that are putting more and more emphasis. Attackers are trying every which way to get into people’s environments. They just need to be right once, we need to be right every time with the products that we build, right? Really an amazing career opportunity. Again, want to thank you all for coming here. Hopefully, you’re going to learn a lot about secure development, secure design, how security is just such a core part of development life cycles. I will pass that over to Liane and Nir.

Liane Hornsey speaking

CPO Liane Hornsey talks about the the inclusion agenda at Palo Alto Networks Girl Geek Dinner.

Liane Hornsey: Hello, everybody. I am the Chief People Officer of Palo Alto Networks and honestly, I love moments like this, and I really love moments like this because I’m in the company of a lot of technical women. I always feel, oh gosh, they’re so much better than me. They’ve got all these skills I haven’t got. They know how to code, they know how to build product, they know how to make things happen, and I work in HR. But I also think and feel very, very humble when I’m with technical women, that it is also harder for women in technical jobs to come to work each and every day. It’s harder for them than it is for me.

Liane Hornsey: When I walk through this door, I walk into a function and I’m surrounded by other women. I am not surrounded just by people who are different to me. So I don’t carry that burden of being different as I walk through the door, in the same way as many of you do. Because you work as a minority in many of your teams. I’m doubly in awe, because you can do all these things and you have all these skills that I don’t have, and you have that additional, not burden, but that additional concern of being different.

Liane Hornsey: Now, I have only been at this company for seven months, a little like Varun, about the same time. I joined this company, honestly, not really knowing much about this company. But truly, I have come to love this company with all my heart. I really love this company, and I want to tell you why. Partly it’s this, I truly believe you have to work for a company that is doing good stuff.

Liane Hornsey: Every night I drive home and I turn on my radio and I feel just that little bit less safe. Every day I think about my children online, who are a bit bigger than your children. But I think of them online, and I think about their safety. Every day, particularly as a European, I think about the importance of cybersecurity. I know I am working for the good guys and I’ve got to tell you, that feels really very, very nice, but it’s not just about what we do. What I really love about this company is how we do it. When I first came here I met my team and the first thing they said to me is, “We don’t have D&I here. We don’t have diversity and inclusion.” I’m like, “Whoa, bit weird,” and they said, “No, we have inclusion and diversity.” Then I thought, yeah, yeah, that’s a bit of a fad. You’re just changing the words around.

Liane Hornsey: But I do want to impress something upon each and every one of you. Diversity and inclusion does not work. There is no point putting in more underrepresented minorities into companies that can’t change and make them feel welcome. There is no point pulling more women into technology, if you can’t make them feel like they can bring their whole selves to work each and every day.

Liane Hornsey: For me, it’s not the diversity agenda. It’s about the inclusion agenda, and that is what Palo Alto Networks is going to be known for. That is what we are going to do that is different and unique. I don’t believe there are companies in the valley that have solved the diversity and inclusion issue. We all know we’re spending a ton of money each and every year trying to encourage minorities, trying to encourage more women, trying to encourage difference and we’re failing. And we’re failing, I realize now, because we are doing it wrong.

Liane Hornsey: It’s about time we understand, each and every person in this room, even if we’re united largely in agenda, we are not the same. I am not the same as every other woman in this room. I am an individual. I am unique, and I am special as are each and every one of you, and that is what Palo Alto Networks is going to be about. It’s going to be about over the next couple of years, making sure that each and every individual that joins this company feels special, feels that they’re doing amazing blooming work, work that will change this world and work that will make everybody safe, and that we can all be whoever we want to be at work. I think if we crack that, we’ve done something pretty darn good.

Liane Hornsey: I’m not going to say much more to you. I am so glad that you’re here. I am so glad you can see everything, that’s wonderful. But I’m most glad for you that you can hear from our founder. In my career I have worked with a number of founders, and I’ve got to tell you, it is not always a joy. They can be a little unusual. This time it’s an absolute, an amazing joy, and I’d like to introduce Nir.

Nir Zuk speaking

Founder and CTO Nir Zuk talks about the past, present and future of cybersecurity at Palo Alto Networks Girl Geek Dinner.

Nir Zuk: Thank you, Liane. Thank you all for being here. I’m Nir, I started this mess about 14 years ago. We got funded about 13 and a half years ago. We’ve been selling products for about 12 years. Like Varun said, we are the largest cybersecurity vendor in the world today, we’re also the largest cybersecurity business in the world. Even businesses inside other large companies are smaller than us and these businesses have been around for 25, 30 years, sometimes even more than that.

Nir Zuk: How does a company that’s only been selling products for 13 years, becomes larger than companies like Cisco and Juniper and Semantic and other large cybersecurity vendors? Of course, it would through disruption, right? To disrupt the market, you completely change the market, and maybe I’ll say few words about disruption.

Nir Zuk: The first thing about disruption is that it’s a weird thing. It’s not like it’s… The way you disrupt the market is not by building a product and starting to sell it and then figuring out, wow, I disrupted the market. It’s actually the other way around. You find the market that’s ready for disruption. You find the reason why it’s ready for disruption and you address that, right?

Nir Zuk: If you think about it, some of the companies that you work with and a lot of the companies that have changed things like the taxi industry, and the hospitality industry, on the consumer side, and then companies that have changed the way we do HR and the way we do salesforce management and CRM and the way we do IT operations and so on, they were all going into markets that have been doing the same thing again and again and again and again for many, many years and found the reason to disrupt those markets, disrupted the markets, and have been successful at that. We’ve done the same thing.

Nir Zuk: The next question that I always get asked is, how do you make sure that nobody comes behind and disrupts you? It’s not easy. The thing about disruption is that when you face disruption as a large company, it’s very, very difficult to deal with that. It’s very difficult to deal with disruption because you have two pretty much bad options. The first option you have is to embrace the disruption, meaning to say, wow, this is very disruptive. Everything I’ve done so far is irrelevant. Let’s embrace the disruption. The challenge, especially as a large company, as a publicly traded company and so on, is that that really kills your business, and you have to start again. It’s not that you start from scratch, but it’s enough that your revenues go down 2, 3% and you’re done. Right?

Nir Zuk: Embracing disruption is hard because you have to start convincing the markets that you are disruptive and then you have to buy and sell them something new while they don’t buy your old thing. Then you can fight the disruption, but if the disruption is real and true, then you’re going to eventually end up staying behind, which is really what happens to our competitors when we started disrupting the market. They all fought the disruption, they all went through the five stages or first denial, right? Nobody needs it. Then we do it too, and then eventually it’s, okay, let’s go and find something else to do.

Nir Zuk: To make sure that we don’t get disrupted ourselves, the only logical way to do it is to disrupt ourselves. Keep looking why the market is ready for disruption and going and disrupting it at the risk of hurting your existing business, which we do. We keep doing that all the time and we don’t have time to talk about it right now and today, but we keep disrupting the market, we keep changing the market and changing the way the cybersecurity market works. I think that that’s the first thing that we’ve done.

Nir Zuk: The second thing that’s interesting about the cybersecurity market is that when we started, it was made of two types of companies. It was made of very large vendors. Again, I mentioned some names, Cisco and Symantec and there’s another company that they used to work for in the past called Checkpoint out of Israel, which is also a very large vendor in the industry. There’s McAfee and Juniper used to be a large vendor in the industry and there are a few others, and they all sell products that are very, very successful, but really aren’t doing anything to secure their customers. In fact, they all sell products that we call firewalls, you’ve probably heard about firewalls and everybody knows that you need the firewall, it’s just firewall is not going to make anyone secure.

Nir Zuk: Firewalls are not a security product, they are a hygiene product. Saying that the firewall is security products is like saying that soap is going to make you healthy. It’s a hygiene products, it’s not going to make you sick, but it’s not going to make you healthy. You’re not going to prevent some or the most important diseases. Right? That’s one set of companies.

Nir Zuk: The other set of companies that we saw when we started the company 14 years ago was the innovative companies, the companies that actually do something for their customers to stop the bad guys and to make the world safer, but those companies just never took off. There was this disconnect between the two when… and part of it is because it’s very hard for customers, especially very hard for organizations to tell what’s working and not working, what’s not working. Like how are you going to evaluate a cybersecurity product? They’re going to hire a bunch of hackers and pay them a lot of money and go create an attack against yourself and then see if the product… Nobody does that, right? Usually you get a script from the vendor and you followed the script, then guess what? It works, right?

Nir Zuk: When we started the company, we decided to be different. We decided that we’re going to build the product that is both going to be big, and is going to actually do something for our customers, and that’s part of our culture. There are other things in our culture that I think are very important. But I think… and I’ll talk about him in a second, but I think the most important thing in our culture, or about culture is that we strongly believe is that cultures create companies and not vice versa. Meaning it’s the culture that you have when you start a company, and if you work really hard and make sure it doesn’t change much, it’s the culture that you have over the years that’s great in your company versus your company creating a culture. Okay? If your culture is to be disruptive, then you’re going to be disruptive. If your culture is going to be, you’re going to invest in sales and marketing to convince the world that the products that you build that aren’t doing anything, actually do something, then that’s going to be your culture.

Nir Zuk: There are a few very important things that we created in the culture of the company that I think have brought us to where we are, and the largest vendor in the cybersecurity industry, and we’re also growing much faster than everyone else. There are areas where we’re by far the largest vendor, well, there are areas where we’re bigger than everybody else combined. Doing really well, and again, it’s our culture and it’s things like being disruptive. It’s things like we always… we don’t solve simple problems. Meaning, if there was something in cybersecurity that we think someone else is already doing well or we don’t know how to do better than them then we’re not going to do it.

Nir Zuk: Customers keep asking me, “Why aren’t you doing the… Distributed Denial of Service protection?” Whatever that means, right? Because I just don’t know how to do it better than others that are doing it today. They ask me, “Why aren’t you doing web application firewall?” I just don’t know how to do it better than others, so why would I do that? Okay? The things that we do here are things that we know how to do better, or we think at least we know how to do better than everyone else. That’s in our culture. Like when we make a decision whether to do something or not, that’s a very important criteria. Criteria, right? There are other important criteria. That’s one part of our culture.

Nir Zuk: The other part of our culture is to always do the right thing for the customer. Now, of course, every company that you work for will say that they are doing the right thing for the customer, but as an example that I used just a moment ago, if you invest in sales and marketing to convince your customers that the stuff that doesn’t work, doesn’t do much for your customers actually does, then that’s not your culture. Your culture is not to do the right thing for the customer and… For us to do the right thing for the customer, I think the way we think about it, the way we’re presenting this, we always do… we only do things that we can be proud of. Okay? I cannot be proud of selling a customer a product that doesn’t do what the customer thinks that the product does. So, we’re just not going to do that. We’re going to do the right things so that we are proud of what we do so that customers eventually will get the benefit of the products, and that’s very important for us.

Nir Zuk: Another area that’s very important for us is self-awareness, okay? Many companies just aren’t self-aware when it comes to the issues that they have. Whether in their structure or in their products or in whatever it is. We are very very self aware. I mean I’m not going to, of course, wash the dirty laundry here, but in meetings we always talk about the issues that we have. We always talk about competitive issues that we have, we always talk about organizational issues, we always talk about the different things that are going to make us not successful, or are making us not successful in some areas, and we’re very self aware of that and we fix it. We certainly don’t kill the messenger up, we promote the messenger here, and take care of that. Those are important things that just don’t exist in many companies. When you look back 14 years ago and we look at the set of companies that we compete against today, they just have a very, very different culture than we have today.

Nir Zuk: The last thing, which you’ve already heard, that’s important for us in the culture is diversity. Diversity is not just gender diversity, which is very important. I think among the first 25 employees of the company, about a quarter, 25th and a quarter were women. But it’s not just gender, it’s also underrepresented minorities. It’s also diversity as to where people come from in terms of the companies that they come from. We don’t just hire from two companies, we hire from as many different companies as possible, so we get as many different opinions as we can. When we think about diversity, we think about diversity across everything. It’s really an important part of our culture. Like if you walk around and you see the list of things that are in our culture, which are posted in various areas of our buildings, that’s one of them. Being diverse is very, very important for us. We just think that it makes us better and it makes us build better product for our customers. Okay?

Nir Zuk: Maybe the last thing I want to talk about is would… like Liane said, not too many people know about Palo Alto Networks, especially if you’re not in the enterprise space and not in cybersecurity space. You don’t know much about Palo Alto Networks other than maybe you every now and then you’ll hear about our financials or things like that. But if I look at the things that we’re proud of and the things that are somewhat unique to us, we are one of the large… we have one of the largest infrastructures in the world, or certainly building one of the largest infrastructures in the world. Cybersecurity is becoming more and more, and that’s something we’re driving, but it’s becoming more and more a data problem. The amount of data that you need to deal with in order to find the bad guys and stop them, it’s just unbelievably huge. We’re talking… I mean, if we today had to collect or are able to collect all the data that we need from our customers, we’re talking about several billions of events per second. Okay? This is the kind of infrastructure that we need to build. We’re talking about many, many, many, many exabytes of data in order to make our customers secure. I mean, I’m not saying we’re there yet, but that’s something that we need to build, and over the next few years we need to build.

Nir Zuk: Cybersecurity is becoming a data problem and we’re leading that. We’re very large infrastructure company.

Nir Zuk: One of the things that we’ve done, and one of the disruptions that we brought to the market is we have transformed the cybersecurity market from a market where you buy a lot of products. A typical organization and typical enterprise will have dozens and sometimes more than 100 different cybersecurity products that they deploy in their infrastructure. We transform that into a market that’s delivered via SaaS. Okay? That’s another thing that’s important about Palo Alto Networks, and yeah, there’s also the cybersecurity aspects. You’re going to be a cybersecurity expert to work at Palo Alto Networks. The number of people here that actually know cybersecurity, probably 200 or 300 of our employees, actually are cybersecurity experts. All the rest are data experts, and service delivery experts, and operations experts, and of course, that’s in the engineering department and we have many other organizations within the company. Okay? That’s what I had to say. I’ll stick around if you have some questions. We don’t have time for questions right now, and I guess next one is Citlalli. Thank you.

Citlalli Solano speaking

Director of Engineering Citlalli Solano talks about loving where she works because she identifies with Palo Alto Networks’ mission of securing “our digital way of life.” She is a proponent of the security-first mindset.

Citlalli Solano Leonce: Hello, everybody. My name is Citlalli Solano Leonce. I am a director of engineering here at Palo Alto Networks. I’m a software development and I really couldn’t be more proud of having you guys here tonight. A little bit about myself, so let me share a little bit of my story.

Citlalli Solano Leonce: I grew up in Mexico City, back in the day there were no cell phones, no tablets, no flat TV screens, no nothing, right? No, internet even, and I remember vividly how my mom would take me with her to the bank, right? The old big computers with black screens and green letters and characters going around. I always wonder what is happening behind? How could that person type something, and then some magic happens? Right? Fast forward a little bit. I got… that’s what I… got me to study computer science.

Citlalli Solano Leonce: Finally right out of college, my first job was at the central bank in Mexico. I finally, my dream come true. I was able to understand what was happening behind the scenes, but there was a slight difference back then, and is that I was not only understanding what was happening, but I was in the driver’s seat. Here I am, 21, 23 year old, building systems for my country.

Citlalli Solano Leonce: I was developing in C++ and my modules eventually ended up in the payment systems. Now people are able to transfer money from one bank to another immediately. I was paving the way for the digital transformation of my own country. That was… at that time probably, I didn’t realize that impact, but looking back it’s like, really I was a key player there.

Citlalli Solano Leonce: Fast forward a little more. Here I am standing in front of all of you in the middle of the Silicon Valley. A day in the life, you wake up, your phone plays a nice tune for you. With the internet of things, you can have your coffee machine make coffee for you, and then you wake up to the very nice smell of coffee beans. You can say, “Alexa play, what’s the weather today? What’s my stock options? You take your car, the car drives you wherever you want, right? Like that, so it’s amazing, right? All these transformation, I can’t believe I have been fortunate in life to live this revolution, right? But there’s another side to that. What is happening with all of that? Now, we all have our lives in the digital world. Raise up hands, how many of you do your banking online? Probably everybody, right? How many of you do video gaming or your kids do video gaming? Right? Now, even that is online.

Citlalli Solano Leonce: Some of us are doing… those DNA test, 23andMe, okay? Then we can share and, or maybe we’re cousins, we’re third cousins or whatever. Right? That’s amazing. But, where do you think all these data is going? Everything is hosted in the cloud, right? We are leaving our digital fingerprint over there, and it’s not only the data, these services themselves are deployed in the cloud. They’re either running in AWS, Azure, GCP. Who knows? right?

Citlalli Solano Leonce: Amazing. But we also have a big responsibility. Everything is interconnected. How do we prevent the bad guys from getting that? It’s not only just your little blog post, it’s now your financial information, it’s now your DNA information, right? Who knows what’s going to happen in a few years.

Citlalli Solano Leonce: Let’s look at how we are developing those various systems, and something that Nir was referring to, it’s not only about cybersecurity and cybersecurity professionals, right? We at Palo Alto Networks happen to make software that secures the enterprise. But security is responsibility of everybody. Who is building that 23andMe mobile app? Probably one of us. Right? Who is building those banking applications? One of us, right? What are we doing to prevent that from being vulnerable? It shouldn’t be an afterthought and in and out of the job of the InfoSec guys. Archana, here, who specializes in InfoSec, can tell you a lot more about the security practices, but that should start before.

Citlalli Solano Leonce: Looking at this SDLC, it’s something that’s probably very, very familiar to many of you. What do you think here is missing? Any ideas? We have the the planning, we have architecture and design, implementation, testing, deployment, maintaining, anything that is missing here?

Audience Member: Security.

Citlalli Solano Leonce: Security. Where do you think security should go? What circle are we missing? Where do you think that goes?

Audience Member: Everywhere.

Citlalli Solano Leonce: Everywhere? Yeah. Oh, you guys are too good for me. Yeah, spoiler alert. Yes, security is everywhere. It’s not, oh, QA should test for security, and Meghana can tell you a lot more about all our QA security practices. But this goes before, even as we are designing, Paddy here also will talk to you about product management, but it’s everybody’s responsibility.

Citlalli Solano Leonce: Circling back, we are living in this amazing world. We have all these services at our fingertips, right? Everybody’s now, now our kids, everybody is. But also we have a big responsibility. I personally love working here because I really identify with our mission of securing our digital way of life. I truly believe that. As the previous presenters were saying, it’s truly our responsibility and we are hoping for a better world one day after another. I’m hoping that tomorrow is going to be a little safer than today, so that the world that I leave to my kids and my legacy is much better than what I’m living right now. I invite you all to adopt security as your own, and let’s build that secure world together. Thank you very much.

Meghana Dwarakanath

SQA Engineering Manager Meghana Dwarakanath says, “We have to continuously rethink our role and what we need to do in our roles to be successful. This mindset is not only encouraged here at Palo Alto Networks, it is expected, and that is what I love the most about working here” at Palo Alto Networks Girl Geek Dinner.

Meghana Dwarakanath: Hello, everybody. My name is Meghana Dwarakanath. I’m the Software Quality Assurance Manager for public cloud security here at Palo Alto Networks. Now, I have been able to contribute across three different products here at Palo Alto Networks: WildFire, which is our malware protection as a service, Aperture, which is our data loss prevention as a service for SaaS applications, and now with public cloud security product RedLock. I’m sure you all know already all about it, with all the demos you’ve attended.

Meghana Dwarakanath: How did I get started? I like to tell people that I’ve worked my way up the networking stack. I started off on CDMA. Then IP, TCP, SUDP, finally landed in the cloud, and out of pure curiosity took a right turn into security. This is a story you’ll hear a lot more from people who are working here. Because, initially when you think security, or at least when I heard about security, the first thing that comes to your mind is some Mission Impossible scene. There’s lot of screens, hackers. But then working here I came to know it takes a lot of people from a lot of different backgrounds and expertise to come together and make a good security product. Now, if you take my team, for example, I have people from DevOps background. I have people from Dev background, of course QA background, security company experiences, non-security company experiences, and with all those different perspectives, we are able to build a much more secure and successful QA process, which is what I’m going to talk about today.

Meghana Dwarakanath: One of the axioms in security is, you’re only as strong as your weakest link. Now let me ask all of you something. What do you think is the weakest link in your companies? Maybe you don’t want to say it out loud. But the answer should be, nothing. We are all strong, we’re all doing good, and we agreed, right? Now, of course, when it comes to our production environments, we are very thoughtful about protecting them, and we should be. Because it has our customer data, it has our reputations, and it needs the protection. By the time we come to our QA environment, it kind of tapers a bit, right? Why? Because you’re thinking it’s QA.

Meghana Dwarakanath: We don’t have customer data in there, hopefully. It’s an afterthought, we really don’t think about it. But if you really think about the challenges we have and the kind of products we are testing today, we need to think about why we need to secure QA environments. Because when somebody gets to your QA environment, there are a lot more things they can get out of it, apart from customer data. For example, they can get an insight into your system internals. They can figure out how your systems and services are talking to each other and you’re literally helping them make a blueprint to attack your production environment. You have proprietary code, of course, that is running in your QA and staging environments, and so there’s a potential loss of intellectual property there.

Meghana Dwarakanath: Again, hopefully you don’t have customer data in your QA environments. I really hope you don’t, because here at Palo Alto Networks, the InfoSec team, Archana will tell you more, they’ll find out, come hunt you down, and take that data. Then, of course, if you’re the unfortunate victim of something like a bitcoin mining and that, you get a very massive bill at the end of the month, a very, very unpleasant surprise, right?

Meghana Dwarakanath: This is just your test environment. What is the other aspect of testing? Test automation, right? Anybody who is testing the SaaS service will tell you they test against production. Every time you release, you want to make sure that your production is doing okay. All the features are doing okay. So what do you do? You run your test automation against production, which means your test automation now has credentials that can access your production environment. You probably have privileged access because you want to see better what you’re testing, and now you’re co-located next to customer data, which is a very–potentially–a very unsafe mix.

Meghana Dwarakanath: How do you do the security? One of the ways we have been able to do this successfully here, is to consider test as yet another microservice that is running in your production. All those production microservices that you deploy, test is just another one of them. How do your microservices store credentials? That is exactly how you test automation will store credentials, the same SDLC process that Citlalli talked about, where security is not an afterthought. The same thing applies to your test automation code as well. You deploy monitoring for your test automation services just like you would do for your production services, and then whatever deployment automation you have, your IS automation code you have, you first test deployment into the same very architecture, and now you have all the added protections that your production microservices are getting.

Meghana Dwarakanath: There are a lot of fun new QA testing concepts, right? AB testing, blue-green testing. How do you test this global? With this, we are able to be in every single stack we deploy, test continuously, and get continuous feedback about our test and production environments.

Meghana Dwarakanath: Now we have the right people, we have the right mindset, we have the right intentions. We just want to ensure that our intentions have the right impact. What do we do? We just happen to have a set of world-class microservices at our disposal, so we don’t put our own environments, which means for example, all my test environment are monitored by RedLock, to see if we have any security vulnerabilities there so that I can immediately know about them and then I can make sure they’re secured, right? This is a win, win situation, of course, because we are in the same cycle of continuous feedback. We tell how the product is doing, the product is securing us.

Meghana Dwarakanath: Now, from this talk, I really want all of you to have two takeaways from this. One, of course, to really go and think about how your QA practices are, are they secure? And what needs to be done to make them secure. The second thing is to realize that we are in an ever changing landscape and there are different and new challenges, right? We have to continuously rethink our role and what we need to do in our roles to be successful. This mindset is not only encouraged here at Palo Alto Networks, it is expected, and that is what I love the most about working here. Thank you.

Archana Muralidharan speaking

Principal Technical Risk Analyst Archana Muralidharan reiterates that “security is not a one-time concept. It’s a continuous process” at Palo Alto Networks Girl Geek Dinner.

Archana Muralidharan: Good evening, everyone. I am Archana Muralidharan, I work as Principal, Technical Risk Management, here at Palo Alto Networks, InfoSec department, and the same function of a lot of people refer to now. I feel more responsible now to deliver what exactly we do put into product security here.

Archana Muralidharan: Before we get into the specifics of how we do stuff at Palo Alto Networks, let me share with you some fun facts about me. I was born and raised in Chennai, a city in southern part of India. Where the weather is really hot all through the year, 365 days a year. There are only three seasons, according to us, hot, hotter and hottest.

Archana Muralidharan: There is there are no cold seasons that are known to us. If you ever see me wearing a jacket when it’s 70 degrees outside, you know why it is. My childhood dream was to actually become, any guesses? Was a Bollywood singer. Honestly, I still learn Indian classical music just for the fact that I couldn’t become one. But destiny was something else, I completed my engineering and I ended up becoming a software engineer.

Archana Muralidharan: It was by accident, I would say that I got into information security, because I didn’t even know what it was like 12, 13 years ago when I started my career in InfoSec. After having been in InfoSec for so long, I really, really love the domain. It is so interesting because it throws a unique set of challenges and problems for us to solve. Now that we heard a lot of our leaders, Citlalli, Meghana, touching upon how important is security to be incorporated as part of SDLC, let me dive deep into that.

Archana Muralidharan: There are some debates here and there in terms of the actual estimates, but all research does confirm the cost and time involved to remediate the vulnerability, grows exponentially over the different phases of SDLC. That’s why it’s really important for us to start thinking about security, during the initial phases.

Archana Muralidharan: Especially when you’re delivering the cybersecurity product, we want to be doubly sure, triply sure, over cautious sometimes to ensure the way we develop [inaudible] makes us really secure, because we have commitment to protect the digital way of life.

Archana Muralidharan: Our approach here at Palo Alto Networks is to embed security as part of every phase of [inaudible] like how you just heard from a lot of the speakers who spoke previous to me. As part of requirements, we make it a point that we collect security requirements as an NFR, meaning non-functional requirements, in addition to the normal performance ahead of requirements. We ensure that they are understood, well documented so that we could potentially prevent a lot of vulnerabilities creeping down street.

Archana Muralidharan: As part of Design phase, being from InfoSec, worked very closely with the product architects to understand the architecture and review it from a security perspective to ensure… to look for all possible attacks, incorporate possible mitigations well in time to prevent design flaws that would otherwise result in vulnerabilities in the product.

Archana Muralidharan: As part of Build phase, we primarily do two activities. The first one being static code analysis where we look for vulnerabilities and remediate in the custom code what we developed, as part of product development. The second piece being, using this open source vulnerability assessment tools to figure out the vulnerabilities in the open source libraries and frameworks worth the use in our product. But it’s really important that we understand what we sign up for.

Archana Muralidharan: During Testing phase, we do something called as application integration testing to find vulnerability that we had missed as part of Build phase. For instance, when we do static code analysis during Build phase, the code doesn’t run, [inaudible] it is static. When more components are integrated, come together, there could be a possibility of more vulnerabilities, which we typically find, specifically targeting areas, some of the stack like versus logic errors, privilege escalation, which no static analysis tool can find as of today.

Archana Muralidharan: As part of Deployment we perform deployment architecture review. This is very similar to what we do as part of design phase. The only reason is because we are in the [inaudible]. We follow [inaudible] frameworks, we build stock so fast. There’s always a chance that they may miss the actual design, what was approved versus the actual design one gets to plan, finally may differ and you want to be really sure that the final architecture, what gets deployed is indeed what was approved.

Archana Muralidharan: Finally, I’m very sure all of us would be aware and agree that security is not a one-time concept. It’s a continuous process. We monitor… We scan our product environments for vulnerabilities in infrastructure, web application, API, SQA configuration, so forth and so on, and remediate those vulnerabilities well in time.

Archana Muralidharan: Aside from that, there could be a situation where a vulnerability is out in the market, but it’s not part of your scan cycle, so we don’t want such vulnerabilities to be executed and end up being in a breach situation. We use runtime application, self protection to detect those vulnerabilities and lock it from getting executed during run time. These are all the activities that precisely we do as part of software development life cycle. We take security really very serious.

Archana Muralidharan: Before [inaudible], I want to share, why do I love working for Palo Alto Networks? Trying to give a basic… I would like to share my personal story when I interviewed with Palo Alto Networks. Having been in consulting for 10 plus years, the very fact, the very idea that I’m going to work for a cybersecurity product company, really thrilled me, really excited me.

Archana Muralidharan: I applied for a job, I went for an interview, everything went well, and always we have this feeling that we could have done probably a little better. Any of you think like that? After any interview? I felt the same. But all well, I get a call from the hiring manager, did a very appreciative of all the great qualifications, what I have and I was super excited. I thought I was [inaudible] the job, but then there’s a slight twist to it. I did not get the job. Difference, I was not a right fit for that job. Instead, they offered me a totally different job, which in their opinion, they believe that’ll be a better fit for me. As you all are confused now, I was completely lost and confused, because never in my career of 15 plus years, there was ever a situation where something like this happen. It is always either a yes, or a no.

Archana Muralidharan: With a lot of confusion, I agreed. I accepted the offer. Glad that I made the decision, no regrets whatsoever after that. It has been a great learning experience here. The reason why I’m sharing this with you today is to reemphasize that teams here at Palo Alto Networks think very differently to solve the problem statement. That’s what makes this place unique and a great place to work. Thank you so much for your time.

Paddy Narasimha Murthy

Senior Product Manager Paddy Narasimha Murthy talks about PMs and Security PMs, and how PMs work at Palo Alto Networks Girl Geek Dinner.

Paddy Narasimha Murthy: Thank you, Archana. Hi, everyone. Glad to be here with all of you. I’m Paddy Narasimha Murthy. I’m a product manager on the Cortex team, an engineer turned product manager. That’s a very brief introduction about me and I’m here to talk about the perspective of PM-ing at Palo Alto Networks. What does that mean? You heard from a development manager’s perspective, QA, and InfoSec perspective, and now this is the PM perspective. But before I go into the details, I want to go over… what does a PM do, and then what does a Security PM do, and finally, why is it fun working here at Palo Alto Networks?

Paddy Narasimha Murthy: Many of you might’ve seen this image. This is a classic image where you see different perspectives for the exact same element, and here the element is elephant. What a PM does is basically intuit what a customer wants. Let me go over that with an example. Let’s say Customer A comes to you and they say, “I have certain data set and I want only the senior management to actually have access to that data set.” Okay, great. As a PM, you make an order for it and you say, “Okay, this is probably how I’m going to go build that feature.” But in the meanwhile, Customer B comes to you and says, “I have a data set, but I only want my support engineers to access that data set,” and you go, “Okay, that’s also great and I can build a feature for that.”

Paddy Narasimha Murthy: Imagine if you are a PM and you were to build a feature that satisfies that Customer A, and another feature that actually satisfies Customer B. Do you think that’s going to be sustainable? Because it’s very soon you are going to run into a situation where there’s going to be dozens of customers and probably even hundreds of customers asking for something very similar saying, different people need to have access to it. That is where you as a PM come into a picture and where you actually help draw this elephant. In this particular case, you could solve this problem by building something called a role-based access control, for example, where you can actually have a common solution that would satisfy with Customer A, Customer B, as well as thousands of customers who could have the same need in the future.

Paddy Narasimha Murthy: Role-based access control system, just a brief introduction is basically setting up rules, which are privileges, and those privileges tell you what users have access to and what they don’t have access to, and you can assign these privileges to users. That is one way of solving this problem. This is what a PM [inaudible] does.

Paddy Narasimha Murthy: The other important aspect is that PM also helps understand teams the big picture. For example, different teams when they are building different features, what they see is just a tiny part of it and probably an isolated view of that feature because they might only be integrating with one more team or in some cases just couple of more teams. They’re a very isolated view of the work. So a PM’s job is to step in and actually help draw the elephant where you tell teams that, “Hey, this is what we’re building and here is how your piece is going to fit in.” That’s the job of a PM.

Paddy Narasimha Murthy: That said, what does a Security PM do? A Security PM does all of what I mentioned, and a little more. The first factor is security actually takes time. It’s not a one or zero or, okay, let’s do this feature or let’s not do this feature. There’s a cost to it. As a PM, what you do is typically you try to figure out how to build a secure product. If building a secure product, let’s say, you can only… ship five features in a product instead of 10 features, then so be it, because that would actually make your product a lot more secure because you’re able to spend more time on security related features.

Paddy Narasimha Murthy: Next is it’s actually an investment. By that, what I mean is it pays in the future. Let me explain that with an example. Many of you might’ve heard two factor authentication. It is basically you put in your password as well as another form… another factor for authenticating yourself. We all know 2FA is important and many online services and companies and so many others online accounts offered 2FA. But how many of you go turn it on, or how many companies even go turn it on. Even though this is a new feature and explain it to the customers as to why this is important, it actually go ahead and build this feature and explain it to the customer as to why this is important, because this is going to prevent them from the ever evolving threat landscape, and pushing this feature out in the next 10 years or so is not really going to benefit our customers. That’s what you may have trade off.

Paddy Narasimha Murthy: Next is, it is ongoing. Let’s say as a PM you decide that your product is reasonably secure, so you put the secure stamp on it, you ship it out into the world, and that’s it, your job is done. No, it’s not. Because security is constantly ongoing and you have to evaluate, is your product continuing to secure the customers? Is there more to it? If I were to extend the 2FA example, what I would be doing for the ongoing aspect of it is to now figure out, maybe I should be offering multi-factor authentication and not just two-factor authentication, because that is how I am going to protect my customers from the ever evolving threat.

Paddy Narasimha Murthy: Moving onto why PM in Palo Alto Networks. Security up and down the stack. Because Palo Alto Networks, we have a wide suite of products that our different speakers alluded to earlier. We have firewalls, so ranging from the physical devices up to the cloud, we have a whole suite of security products. If you were to join as a PM or in any role, you would actually get to work across the stack of products.

Paddy Narasimha Murthy: Product-oriented engineering is another factor. Where we don’t just stack up products because some customer came and told us, “Hey this feature is cool and I would like to see this feature in my product.” That’s not how we go about it. Everything that we build here at Palo Alto Networks starts with a problem statement. PM sits down and write a very cohesive problem statement. We start our process on there, and with that problem statement would be good, we actually sit together with the PM teams and we go over that problem statement and we convince ourselves, is this the right thing to do? Is this the right problem that we would need to solve? Is this the right thing for our customers. We attack the problem from different perspectives to make sure that we’re actually going after a problem that really needs to be solved. That is another factor that I really like.

Paddy Narasimha Murthy: The last one here, everyone here wants to do the right thing. Palo Alto Networks is a pretty large organization. We have several different teams. If you think about it, different teams have their own ways of doing things. We have different priorities, and they have different incentives too. But in a lot of cases when we have to work together, there is going to be conflict. But it’s really easy to work together because everyone in the room really wants to do the right thing. That is the biggest reason why I really enjoy working here. With that, I’m done, so are all the speakers. Really want to thank every one of you for coming here and spending your evening with us. Thank you all, we’ll be hanging out here, so happy to answer any questions you have. Thank you once again.

Pictured: Citlalli Solano (Director of Engineering) at Palo Alto Networks Girl Geek Dinner 2019.


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Girl Geek X SurveyMonkey Lightning Talks & Panel (Video + Transcript)

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Gretchen DeKnikker, Robin Ducot

COO Gretchen DeKnikker of Girl Geek X introduces CTO Robin Ducot at SurveyMonkey Girl Geek Dinner in San Mateo, California.

Speakers:
Robin Ducot / CTO / SurveyMonkey
Sarah Cho / Director of Research / SurveyMonkey
Sarah Goldschmidt / Product Design Manager / SurveyMonkey
Mala Neti / Software Engineer / SurveyMonkey
Shilpa Apte / Engineering Manager / SurveyMonkey
Jing Huang / Director of Engineering, Machine Learning / SurveyMonkey
Erica Weiss Tjader / VP, Product Design / SurveyMonkey
Gretchen DeKnikker / COO / Girl Geek X

Transcript of SurveyMonkey Girl Geek Dinner – Lightning Talks & Panel:

Gretchen DeKnikker: Hi everyone. I’m Gretchen. I’m with Girl Geek X. Thank you so much for coming tonight. Welcome to SurveyMonkey. How awesome is this space?

Gretchen DeKnikker: It’s so good. I love it. I love it. Also, I’m going to introduce a unicorn in one second after I do my little spiel.

Robin Ducot: Spiel?

Gretchen DeKnikker: Spiel.

Robin Ducot: Spiel.

Gretchen DeKnikker: How many first Girl Geek dinner?

Gretchen DeKnikker: A lot. Welcome. We do these every week. We’ve been doing them for ten years. We’ve done like 250 of them so far. We also record them. They’re on YouTube. We do a podcast. It’s in the podcast places, so definitely check those out. Something we were talking about a little earlier, I was thinking the reason that we do these is to give women the opportunity to get up on stage and talk about being awesome rather than talking about being women. One thing I’ll challenge you guys with is find yourself a woke male and bring him next time, because there’s nothing gendered about this content, and building ally-ship is a really good thing.

Gretchen DeKnikker: Without further ado, I know I’m going to get comments on this, but I can’t wait to hear what the feedback is. Send it my way. I’m ready.

Gretchen DeKnikker: Now–

Robin Ducot: Hello.

Gretchen DeKnikker: Hi. I don’t know if you’re ever met a female CTO live and in person, but you’re about to. She’s amazing. In the like three minutes, we’ve just decided we were separated at birth and are going to be best friends now. Right?

Robin Ducot: We’re going to get caught saying something inappropriate at least once. We know this.

Gretchen DeKnikker: Yeah. We were really happy our mics were muted is basically what happened. Without further ado, please welcome the CTO of SurveyMonkey, Robin.

Robin Ducot: Hi. Nice to see everybody here. I’m so glad y’all could come. I’m Robin Ducot. I’m the CTO of SurveyMonkey, and we’ve got a great set of talks tonight. I guess we’re just, without further ado, we’re going to get started. Please, at the end we’re going to be taking questions right after the panel. We hope that you guys will have some interesting questions for us because we are excited to talk to you then and afterwards.

Robin Ducot: Why don’t we get started? Yeah? You ready? Why don’t I bring on stage Sarah. She is from our survey research team, and she is going to talk about surveys.

Sarah Cho speaking

Director of Research Sarah Cho gives a talk on “Surveys: Why Do They Matter?” at SurveyMonkey Girl Geek Dinner.

Sarah Cho: Hello. Thanks. Hi. I’m Sarah Cho. I’m Director of Research here at SurveyMonkey. You’re probably wondering what a director of research at SurveyMonkey actually does, but what we do is we consult with all the different areas of the business from product to engineering to marketing to sales to give them advice on what is actually good survey best practices. You can think of our team as basically being the biggest survey nerds, or I guess for this crowd I should call them survey geeks, at this company. Of course, we can’t invite you to SurveyMonkey and not talk about surveys, so that’s what I’m going to be talking to you about today is first, let’s level set a little bit about what I mean about at survey. There’s a lot of different things that the word survey can mean. While this photo looks amazing and awesome, like I bet a lot of us would like to be up high on this mountain top, and we’re not talking about land surveying here. We’re really talking about survey in questionnaire form.

Sarah Cho: What I like to kind of describe surveys as is you’re having a conversation with a very specific purpose at massive scale. First, I’m going to walk through a couple of different ways that you can do surveys, talk about the different types of surveys that you can conduct, and then hopefully you’ve been inspired that you can go home and do some surveys on your own. I’m going to give you a couple of tips on how to make sure that your surveys are going to yield the highest quality data because it’s a little bit of art and it’s a little bit of science.

Sarah Cho: Surveys. They come in many, many different shapes and sizes. Has everyone taken a survey before? Yes. It could be on the phone. These are like the surveys that call you when you’re sitting down at dinner and you’re right about to take your first bite of food and they’re like, “Hey, will you take a survey?” It could come in person. Maybe it’s someone who’s knocking on your door or maybe you’re at the doctor’s office and they’re asking you a little bit about your medical history or increasingly, obviously what we deal with is surveys that are online. The great thing about online surveys is that they can be provided in a variety of different avenues. One of the more interesting things is surveying kind of where people are working, so utilizing Slack if you guys utilize Slack, and surveying people in Slack or maybe surveying people in Facebook Messenger. Really going to where the people are rather than trying to bother them in the middle of dinner or maybe in their face knocking on their door.

Sarah Cho: The beauty of surveys is that they can really be on any kind of topic. The most famous survey is probably the US Census, or the decennial census. Actually next year in 2020 is going to be the next census, so for everyone regardless of whether you are a citizen or not, that is kind of one of those myths they tell you about the census. Everyone needs to respond. If you don’t respond, technically you could go to jail, although I wouldn’t worry too much about it because they actually haven’t prosecuted anyone since 1970. It’s very highly unlikely, but the census is a really important survey. Things like congressional seats, which eventually turn into who is going to be in the White House, which we’ll leave politics out of it, but anyways, obviously very important decisions are made from the census.

Sarah Cho: The census is a really big government–Surveys aren’t necessarily meant for just only for big government or big business. You really can use them in many, many different contexts. If you know me in my social life, I tend to spam you with surveys a lot, all for various things like organizing camping trips. For this screenshot, which is a little bit blurry, I’m trying to organize friend’s birthday dinner at Beretta in San Francisco if any of you guys have been and just trying to figure out what to offer on the prix fixe menu. Very practical. Very helpful.

Sarah Cho: Another good way that people have utilized surveys in sort of a personal context that I haven’t really shown you here in this deck, but one of my co-workers have actually utilized surveys to ask people about tell me three words about myself on what you think about me. There was a lot of words that came up, things like thoughtful, really considerate, but what was actually more revealing in terms of thinking about her own professional development and growth is the words that weren’t represented. You can also utilize surveys for your own professional growth and development.

Sarah Cho: I talked a little bit about the government context, but another interesting government context is actually how you can utilize surveys to form opinions, sorry, to gauge opinions and make changes, whether it be in the government context with this where they were asking people who were serving in the military about what they thought about serving with a gay or lesbian service member. What they overwhelmingly said was that actually we think that regardless of someone’s sexual orientation, they can effectively do their job. That eventually was evidence that congress used to repeal Don’t Ask Don’t Tell. You see this in the workplace a lot. A lot of organizations are asking employees about what they feel about their workplace. Employers are actually taking that information and making meaningful changes.

Sarah Cho: We do that, for example, at SurveyMonkey. Obviously we like to eat our own dog food or drink our own champagne, whatever the better phrase is for you guys. For example, we did a survey about do people feel like they are included within our SurveyMonkey community? Do they feel like they belong? Actually, because of that, we found that a lot of people didn’t feel like there was a good path to growth within the company, so we made a lot of different changes like having a career ladder, changing from a yearly review cycle to a quarterly what we call growth impact and goals cycle. We’re able to make a lot of these changes and a lot of organizations are doing similar things.

Sarah Cho: Then finally, a lot of people use them for market research. I like to use this example because it’s a silly example. Maybe they should have used some market research here. This is a product called a UroClub. In case you’re ever on the golf course–I don’t golf myself so maybe it’s a bad example, but in case you’re ever on the golf course and you need to go to a restroom and there is none available, you can utilize this golf club to relieve yourself. Clearly they didn’t use any market research for that, so obviously it’s good to use surveys to make sure that you are doing well in that area.

Sarah Cho: Now going onto a few tips about how to create better surveys for you. The first thing is questionnaire design. You can see here, if I were to read this entire question, that would take up the rest of my 10 minute lightning talk, so I’m not going to, but you can see already visually without even reading any of the words, it’s a bad question. There’s a lot of words, TLDR. Remember when you’re writing survey questions, surveys are super visual. If you have a huge block of text, whether it be in the questions or a lot of answer options, people don’t like to read through that, not because they’re being lazy, but you really should be designing with your respondents in mind.

Sarah Cho: The next thing that I like to point out is jargon or industry terms. A lot of times we are so specialized in our industry, so in the survey industry there is this thing called acquiescence bias. Has anyone heard of it? No.

Sarah Cho: If I asked you guys about acquiescence bias, one person maybe, yeah. Most people would be like, huh, what. That’s the whole point. You shouldn’t use terms that only people in your industry are aware of, or the worst is acronyms. Here it’s how would you rate our POS system? Has anyone worked in retail or restaurants? You probably know what a POS system stands for. It stands for point of sale. If you don’t work in restaurant or retail, POS might mean something very different, like are they asking me about the toilet? Instead, you should be very clear. You really want to know how was the checkout process? Instead of using any acronyms or jargon, really stick to something that’s really clear that can be understood by everyone. A good rule of thumb is things are at an eighth grade reading level. That’s generally a good rule of thumb for surveys.

Sarah Cho: You can spend a lot of time on your questions and a lot of time looking at your answers, but then, sorry, you already got the joke. Sometimes you also need to pay attention to your response options, not just the questions themselves. This is a good example. It’s probably someone who maybe was asking about ethnicity and accidentally included Chinese in sexual orientation, but clearly that’s not right. This is also a key for you guys just to remember if you are doing surveys, always have someone else preview your survey for you because it’s like writing a term paper when you’re in college. You don’t realize there’s a typo in the first sentence of your paper that’s like 20 pages long and you’ve read it 15 times. A lot of the times, if someone else takes a look at your survey, they’ll be able to point out things like this that you may have missed.

Sarah Cho: You could write the perfect survey with the perfect response options and then kind of bungle the data analysis. In this particular example, does anyone know what might be wrong here?

Sarah Cho: Yes. It adds up to more than 100. It adds up to 120 and the last time I checked, a closed ended question like this typically adds up to 100. Just make sure that you’re double checking what we like to call number checking or fact checking. That is a crucial step. Another, again, I’m sorry I’m picking on Fox News, but their graphics department is pretty horrible. You can see here that they’re showing a difference between, it looks like a really big difference, right, like between now and January 2013. It looks really big, right, but actually it’s only 4.6 percentage points. It’s 35 to 39.6. That is actually where someone is playing with the axis and making a difference much more magnified than it actually is. This is a good example of not only things you should avoid, but other things you can kind of see when you’re interpreting other people’s data to see if they’ve kind of messed around with the interpretation of it.

Sarah Cho: Just to wrap up because I only have around a minute left, or actually I’m over a minute, sorry. I don’t know how to use this timer. Here are a couple use cases that you can think about. We’ve talked a little bit about them, but remember you can always survey your customers. Even if you don’t have customers, say you’re a teacher, you have students. Survey your students. You can always gain product feedback. Say you are thinking of starting your own company, but you’re probably going to get very biased opinions if you ask your friends and family member. They’re either going to say that’s a really awesome idea, because they don’t want to offend you, or they’re going to say maybe you should stay away from that because they think you shouldn’t take that risk. Always ask for feedback from people you don’t know.

Sarah Cho: We talked a little bit about employee engagement, but there’s a lot of different ways to make sure your team is happy. We talked about inclusion, but there’s always from the minute they step in your door as a candidate to the minute they leave as someone who is no longer an employee of your campus. You can always, we like to say we want to empower the curious, so satisfy curiosities whether it’s thinking about what markets you can potentially expand to or maybe if you want to go back into academia or just put your academic hat on and just think a little esoterically about one specific problem, you can always think about what is the survey component to that.

Sarah Cho: Finally, I talked a little bit about the example about utilizing it for personal and professional growth, but just to wrap up, this is just saying that even if you don’t want to create your own survey, you can still help us survey nerds out there by being a respondent. Make sure if someone sends you a survey request, just take a few minutes out of your time, respond to that survey because that’s really going to help the people out who are sending it out. I’ll be here around in the networking hour and for Q&A. Thanks for listening.

Sarah Cho: I’m also going to now turn it over to Sarah on our product design team. We’ll keep it easy with the same names.

Sarah Goldschmidt: We good? Hello? Hi everyone. Good evening. Thanks for coming. I have a slide, I promise.

Sarah Goldschmidt: It’s not? I’m holding the clicker. Duh. Anyway, user experience. Thanks all.

Sarah Goldschmidt speaking

Product Design Manager Sarah Goldschmidt gives a talk on “Human Readable: Designing Data for Carbon-Based Lifeforms” at SurveyMonkey Girl Geek Dinner.

Sarah Goldschmidt: I’m a product design manager here at SurveyMonkey, and I’m here today to talk about designing data for carbon-based lifeforms. What does that mean? I know, it’s funny. You’re laughing. It’s designed to laugh. That’s great. We’re going to talk about designing for carbon-based lifeforms, which is us, people.

Sarah Goldschmidt: I want you to take a moment and just think about in 2019 the way we think about data has really evolved from the output of a product to kind of the product itself. I want you to hold that in your mind for the next ten minutes because it’s really the crux of the conversation that we’re going to have today. We as makers of products, whether we’re designers or engineers or product managers or marketers, all play a role in defining the relationship between the product that we make and the data that it collects, creates and disseminates into the world. What I’d like you to walk away with is kind of a call to be more curious and more creative and more expansive in your thinking about how we define this relationship.

Sarah Goldschmidt: This is a chart. Everybody has probably seen a chart like this at some time in their life. You’ve probably made one. You maybe made one in elementary school. Charts and data visualizations are a powerful way to make data, particularly numeric data, visible to the human eye. They can also be a crutch. We can over index on them. I say this as a designer who has probably been guilty of this. We receive data that we’re told is important for a product. Users must use this somehow. We spend a lot of time designing the container for that data. We visualize it. We make really beautiful lines and then we kind of leave it there. We don’t ask more questions. We don’t curate the palate of data that we might be working with.

Sarah Goldschmidt: Charts are great for making data visible, but not human readable. That requires meaning. What’s this idea of human readability? I will confess, I made it up. I will define it for you. Data becomes human readable when through the power of design we wrap that data in meaning. Meaning is how we get from 1, 2, 3, to aha. That aha being how people understand how to feel about the data, how they react to the data, and how they can act with it.

Sarah Goldschmidt: I want to talk a little bit about two products here that are really wonderful examples of thinking more expansively about data as a product and about making that human readable. One of my favorite examples is Spotify. Spotify is not typically what you think of when you think of a data company, but Spotify is sitting on mountains of data, millions of users and all the data associated with how they listen to music. They don’t surface this in the app. You probably don’t want to know how many times you’ve replayed the Justin Timberlake song over and over and over. It probably wouldn’t be good for their business model, but somebody at Spotify decided to sift through that data and thought maybe it could become a product itself. Thus, the Wrapped report was born.

Sarah Goldschmidt: I don’t know how many people here get a Wrapped report. I get a Wrapped report. You get a Wrapped report? Awesome. For those of you who haven’t gotten one or don’t know about it, what happens is at the end of the year, in this case, 2018, Spotify is going to send you out this beautifully designed, curated mini-site that essentially tells you the story of your year through the way you interacted with music. There’s really lovely insights. Sometimes it’s funny. Sometimes it’s cringe worthy, but it’s really designed to share. Of course, this exploded into a phenomenon. We’re posting it all over buildings. We’re talking about it on the news, and of course, we’re sharing it with our friends. One of the remarkable things about this is that it wasn’t successful because the data was solving a really huge problem or being used in some kind of scientific theory. It was making people laugh. It was making people reflect, and it was helping them connect with each other. That’s human readable data turned into a product.

Sarah Goldschmidt: This is one of my favorite examples. They went further, right? They were farther and somebody sifted through all that data that Spotify has to come up with these advertisements that went a step further and told the story of the cultural year of 2018. Some of you might have had the great pleasure of seeing shark do-do-do-do-do, a viral kids video that’s actually quite annoying. This is just one example of this advertising campaign that they’ve rolled out. I encourage you to look it up. They are really funny, but again, taking what is actually just a pile of data somewhere in a database and telling a story with it, making it meaningful and having it touch people in various ways. Making them laugh.

Sarah Goldschmidt: Another example that might be more relevant to us in the room, those current product managers, designers, and engineers or aspiring ones, this is SurveyMonkey Engage. Engage is a stand alone product that we make here at SurveyMonkey. It’s designed to help employers connect with their employees to better understand what’s going on and improve their workplace culture. The data that Engage collects and disseminates is almost completely numerical, so we’re stuck in that position of saying we’re going to have a lot of charts because we have to display that data. We have to display the relationships between that data, allow people to filter it, et cetera, et cetera. What you also see in this interface are a lot of words. That was the secret to making this data more human readable.

Sarah Goldschmidt: Where we got to this is we decided people are changing human culture. What’s important to them? It’s probably not sitting around and looking at a bunch of numbers. Our users want to spend more time connecting with their employees and creating change, and numbers don’t create culture change. People do. Conversations do. Relationships do. We thought how do we apply that to numeric data? And the secret was in what we call the core factors of engagement. We did a bunch of research, looked at all the data points we were collecting, and we saw that they grouped into conceptual chunks. What that allowed us to do is instead of giving a bunch of data points related to how people interact in your workplace assigned to a number of questions in a table, we wrapped it in words. That’s team dynamics. Then we named a bunch of areas of engagement, purpose alignment, visible future. We created language. The focus for our users, instead of nitpicking at the data itself, which is available when you want it, you have shared language with your employees to be able to talk about what’s going on. The data, the numeric data displays that kind of supporting role to be able to talk about direction at a later date.

Sarah Goldschmidt: Something that these two really have in common, you’re probably hearing me say the word story. It’s not just meaning that we need to make data human readable, it’s story. When you string meaning together, you really get a story. That’s what a story is. Stories have been used for thousands of years for humans to be able to understand their world, their place in it, and how they can act. It provides that extra oomph. When design transforms data into story, that’s when the magic happens. The magic is that connection and action.

Sarah Goldschmidt: What I think is really important for the take away today is that anybody can make the magic happen. It’s all about starting a conversation and providing perspective. I’m going to give you four steps that anybody in this room can take to start the conversation in your organization or your school or your product company to get data from being kind of just a set of numbers in a table, maybe, to human readable data.

Sarah Goldschmidt: Step one, find what’s important to your people. I use the word people very specifically here, not users. Users are users when they happen to be using your product, but they’re always people. Ask yourself what’s important to them when they’re using the product. Sure, it might be in a business context, but what’s important to them as a human being? Maybe they’re particularly concerned about what their boss thinks of them. That’s nerves. Maybe they’re stressed out. Maybe they want to buy a really cool shirt and your data is going to help them do that. I don’t know, but that’s the questions. When you find out what’s important to your people, it tells you what kind of meaning you need to wrap your data in.

Sarah Goldschmidt: Step two, prepare your palette. Your data palette. As a painter, I want to be able to paint with as many colors as I possibly can to open up more and more types of stories that I can tell. Don’t cut yourself off early by assuming you know what kind of data you need to display and what you can do with it. Take it all, but remember to do it ethically and responsibly.

Sarah Goldschmidt: Step three. Design a story, not a chart. Those charts are going to come in and really help you tell a story visually, but think about the story first. What kind of meaning do you want to string together? What do you want somebody to be able to do, and then build your charts after that to help support the story.

Sarah Goldschmidt: Step three. Validate the aha. All I know for designing with data for many years is that every time I think I’ve really got it down and I’ve got a universal story that everyone is going to understand, it’s absolutely not true. Users find out a new thing to do with it. I get to learn from that, so always validate your aha and watch your story evolve. It’s a participatory sport.

Sarah Goldschmidt: With those four steps, you’ve really got what it takes to start working with human readable data like a champ. I’m going to encourage you today to be curious, have fun, and make something meaningful. Thanks so much for having me today and for listening. I will be around for questions if you want to talk about product design or data or this weird concept of human readable data. Thank you so much.

Sarah Goldschmidt: I’d like to call my colleague Mala up here to talk about engineering.

Mala Neti speaking

Software Engineer Mala Neti gives a talk on “Transforming SurveyMonkey’s Front-end Platform with GraphQL” at SurveyMonkey Girl Geek Dinner.

Mala Neti: Hi everyone. I am Mala. I’m a software engineer here at SurveyMonkey. Today I’m very excited to share with all of you our journey of transforming SurveyMonkey’s front end with GraphQL. Let’s start by talking about 2019. 2019 was a pretty fun year for us here at SurveyMonkey in part because we were able to completely reimagine our front end architecture. What did this mean for us?

Mala Neti: To start, we were able to work towards consolidating our numerous individually deployable and siloed micro webs into just a handful of apps built on React and Node.js. We were able to introduce a very slim aggregation layer with GraphQL that sits between our front end and our back end collection of rest APIs where all of our business logic and application logic are hosted.

Mala Neti: Today I wanted to focus on the aggregation layer portion using GraphQL, but before I do that, I would love to get a gauge from the audience. How many of you have heard of GraphQL?

Mala Neti: Nice. How many of you have worked with GraphQL in any capacity? Not bad. More than I was expecting.

Mala Neti: For those of you who haven’t, GraphQL is simply a query language for APIs. You can think of it as making it easier to build out your front end by providing a declarative way of fetching data without having to have knowledge of the entire system. In that way it kind of separates the back end–innovation of the back end, from the front end and kind of makes them completely independent. In addition, graph APIs are organized in terms of types and fields rather than endpoints, so the client can get as many resources as possible in one single request to one single endpoint or as I like to call it one endpoint to rule them all. I did not come up with this even though I think it’s pretty genius.

Mala Neti: I think it’s easy to see why GraphQL or the performance benefits that probably come from using GraphQL with this declarative and efficient type of data fetching. Spoiler alert, it worked. For the pages that we have today powered with GraphQL, we saw a huge reduction of payload and a huge reduction of data sent to the client, and a huge improvement in our time to first interaction. This is a really big win for us and for all of our users of SurveyMonkey product.

Mala Neti: Now that we know that it works, let’s talk a little bit about how it works. We have our GraphQL client and our GraphQL server. At the center of our GraphQL server is our schema. Our schema is basically just the contract between our client and our server telling the client how it can access the data. It does this via API operations and data types. The API operations can be read and write operations like queries and mutations, which are basically sort of top level entry points into the graph, and data types like [inaudible], scalers, objects, and the list goes on.

Mala Neti: Facades are then R functions, sorry, resolvers are then R functions that map our API operations to our back end services code. Once we have our schema and our GraphQL server sort of built out, we can easily then build out our GraphQL client knowing what data is available to us and how it’s available to us. As we talk about building out our GraphQL client, it’s also very important to talk about the amazing tooling ecosystem that GraphQL provides us. At SurveyMonkey, we use a GraphQL playground which is basically an in browser IDE and it allows me to hit my GraphQL server and build my queries directly in here in this tool and see my responses. If I didn’t have any sort of involvement in actually designing my schema, I have all of my schema details documented right here. I have my queries and mutations that are available to me, my type details, what fields are nullable and non-nullable and so much more.

Mala Neti: Not only do we have an amazing performance benefit that we talked about earlier from GraphQL, but we also have an increased developer discoverability and productivity, especially from a front end perspective, which is pretty exciting. Now that we have a little bit of context as to what the GraphQL server entails and some of the tools that we can use to build on top of it, let’s dig a little bit deeper into building out our GraphQL client.

Mala Neti: Say I was building out this My Surveys page and I wanted to fetch data that told me what surveys to render. Looking at my tooling and my schema code, I know sort of that I have some options and what’s available to me. I can start by building out my query. This is just a simple query. I have named my query for the purposes of debugging and discoverability. As you can see, I pass in an argument which is language ID, which we have set to be a non-nullable integer, and I pass that in as variables as well as in pagination properties to my survey categories nested field. Under the hood, this basically dictates how my data is going to be resolved and what data I get back.

Mala Neti: Then, as you can see, all I asked for, the only subfield I asked for on items is ID and name. Nothing more and nothing less. I’m truly just asking for all I need. As you can see from my response, the structure of this response mimics the structure of my query. This is really great because I ask for something and I get predictable results back. One of the things to keep in mind as you’re building out your GraphQL client is that at the end of the day, GraphQL can be driven by the data requirements of your products. The people who are building, or the developers who are building your UI can have a little bit of that responsibility as to how they get the data that is building their UI.

Mala Neti: Now that I have my query, how do I actually, or I’ve built out my query, how do I actually incorporate it into my front end? How do I incorporate it into my React application? At SurveyMonkey we use the Apollo client platform, which is basically just a GraphQL implementation. It exposes me to a lot of cool things, one of which is my query component. I can basically pass in the query invariables that I wrote and built earlier as props to my query. I can also pass in this render prop function, which as you can see, exposes me to my various different query states, whether that’s loading, error, and so on. Based on my query states, I then can intelligently render my UI, which is pretty awesome.

Mala Neti: One sort of best practice that we like to follow at SurveyMonkey when we’re building our components and their respective queries is modularity, the idea of modularity and reusability. GraphQL works very well with that because it allows me to co-locate my data with my components. The data requirements of my components can live right beside it. That’s important because if I needed to add fields, delete fields, delete a component, really make any sort of change, GraphQL, doing it this way allows me to do that. I don’t have to worry about going up the component tree and having a query that basically powers multiple different components. I can just deal with the component at hand and the data that belongs with it.

Mala Neti: Another sort of application of this concept is component boundaries. If I have a network error or error fetching my GraphQL data, rather than having my entire page fail or multiple components fail that are dependent on a particular query, all I have to worry about is gracefully degrading my components that are dependent on that query, which is great because this is a much better user experience.

Mala Neti: All of this is awesome, but this means that by default every component will have to make their own network request, and we did just talk about how one of the selling points of GraphQL is minimal round trips. Because of this, GraphQL has actually come up with various ways to deal with this problem. What we are currently using today is query batching. That essentially allows all of my queries to be combined into one request. This has advantages and disadvantages. There’s alternatives to this, but we found as of now this works for us because it allows us to think about modularity while still reducing the number of requests and kind of gaining that performance benefits from GraphQL.

Mala Neti: From this example, I hope that it’s easy to see why we at SurveyMonkey love GraphQL. I think, A, our developers are happy because we have exposure to an amazing tooling ecosystem. We have a predictable developer experience. Our back end engineers are also happy because we have, they can sort of iterate on their code independently of sort of the new requirements that are coming in on the front end. My customers are happy because I have a performant robust product. If my developers are happy and my customers are happy, we have a really happy SurveyMonkey.

Mala Neti: With that, I wanted to say thank you so much. We’re really excited about what we’re working on here at SurveyMonkey. If any of this sounds exciting to you, please come hang out with me after and I’d love to chat. Thank you.

Robin Ducot: Now we’re going to have a little chat with some of our leaders here at SurveyMonkey about career topics. I’d like to welcome to the stage Mala. Not Mala. Mala just left. Shilpa, Jing, and Erica. Thanks, guys.

Robin Ducot, Shipla Apte, Jing Huang, Erica Weiss Tjader

SurveyMonkey girl geeks: Robin Ducot, Shipla Apte, Jing Huang and Erica Weiss Tjader share advice and stories at SurveyMonkey Girl Geek Dinner.

Robin Ducot: I have a few questions, but let’s get started with introductions. I’m the CTO here at SurveyMonkey. I have been, let’s see, 30 years doing technology and about 15 of those years, last 15 years as an executive. I’ve managed everything from product, program, engineering, QA, ops, I don’t know, security, IT, all different types of areas from companies as big as Adobe to companies that you’ve never heard of that are gone now. I love engineering, and I’ve been here at SurveyMonkey 18 months. It’s just been a really exciting journey. Fun fact. Fun fact, I used to play in punk rock bands. People will tell you this and laugh. Also, 25. This number is the metric I use to measure the number of engineering leaders I’ve created in Silicon Valley. I love coaching and mentoring leadership skills for technologists and helping people grow into leaders of technologists is one of my passions, so 25 in Silicon Valley.

Robin Ducot: With that, why don’t we get started with some introductions of the other folks. Shilpa?

Shilpa Apte: Sure. Hello? Can you hear me?

Robin Ducot: Yeah.

Shilpa Apte: Sorry. Hi. I’m Shilpa. I’m an engineering manager here at SurveyMonkey for the respondent experience team. We’re the team that manages and innovates on the survey taking page. It’s the page you see when you take a survey. I’ve been at SurveyMonkey since I was an intern in 2012, so just about seven years. Let’s see. Highlight of my career has been getting to move to Dublin for two years to set up the engineering team there. That’s Dublin, Ireland, not Dublin, East Bay. My fun fact is that while I lived abroad, I traveled to–I did 17 weekend trips to countries I’d never been to before.

Jing Huang: Hi everyone. My name is Jing Huang. I’m a director of engineering focused on [machine learning here at SurveyMonkey. I joined SurveyMonkey for three years. Fun fact, I did a hiking trip to Everest base camp with a 14 day hike. If you’re ever hiking in a high altitude you’ll know like if you get a cold, it’s devastating. I got a cold in day five, but luckily I’m here, so I survived. I was able to complete the hike. The highest point I was able to reach was more than 18,000 feet, which is something I get to blab a lot. Some highlights of my career, I studied robotics and artificial intelligence. After graduation, I didn’t find a job in ML that was like more than a decade ago within a prime time for ML, but I was able to work on different applications from network security appliances to cloud management to big data. Finally I got an opportunity to work on ML here in SurveyMonkey, so that’s where I am.

Erica Weiss Tjader: Hello. Good evening. I’m Erica Tjader and I’m the VP of Product Design.

Erica Weiss Tjader: We had a joke in rehearsal that I wasn’t even going to need a mic I’m so loud, and they turn mine off. That’s a funny joke.

Erica Weiss Tjader: I’m Erica Tjader. I’m the VP of Product Design here at SurveyMonkey. I have been here two years. The baby is due August 1st. I thought I’d just get that out of the way so we can be done with the awkward like is she, is she not. Anyway, highlight of my career was landing this job at SurveyMonkey. I know that sounds really cliché. I promise they’re not paying me to say that. Tom, my boss, isn’t here, but I think the reason why it stands out as such a highlight to me is not just because of the great role that it is, but actually what it represents in terms of me doing some things that were really out of character for my personality. One was risk taking. When I first kind of, well I don’t know if I applied for the role, but when I first pursued the role, it was a really big step up for me in my career. I definitely did not meet all of the requirements in the job description, so it was a big risk to kind of throw my hat in for it. I think that was one big piece.

Erica Weiss Tjader: The second was intentionality. When I was starting my job search, I made a list of two, just two, criteria that I absolutely must have in my next role. I was really specific about looking for that and not settling for a role that had less. Then I think the third is patience, not my strong suit. Over the course of a couple of years, the first time I passed on SurveyMonkey, the second time they passed on me, the third time was a charm. Just the highlight of my career just I think because of how I’ve reflected on what it says about me.

Robin Ducot: Thanks, Erica. All right. Let’s start with some questions. How about we talk about your current work life. One of the things I think is really, really important is that for you to be successful, if you don’t, aren’t really engaged in what you’re doing, if you don’t really like it, it’s really, really hard to be successful because you’re just not going to be excited about putting the effort in that it really takes to make a success of yourself. What I’m curious about is what is one thing you do in your job function that gets you really, really excited to come to work? Why don’t we start with you, Shilpa.

Shilpa Apte: I love coaching and mentoring people. I love getting to know people and figuring out what their aspirations are, what skills they want to learn, where they want to take their careers and kind of seeing that progress being made over time. I see every single day as a new opportunity to learn something new about someone on my team mainly because people are complex and they change. I just think it’s an interesting problem.

Robin Ducot: Jing, what about you?

Jing Huang: I mentioned I studied robotics and I was a SciFi fan ever since I was little. I was always curious about how AI will shape our future. Getting to work on machine learning here is just dream come true. We have more than 40 billion people [inaudible] data collector here at SurveyMonkey, so this is really a dream job.

Robin Ducot: Erica?

Erica Weiss Tjader: For me, I think one of the things that I really enjoy about this role is the strength it plays to. Anybody familiar with the StandOut strengths assessment? It’s a survey template you can use in our library, but anyway, they also didn’t pay me to say that. Imagine that. I’m a connector. That’s one of the strengths that always stands out for me. I think it’s something that I get to do a lot of in my role. Whether it’s the day-to-day of connecting designers on my team with new challenges or mentors or growth opportunities, whether it’s working with teams to find ways to connect teams with other teams that have similar products or project challenges, and of course even in the nature of our product itself which is about connecting our customers with their customers for feedback. I think it’s just a role that I really get to leverage the strength a lot and that’s really energizing for me.

Robin Ducot: Thanks, Erica. Why don’t we talk a little bit about your career journey. One of the things that’s really, really important is being able to advocate for yourself. How have you guys advocated for yourselves throughout your career and what tactics have really been helpful in making you be heard? We’ll start with you, Jing.

Jing Huang: Sure. To be honest, I’m an introvert, so self advocating wasn’t natural to me. My pivotal point came when I realized self advocating is not only about self, it’s actually about advocating for your team. It’s also mutually beneficial for you and for your manager. There are two tactics I want to share today that will be helpful. I think it was helpful. Number one is to do regular updates of your work progress. Doesn’t matter if your manager asks or not, but do it. You can do it through email. You can do it through your one-on-ones. Do keep those cadence. That’s just going to be mutually beneficial because your manager wanting to know your work. That’s the number one thing.

Jing Huang: Second thing is share your knowledge with your peer, with your cross functional partners. Do tech talks. Do lunch and learn. When you go [inaudible] try to talk in conferences. This is also a mutual beneficial thing. It’s self advocating in one way, but it’s also sharing your knowledge. Everyone else is going to learn from you. Those are two things I wanted to share.

Robin Ducot: What about you, Shilpa?

Shilpa Apte: Yeah, for me self advocacy, for me it was a pivot when I realized that if you do it a little bit over time, it’s much easier to have important conversations when you really need to rather than trying to do a big one all at once. The way in which I do that is, one, to just believe in myself. I think if you believe in yourself, build confidence in your abilities, it trickles into everything you do. Two, understanding what your manager expects of you and meeting those expectations, it’s just easy points. That’s not to say that you should feel restricted by those expectations, but I think that’s kind of a baseline. Beyond that, you should kind of like, what Jing said, be giving regular updates about what you’re working on. The third is really being able to articulate what value your work is creating for the business and for your team and making sure that your manager understands that as well.

Robin Ducot: Those are great suggestions. It’s funny, for me, one of the things I’ve noticed is that developing a very strong sense of entitlement, which sounds negative, but I swear it’s positive, developing a sense of entitlement that you are allowed to be in the room, especially for female technologists I’ve noticed this is an issue. I was fortunate in that I’m third generation technology leader in my family, so I didn’t realize women weren’t supposed to have a voice around technology. I’ve noticed that it’s really, really important that you feel entitled to speak up. Your voice is just as important as anybody else’s. If somebody interrupts you, interrupt them back. You know?

Erica Weiss Tjader: Well said. Well said.

Robin Ducot: All right. Moving on. Mentorship. People talk a lot about mentorship, but what’s interesting is some of the most influential relationships that you end up having because they’re more common are the allies that you develop in the workplace. I’m a little bit curious about, for you, Erica, tell me a little bit about some of the experiences you’ve had with allies.

Robin Ducot, Erica Weiss Tjader

VP of Product Design Erica Weiss Tjader shares tips for making allies in the workplace, for your professional success, at SurveyMonkey Girl Geek Dinner.

Erica Weiss Tjader: It’s an honor to have Robin Ducot ask me this question because she is one of my greatest allies here at SurveyMonkey, but that’s not what I’m going to talk about. I was actually trying to think of a really good example, and I found the list was so long I couldn’t even remember the last names of half of the people that were coming to mind, which I think is either indicative of my memory or actually the nature of allies. Unlike mentors, allies are not big investments in relationships over time. They are episodic. They are based on a specific purpose at a specific place and time. As a result, they can have a really much bigger impact on something you’re trying to achieve at the time.

Erica Weiss Tjader: A good example that I thought of is in a previous role I was a design leader of a smaller team. One of my biggest challenges that I was facing was making inroads with our engineering leadership around the notion of, the importance of front end development, design systems, some of the topics that design and leaders and engineering leaders often talk about. I was having a hard time getting traction. It was one of those tough problems because it was probably the most important thing to my team and yet the thing I had the least direct control over. This was an example. I have to influence because I don’t own the answer to the problem. This particular ally was a new engineering manager that joined the organization. In my initial just meet and greet with him, I learned that he had some expertise around developing front end teams and design systems and sort of an interest. Perhaps most importantly, I learned that he had a personal relationship with our CTO who was the person I was having the hardest time making inroads with.

Robin Ducot: Wasn’t me.

Erica Weiss Tjader: They were personal friends. No, it was a different story. I’ve got a lot of stories.

Erica Weiss Tjader: What I did is I really just started out by befriending this guy. I’m like I’m going to make your transition into this company really easy. I’m going to introduce you to people. I’m going to tell you all the secrets. We had lunches. We had coffees. We started to build a relationship, and in a very short period of time we were able to transition that relationship into finding a mutually beneficial place where he was able to leverage his expertise and his influence in the engineering organization to start a front end team and I was able to give him disproportionately more resources and support from the design team to really improve the value and success of that.

Erica Weiss Tjader: I think it’s just a great example of an alliance that was very intentional, but looked very different than a mentorship relationship because it was really about a place and a time and a need and a relationship right in that moment.

Robin Ducot: That’s a wonderful story. I mean I think that’s something that’s really, really important. I know as an engineering leader, one of the allies that I always develop when I first join a company is the person who runs the customer support team, making sure that they understand that I am there to help them when we screw up because obviously the site does have issues on occasion. Making sure that you have that relationship so that they support you when you inevitably screw up and then you can support them. I’ve noticed over the years that this is a pattern that really, really works.

Robin Ducot: I do have a question. We are in sort of the center of the feedback economy, SurveyMonkey is. I feel like feedback is–one of the reasons I love working here is because I love data, I love feedback, I love learning new things and driving insights from data. One of the things, though, that I’m curious about is feedback is so important in developing our career. What is some feedback that you’ve gotten? We’ll start with you, Shilpa, that you’ve gotten that really made a material impact on you?

Shilpa Apte: It really can be summed up in two words. Be reliable. That’s not to say I was unreliable, but you commit to something and it starts slipping and you don’t tell the person that you told you would do it in time that it’s slipping. I don’t know. These little habits that build over time I think I kind of realized that you can be the smartest person and the most talented person in the room, but if people can’t rely on you long term, they’re not going to want you to be on their team. I think once I realized that, that kind of just staying on top of things and making sure, even if I’m not going to complete something that I said I was going to, just communicating that out made my relationships and trust between colleagues a lot stronger. That was kind of a career shift for me.

Robin Ducot: That’s great. For me probably, if I think of some of the best feedback I’ve ever gotten, I have a lot of imagination and I like organization structures and redefining things. As a leader, I got the feedback from an executive coach some time ago that, you’ve got to stop reorging every week. You’ve got to stop all that shenanigans with the reorgs because people, you may be able to surf over the top of all this change and this chaos and you like change, but people, a lot of people like stability. Stop. It was really, really helpful to me because it helped me see the world slightly differently than the way I’d been seeing it. I was like but it’s so exciting all this change. They were like actually you’re killing people. I think that getting feedback, soliciting feedback and listening to it is a really, really important part of developing your career.

Robin Ducot: Advice for others. What skills and experience have been the most valuable to you in developing your career growth? What advice would you give to somebody if they wanted to turn to a career in tech? Jing, we’ll ask you this question.

Jing Huang: Sure. When I think of this question, I actually think of it from a different angle because tech, or the industry we’re in, is fast growing, ever changing. It is not any particular skill or experience that will determine our successful in this industry. It is what I believe is the growth mindset that we all should have and the willingness to learn new things and the courage to actually take on new challenge. I think if you have that, you will be able to learn. Just be sure that you’re actually enjoying doing tech in the first place, right? If you’re sure with that and learn, you will be successful. It’s just time.

Jing Huang: One thing I liked about what Steve Jobs said, long pause, this is an old sentence, but I think it always inspired me is really you cannot look on how dots connected when you look forward. You only see the connections backwards. When you see a new challenge, when you see a new opportunity, take it. Do it. You will find how that’s connected after some years. Robin would know better.

Robin Ducot: Because I’m old, yeah. Lots of connections.

Robin Ducot: I think one thing that’s really important, if you’re thinking about a job in tech is that you have to like solving problems. As an engineer, that is your job. Your job is to come up with interesting and creative ways to solve problems. If you don’t like solving problems, if you think problems are a pain, then you’re not going to really enjoy being an engineer. To Jing’s point about start first to see whether basically this looks like an interesting career to you because if you don’t enjoy it, if you don’t enjoy solving problems, you’re not going to enjoy being an engineer.

Robin Ducot: With that, our final question we’ll take to Erica about finding the right company, the right place to work. What advice would you give the women in the audience who are looking to change companies?

Erica Weiss Tjader: First, I’d say the recruiting booth is over there. No, in all seriousness, I think the first question I’d ask is why are you looking to change companies? Are you running away from something or to something? I think it’s really important to be true to ourselves and be really specific with ourselves when we start to think about making an important change like that and start with the foundational assumption that there’s no perfect job, there’s no perfect company, there’s only the right job and the right company for you right now. I think how do you get to that assessment? I always encourage people to start with a list of what are the top three most important criteria for your next role. You only get three. There’s somebody in the audience I know I’ve interviewed recently, so she’s familiar with the question. Don’t worry. She’s joining.

Erica Weiss Tjader: Anyway, I digress. Start with your three criteria and then be really intentional about how you go out and look for a role that meets that criteria. As women in technology in the Bay Area, we all have the luxury of recruiters hitting us up all the time, of going to events like this where hiring is a big focus. Talk to those people who are seeking you out, but also seek out companies and people who you think are interesting or who you think might meet your criteria well. Have coffees. Have lunches and casual conversations. Find that role that really speaks to what you’re looking for. I often say that the best reason to look for a new job, not the only reason, but probably the best reason is because you’re looking for a very specific type of growth or opportunity that your current company can’t give you at this time. Usually it’s no fault of the company. It has to do with the size or the stage or the priority.

Erica Weiss Tjader: Have those specific criteria, be deliberate, and then go out and look for a job and do not accept a job that meets any less than two of your three criteria. I think just be really true to yourself there. I think the last thing I would say in terms of advice here is to really be open minded and flexible because after you’ve gone through that process of thinking through your criteria, of talking to people, you actually might find that you look at your current company through a different lens or see opportunities there in a different way. It might be that right now that company is the place that meets your criteria the best. Really just be open minded in that search and clear about what you’re looking for and what you’re running away from or running towards.

Robin Ducot: That’s really, really great advice. Another thing I would also think about is that you are joining a group of people and if you don’t like them or if you don’t like the person you’re going to work for, doesn’t matter how great the company is, your job is going to suck. They really are not going to be good advocate for you. If you don’t connect with them, if you don’t feel like they are somebody who is going to really understand your deal and what’s good and strong about you in particular, they don’t appreciate it, then find somebody else to work for. That’s my small piece of advice on finding companies to work for.

Robin Ducot: That is our last formal question. What we’d love to do is get questions from the audience. We are, I’m just wondering, do we have a mic we can hand around? All right.

Erica Weiss Tjader: Bernice is over there with a mic.

Robin Ducot: We have a question here.

Natalia: Hi. I’m Natalia.

Robin Ducot: Hi, Natalia.

Natalia: Should I stand up so everybody can see? I’m really curious about how you approach difficulty to make people feel in the survey. We’ve already heard about best practices, how to run great survey, but how to encourage people to look into it? Maybe let me also explain the question where it’s coming from. Five years ago whenever I received a survey, I just filled it in because it was new and it was so cool. Now I receive surveys like in my career and then private ones and then some place for my husband and so on and so forth. There’s a lot of them. How do you make people start the survey?

Robin Ducot: I think I’m going to have Sarah, if she’s okay with that, come up here and maybe answer that question just as our survey research expert.

Erica Weiss Tjader: Sarah, I’ve got a mic for you. You thought you were getting away.

Sarah Cho: It’s a little hard to hear over there. Do you mind repeating what you had to say?

Natalia: Can you hear me?

Sarah Cho: Oh, how to increase response rates. Was that the question?

Natalia: Yeah, so how do you make people actually start the survey because [inaudible] so many of them from various sources.

Sarah Cho: That’s a really good question. A lot of people worry about response rates, so there’s a couple of things that you can think about. Number one, how are you inviting them? How many of you guys, every workplace has this, has this type of person. We utilize Slack here, so I’m sure you guys might utilize this. I hate it when someone Slacks me and says, “Hey.”

Sarah Cho: Then you’re forced to say, “Hey, how can I help you?” I find that, that’s like one of my pet peeves. It’s the same thing with survey invitations. If you just say, “Hey, take my survey” what’s the incentive for anyone to actually take your survey? That’s not engaging. That’s not personalized. That’s nothing, right? One of the things is to really think clearly about your invitation. It’s best if you can customize it. If you know the person’s name, utilize the person’s name. If you can disclose what the survey is about, give a quick one sentence, not too long again, description of what the survey is about. The other thing to remember is the first impression is the biggest impression that you can make. Again, thinking about the invitation, you don’t want to use too much text because people are going to get overwhelmed and not read it. Same thing goes for the first question in your survey.

Sarah Cho: If you start with a really hard question, we actually see this because we collect so many responses. We can actually go through our database and see what decreases response rates and what increases it. The first question is actually one of the most crucial. If you start with an open-ended question, which is really hard for people because you have to type out your answer, your completion rate automatically drops on average around 15 percentage points. That’s a lot. If you just start with an easy question, even if it’s like a soft opener that you kind of need to throw away, that’s always best. Start with a multiple choice easy question.

Sarah Cho: Those are two small things that you can do. Number one, personalize how you’re inviting people in, and number two, make your first question easy. There’s a lot of other things that you can consider, like incentives, but that’s a whole ‘nother talk. I’ll save that for later.

Shilpa Apte: I would also just add on that within the product itself when you’re creating a survey, there’s a tool called Survey Genius that actually tells you, you’re welcome, that tells you, kind of scores your survey and gives you feedback on how you can improve response rates based on question ordering and length and all that.

Robin Ducot: Who’s got the mic? Bernice.

Audience Member: Can you hear me? My question is if we’re not necessarily sure our three, oh sorry. I won’t yell. All right. If we’re not necessarily sure what our three criteria are, what we want to do, what we want our next step to be, how can we go about finding that next step and just kind of a general what do you want to be when you grow up more?

Erica Weiss Tjader: A couple of us might have thoughts here. My first thought is don’t try to make one of your criteria like this is what I want to be 20 years from now when I grow up. That’s like this well thought through career that probably won’t even exist 20 years from now, right? I think when I talk about criteria, I’m actually talking about really specific attributes of your role. For example, one of my criteria when I was joining SurveyMonkey was I had a 10 month old at home. I knew that eventually I was going to want to have another child. I knew that I was going to work a lot of hours no matter where I went, so I knew short commute was super important to me. One of my two was short commute.

Erica Weiss Tjader: I think it’s about what is important to you in your life right now. If you’re earlier in your career, you might say what I really like is I’m a really outgoing person and I really get a lot of energy from talking to people. If I don’t know what function I want to be in, I know that it’s super important to me to have a role where I interact with people for more than half of my day. Then you can start having the conversations and you’ll find out which roles actually fit that criteria and which don’t, but don’t start out with like I must be in sales or I must be a front end engineer, like trying to get too specific about the career path. I think that will emerge for you as you think about what kind of work or environment gives you energy and you’re passionate about.

Jing Huang: One thing I think I can add on is when you really don’t know what you really like, I think when I was in school this was a question. Look at what other opportunities are out there. Try to do them. You can always think about you like or not, but that’s just thinking. You have to do it and actually test if you actually like it or not. Don’t pass an opportunity thinking you may not like it. If there’s an opportunity, actually catch it and try to do something about it.

Robin Ducot: Experiment.

Audience Member My question is how do you solicit constructive feedback? I find, personally I find asking directly is not the most effective way. Actually, I’ve been thinking about sending out survey. I’m wondering if you have any insights.

Robin Ducot: We’re running a feedback survey right now in engineering. Anonymous is good. If you really want to find out, for an organization or for something that you’re doing, anonymous is good. If it’s personal, if you’re trying to get feedback from people personally, you just have to show that–it takes time to get people to trust you, that you won’t freak out. Ask for feedback and it’s still too sugar coated, poke a little. Have it be a little less sugar coated. Poke a little, less sugar coated. Not reacting. Just keep asking questions. Then people will start being willing to give you the kind of feedback that you really need because you need people to believe that you can handle it, right? That’s why people sugar coat things because they don’t want to deal with people’s emotions when they upset them.

Robin Ducot: Present yourself as somebody who is just interested in the facts and it really, really helps.

Erica Weiss Tjader: I think another trick I’ve called on for some of the folks on my team, I’ve had people reporting to me who are the type of people who always get positive feedback. Every time we send the anonymous peer feedback 360 survey, everybody says they love working with me. By the way, that’s true. That means that you’re great and you should feel really good about that, but obviously it’s not as constructive. I think there’s a couple tricks. One is ask a different level of person for feedback. Perhaps you’re asking people who are your current peers, not the people who you would like to be your peers in your next role, right, in terms of thinking about asking the next level.

Erica Weiss Tjader: The other thing is asking the question in a different way. Rather than saying, let’s just say your ambition is to be a more influential leader. Rather than asking somebody what room for improvement do I have or some sort of generic question, ask I’m really focused on trying to have more influence as a leader. What are some areas where you think I could be more influential? What could I do differently to have more influence? Really ask about the thing that you have identified as the thing you want feedback on specifically as opposed to just general feedback questions.

Robin Ducot: Yeah. I’ve noticed also real time feedback. You’re in a meeting and the meeting’s over. Asking the person do you think that thing I said in the meeting was okay, where you’re right there in the moment and they might be more inclined to give you feedback because you just had this experience. It’s hard also for people to remember if you’re asking things that are too general. It might be another thing that could help you.

Robin Ducot: We’ve got a question back there in the orange.

Audience Member Can you hear me?

Robin Ducot: Yes.

Audience Member Thank you again for organizing this. I have used SurveyMonkey for many years for my own events. I used to be in marketing, so thanks for this opportunity to see you in person. I used to be an engineer who moved into marketing, product management, sales ops, kind of seen all the 360 of the business. One of the comments Robin made around problem solving, that one aspect that I learned in engineering has stayed with me throughout my career, so I just wanted to say that to the audience and also to anybody who is in tech, if you don’t like problem solving, then your career, you basically are lost.

Audience Member: The one question I have is in engineering especially, given that I’ve done everything, I’m realizing now that if I wanted to come back, what sort of strategic leadership roles could one aspire to? Is that even possible?

Robin Ducot: You mean you want to move laterally from where you are, the level that you’re at now, back into engineering?

Audience Member: Yes.

Robin Ducot: Probably you’d have to go join engineering at the level you left, not the level that you are, just because engineering leadership, usually you need to have the respect of the engineers that are working for you, and that means having been sort of through the ranks of leadership and engineering. At least that’s been my observation. If you’re willing to go back and if you left as an engineering manager, joining as an engineering manager again and working your way up, at least that’s what I would guess unless you go to a start up. A start up, everything’s possible. You can be a CTO at a start up with an accounting degree. It’s totally fine. Just write some code.

Robin Ducot: Sometimes I’ll tell people that. You get somebody who is like I want to be a CTO now. I’m like go join a start up. You can do that. Knock yourself out. Anyway, I digress. I think if you really want the leadership role early, start ups are great for that.

Audience Member: Hi. I have a question. What if you like what you’re doing, but you just don’t like the people you’re working with?

Robin Ducot: Get a new job. Get a new job.

Robin Ducot: We got recruiting over there.

Robin Ducot: Life is too short. If you hate the people you work with, get a new job. You’re not going to be able to fix them. I’m just saying. I don’t know if somebody has a more sophisticated answer than that.

Audience Member: Hi there. My name’s Vidia. It’s fantastic to be here and see all these women at the panel here. It’s been great. Robin, my question is for you. It’s great to see a female CTO. My world is full of the other gender, so it’s very nice seeing this. Can you talk about your journey? You said you’ve been in tech for 30 years? What were your pivotal moments when you look back now and said okay this was a game changer? I’m sure you have a few.

Robin Ducot: Oh boy. I was really lucky. Like I said, my mother ran a huge research team at MIT, so I didn’t know. I didn’t know. I didn’t know women weren’t supposed to be engineers. Nobody told me that. I also liked being an outsider. I was a punk rocker. I didn’t mind being the only female engineer in the room, and again didn’t realize I wasn’t supposed to be there because nobody told me and I didn’t mind being an outsider. I was really, really lucky. I think that along the way things that I had to learn that were hard to me, when I realized that after getting into fights with more than one boss over multiple companies realizing that it was me, that it wasn’t them, that it was me, and that I had to work for people that I liked and who understood my special snowflake self.

Robin Ducot: I think that everybody’s got a certain set of strengths and weaknesses. Over the years, developing a career around my strengths and then hiring from my weakness. It’s not one specific story. It’s sort of a constellation of experiences that have led me to believe that if you focus on your strengths and hire for your weaknesses, you could actually be really, really successful. I don’t know. It’s kind of a long, windy answer to that because I don’t really have specific things that come to mind as oh my God that time when. There have been moments in time of pieces of advice I’ve gotten. Because I will have a street fight about things, I got the advice once of, Robin, sometimes you just got to keep your head down. Keep your head down and just keep moving. All those people that you want to kill, they’ll be gone and you’ll still be there. Then you get to run the show.

Robin Ducot: The guy who gave me that advice is my boss here. I worked with him 20 years, I mean we’ve been working together on and off 20 years. That was a long time ago. It was great advice. Anyway, there’s been lots and lots of little experiences that have brought me where I am, but I do think focusing on your strengths and being resilient. You’re going to get your ass kicked every day. Just keep showing up. That’s been my experience. Again, like I said, I liked being an outsider so I didn’t really mind. I always thought this is my fight to have, but what I’m realizing and what I’ve come to realize as trying to help other women move through, not everybody likes being an outsider. Not everybody wants to have that fight and they shouldn’t have to. You shouldn’t have to have that fight. It shouldn’t be part of the deal. You should just be able to be a woman in tech and not have it be a big deal.

Robin Ducot: It kind of annoys me actually sometimes. I feel like I’m a prized poodle that’s being trotted out. Female technology leader. I want that to be the norm. I want that to be everyone can be a CTO and be female. It’s like that’s not a thing, but we’re not there yet. I recognize that. That’s just my long winded answer to your question.

Audience Member: Hi. My question is SurveyMonkey consider yourself like Uber in survey industry? If not or yes, what is your major competition?

Shilpa Apte: Do we consider ourselves to be Uber in surveys and who is our major competition?

Robin Ducot: We are the Uber of surveys. Oh yes. Oh yes.

Robin Ducot: It depends on what market, actually who our biggest competitors are. It depends on whether it’s the consumer market, sort of low end surveys, basic surveys, and then you have Google forms and things like, I don’t know, Type Form. That’s who I was thinking of. Type Form. See how much I worry about them? Then at the high end in market research you have Qualtrics. One of the things I love about SurveyMonkey is that our product works for all of these markets, for the big and the small, and that’s actually what makes us unusual. Type Form doesn’t work for market research and Qualtrics doesn’t work for the basic user.

Robin Ducot: Yes, we are amazing. I totally think that.

Angelica: I had a question. I actually had the reverse question of someone here who asked a question. My name is Angelica and I’ve been in the tech industry for about ten years now. I’ve been fortunate to have a very supportive boss and team. My situation is I don’t really like what I’m doing anymore. It’s a short glass ceiling where I’m at and there’s not really a lot of room for growth or advancement. Just asking for anyone’s opinions about being in that kind of situation, having a supportive team and a supportive boss, but not really being happy with what you’re doing.

Erica Weiss Tjader: I think we call that the curse of being too comfortable or something like that. Again, I started with the there is no perfect job, there is no perfect company. I think it depends where you are in your life. I think you might be at a point in your life where you’re like these are the years where I want to work hard and I want to charge ahead and I’m willing to pay the price to do that. Therefore, staying in a role where you know that there’s no growth for you is probably not a good idea. You may be at a stage in your life where you’re like you know what I need? I need to feel supported. I need to feel happy going to work every day because the people I’m working with. At this stage right now maybe actually climbing that ladder is not my top priority.

Erica Weiss Tjader: I think it really depends where you are, but I think if you are at a place where growth is important in terms of your–personally and you recognize that is not what you have at this company, I guess the first question is are there other roles within the company where you could find growth and other avenues to explore there? If not, that’s probably the right time to start looking at what else is out there.

Robin Ducot: Absolutely.

Audience Member: Hi. Thank you very much for sharing your advice today. I came from a finance marketing background and being in the Bay area, obviously tech is where it is. Want to know what’s your perspective on boot campers as well as if you have any advice for reframing other industry experience for transitioning to tech. Thank you.

Robin Ducot: I have some thoughts about this, but I don’t know if you guys want to share. I think that boot camps are typically really, really great feeders for small startups and tend to be less effective for getting jobs at larger companies who have big internship programs, but startups usually don’t. They are very excited about taking boot camp folks. I’ve worked at all different size companies and that’s been the pattern is that typically small companies eventually grow out of the boot camp feeder just because there is a lot more risk. As companies get bigger, they’ll take the CS degrees from their intern programs as the sort of feeder into the low level engineers.

Robin Ducot: I love startups. I think the experience you get at startups is amazing. I think that going through a boot camp and ending up at a startup is an amazing way to start your technology journey.

Jing Huang: One thing I think of, like your background in finance, right? Cross functional. If you think about tech today, having a knowledge of a different industry is actually very valuable. Taking tech applied for finance. Think about, for example, data science. There’s a big application on data science for finance. Those are areas where you actually have a unique strength to segue into tech if that’s what you want to do.

Audience Member: Everybody heard about the bro culture here in Silicon Valley. Is there a thing in SurveyMonkey or any other job you had before and how did you deal with it? How did you handle situations like mansplaining or competing for role, climbing the ladder?

Robin Ducot: Mansplaining? Sarcasm. Really? Really?

Audience Member: What about the career ladder?

Robin Ducot: For career ladder, I mean SurveyMonkey does not have a bro culture. It’s actually one of the wonderful things about SurveyMonkey. Do you guys agree with that? Yeah. I think that’s one of the things that actually was a little bit interesting of a transition for me when I joined was that I didn’t have to have that kind of, didn’t have to whip out the sarcasm quite as frequently. I think from the career ladder, I think it’s really just important to advocate for yourself. Men ask. I always asked. Always. Every single promotion I’ve ever gotten, I asked for. Every single one. It’s not because they didn’t think I was good. It’s just that people pay attention to people who are asking. That would be the thing that I would say is that the bro culture thing, I don’t know what to do about that.

Robin Ducot: I just tell them to knock it off and move on. I don’t know if you guys–

Shilpa Apte: Getting more women into tech.

Robin Ducot: I think that’s actually the best way to solve for it is if you’re a leader is to bring more women in. Then it gets diluted and, I don’t know, slows down. As an individual that doesn’t have the power to change it, if the company is really obnoxious and doesn’t fit your cultural values, then maybe look for some other place. Also, just tell people to knock it off. That’s my favorite thing to do. Whether you feel comfortable doing that is really sort of your thing. As for career growth, you really have to just keep, I mean one of the things that Jing mentioned, which is so important, is making people aware of what you’re doing. Just making sure that your competency is visible and whether it’s tech talks, speaking, things like that so that people become aware of your value to the organization.

Robin Ducot: I don’t know if that’s helpful. I don’t know what to say about the actual bro culture, I mean to fix it. It’s mostly just bringing more women in and not tolerating it when people are obnoxious.

Olga: Hello everyone. My name’s Olga. My question is about technical excellence. Whenever you come as a technical lead or an architect to the company, to the new company, you always have to prove yourself. Unfortunately, I am doing my engineering for 15 years. I built system that always run whenever I leave the companies, but still, like five years ago when I joined Salesforce, I had to prove myself by designing this complex system and building it myself. Then people realized what I really worth and was very surprised that I did this. Unfortunately, I do the same at Google right now. I still have to prove myself and building this complex system and designing this myself because I find that people, maybe they trust me, but they don’t trust as much as I would like. I see they trust some other people. They’re just not the same kind of expertise and the same bar that they expect from the technical lead.

Olga: I was wondering, is it going to happen at all the companies, just like when I join any new this is what happens? You try to stay at the same company for longer or there’s some other skills you can do so you can prove without building this complex system, like writing the code yourself?

Robin Ducot: I think storytelling is a gift that it takes, it’s useful to develop. I’m not sure if you guys agree with this, but I think that one of the challenges, and I don’t think this is a male/female thing actually. I think this is maybe an introvert/extrovert thing. You’ll get people who are just really good at telling their story and selling themselves. These are skills you can develop. Storytelling, selling skills, being able to tell the story of the things you’ve done in the past and being confident about it, feeling a sense of being entitled to be in the room and telling your story is really, really an important skill that will shortcut some of that. I think in engineering, though, engineering tends to be a show me kind of culture. It’s this intersection of being able to talk about technology and learning how to tell the story of all the things you’ve done in the past so that people will listen and telling it in a way that they will listen, not the way that you want to tell the story, but the way they will hear it.

Robin Ducot: You can definitely get coaching in that specific area if it’s something that you’re finding frustrating. I mean some of it is just when you start a new company you do have to tend to prove yourself a little bit. That’s just sort of part of it. I don’t know if you guys have some thoughts about that.

Jing Huang: Totally agree. I was an engineer developer myself. Like I said, self advocating was not natural. Same thing for you. It just feels like we need to do the work to prove ourselves, but in a lot of cases, we have peers or male peers that came to them more naturally where they’d just be able to tell the story about the work they have done instead of having to build something again and again doing the same job to prove what we already been able to do. Learn the skill to really be able to sell your story, self advocating. If that doesn’t come naturally, like Robin mentioned, get some coaching. Really just improve that set. Be confident.

Robin Ducot: Strategically placed solving other people’s problems also becomes a story that people will tell about you. One of the ways when I was still writing a lot of code, I would come in and help somebody solve a problem that they were having. You do that enough and people will trust you without you having to be designing something from scratch and building a whole up system, but being able to troubleshoot their systems because if you’re good at writing a system, if you can really build such a system from scratch, then you might be able to help somebody else fix theirs. Helping people fix their problems makes you very, very popular. Very popular.

Robin Ducot: What’s going on back there?

Audience Member: First of all, thank you for sharing your experiences as inspiring technology leaders. Looking back at your career journey, what was the best decision you made and the worst decision you made and why?

Jing Huang: It’s such a hard question.

Robin Ducot: Don’t try to get your boss fired. Don’t try to get your boss fired. It does not work. Even if they suck and they deserve to be fired, don’t try to get them fired because…. Complex, yeah. How about that?

Robin Ducot: Jing, you got something more?

Jing Huang: I couldn’t think of any like really worse decision you could make. I think every decision, there is different perspective. There is different outcome, but there is always a way out. I think that’s an opportunity. Nothing really bad could happen. Either you stay with a job or you leave for another company. It’s a choice. It’s an opportunity that you will make because of your decision. There’s nothing really bad that’s going to happen.

Robin Ducot: Yeah. It’s actually interesting. The most important thing is how you get back up if you, so take risks. You’re going to fail. It’s okay. You learn. I mean in my experience you learn from failure, not from success. Take everything as a learning experience and get back up and do it again. I don’t know. I’ve had so many learning experiences that have helped me learn.

Robin Ducot: Okay, we are at 8:30. Holy mackerel.

Robin Ducot: One more question right here I guess, and then we’ll-

Audience Member: I’m actually looking for advice. Imagine a manager kind of experienced outsider looking for a new position. This manager, let’s say me, I find a position in a company that I really admire. I look through the qualifications and I look through this job responsibilities and I know that I’m going to excel at this job, but all of this preferred qualification may not match what you actually have on resume. How do you grab this attention? How do you break through? How do you be noticed by either a recruiter or a hiring manager when you apply to this job?

Robin Ducot: I mean the question is, so you have the qualifications, but your resume doesn’t illustrate that you have the qualifications?

Audience Member: [inaudible] some specifics. For example–

Robin Ducot: Yeah, what’s an example of a specific? A specific programming language or something?

Audience Member: Yeah. It’s like a particular experience or, let’s say, experience in network or experience of working with healthcare for example.

Robin Ducot: You know, it’s funny, men will just apply. You just apply. This is one of the things we talk about. Actually when we create job descriptions, we’re really careful to make them so that they’re inclusive, that women are not going to automatically exclude themselves because there’s too much specificity in them. If you reduce the amount of specificity, then you’re going to get a wider range of people because the reality is that you don’t really know what you want exactly. You write a job description and then people show up and you’re like, hey, I kind of like you. You really don’t match the job description exactly, but you have something that’s special that will really resonate with the team. Apply anyway.

Audience Member: [inaudible].

Robin Ducot: Sorry, I can’t hear you.

Erica Weiss Tjader: I think, how to stand out. One thing, I’ll take on that, the reality of, depending where you’re applying, most companies the resumes that are coming through the application system are being reviewed by the recruiters and the recruiters, while great partners to the hiring managers, they know what they’re supposed to look for based on the resume. If it doesn’t match, you’re most likely to get passed on. Doesn’t mean you shouldn’t apply and you shouldn’t go through the recruiter. I think it’s a yes and figure out how to get in to a company, how to talk to real people, how to network. Again, I think it’s a lot harder. Let’s say you were interested in a design manager role on my team, which hopefully you’re not because then this will become awkward, but let’s just say you reach out to me and you’re like I really want to be considered for the role. Can we talk?

Erica Weiss Tjader: I might look at your resume and go I’m not sure, but if you reach out to me and say your experience looks really interesting, I’d love to pick your brain. Can I buy you a coffee? I might be like, oh yeah, okay, maybe, yeah. Then while we’re having coffee, you might somehow slip in the fact that actually I’m looking for a job. Would you ever consider somebody like me? Again, hopefully I didn’t just play out some future scenario that we’re going to have because that would be really weird, but I think it’s like if you come at it from I’m a job seeker, I’m a job seeker, I’m a job seeker, you might find that’s not the best way to build a relationship. Talking to people in the organization and finding your way through is how you’re going to stand out either because your resume looks exactly the same as everybody else’s or not quite the same as everybody else’s.

Robin Ducot: See if you can find out who the hiring manager is and then use LinkedIn to see if you’re connected to them. I mean that’s probably the most straightforward way to sort of do an around the process. Yeah. LinkedIn is your friend.

Robin Ducot: We are being kicked off the stage. Thank you so much and please enjoy the rest of the evening.

SurveyMonkey girl geeks and Robin Ducot

Thanks to all the SurveyMonkey girl geeks who helped make the SurveyMonkey Girl Geek Dinner possible! We had a fantastic time.


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Girl Geek X HomeLight Lightning Talks & Panel (Video + Transcript)

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Sandy Liao speaking

Head of Talent, Culture & People Operations Sandy Liao kicks off a HomeLight Girl Geek Dinner in San Francisco, California. HomeLight girl geeks share how they use data and human emotion to empower decision making.

Speakers:
Sandy Liao / Head of Talent, Culture & People Operations / HomeLight
Mary Remillard / Talent Operations & Culture Specialist / HomeLight
Molly Laufer / Director of Offline Marketing / HomeLight
Sam Ryan / Product Manager / HomeLight
Ames Monko / Product Designer / HomeLight
Jenn Luna / Senior Software Engineer / HomeLight
Tina Sellards / Facilities & Administration Manager / HomeLight
Vanessa Brockway / Senior Manager of Business Development & Strategy / HomeLight
Gretchen DeKnikker / COO / Girl Geek X
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X

Transcript of HomeLight Girl Geek Dinner – Lightning Talks:

Gretchen DeKnikker:  From Girl Geek, thank you guys so much for coming tonight. If you guys want to come in and have a seat, we’re going to get started. So we’ve been doing these for about 10 years and this is over 200 that we’ve done so far, so we do them every week. How many people is this their first one? Cool. So stay on the mailing list. Come, you can do these every week up and down the peninsula into the South Bay. And this is Sukrutha.

Sukrutha Bhadouoria

Girl Geek X CTO Sukrutha Bhadouria encourages people to sponsor and rally their teams to plan a Girl Geek Dinner to increase your visibility in the organization and boost your career.

Sukrutha Bhadouria: Hi. I’m glad that there’s no more feedback. It was driving me crazy. Welcome, everyone. Like Gretchen said, this has been going on for 10 years. We branched into virtual conferences and podcasts, so you can listen to our voices some more if you go to whatever your favorite podcasting service is. A little history; we started off in 2008 and it was just a way to get women from various companies together. You got a sneak peak into the company and what they’re working on and the companies had access to these amazing women and these amazing women had access to each other. You don’t often get to hear about these wonderful accomplished women like those who are sitting behind me as easily if you don’t attend an event like ours.

Sukrutha Bhadouria:  So we’re hoping that you’re going to be building your network tonight and making connections. The other thing is that we’re always looking for ideas and content that you might want, so do send us your recommendations and your requests, but please do get your companies to sponsor because that just increases your visibility within the company. I can tell you I got a lot of visibility and access to my CTO in my company when I got Salesforce to sponsor. It was great. You don’t get to get access to them as easily. As it is out of it, it just made my career trajectory improve drastically. So you want to do that.

Sukrutha Bhadouria:  More than that, you want to, like I said, make connections tonight and please, there’s a lot of people who wanted to be here and couldn’t make it because we filled up and also because it’s a weeknight, so please tweet and share on social media. Our hashtag is GirlGeekXHomeLight, and I hope to see you at more events. We have one every week, like we probably already said. But we’re filling up really quickly this year, so hope to see you soon. All right, thank you. Sandy.

Sandy Liao:  Hi, everyone. We’re going to … it’s always funny at these events where there’s no one ever sits in the first row or the first seat next to the speaker. But make yourself comfortable. Move up if you have to for anyone else in the back. So quickly, I just want to introduce myself. My name is Sandy. I’m actually the head of Talent and People Operations here at HomeLight. This is actually super exciting personally. I’ve actually been a fan of Girl Geek for almost two years now. Thanks, Jenn here, who introduced me to the group. I’ve had the opportunity of attending multiple events. These things are really … people ask me, is this for recruiting, is this for anything? To me, it really is just for yourself. It’s all of you guys taking the extra time and after a long day of work, after a long week, you guys are taking the extra time to come out, to network with other women in different positions also working in the technology world. I just want to thank you guys all for coming. This is our very first women’s sponsored event at HomeLight. I’ve envisioned this for a long time and I couldn’t have expected a better outcome. So thank you all for coming and welcome to our office here.

Sandy Liao:  Great. So I want to kind of start off … we actually have a really awesome panel tonight. The way how we structure our panel is that we want everyone here to get a different flavor of the people that we have and all of our team, so from facilities to operations to marketing to product and engineering, we want everyone here to be able to understand a little bit about everyone’s role here at HomeLight and how we’ve all kind of came through all of our stories to become in the role that we are today. So we have a ton of buzz words in this valley talking about the word “diversity.” To me, I truly believe outside of diversity, it really means more than that. It means a balanced culture, it means a culture where you’re learning a little bit about everyone’s experience and background. It shouldn’t just be about your ethnicity or your race or anything else. It really should be about how everyone came about to become the person that they are today, and that’s how I define diversity and what it means to have a balanced culture. Very proud; I’ve been here for about three years. I’m very excited, I’m proud to have the team that we have today and I hope all of you guys are going to have a chance to meet some of our team member, and have a good time. So, thank you.

Sandy Liao:  A little story before we begin to pass it on to the panel, I kind of want to quickly introduce myself as well as tell you guys a little bit about HomeLight. So who here has actually heard of HomeLight before the event today? Okay, nobody. No worries. That exactly was my response three and a half years ago. Who here has actually gone through a home-buying or selling experience in the past? Awesome. There’s a few of you.

Sandy Liao:  So, the story of how I came about HomeLight was that three and a half years ago, I was actually in the process of buying my first home in San Francisco. I grew up in the city and I thought that I knew a lot about San Francisco, I know what neighborhood’s great, and I also consider myself fairly tech savvy. You know, I know how to use the Internet, I can go on and search for a realtor and do all that fun things. My mom was actually telling me, oh, use my friend. She’s great. She’s been a real estate agent for 25 years, but she’s never sold a home in San Francisco. And that’s the interesting part about this real estate world is that all of us really envision an idea of what the process would look like to one of the most important buying decisions or selling decision your life, but the truth is is a very complicated and emotional process.

Sandy Liao: So while I was going through it myself, I went online and I searched a couple of different real estate company online, and to be tech savvy that I am, I put in my contact information online and I was like, all right, I’m going to get some help here. And I did. I got 27 missed calls from random numbers within the same day. No idea who these people were. I got a whole lot of voicemails. Everyone’s introducing themselves, they know my name, they were telling me how wonderful they can be to help me, but the truth is I can’t … I don’t know who to call back. I can’t decide who’s actually going to be great. So I didn’t end up responding to anybody.

Sandy Liao:  So that was my story initially while I was going through the process. Through a very similar networking event like this, I actually met a woman who was actually in a viewing at HomeLight and I was telling her that I’m looking to buy a house and I’m in the process of looking, she end up referring me to HomeLight.com, and she said, “Hey, maybe you should check out this company. I just interviewed with them. I don’t know what I’m going to …” She didn’t end up working here, but she was the reason that I’m here today.

Sandy Liao:  HomeLight’s mission is that we empower people to make smarter decisions during one of life’s most important moments: buying and selling their home. Our goal is we analyze millions of home selling datas to be able to find you the best performing real estate agent in your area, so that you can make a great decision when you’re looking to buy or sell. Our CEO, Drew, who founded the company eight years ago was going through a very similar process with his wife, also looking to buy a house in San Francisco, and just find out how challenging and difficult it is to go through that process. With everyone here, we all believe there is a better way of doing this, and buying and selling a home should be a very, very exciting process in everyone’s lives. So we’re here to make that better.

Sandy Liao:  Before I pass it down, today our topic here is to talk about how we utilize our data as well as our human emotions to empower all of our decision making. I’m going to hand it off here to Mary on the talent team who’s going to share with you guys a recent experience of hers utilizing HomeLight, our platform. So, thank you.

Mary Remillard speaking

Talent Operations & Culture Specialist Mary Remillard gives a talk on “How the Marriage of Data & Human Connection Resulted in my Successful Home Purchase” at HomeLight Girl Geek Dinner.

Mary Remillard:  Thanks, Sandy. Hi, everyone. Thanks for being here today. I’m actually on Sandy’s team. I’m the Talent Operations and Culture Specialist, which essentially means that I spend most of my days focused on recruiting on our higher needs across the board. I also do have a hand in our HR and administrative tasks, as well as our cultural and employee engagement initiatives, so a lot going on there. But I truly have been passionate about HomeLight since Sandy reached out to me, two plus years ago on LinkedIn and introduced me to the company and the people and the culture and our mission, which is to empower folks to make a smart decision as they’re going through one of life’s most important moments, which is buying or selling their home.

Mary Remillard:  I have, in my two plus years, been pitching HomeLight as a recruiter literally thousands of times. I did the math, which is crazy. It’s been thousands of times. I have always felt like I genuinely appreciated the service that we offer, and I understood why we have this purpose of giving this service to folks. However, it was only until recently when I went through the buying process myself with my husband that I was able to fully comprehend the emotions and the weight of such a big moment in your life of buying your very first home.

Mary Remillard:  So my husband and I, we’re super frustrated. We have always rented and we were probably touring our maybe 12th or 13th complex, and we were just never able to find that perfect situation for us. It was either too far from work, too expensive, not clean, the folks at the front desk were too grumpy for us. Whatever it was, we just figured out, you know what, maybe it’s time we stop buying … or renting, rather. So we’re very proud upstate New Yorkers, never thought we would leave home, but we found ourselves in Scottsdale, Arizona, and decided that, you know what, we are not getting any sort of return on investment as we’re continuing to rent. Why not put down some roots in the desert here and embark on this buying process.

Mary Remillard:  So luckily, having been an employee for two plus years, I knew exactly where to turn. So within an hour of my husband, Will, and I making that decision, we were on our couch and we were engaging with Kimmy, who’s one of our home consultants in the Arizona office. She just asked us some quick questions around the home that we envision ourselves in. She asked us price point, location, timeline we were working with, those things of that nature. And basically she’s gathering that information to then plug into our own algorithm that analyzes this really robust database that we’ve been building since 2012. That’s how we’re able to determine who are going to be these best agents for Will and me as we go through this crazy task of buying our first home. But by the end of the day, we had engaged with two phenomenal agents and then we had this whole other issue where we had to decide between two great people. That’s a great problem to have. Unfortunately, a lot of folks don’t get to have the experience of that being a problem.

Mary Remillard:  So ultimately, Will and I went with a gentleman by the name of Chris Benson, who’s an agent in Arizona. He’s lived there for many, many years, knows the area like the back of his hand, has closed 425 transactions, has nearly two decades of experience and he specializes in single family homes. So Will and I, we went with Chris because it was clear to us that he was going to be someone who would hold our hand and answer our seemingly endless list of stupid questions and just not make us feel bad about it, and make himself available to us.

Mary Remillard:  So within 30 days, and mind you, Will and I decided pretty quickly that we’re sick of touring, we don’t want to rent, let’s buy a home, but our lease was coming up in less than a month. So we did not want to have to figure out a situation between different homes. We wanted to be able to move in immediately. So I don’t know if many of you can relate to that, but when I told people I wanted to buy a home and move in within a month, I usually got a pitying laughter, like good luck, lady. But we were able to do it, and the thing is why we were able to accomplish that is because HomeLight’s algorithm did its job.

Mary Remillard:  Chris Benson was able to help Will and I get into this beautiful townhome that we’re so excited about because he’s closed homes with our needs, we wanted to buy a home around the 200,000 mark, which believe it or not in Arizona that’s doable. And he’s closed the majority of his homes averaging at 214,000. So the reason why he was so good for us is because he’s done this 425 times. He could do it with his eyes closed. So not only are we having a great experience, but so is Chris working with HomeLight because we’re basically teeing him up to work with people whose areas of need are right in his areas of expertise.

Mary Remillard:  So we obviously had a really great time, but what also made this so wonderful of an experience is because Chris is a human. Chris has raised two daughters who he absolutely glows when he gets to talk about them, he knew the highways that I just wouldn’t tolerate for traffic and a commute, I live a mile away from work now. He speeds on the 101, he’s proudly proclaimed that, and he’s a Cubs fan, so him and my husband were able to go back and forth while I was just like, okay, baseball, woohoo.

Mary Remillard:  But long story short, Will and I now are so excited about our future in Arizona because HomeLight did its job, its algorithm worked, it matched us with Chris, and because Chris is a phenomenal agent who’s experienced, and again, he’s done this 425 times. So that’s really the HomeLight difference right there, and I’m so proud to work for a company that now I know firsthand is truly making a huge difference.

Molly Laufer speaking

Director of Offline Marketing Molly Laufer gives a talk on “Offline Performance Marketing: Using Art and Science to Drive Response and Revenue” at HomeLight Girl Geek Dinner.

Molly Laufer:  Apparently I need a new headshot. That photo was like, eight years old, one toddler and many gray hairs later. I’ll work on that. So hi everyone, my name is Molly Laufer. I’m the Director of Offline Marketing here at HomeLight. I’ve been here for about seven and a half months, so I think on the panel I’m probably relatively newer to the team from everyone else. Here at HomeLight, I’m responsible for channels like TV, radio, podcast advertising, out of home, direct mail, and some of our large scale brand sponsorships. Now here at HomeLight, we utilize these channels not just to drive top funnel awareness and sort of general brand awareness and market share, but also to actually drive immediate performance. We utilize these channels as performance channels to drive leads and revenue, and I’ll get into that in a little bit more detail in a minute.

Molly Laufer:  All right, so we were prompted here to talk about some of our passions and our hobbies that we have as well outside of work. When I thought about it and realized that I have a gregarious 17 month old, I realized that most of my current interests outside of work really are just around keeping my toddler alive and trying to main some semblance of balance, which to be honest, I don’t know how that works. So don’t ask me for any advice on that. But professionally outside of offline marketing and customer acquisition, the things that are really important to me specifically are around supporting veterans and their transition to the tech world from the military through networking and storytelling, as well as finding community and support for myself and other working-out-of-the-home moms, especially when they’re making their transition back into the tech world.

Molly Laufer:  I started my professional career in 2007 as a surface warfare officer in the US Navy. I spent four years deployed as part of Operation Enduring Freedom, Operation Iraqi Freedom, as well as a handful of counter-narco terrorism missions as well. I was the ordinance officer and force protection officer onboard the USS Samuel B. Roberts where I was one of three women on a ship of about 280 men. So being in this room with this many women in the inverse is freaking awesome. This is a really cool balance. And then I was also a training and readiness officer onboard the USS Nimitz, which is the photo here. This was probably back in 2010.

Molly Laufer:  So anyways, that’s how I started my career. In 2011, I made what I think, looking back, was a very clumsy transition to the civilian world in technology, specifically in Silicon Valley. I joined a pre-revenue, pre-funding, pre-product, pre everything startup. I was the first employee at the direct to consumer e-commerce net company called NatureBox where I worked on community, I did a lot of our social media, our initial paid social media marketing, as well as influencer marketing, which then, for me, really pivoted into focusing on offline, like podcast and TV and radio. I was at Nature Box for about four years, and then I made a kind of non-traditional transition to the agency world. I worked at an offline performance marketing agency for a handful of years, and it was a great experience. I got to work with a lot of really interesting businesses and a lot of really interesting business models, but ultimately I was really eager to get back to be really hands on internally. I found HomeLight about seven months ago, and I couldn’t be any happier.

Molly Laufer:  So I like to make this joke in some of my interviews which was in the Navy, the closest point of approach is when two ships are passing in the night and you want that CPA to be as high as possible, otherwise you have collisions at sea. When I came to the tech world and realized that CPA actually meant Cost Per Acquisition, and if you were doing your job right, you wanted it to be lower, that was a huge surprise for me, but that’s a whole ‘nother TED talk for another day.

Molly Laufer:  So I’m going to talk a little bit specifically about how we approach, or how at least I approach, offline media planning and it’s really interesting that our topic today is around sort of using data and emotion to make decisions because I’ve always said offline marketing is this real mix of art and science. There’s a lot of data, there’s a lot of those really concrete, quantitative information that can go into making a media plan. But at the end of the day, like every decision that we make, whether it’s buying a home or even just looking at your grocery budget, you have to make some sacrifices, you have to make some decisions in your media plan because most of us work in areas of business where you can’t … money doesn’t grow on trees, you can’t afford to do anything.

Molly Laufer:  So, you know, at HomeLight, I’m going to speak to a couple of these things. This is certainly not exhaustive. I listed a couple of different attributes that go into building an offline media plan. But some of the things that we do here at HomeLight that I think are really unique, we’ve been in business for about seven years, so we have really robust consumer data, and we can take that lead data and we can input that into traditional media planning tools like Nielsen and like MRI, and we can actually get really great personas about who our customers are, how old they are, generally where they live, what type of media habits they consume, are they more likely to watch TV on Roku or an AppleTV or Hulu versus a traditional linear buy, what types of stores do they shop at, and these are all the different types of inputs that we can start to input into a media plan.

Molly Laufer:  Because when you think about buying cable TV, there’s hundreds of channels, there’s many different approaches. You have to start to narrow down the way that you think about what are going to be the right buys to attract the customer that’s right for HomeLight. Things like seasonality is also really important when it comes to doing an offline media buy. You know, there’s … every business has its own unique seasonality that they tend to see better efficiency for their business, but the thing that’s really challenging is that the media landscape also has its own unique seasonality. So for example, things like political campaigns, Black Friday, the end of quarter, and all of the local markets, you’ve got all the guys that are selling mattresses and trucks and they’ve got to get them off the lot at the end of the month. All of these things where you think yeah, I’m really jazzed up because I’m going run this amazing campaign at the last week of May, well guess what? Every single car dealership in America is trying to sell cars on Memorial Day weekend, and so you might end up being kind of SOL if you’re really banking on certain weekends like that.

Molly Laufer:  So there’s all these factors that are kind of outside of your control that you need to have a really good grasp on before it comes to planning a media campaign. The other one that I’m going to touch on here before I move on is specifically around the competitive landscape, and I’ll talk a little bit more about this later on, but what’s really interesting is that in certain offline marketing channels, the competitive landscape either can work to your advantage so you can see where your competitor’s advertising, and you can take the move to maybe follow them. In absence of data where you haven’t advertised before, you could look at competitors or like-minded companies, see where they’re advertising, and choose to do the same thing. However, this approach really doesn’t work in other media channels. For example, podcast advertising or radio endorsements where you have an actual human, a person who’s standing up and saying all right, now onto a word from our sponsors. Those types of ad placements, they can really only have room for one type of product at a time. It would be very, what’s the word I’m looking for? I don’t know. It would be very inauthentic if a person were to endorse, say, one mattress company and then the next week turn around and advertise for another mattress in a box company. So things like competitive landscape and this sort of winner-take-all in the space can be really important.

Molly Laufer:  These are just a couple of the facets that go into planning an offline campaign. The output that you see here, which I realized just looks like a bunch of dots and bar charts, because everyone’s impressed by dots and bar charts. No, but in all seriousness, what this tells us is this gives us an output of who our customer is, what types of media are they watching, and where are we going to be more likely to not only reach a higher percentage of our audience, but as you can imagine those are the placements that tend to be really expensive. It’s no surprise that most of our customers and probably all of yours are watching ABC and NBC and CNBC because guess what? That’s what all of America is watching. And so you get a lot of really interesting data down here on the other end when you look at well, what are some of the smaller networks that the audience is also watching? Can I add frequency and can I add additional touch points for our brand using lower reach, but very low-cost and high efficiency media.

Molly Laufer:  So again, those are some of the factors that go into when you’re actually looking at a media plan. When you are using these tools and you get an output, at the end of the day, you can’t buy everything on a media buyer. You have to use some sort of prioritization and rankers. It’s different for every business. It’s different if you’re a national company versus a geo-based company. But those are some of the factors that I use, at least, here at HomeLight.

Molly Laufer:  Another chart with lots of dots and bars. But this is really interesting. So I thought a lot and hard about how can I talk about offline media measurement. I could take an hour, and I think I have seven and a half minutes and I’ve probably already burned through five of them right now telling you about crazy stuff I did before I joined HomeLight. So I wanted to use this specific example because I like to be specific when possible. So the team knows this. I was in the Navy, so I use really nerdy, nautical analogies that no one really understands. But what’s really interesting is when you’re in the Navy, there’s actually two places that you can drive a ship from. The first is you can be in the bridge, right up there with a little wheel. It’s not really big like you see on the Titanic. It’s actually a little wheel that’s this big. It’s super anti-climatic.

Molly Laufer:  So you can either be up there on the bridge looking out, seeing, hey, I see a ship over here off the port side, hey, I see a ship over here off the starboard side, and you can use your eyes and drive the ship, right? You can also, this is crazy, you could not have anyone on the bridge of the ship. You could all be farther down in the ship in the combat information center and using your radars to drive a ship as well.

Molly Laufer:  Now I wouldn’t necessarily recommend that because you lose that eye contact to actually see what’s out there, but the analogy that I always like to make in offline marketing, and I promise there’s a good analogy here, is that when it comes to offline marketing, we have a really tangible way to get sort of directional signal-based indication of what type of media is working better than others. I would really equate that to sort of being downstairs in the combat information center, being able to just look at what the radar is telling me and using that to make navigation decisions. You’re certainly not going to get the full picture, and there’s no substitute for actually going above deck and putting your eyes out and saying, does that ship actually look like it’s pointing in the direction that the radar says it is?

Molly Laufer:  But for us, specifically on … I use this example for TV because I think it’s really visual, but what we do here is, and this is … I wouldn’t say this is necessarily unique to HomeLight, I think this is pretty common in offline marketing, but a lot of people don’t know. We’re all sitting at home, we’re all watching TV. If you’re like me, you’ve probably seen a million e-commerce, direct to consumer companies pop up on TV over the last couple of years. And what’s really cool, and I had a stock image of it but it was kind of cheesy but I took it off, it was basically a couple sitting on the couch watching TV while also scrolling on their iPhones. Because let’s be honest, who does that with their spouse or their friend every night?

Molly Laufer:  Yes. I love that. That is an offline marketer’s dream, right? Because when they’re watching a commercial and they see something really interesting, they just start Googling it. So this is the type of signal that we get when our TV commercials air. We can start to see directionally, well what type of response do we see when we air a spot on CNN at noon? How does that compare to a spot that we air on HGTV Property Brothers at 8 p.m.?

Molly Laufer:  That’s certainly not going to give you the full picture of the impact of your media buy and I would probably need another two hours to go into that, but this is giving you some really good signal-based direction that we can use to make media optimizations. If you have a background in digital marketing, I would say this is the equivalent … this is about the closest thing that you would get to a direct click. In digital media as well as sort of some older types of advertising where you’ll see phone numbers on TV. You still see that today if you’re looking at a lot of lawyers and there’s a lot of local businesses that will really utilize phone numbers, and that’s what we use here at HomeLight.

Molly Laufer:  All right. So I’m going to pivot and just sort of close with that’s all great, but if you don’t do offline marketing, how is this actually going to be interesting for you? So I kind of took a step back and thought, all right, what do I do when I have a decision to make? I like to use all of the data. We all do. But guess what? As we’ve talked about here and as you’re going to continue to hear, the data only goes so far when it comes to making a decision. So I thought I’d kind of leave with four pieces of advice that I try to follow myself when I have a decision to make, and I don’t necessarily have all of the information that I need.

Molly Laufer:  So the first … maybe I should have put this last, but this is my favorite is building a professional or a personal board of advisors in your general role or industry that you can turn to to help when you’re facing a tough decision and you just need a little bit of outside perspective. So you certainly wouldn’t want to go to a competitor, you certainly wouldn’t want to ask a agency who’s working on a competitive product. You’re not going to maybe give them all the answers, but this has been really helpful for me and it’s events like Girl Geek, it’s events like even just talking to some of the partners that you work with. For example, at HomeLight, we do a couple of key large national sponsorships.

Molly Laufer:  And so even just reaching out to those folks and saying hey, I noticed that you also have Wayfair sponsoring. Can I talk to the person who runs offline marketing at Wayfair? Hey, I noticed that Visa’s a sponsor, too. Would it be possible for you to be put me in touch with the person who has my role at that company? More often than not, people tend to want to be helpful and give advice in areas that they have experience in, especially if it’s not competitive. So trying to build up that board of advisors wherever you go in your career, it’s always been really helpful for me to get that outside perspective from someone outside of HomeLight.

Molly Laufer:  This is interesting. So evaluating the risks and having worst case scenario planning. I’m a very positive person, but when it comes to making a decision, my mind first thing goes to what if this is the wrong decision and it completely fails? Not everyone’s like that and if you’re not, teach me your ways. But if you are and you tend to go to the worst case scenario, I like to think well, could I handle that? What would be the worst case? What would be the worst case scenario? And then what would I do about it? So when I made the decision to leave a very fast growing startup to go to an ad agency, I was really, really worried because I thought, God, this could be a career killer for me. Everyone says don’t go to agency side, you don’t get the hands-on experience, you’re going to be working crazy hours, it’s going to be crazy. They were right. They weren’t lying.

Molly Laufer:  But I said, okay, what if they were right and I’m absolutely miserable in this role? It was just the worst decision I’ve ever made. I said well, I would leave and I would find another job. I said, huh, you probably can’t do that every career move, right? If you start to do that over and over again, you just become a career hopper or a serial hopper, but I thought if that’s the worst case scenario, I could handle that. Now what I didn’t do is evaluate what would be the best case scenario and the best case scenario, to be honest, was I think what ended up happening which was I got great experience, I touched different business models, I touched different products, I got my hands on media channels that I would have never otherwise had the opportunity to work on. And now, to be honest, that’s a strategy that I use in general, personal and professional.

Molly Laufer:  This one I think is really interesting. I’m going to use an example from HomeLight which is when in doubt, let your values, whether it’s a personal decision or your company’s decision, guide what you do. If you’re ever at a turning point and it’s yes or no, you say what do my values tell me? And the example that I would use for this most recently was we recently announced a sponsorship as a title sponsor of the US ski and snowboard team, which we’re super excited about as you’ve seen probably from our conference rooms, all of our conference rooms are named for different ski resorts because one of our values here at HomeLight is work hard, ski hard. In my case, it’s work hard, mom hard. I don’t do a lot of skiing right now. The point is when we evaluated this proposal from the US ski team, we used a lot of data, we looked at what were overall CPMs, what type of response rates do we think we could get from the live and broadcast opportunities. But there was all this unknown that we weren’t quite sure about how we were going to measure or was it going to work.

Molly Laufer:  So after evaluating the worst case scenario planning and saying if we were wrong, how will this impact our bottom line, we said, let’s let our values really guide us. One of our mottos here at HomeLight is work hard, ski hard. Let’s do this. And so that has been an area where I think whether it’s in your personal life or in your career specifically, taking a minute to think about the company values, which we all have on our walls and we talk about in all hands, but when you ever need to make a decision, let the values guide you because that’s technically what values should be for is for guiding decision making, not just for putting on a wall and using it in recruitment.

Molly Laufer:  And the last thing I’ll say is trust your gut. I know I’m running over so I don’t think I’m going to give a specific example of this. Only just to say that personally, since becoming a mother in the last year and a half, I’ve realized that out of all the … you can go as evidence-based as you want on everything, but at the end of the day, there’s no one right way to be a parent, just like there’s no one right way to do your job. At the end of the day, trust your gut because it’s probably a lot better than you think it is, and have confidence in what your gut tells you. So, thanks for letting me chat.

Sandy Liao:  If anyone wants a refill on wine, feel free to do so. I’m going to do that myself, so help yourself.

Sam Ryan speaking

Product Manager Sam Ryan talks about her career journey and product management at HomeLight Girl Geek Dinner.

Sam Ryan:  Hey guys. Sorry. Apologies in advance. I’m suffering from a little bit of a cold right now. But, Molly, thank you for that inspiring talk. Hard to follow up on that. But hi, I’m Sam Ryan. I’m a Product Manager at HomeLight. Thank you all for coming here. It’s actually quite unbelievable that we’re actually hosting this event in this office. So today I’m really excited to talk to you about a little bit of my journey at HomeLight into product, and a little bit about what products and engineering looks like at HomeLight.

Sam Ryan:  So I was hired at HomeLight in 2016 by Sandy and I think I was employee number 38 at HomeLight generally and employee number four or five, I believe, in our Phoenix office. So not only was I hired at HomeLight, but this cemented my move from New York City to Scottsdale, Arizona, which I never expected. I had a very memorable first day in which I was tasked with building my desk, my IKEA desk, and hooking up my computer. But you know what? It really inspired, I think, my journey up until today.

Sam Ryan:  So I was actually hired as what they called I think at the time, Sandy, you can correct me, but I think an experimental account executive/sales person. But really my job was I talk to agents for 40 plus hours a week because those are our users, and talk to them about what they like, what they dislike, what type of problems are they facing not only within the HomeLight platform, but generally, and what we could do better to support them. I was trying to solve a problem. We would introduce highly motivated buyers and sellers to top performing real estate agents across the country, but agents did not really like the HomeLight platform, and therefore we were having a lot of trouble getting updates from them in terms of the progress that they were making with the clients that we were introducing to them. So this caused inefficiencies not only within the sales organization, but obviously company wide.

Sam Ryan: So after a few months of this, I was obviously overflowing with feedback. I would turn to all of my teammates any time we would have someone from our San Francisco office at the time visit and I would just be like, guys, we have a problem and we need to improve the product or we can’t solve the problem at hand. So I think it was a few months into my career at HomeLight as an unofficial product manager, because we didn’t have a product team at the time, I had my first release. So I worked with one of our awesome UX designers, Wally, and one of our killer engineers, Charlie, who both are still on my team today almost three years later, which is quite amazing, in redesigning the referral manager or the CRM type product that our agents use to update us on the current status and progression of the clients that we introduce to them at HomeLight. And the users loved it, which was pretty crazy.

Sam Ryan:  So I think it was really maybe a week after my year anniversary at HomeLight where I was officially moved to the product team, and I think I was employee number two. And the one thing I carried with me, or team member number two, the product team, and I think the one thing that I carried with me from working this experimental role where I talked to a lot of agents to being actual product manager was there is nothing more important to being close to your customer. However, HomeLight moves quickly. We release, and I think rapid cycles is putting it lightly, we release at a pace that’s unreal sometimes. Our team is just here for it and work so hard to do it. But, it’s really hard to use the traditional surveys and interviews, though we still do, to get rapid customer feedback.

Sam Ryan:  So I think it’s so important. I spend many hours on the Internet scouring relevant news articles, forums, threads, reading the comments on these news articles, digging into Reddit. I have spent way too many hours on the real estate subReddit, just understanding, querying every type of HomeLight query that is possibly out there and just trying to dig in to what people are talking about, not only for HomeLight but the industry in general. Trying to embody my user but I don’t have time to be a real estate agent, though I worked in the industry before in New York City. To try to understand and this is an industry where we’re constantly innovating and the tech industry’s constantly innovating and real estate agents have a thought of fear and a thought of let’s embrace this, and what are we doing. HomeLight’s here to empower them and that’s super exciting. So staying close to the user.

Sam Ryan:  Things that we do at HomeLight to kind of embrace the user and embrace their feedback and experience, but also release rapidly. I kind of gave a brief strategy and I kind of compare those and it’s funny that Molly talked about working on a ship and kind of some things there because I compared it to a rocket ignition system, which I had to caption because I kind of just Google image searched a launch button and this came up and I’m like, oh, there’s a lot of switches here and that makes sense. Because what we try to do because you have to release rapidly and we’re trying to gather all this feedback and all of these plans and just go, we have to have a lot of checks and balances in place to ensure that we’re not going to burn down the house, and we haven’t yet, which is super exciting. It’s been two years, so maybe I should knock on some wood somewhere.

Sam Ryan:  But I wanted to give you guys, I don’t know, some of the strategy that my team uses to just ensure that we can release quickly, efficiently, but also keep the user at top of mind and ensure the success of the user and ensure the success of our product. So some of the things that we’ve done; we find users who love our product generally, and users that are … this might not be the best advice, but users who might be a little bit more tech savvy than the average user, and are willing to use things until they break and are willing to struggle a little bit to provide us feedback. We have small focus beta groups that we can roll out to. We really utilize blind, human testers.

Sam Ryan: Actually, before every single deploy at HomeLight, we employ our global app testers, GAT. It’s a great product and they employ actual human testers all across the country that will go through and follow step by step directions and use your product and provide you very, very granular feedback and the test usually fail because of silly things like copy or you accidentally said next and it says, “submit.” But it does point out, I don’t know, very interesting insights about the product and things that you can improve upon, fix, or fix your instructions.

Sam Ryan:  Also, our support and sales team, so for every major release, I really encourage, generally, not only in support and sales, actually company wide, who wants to be involved in this testing process? I got this spreadsheet going, let’s go bug bash. So I really try to widely encourage company-wide involvement in those types of things, not only in forums that people who are talking about these things, but it helps me be informed about my product.

Sam Ryan:  We utilize roll outs often. Any type of risky, major feature, we really like to utilize roll-out flags so that we have that after-launch protection. So worst case scenario, again, hasn’t happened yet, but we can roll back.

Sam Ryan:  I also … In the planning stage, we implement tracking so that there are those flags that pop any time that something could go wonky even a little bit. So I really like utilizing user events, maybe a little bit too much, but I always have a dashboard the day before release that’s ready to go the second that we release and can trigger anything that could go awry at that time. Sometimes it’s triggering nothing. That’s best case scenario.

Sam Ryan:  Also, we use Sentry for error tracking, which we use for all of our staging environments as well as production and consistently monitoring that around these major releases as well. Again, around release time, I stay very close to our sales and support team. They’re generally headquartered in our Arizona office, so we just made a major app release last week, so I was there in the Arizona office literally sitting at the desk next to them. It’s like, okay guys, let’s go. What’s happening? You guys are talking on the phone. What’d they say? Have they used it? Have they used it? They’re like, we’re making them download it now. I’m like, good. Let’s call them back tomorrow. But I think that’s some of the most valuable feedback that I get, of course.

Sam Ryan:  Really encouraging direct channels of feedback, and making it not weird. You’re not bothering me. If I don’t answer you, it’s not you, it’s me. I’ll answer you eventually or maybe I won’t, but again, I really value all of it. I personally like utilizing Slack for these things, but of course not everyone loves Slack, so email, whatever. Just get in touch with me and get in touch with me two or three times if you need to. I don’t know, just encouraging that direct feedback loop. One thing my team embraces and the ping pong emoji is something that we use back and forth on Slack often. The ball is in your court. HomeLight generally really encourages ownership, not only over the products that we manage, but over the release and the success of those products. It’s not only me personally, it’s the team. So I currently oversee what we call the pro’s team, and that’s the professional experience at HomeLight that not only spans real estate agents, but other real estate professionals generally within the industry.

Sam Ryan:  So we kind of pass this emoji back and forth because if the product fails, it’s not only I failed or you failed or he failed, it’s all of us. So we really like saying the ball is in your court. Like hey, I wrote this back, but … this name tag keeps falling off. But hey, you perform again, Sam, we’re going to test together and if I miss something, it’s all of our fault. But I don’t know, we like passing the ping pong emoji back and forth. But anyway, it’s been great having you guys in our office and it’s amazing that HomeLight has grown to the size that we are at today to be able to host this type of event. And Sandy, thank you again for introducing me to the HomeLight family. It’s been a great almost three years. Thanks.

Ames Monko

Product Designer Ames Monko gives a talk on “Using Design and Empathy to Create Joyful Product Experiences” at HomeLight Girl Geek Dinner.

Ames Monko:  Hello. My name is Ames and I’m a product designer. Tonight I’m here to talk to you a little bit about how I use design and empathy to create joyful product experiences. So I was going to ask this question, but Sandy stole my thunder, about if any of you have had gone through the process of buying a home, or know a friend who has gone through it. It sucks. It’s like the worst thing. So … you can go to the next slide. And I also need to go to the next slide. Manually. It’s mine. Ugh, this is the worst. Okay.

Ames Monko:  So we all know, or if you don’t know, mortgages are a time consuming, confusing, and overall stupid daunting, bureaucratic process. Fun fact; traditional lenders don’t actually care about you or the experience that you have. Mortgages are technically, I would say, a very small percentage of their actual revenue making, they make money in tons of different ways. So they just kind of choose not to fix the process and then in turn, will just make you go through their very inundated, crappy process. Essentially they attempt to try to innovate, but by innovating, they kind of put a shiny UI on the top of the funnel, like put in your name in this and it’s so sleek and it’s modern because it’s the Internet. And then once they get you, you’re kind of just thrown back into their very clunky, not … just very cold process.

Ames Monko:  Since the subprime mortgage crisis, home buyers know they deserve a higher quality of experience and making one of the biggest financial decisions of their lives.

Ames Monko:  Oh yeah, I should put that there. So the already anxiety-provoking experience of borrowing money is currently made worse by multi-step process riddled with mortgage jargon, AKA anything you’ve ever seen from Rocket Mortgage, it’s not a rocket. It’s not. Sorry if anybody … you work at Quicken. HomeLight’s hiring. Just saying. My approach is like, what if in addition to streamlining the process … next slide. We could approach our design from a place of compassion and empathy. Throughout the past six years, I’ve worked in the mortgage tech industry with the goal of demystifying the process. I spent four years prior to being at HomeLight at Better Mortgage. I was one of the first initial employees of that whole project. It was myself, one front-end engineer, one quote unquote mortgage professional, he was just sent to go learn about mortgages, and one back-end engineer. We sat in a very small conference room in New York. In three months, we basically built what is the backbone of Better Mortgage.

Ames Monko:  So that’s when I started … my Aries brain was like, oh, this is a pretty tough problem to solve and it’s kind of holding my attention and I would never say that in a million years, like I’m really passionate about mortgages. Because talk to me eight years ago, I’ll be like, what? I don’t care about mortgages. It’s not a thing. But as an empathetic person myself, having seen people, friends of mine, family members, go through this process, I’m like, oh, maybe I can use my expertise in design and also my empathy as a human being to try to start fixing this process. Next slide.

Ames Monko: From a design perspective, to remedy any potential pitfalls and offer support when needed. My approach is you want hands on? You can have hands on. You’re tech savvy like Sandy? You don’t even have to talk to anybody. If you can figure it out? Cool. You can do it all by yourself.

Ames Monko:  These are millennials. Apparently I’m considered … I was born in 1980, which I’m apparently a millennial, but I didn’t really get the Internet until, I don’t know, I was graduating from high school, which is in 1999. I didn’t get my first cell phone until 2004, which was a cool flip phone. So the fact that … I was like, I need to find a picture of millennials and I just put these together. They look like millennials, I think. But more importantly, more than any other group, they are relying on financing for their home purchases. Many have already been confused and sort of let down by the student loan process, but nonetheless are still willing to borrow. But they expect the former archaic, home financing process to be simplified, transparent, and pleasurable? Which I don’t think we’re there yet. Next slide.

Ames Monko:  So there’s this really great article. I put a link in here and I was like, oh wait, but these people are probably not going to get the link. But Adam Grant and Erin Henkel wrote a piece for the Harvard Business Review. In it they say that the first step in empathizing with your customer is to gather insights and ask what is broken, frustrating, surprising, or uncomfortable for your customer. The second that you can train employees to put a customer first, it will dictate how you build and design a product. From a design’s perspective, fixing these problems in a visual way that makes people laugh, feel reassured, or feel like their needs are being met or anticipated is a solution that builds trust in my work, or our work.

Ames Monko:  When we take something tedious and scary and turn it into a pleasurable experience, we make the applicant feel valued. If you can give a customer the tools, they feel empowered by that. This is their most important decision and if you can help them get there by just simply adding a more confetti button, do it.

Ames Monko:  My goal has always been rooted in keeping joy at every step. People should feel excited about buying a home, not dreading it. I want them to look back and think about how great it was to buy a home, not the horror of the experience. It will definitely make meeting up with your friends less interesting because they don’t have anything to complain about and talk like, ugh, that was just like the worst thing in the whole world. So that will go away. Unfortunately, you’ll have to talk about more positive things. Next slide.

Ames Monko:  The future direction of HomeLight at the helm is one where curiosity about customers’ experience gives us a unique perspective to stay connected to them. And with all the technical difficulties, I am now done.

Sandy Liao:  Thanks, Ames. They flew all the way here from New York just to join us for the evening, so thank you so much for being here.

Jenn Luna speaking

Senior Software Engineer Jenn Luna gives a talk on “Engineering’s Software Stack and How We Power our Matching Algorithm” at HomeLight Girl Geek Dinner.

Jenn Luna: Hey, everybody. Software Engineer, introvert, so I’m going to do my best. I was really nervous to go after Ames because her slides were so beautiful and mine basically look like a 10-year-old’s book report, and not a gifted 10 year old, just a regular 10 year old. So bear with me. Okay, so these are the things that make me who I am. Software Engineer for, I think, almost 10 years now, which is absolutely crazy. I am also a real estate agent on the side. I only do it for friends and family because I don’t have time. I’m a new-ish mom. New-ish because she’s almost nine months old and time flies. I’m all these things; I’m a teammate, an employee. In my free time I like to snowboard. I have dance lessons on Wednesdays and travel is pretty much the most important thing to me sometimes, besides my daughter, of course.

Jenn Luna:  So here’s the most embarrassing picture of me that I never share with anybody. I started at Intel in 2008. I was a double E and I was hired as an electrical engineer. This is me in the sub fab. I really loved this experience because I got to go see all the robots making wafers and things like that. In the sub fab, you only wear half of the equipment, but in the fab fab, you have to put the whole bunny suit on where order matters and if you put your boots on before your hat, you have to redo the whole thing. It’s nuts.

Jenn Luna:  So after four years at Intel, I decided I wanted to jump into software, so that brought me to San Francisco, of course. I found a company called SolarCity. Anybody heard of it? Awesome. They are now Tesla, but for five years, I was at SolarCity working in the solar industry. This is me at Bay To Breakers, just fully embracing the San Francisco culture. I loved it. I ended up moving back to Arizona, but everybody goes here and then goes back somewhere else. Anyways …

Jenn Luna:  So when I started there, it was a super small team. I was in crazy startup mode. This part of my life was so exciting. It was nuts. There were just no requirements. Here’s a picture of one of my first requirements meetings with the CTO and it’s like, here’s what we want, let’s put it on a whiteboard, just spent three hours in a room and if you didn’t take good notes and you don’t build what I want, you’re fired. So this was crazy to me. This was actually my first project. And here’s another one that makes me laugh because what is this? It’s like, squares inside of octagons. I don’t even know how I completed this, but anyways. Yeah, so to make things worse, here’s our software stack. It’s just a giant monolith. We have a database and lots of codes that go to it, but no one can figure out how this thing works, right? So it’s like it was just really intense. Makes you feel like this. Super excited about a moving gif in my presentation.

Jenn Luna:  So every day felt like this, but I truly enjoyed it because I was learning so much. It made the team bond. We sat for late nights together, drinking and trying to figure things out. It was a blast. I learned so much. The point is this was the most valuable five years of my software experience. We had a huge monolith. We built it into microservices. We went from a startup to well-oiled machine. We used to use SourceSafe for source control. Does anyone know what that is? When you check out a file, it’s locked. No one else can check it out. It’s just ridiculous. I don’t know. Maybe I’m the only engineer, is that why I’m the only one that thinks that’s funny? Okay.

Jenn Luna:  So I’m going from this 10-person team on to five years of trying to build this thing out, and then eventually we have 150 people on distributed teams all over the nation. I worked remote from Arizona for three of these years, so I was coming to San Francisco every month. We didn’t have any processes. Like I said, we’d lock ourselves in rooms and then at the end of the day, we had scrum, agile, we were just knocking projects out quick. Requirements were everywhere. There was no way I could forget anything. Everywhere I looked, the requirements were there. So if I messed up, it was on me. Like I said, late-night releases. After that, we had pipelines, you’d push your changes to production, it gets pushed up to actually be released, and your stuff is out there, but not before going through massive amounts of tests. So it was way harder to mess up.

Jenn Luna:  So everything was perfect, right? Sunny days every day, and I get bored. So to quote Miley Cirus, it’s definitely the climb because I really enjoy just trying to get what was messy into something beautiful and it was so much fun and I learned so much. So here’s a quick snapshot of our software stack afterwards. It was just really nice, microservices everywhere.

Jenn Luna:  So since I became bored, I was looking for the next challenge. I had gotten my real estate license with my husband during late night classes. It was just something I was interested in. Him and I bought and sold a few properties together, so I wanted to truly understand this experience and I also didn’t want to pay commission to anybody. So it was nice to just get my license. I don’t know. Why not, you know? One of my things is I just try to do too many things, and it’ll drive me nuts, but at the same time I love it. Uh oh. Oh. Okay.

Jenn Luna:  So I joined HomeLight … back to the monolith, right? It’s seriously not this bad. But it is a monolith. We have a giant code base. Here’s a more realistic representation of our software stack. Our sales app, our HomeLight.com, all the blogs related to that, internal tools, everything’s built on top of the same code base, right? We do most things in Ember, but we’re quickly adopting React. We have Ruby on Rails backend. We use Sidekiq for all of our acing job processing, and then we utilize Redis for things like queuing, and then we use a Postgres HomeLight database.

Jenn Luna:  So HomeLight agent matching. I don’t actually work on the agent matching or the algo, but this, to me, is the core part of our business. I’m more of internal tools, sales app stuff, but because this is the most important part of our business, I wanted to talk about this so I had the engineer that works on agent matching give me the details through a fire hose a few days ago. So it’s definitely more than just swiping left or right. You’ve heard all these ladies talk about matching. We have algorithms, like Silicon Valley. That’s our secret sauce. We have four versions. These versions have over 150 data sources that power them through ETL and we have just under about 50 million transactions that are analyzed for around two million agents. So it’s a lot of data. Also a gif that moves.

Jenn Luna:  So our matching process; I’m just going to quickly talk about it because it’s very involved and very well-thought out and it works extremely well and it’s definitely our pride and joy. We take in raw data, it gets summarized, and very recently we’ve been utilizing elastic search like crazy for scaling abilities. Before this last version, before our scaling was kind of on a vertical level. There was no way we were going to be able to keep searching through all this data as it grows and be productive. It took many seconds, which is bad in software world. So for millions of agents and transactions, we needed some other solution, so that’s what V4 has done for us. Elastic search also has some really great geo-spacial search context and it leverages scoring algorithms and decay functions that basically just helps you search the data better. And then after that, we apply all the basic matching criteria that these ladies talked about, like area, buyer, seller, property details, all the basics. Sorry about that. I don’t know what that was. Yeah.

Jenn Luna:  So then after that, we geo-code the address. What we noticed is that neighborhood knowledge is very effective, so if the agent has had many transactions in an area where this house is being sold or wanting to be bought, we will boost those agents because neighborhood knowledge is just very effective with people. It helps them, they feel more comfortable, and I don’t know, you just kind of know things that maybe you wouldn’t have known if you are just diving into that neighborhood. Then we analyze these agent metrics, we rank the agents, these are based on things like number of transactions, how long it takes them to close a house, just a bunch of stuff like that. And then at the very end, we will apply agent preferences because it’s a two-way street and agents should have preferences. So if they want only sellers with blue hair, hashtag picky agents … so we should also let them choose what they want so that it’s a two-way match. I was going to put a picture of people with a heart but that’s too personal I think.

Jenn Luna:  So lastly, performance is key for our data processing because we have millions of agents in our database, we definitely need to keep scaling correctly. So this Version4 that we have has brought our searching from eight to 15 seconds or so down to under a second, which is pretty incredible. So they can just keep scaling horizontally and it’s going to be totally fine. And elastic search … I think I already said this, I’m going to skip that. And then also, we are constantly refreshing this data every month. We don’t want any stale data. We don’t want agents to be picked up that have retired or don’t have any transactions in the last few months or anything like that. So we make sure that it’s meaningful. Then lastly, we do very slow roll-outs. We will roll something out, see what the results are basically in terms of conversion rate, so if something’s working really well, we’ll keep it but we’ll finally tune these algorithms and then once we have something that we think is working the best for us, we roll it out nationwide.

Jenn Luna:  So that’s it for me. Thank you, guys.

Tina Sellards speaking

Facilities and Administration Manager Tina Sellards gives a talk on “Connecting Data and Technology to the Human Experience” at HomeLight Girl Geek Dinner.

Tina Sellards:  Thanks, Jenn. Hi, guys. We are going to have a dessert bar in the back. You are welcome to grab some now if you like. It’s cookie dough, but definitely something to stick around for.

Tina Sellards:  So a little less on the technical side for me as the Facilities Manager, I’m sure you can imagine. My name is Tina Sellards. I am the Facilities Manager here at HomeLight. That is definitely not all that it encompasses my job. As many people know in a startup, I am an administrative assistant to our CEO, I do a lot of our licensing on our brokerage side and really kind of jumping into our title marketplace side as well, but then also this space that you see here, the food that you’re eating today, all of that stuff is definitely me. Thank you. So the human side is pretty huge to me, as you can imagine.

Tina Sellards:  A little background for you on me. I went straight out of college, graduating from the University of Central Florida, very proud of that, UCF, go Knights. And then went into AmeriCorps right out of that. Really had that if not us, then who, if not now, then when mentality when I came out of school, and was ready to change the world. Learned a lot about government and what kind of bogs down that world as well as I went into that, and decided I wanted to really jump into changing that world as well from the inside and was lucky enough to join the ’08 Obama campaign. Really that network that you build, so huge, your tribe, the people that I met, my AmeriCorps experience helped me bridge that changeover into my work on the Obama campaign in ’08. I ran a region of Florida for them. Everything from getting the volunteers in the door, staffing, getting an office, doing all of those things with no money, really, on that side of things. So super interesting.

Tina Sellards:  But something that was really interesting to me on that ’08 Obama campaign was the data, honestly, and the technology that was being used. This chart right here is from the Pew Research Center. It was really the first campaign that was using Internet as a main source of information for people. As you can see here, from 1996 all the way through 2008, among adult users, Internet usage for your political information went up significantly and they were utilizing a … I don’t know if you all are on it, a service called MyBarackObama.com. MyBarackObama.com actually was a community-based system. They had over 35,000 groups that organized 200,000 events throughout the US to get him elected. In some great foresight, decided to keep that live and use that as a community organization tool throughout his administration and then into the next campaign, which was actually pretty amazing. And then I also noticed something as I was looking at this research, too, which was very interesting to me which was how voters communicated about the campaign. Look at that Twitter down there. In 2008, only one person said they used Twitter to communicate. So just want to let that sit in a little bit as we kind of think about that. On the Twitter side of things, I think we’ve come a long way.

Tina Sellards:  And come into the 2016 campaign. And I make this transition really to talk about Twitter, Facebook, Google, all of those things as we’re using and the data that we’re using, the technology that we’re using, and does it really connect us more. Does it do those things? Do you get the information? Is that the correct information? Are you getting to connect with people in the same group as you, those kinds of things. It was really important to me as I kind of came off of that campaign and started to move into a more kind of people-role in organizations that I was doing, how do we, as a group, as a community, really build that interaction and not silo ourselves into those easy data groups or easy breakup groups that we can kind of put ourselves in. I think one thing that just kind of zoomed in for me was fear. Fear is really kind of a driving factor, right? And why we allow ourselves to be siloed into some of these groups. A fear of maybe that big tech company to breakup your industry, or a fear of the unknown of a different group of people or community than you. Unfortunately, fear really can kind of drive some of these things and I think that’s kind of where we’ve come with some of the data and technology. How do we get away from that is the next question.

Tina Sellards:  I think, and I very much subscribe to Brene Brown. I don’t know if any of you ever listened to Brene Brown or any of that, but vulnerability is how we do that, and leadership with vulnerability is a really key point in the human connection. I think we can really hurt ourselves and break ourselves up by just kind of communicating with the groups that we know and doing the things that we always know. Being vulnerable and letting ourselves be open to that information and being open to other people’s experiences is really how we build these communities and I think something here that I really appreciate about HomeLight and just bringing it together is a core value for us, and it’s not only a core value, it’s something we really live is being a part of our family and really being that open, unique kind of environment. I think it’s super important because I don’t think we’re going to conquer these fears and these issues that we have as a larger society if we don’t start opening up to that and really starting to have those conversations as a group.

Tina Sellards:  So I just wanted to share a little bit about my experience on that and data, and the human connect and hope you all stay vulnerable, open, and communicate as a whole community together, because that’s important in building communities like HomeLight and other … Girl Geek, and things of that nature. Keep those communities open. Be vulnerable.

Vanessa Brockway speaking

Senior Manager of Business Development & Strategy Vanessa Brockway gives a talk on “Data & Emotion in Making Career Decisions” at HomeLight Girl Geek Dinner.

Vanessa Brockway:  Hey, everybody. Vanessa Brockway. I’m on the business development team here at HomeLight, and that means a bunch of different things, but we won’t get into that today. So one thing’s we’re asked about, things we’re passionate about. So in my spare time, love to travel and I love to do interior design. But the thing I’m going to talk about today is using data and emotion and making career decisions. I think that’s probably a common thread among everybody. Often times people are drawn to events like this when they’re thinking about the next move or what they should do next. I’m going to share a bit about my perspective on this and then how that led me to HomeLight.

Vanessa Brockway:  So I think careers are a lot like The Game of Life where it’s not just kind of this up and to the right or corporate ladder, there’s a lot of twists and turns, unexpected events. You kind of sometimes are accelerating, sometimes you’re in cruise control and you can’t always predict everything that’s going to be coming your way. And so when thinking about how to approach your career and how to plan for it or how to decide what the next step is evaluating your life as a whole and the things that kind of get you going and what motivates you. As the qualitative aspects, it’s the emotion to drive the data that will also influence this.

Vanessa Brockway:  So I put some images up here, but do you love to travel? Do you want to be on the go? Is exploring the world something that motivates you? Or is being close to home and being able to have a more flexible location where you are, is that something that’s important in your life that time? How do you define success? Is being on the cover of Forbes or making a 30 under 30 list? Is that what’s going to make you feel valuable and that you’ve done something? Or is it building a passion project or building a company of something that’s really meaningful to you. Is that how you’re going to define success? What is the environment that you want to be at all day? Is it a big company with lots of people, huge market presence? Does that get you going? Or is it smaller office, more intimate relationships with those people that you work with? What is it that you want to be surrounded by everyday? Kind of taking that step back, evaluating what makes you feel motivated as a person, and then turning that into data elements to actually help drive a decision.

Vanessa Brockway: So in thinking about an actual company or industry, and evaluating what is the actual size of a company that’s interesting to me? Where do you want to live? What are the demands of that? And how can you take what you’ve learned about yourself by reflecting and actually put that into specific data? So these are just a couple of examples of … LinkedIn, you can actually see the size and growth trajectory of a company. Where are the locations of their offices? GlassDoor; how do employees feel about that company that you’re looking at? What are the employee sentiment and benefits, and things that people get? Crunchbase; do you want to be potentially at a startup? How do you actually quantify what that looks like in terms of amount of fundraising that’s happened? Who are the investors? And also just looking at articles about that company and being able to gather what is the industry saying about the industry as a whole, but also that company in particular.

Vanessa Brockway:  And then this is another piece. So separate from the company as you’re evaluating company, evaluating the role. So I found this comic online. I thought it was pretty funny. “I’ve always wondered why you decided to be a dog. I was fooled by the job description.” So don’t take a job description at face value. Take a step back and look at okay, what is this job within the company? What does that team look like? Is this going to be a very specific role where you’re going to be a ,subject matter expert, or is this going to be an all around athlete where you’re going to be asked to wear a number of different hats? What does the hiring plan look like? Is this company on a very, super fast growth trajectory and then it’s soon going to change? Or are we kind of more in a steady state? What is the title? Is that something that resonates with me? The comp, the benefits, does this company have cultural values that I identify with? And really looking at the specific role and breaking that down to specific data points that you can then tie back to how you evaluated yourself and looked at what motivated you and what was exciting for you.

Vanessa Brockway:  So my personal story is I started off at a pre-seed stage company, which was Stitch Fix at the time. We were under 10 people, no funding, very different but it’s my first taste of startup life. I absolutely loved it. And then I’ve also spent time at publicly traded large companies like Shutterfly where you’re working towards quarterly earnings, your massive, massive companies. And also Haus, which was a company I worked before here and it was every step of the way, I got a different kind of slice and flavor of tech companies at different growth points in their trajectory. The way I ended up at HomeLight is I realized this was the exact point in time, the type of company that I wanted to be at. I’ll walk through some of those pieces about it of how I made my decision.

Vanessa Brockway:  So for particularly looking at the growth stage of the company, for LinkedIn down in the bottom left. When I joined HomeLight about a year and a half ago, Series B, solid funding, had a runway that was very, very strong, but at the same time, this office sells under 50 people, so you’re able to do a number of different things and step into a bunch of different roles, which is something I really thrive in and really love. In terms of GlassDoor, so people loved working here. That was a huge check mark. Being able to see that the employees that were there go in everyday and working there. The real estate industry, something I’ve always been interested in. As I mentioned, I loved interior design but it’s not something I knew a lot about, so researching, seeing how the industry was talking about HomeLight, how they were talking about prop tech companies. Things like that really just help inform the decision. And on Crunchbase, looking and okay, who are the investors that are actually investing in this company? Actually reaching out and speaking to some of them, like hey, why’d you invest in this company? What do you think about it?

Vanessa Brockway:  All those data points together help to make sure that the position you’re looking at, the company you’re looking at align with what’s important to you, but then also is setting you up for a successful position after you join. Yeah, that’s what I have to say.

Sandy Liao:  By the way, when I saw Vanessa put all the slides, you actually really did a data analysis of HomeLight because she screen-shotted all those images before because nowadays, if you search HomeLight, our ratings, our LinkedIn, everything is different so you’ve actually done all those research prior to you joining and saved it in a document. That’s why you’re able to pull it into your presentation, which I’m like super impressive. It’s also unprompted. It’s impressive to know that someone actually did the work as much as Vanessa did to know, to identify HomeLight as a great place to be before she accepted the offer. So we’re great to have you and thank you for sharing that experience with us.

Sandy Liao:  I’m going to be closing up here before the end of the night and I quickly just want to give everyone here a huge thank you for sticking around again. But nevertheless, I want to give everyone here on the panel a huge round of applause please. While we were going through the preparation for the night, all of us were giving each other ideas, what we’re going to do, what are we going to do. None of us have a full-time job of public speaking and we watch all these tech talk preparation, we’re like, oh my God, we need to find some sort of inspirational speech for all of you guys to take away. But I think that the big piece from all of us speaking here is that our takeaway is we’re all just going through the same thing in different stages and different environments, but hey, we’re all trying to be here to make something work and to see what some of our potential could be. So I appreciate all of you here that’s on the panel tonight to take this time to challenge yourself to make yourself uncomfortably, becoming more and more comfortable sharing your stories and supporting from one another.

Sandy Liao:  So I’m going to quickly here, I’m going to promise to go through this really fast. But I just thought that while we tie in a lot of data and motions and talking about HomeLight, utilizing data to support our consumers, to really find the agent, and going through different marketing channels and career decisions. I think that it’s very important for everyone here who are looking into new career changes to understand what it means internally on a data perspective and what are some of the data metrics that I am looking into and that we are doing here at HomeLight as well.

Sandy Liao:  So anyone here heard the term people analytics? Great. We got a few hands. So this is just like a dictionary definition that I found online. I don’t even know if this accurate one, but it sounds pretty accurate, but people analytics is the use of data and data analysis techniques to understand, improve, and optimize the people side of the business. So analytics is become this huge buzzword, everyone’s talking about it, whatever role you’re in, what is your data, how do you measure your success and all that fun stuff. We also are doing that on the people side. But what’s really important is that we want to start to be able to create data that’s useful and not just creating data for the sake of it, but we want to create something that’s actually meaningful for everybody and for all the business decisions.

Sandy Liao:  So I’m going to share here on the four strategic imperatives for people analytics and especially for a company our stage, right? We can’t compare ourselves to companies like Google, Facebook who has kept millions and millions of data everyday that they can spend time on analyzing it. But what do we do when we’re only about less than 200 employees, we’re in about five different locations, locally, and what do we do with the analytics and the datas that we have?

Sandy Liao:  So first it is essential for us to set alignment. What it means is that alignment, not just between our employees, but making sure that our leadership, our executives are also aligned with all the decisions that we want to make. So from the people side, we want to say, hey, we want to start having educate more, development opportunities, more events like this, but if leadership is not understanding the purpose of it and that we’re not aligned, these things will not happen. So in the very beginning, it’s just essential for finance, for the VP of finance and our CEO and executives to understand what are some of the goals that we’re trying to make on the business side. Example would be what is the revenue we’re trying to achieve for the year? What are some of the headcount goals that we have? Because without knowing the essential of our business goals, as much as I want to say, hey, people first, people first, but we also need to make sure that we’re going to be able to secure ourselves financially well. So setting that alignment from the very beginning is just very crucial for this stage.

Sandy Liao:  And the second piece I want to talk about here is actually developing a data-driven culture. So this is unprompted, we’re not sponsored by this particular company, but at HomeLight, we use an anonymous feedback tool called TinyPolls. What it means is that every week this software will prompt us to ask all of our employees one question. The question could be how are you doing today to a question like this: in your current job, what is the number one thing that inspires you and that makes you happy here and want to work harder?

Sandy Liao:  So this TinyPoll’s feedback was actually created when we started all of our different offices in different countries, right? Have you heard a couple of us spoke, they started in Phoenix, we’re in San Francisco, we now have New York. How do we still gather data from our employee on the regular basis and be able to have that transparent communication between leadership team and everyone individually? I was fortunate enough to come across this platform who serves just that. We just want people to give candid feedback without being feeling like they’re going to be punished or be in trouble if they were to share anything on how they feel. So this feedback tool, we’ve actually implemented for over two years. It’s actually been working very well internally. With this data, we’re able to understand how people are feeling for whatever location you are and also be able to make decisions and programs that’s actually going to surface the direct feedback from everybody internally.

Sandy Liao:  Simultaneously, outside of the anonymous feedback loop, we also want to incorporate our performance data. What it means is that for us as a company, we started doing performance review on an annual basis, and then we also do a year-end check in, but these are not just data that you want to have between you and your manager, but we want to have 360 reviews that we get feedback from all of our peers as well. As much this is an important data between you and your manager, it is also really important for the business because we want to understand, hey, even if it’s not measurable bullet point percentage that we’re looking at, at least on a regular, quarterly basis that you are speaking with your manager to talk about, hey, I want to be able to achieve these five goals for the quarter and are you able to do that. At the end of the quarter, you guys should be sitting down, looking back at all the goals that you have set initially and if you find out that, hey, I’ve able to achieve three out of those five goals, what can the company provide you with, what type of training, or what are some of the resources for you to be able to hit the two bullet points in order for you to fulfill all of the achievement and goals that you had set initially?

Sandy Liao:  So incorporating performance data is just crucial to the business, as well as yourself. So for any of you guys sitting here, if your manager has not spoken with you over the past quarter or past six months about how you’re doing from a performance standpoint, it’s just super, super important to hold that in your hands and make that calendar invite, and make them have that conversation, right? Because especially working in a startup, these things kind of get out of hand when we’re trying to do hundred things at once, but before any of us sitting here analyzing whether or not we’re excited to look for new opportunity or what not, it is just necessary to take that step to have that conversation with people that is mentoring you and that are working with you directly.

Sandy Liao:  And last piece here, I want to incorporate a little fun before we end the night here, but collecting data is actually huge, right? So as I was interpreting how people analytics is becoming this huge thing, we, as a company, can’t share that we have a whole lot of data on the hiring side because so many of our roles are actually brand new to the company. So we have never hire a data scientist before and we are trying to hire that, so we’re trying to get data as we are developing these new roles and so forth. But a really fun data I’m sharing here today. This is actually a real, process, a number that we have from us hiring our most recent female engineer, Raquel, who’s actually here today. She flew in for this wonderful event. And we have actually sourced 448 female engineers around the country to get 26 recruiters screens. Can you imagine us just playing people, I’m sure a lot of you guys gone through this. Throughout those 24 screens, only seven of them made it through the hiring manager call. With the seven hiring manager, only four people actually got to the assessment stage. So out of the seven calls, only four of them were approved by the manger. With the four assessment, we got three on-site and ultimately we found Raquel here today.

Sandy Liao:  So these are the example of data and this is actually one that’s a fairly good example. We have some ridiculous roles that we have opened for a long time and it’s the sourcing number even bigger, but the point is in order for us to make tangible and actionable items based on data, we need to start collecting them regularly, whether it’s phone screens or whatever sourcing number it is, it’s just very crucial to do that.

Sandy Liao:  So the actionable item here, why there’s a dog. This is actually my dog. His name is Cooper. I rescued him about a year and a half ago. This is a significant picture for him because that was the day he got all his shots and he was straight legal to take on the action. He was ready to go. And since then, he’s been a wild, wild dog and I bring him around here once a while and everyone can share that experience with that. But that’s it for me. I hope this was helpful for everybody. We are a little … we ran a little later than expected, but we’re all going to be here hanging out, eating some desserts. We have wine and you guys are all welcome to just hang out and if you have any questions for us, we’re happy to answer them. So thank you so much for coming.


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Girl Geek X Xilinx Lightning Talks & Panel (Video + Transcript)

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Jayashree Rangarajan,  Lori Pouquette, Jennifer Wong, Ambs Kesavan

Xilinx girl geeks: Jayashree Rangarajan, Lori Pouquette, Jennifer Wong and Ambs Kesavan discuss the latest trends in accelerating computation for real-time machine learning at Xilinx Girl Geek Dinner in San Jose, California.

Speakers:
Eva Condron-Wells / Senior Manager of Talent Development / Xilinx
Niyati Shah / Senior Software Engineer / Xilinx
Changyi Su / Staff Design Engineer / Xilinx
Uma Madhugiri Dayananda / Senior Software Engineer / Xilinx
Tom Wurtz / Senior Director, Documentation & Program Management / Xilinx
Ambs Kesavan / Senior Director, Software Infrastructure Engineering & DevOps / Xilinx
Lori Pouquette / VP, Global Customer Operations / Xilinx
Jayashree Rangarajan / Senior Director, Software Development / Xilinx
Jennifer Wong / VP, FPGA Product Development / Xilinx
Angie Chang / CEO & Founder / Girl Geek X

Transcript of Xilinx Girl Geek Dinner – Lightning Talks & Panel:

Angie Chang: Okay. Here I go. Hi, thanks to you all for coming to Xilinx. My name is Angie Chang and I’m the founder of Girl Geek X. How many of you here, it’s your first Girl Geek Dinner? Okay. A good amount. All right, so Girl Geeks Dinners have been happening up and down the San Francisco Bay Area for the last 10 years. About every week, we’re in a different company. And I’m really excited to be here tonight at Xilinx.

Angie Chang: Personally, I was really excited when I looked up the website and I was like “I can’t wait to come here, check out the technology”. And the demos have been really awesome, and I encourage you to hangout and look at them. And walking down that hall of patents is very inspiring. And of course the food was amazing.

Angie Chang: So, thank you to everyone for coming. One thing I want to encourage everyone who comes to Girl Geek Dinner is to network. And I know that’s a kind of scary term, we’re always told to network. But one thing that I always try to do, even as an introvert, is to meet people. At least one or two people over a dinner, when you guys are chewing your food, just talk to people, ask them what they’re doing, if there’s anything you could do for them, and if there’s anything they could do for you. Because people are often looking for new opportunities, they’re looking to learn about the technology and also just to make friends.

Angie Chang: ‘Cause when you have friends in your workplace, or in your industry, that’s how we can stay in tech. We all know that women are dropping out of the workforce over time, and that’s really why we continue to do these dinners, is to encourage woman to continue coming out, meeting each other, encourage each other, and helping each other stay leaning in or whatever you like to call it, to your career.

Angie Chang: So please enjoy yourselves, and thank you again, Xilinx, for hosting.

Eva Condron-Wells speaking

Senior Manager of Talent Development Eva Condron-Wells welcomes the crowd to Xilinx Girl Geek Dinner in San Jose, California.

Eva Condron-Wells: Wonderful, thank you so much, Angie.

Eva Condron-Wells: So welcome to Xilinx. My name is Eva Condron-Wells and am a senior manager in human resources. I have the pleasure of helping employees at Xilinx listen, give, and feel as though they belong.

Eva Condron-Wells: I’m a social scientist by background, and I grew up in this very specific niche of the semiconductor industry, at another well known company. Most of my career has been in this particular slice of the semiconductor industry. And I think, in this moment, I just want to reflect on the fact that we have many things to be grateful for. And I want to start this evening with thanking a number of people.

Eva Condron-Wells: So first and foremost, thank you to the Girl Geek team for creating this type of forum for us to connect. So thank you so much, Girl Geek. Thank you to our Xilinx greeters, gurus, and guides. I hope that they’re making your visit meaningful. If you haven’t already seen other aspects of our campus, we welcome you to join us in the demo room later on. And, of course our guests, right? So you took time out of your day to come meet us, we know that you work hard and we’re all different types of Girl Geeks, but regardless of that difference, we’re here together to celebrate that brilliance of who you are and share who we are. So thank you for taking time out of your busy days to join us.

Eva Condron-Wells: And speaking of Xilinx, how many of you knew what Xilinx is or does before you saw the Girl Geek invitation? Raise your hands.

Eva Condron-Wells: Wow, that’s pretty impressive. You must be in fairly technical households. Because Xilinx, sometimes called X-links, but we help people understand how to pronounce it, isn’t necessarily a household name. That said, we affect the lives of people everyday. As we’re nested in technology that’s used broadly around the world, affecting everyone’s lives.

Eva Condron-Wells: Xilinx is a 35 year old company. Founded, what I like to say, on friendship. It was founded on friendship and a very incredible idea that is continuing to create many innovations, now and in the future. Our mission is to build the adaptable intelligent world. We have 4,000 employees plus, worldwide, and 4,000 plus patents. Giving us a one-to-one ratio of people to patents.

Eva Condron-Wells: When I articulate the pride I have in where I work, and who I work with, I genuinely mean we have some of the most brilliant people in the world. And you will get to hear from some of them tonight.

Eva Condron-Wells: So we invented the field programmable gate array. Not something everyone hears everyday, but this is a device that makes the life of an engineer easier. It speeds up their ability to perform their responsibilities and have chips work in various ways, right, thousands of applications can be used. But these engineers are empowered to reprogram chips in the field in hours instead of waiting weeks to get a completely new product. So this is the power of what we were founded on, the concept of enablement, empowerment, and acceleration.

Eva Condron-Wells: We have over 60 industry firsts, and our latest product, Alvio… Which is absolutely gorgeous, and is in our demo room, you can see the board… Is plugged into data centers, giving a 90x acceleration over a CPU. This nested technology is inside of thousands of products, changing the way we live, love, work, and play.

Eva Condron-Wells: We are not only diverse in our thought, that creates this technology, we are seekers of innovation, and we welcome brilliant minds who want to play in this space as well.

Eva Condron-Wells: Tonight our focus is on acceleration. You will gain insights into acceleration by the people who enable it. We will have three lightning talks, a panel, and Q&A where we look forward to hearing your questions to dive a little bit deeper into this topic. After 8 pm, we’ll transition to desert for those of you who haven’t already taken advantage of that. Some more demos, just around the corner, and some more networking.

Eva Condron-Wells: This is a very special evening for us, and we’re thrilled to have you. Now onto acceleration. Let’s let the lightning talks being. May I have our first presenter? So please welcome one of our first of three presenters, Niyati Shah. Thank you so much, Niyati.

Niyati Shah speaking

Senior Software Engineer Niyati Shah gives a talk on compilers for adaptable compute acceleration at Xilinx Girl Geek Dinner.

Niyati Shah: Good evening, everyone. So let me begin my introducing myself. My name is Niyati and I work in the logic optimization group. I primarily focus on software architecture and [inaudible] design. Outside of work, I enjoy weightlifting, and traveling, and doing what I love, both at work and outside is what makes me a girl geek.

Niyati Shah: So let me start by asking you all a question. How many of you here are hardware engineers? Brilliant. And how many are software engineers? Perfect.

Niyati Shah: So, as we can see right in this room, we have a range of distribution of engineers from hardware background and software background. And that, I believe, presents the direction in which Xilinx has been headed. Traditionally Xilinx is a semiconductor and FPG chip company, and most of our customers used to be hardware developers. But as we are moved into the data center and acceleration markets, more of our customers are coming from software backgrounds.

Niyati Shah: And, what I’d like to do today, is give you an overview of the tools that we have that help our developers, regardless of their background, use our FPS to run their designs.

Niyati Shah: So we have the Hardware Developers who code using RTL, Verilog, VHDL. And for them, we have our signature product, which is the Vivado Design Suite. Next we have our Hardware Aware System Software Developers, who use C/C++ and SystemC. And for them, we provide them the Vivado HLS Compiler. We also have our Software Application Developers, who tend to use FPS mostly for accelerating their products or their designs. And for them, we have the SDAccel environment. And finally, for our Data Scientists who use frameworks such Caffe and TensorFlow, we have the AI Compilers or Edge Compilers.

Niyati Shah: In the next few slides, I’m going to go into a little bit more detail onto each of these different tools, so that you can get an idea of how they meet the needs of the targeted developers.

Niyati Shah: So as I mentioned, most of our hardware engineers work with RTL, Verilog, VHDL. But their figure is a piece of hardware, and it’s only going to understand binary numbers or bitstream. And so we have to take the RTL through a process to generate that bitstream. And the best analogy that I could give is kind of a translator. So, if you and your neighbor were to speak in, say, different languages, and the translator will go from your language and convert it to a language that your neighbor can understand. And so we take the RTL through a similar process. We start with synthesis. But [inaudible] the RTL, we apply synthesis. And the job of synthesis is to create a logical netlist , which is technology mapped to the targeted FPGA.

Niyati Shah: Once that is complete, then we need to optimize the netlist. And that’s where I come in. My team and I work on optimizing the logical netlist. We’ve optimized the design for power, area, timing, depending on the developer need. And finally create an optimized netlist, which will better use the resources that are on the FPGA.

Niyati Shah: Once that part is complete, we run placement. And the placement essentially takes these logical blocks here, and puts them on physical locations on the FPGA. Finally, we have the router which connects those physical blocks together. And after placement and routing are complete, we have a bitstream that we load on the FPGA to run the design.

Niyati Shah: Now, instead of starting an RTL, if our developers were to start with say, C/C++ or SystemC, then an additional step gets added because we have to first convert those languages to RTL before they can be fed into the backend tools.

Niyati Shah: And that’s where our Vivado HLS Compiler steps in. The HLS Compiler provides an eclipse ID, and allows our customers to design and develop using our product… The Vivado HLS Compiler and be part of this setting on top of the Vivado Design Suite. So, once the C/C++ is converted into RTL then we feed it into the Vivado Design Suite and generate a bitstream. And that allows us to provide a comprehensive solution for people starting with C/C++ or SystemC.

Niyati Shah: Now so far the tools I have talked about address the needs of our hardware developers. But for our software application developers, we also have a tool, which is our SDAccel Environment. The SDAccel Environment and Compiler sits on top of the existing Vivado HLS Compiler and the Vivado Design Suite, and allow users with no FPGA background, no hardware expertise, to take their designs and run them on our FPGAs. They will also allow us to support heterogeneous applications. So most of our software application developers are trying to accelerate their designs using the FPGAs. And so the designs will have a software component and they will have a hardware component. And the best example I can give you, is that of computer vision.

Niyati Shah: So I’m sure some of you have security cameras at home. And, in that case, you know that there are multiple parts to that. There is recording live video, but there is also object detection, where it will tell you there’s your dog is running around outside, or say there’s a robber in your house. And in that case, the object detection part is what gets accelerated using hardware.

Niyati Shah: The SDAccel Environment provides multiple different tools to our customers. We have a debugger, profiler, libraries ranging all the the way from low level mat libraries to high performing DSP libraries, but the star of the show is the compiler. The compiler helps us provide a comprehensive solution for both the software parts and for the hardware parts. The compiler compiles the software part so that it can be ran on the x86 machine. And it compiles all the individual hardware components, the kernels, so that they can go onto the FPGA. The kernels are compiled using the xocc compiler, which internally leverages the Vivado HLS Compiler and the Vivado Design Suite to generate bitstream for the parts that need to be accelerated.

Niyati Shah: So once the compilation is complete, then the software part will run on the [inaudible] machine, whereas the hardware part, which are the kernels, will run on the FPGA and they will communicate with used each of their using Xilinx runtime tools.

Niyati Shah: Now this SDAccel Environment and compilers are very crucial and critical building blocks in our next set of compilers, which are aimed towards our data scientists, who provide us models and frameworks such as Caffe and TensorFlow.

Niyati Shah: Our AI Compilers… The object here is to take the models that the customers have provided and optimize them with Deep Neural Network pruning and quantization, so that we can get optimized models. And these optimized models are then targeted using our SDAccel Compiler, so that they can go into the FPGA and generate a bitstream. Finally, we have our SDI Compilers, which provides bitten interfaces. And so we can integrate very easily with the Caffe and TensorFlow families.

Niyati Shah: What I would like to leave you with is that regardless of your background, whether it be software, hardware, or anything between, we at Xilinx have a tool that will allow you to take your design and run it on our FPGAs easily and efficiently. Thank you.

Eva Condron-Wells: Thank you. Our next presenter is Changyi Su.

Changyi Su speaking

Staff Design Engineer Changyi Su gives a talk on machine learning platforms at Xiliinx Girl Geek Dinner.

Changyi Su: Thank you for your introduction. My name is Changyi Su. I’m a design engineer from the device power and signaling technology team. My job is focusing on memory interface, timing analysis, and where a [inaudible].

Changyi Su: So today, I will go over one aspect of machine learning, the memory. So I will explain why memory is one of the enabler for machine learning and how Xilinx can be part of the solutions.

Changyi Su: We know that deep learning is one of the many approaches of machine learning, which try to simulate the human brain working with neurons. The neural network has a layered structure, each of the layers, the dot, simulate the neuron. The line between the nodes is a wait. So all the neuron network does is a computation. To compute the output of each of the node by multiplying the wait and the each of the input nodes, and then plug into the activation function. So as shown in this figure, compared to other machine learning algorithms, deep learning algorithms scale up much better with small data. Therefore, the performance of deep learning algorithm is limited by the need for a better hardware acceleration for scaling up data size and algorithm size.

Changyi Su: Recently, FPGA become a very strong competitor to GPUs, to serve as well based accelerator for machine learning. So with a programmable, flexible, how well configuration FPGA often provide better performance per watt to GPUs. Xilinx FPGAs support many types of memory technologies, either internal or external to the device. Compared to the off-chip memory, the on-chip memory has lower latency, lower power consumption, but a higher data bandwidth. FPGA devices offer the industrial leading 500 megabit on-chip memory storage space. So this allow the users to create on-chip memory of real size to suit their applications and also eliminate some of the external components. However, the on-chip memory is very expensive, and hard to expand the capacity. Therefore, the hardware accelerators still have to depend the external memory to meet the storage requirement for machine learning. And also the bandwidth of the off-chip memory is a bottleneck.

Changyi Su: So, with Xilinx’s devices, engineers are able to optimize the memory solution for different applications. For example, for machine learning, the intermediate data… Activation data is usually stored in on-chip memory, to reduce the data movement between the processor and the off-chip memory. The HBM and DDR can be used to store the input data in a right [inaudible], the way to write a parameters.

Changyi Su: So, when we’re working on the memory solution, one big challenge is the trade off between the memory and the computer resources, to achieve the best performance with the lowest latency and lowest power consumption. So, this is a most amazing part of my job in Xilinx. And this makes me a Girl Geek.

Changyi Su: As I mentioned in the previous slide, due to the capacity limitation on-chip memory, how the accelerator still have to rely on external memory to provide the massive storage for machine learning. So over the years, the DRAM Chip density is scaling up. Therefore, the DDR memory capacity upgrade is one of the easiest way to immediately improve the system performance. So we can increase the memory density by using high density DRAM chips, or multiple die package of DRAM chips. Also, the dual in-line memory model–DIMM–is very effective to increase memory capacity with minimum PCP space. So also, DIMM is a model which can turn several DRAM chips on one side or both side of a small circuit board. DIMM can be also config to a multiple RAM configuration to further increase memory capacity. However, with multiple loading, the signal integrity of the memory channel is severely degraded. So the entire system may not operate reliably at higher data rates. Fortunately, most of this can be solved by optimizing the channel configuration with the efforts and expertise from memory design system engineers.

Changyi Su: Over the past 10 years, the DDR memory data bandwidth capability did not evolve quickly enough to keep pace with the bandwidth demanding from applications such as machine learning, video transcoding. So to bridge the bandwidth gap, Xilinx introduce high bandwidth memory, HBM. HBM take advantage of circuit stacking technology that puts FPGA, DRAM, side by side in the same package. So, the whole package DRAM structure together with one thousand data bandwidth, HBM not only can provide extra more storage space, but also enable terabyte per second data bandwidth. So with HBM enabled FPGA devices, fewer DDR components are needed. For some extreme case, like this example, without any external memory components, Xilinx’s HBM solution can provide the same capacity, but much higher data bandwidth, and the better power efficiency.

Changyi Su: So the takeaway of my presentation today is evolving machine learning workloads demand varying bandwidth requirements. Xilinx’s diverse memory technologies enable it. Thank you.

Eva Condron-Wells: Thank you Changyi. And our next speaker and final lightening talk presenter is Uma Madhugiri Dayananda.

Uma Madhugiri Dayananda speaking

Senior Software Engineer Uma Madhugiri Dayananda gives a talk on real time video transcoding at Xilinx Girl Geek Dinner.

Uma Madhugiri Dayananda: Hello, everyone. Today we’re going to explore how real time transcoding can be accelerated on FPGA in the context of data center. Can you guys take a guess on what kinds of media applications these are?

Uma Madhugiri Dayananda: Sorry?

Audience Member: Facebook.

Uma Madhugiri Dayananda: Yeah. Any others?

Uma Madhugiri Dayananda: So, that’s Facebook Live and Twitch Live Streaming, that’s used for gaming.

Uma Madhugiri Dayananda: And, it’s just not these two applications, you also have YouTube Live, and LinkedIn just announced their live streaming application this couple of weeks ago. And it’s not just limited to these applications, live video is just everywhere and it’s growing rapidly.

Uma Madhugiri Dayananda: What’s happening behind these live videos? We have a huge distribution of clients here for example, our cellphones, the tablets, the PC, the TVs, are connected all via wireless networks and each of them have their own resolution and network characteristics. And we want to download the live video to each of these clients, so… To download the live video to each of these clients, the live video input is pre-encoded with the HEVC Encoder, at a different resolution and a bitrate of… And using video transcoding. So, essentially video transcoding is the conversion of one video encoding format into another.

Uma Madhugiri Dayananda: What is the advantage of video transcoding? It provides savings in terms of bandwidth and storage [inaudible]. So how many of you have seen live videos then? You experienced video stars by watching live video? Video consumes a lot of processing resources and power, and for live video applications, latencies involves milliseconds, so…

Uma Madhugiri Dayananda: Here’s a plot that shows the encoder quality preset versus the performance. I’m taking a specific example of x265 preset slow, with the quality preset on it’s supposed to be very good, like when you look at it visually. So, comparing that… If it’s encoded with CPU, you get 10 frames per second, but if the same application is being run on FPGA it’s like 120 frames per second. And for data centered context, it’s not just the quality and performance, you also have to consider the power as well. So considering all the three in the equation, you can see that it is like 72x acceleration.

Uma Madhugiri Dayananda: How does the FPGA solution compare to GPU solution? So here is an example of FPGA based HEVC Encoder compared against NVIDIA GPU. HEVC Encoder and see at the same quality level there’s 35% bitrate savings. Which translates into your bandwidth and streaming cost reduction.

Uma Madhugiri Dayananda: Another reason for using FPGA is probably your transcoding. So the video codec world is changing with the introduction of new codecs every few years. If you the timeline, from 2010 to 2020, there’s four new codecs. We already have HEVC and VP9, and AV1 was just standardized last year, and VVC is going to be standardized next year, so… You have a hardware or a custom chip for each of these codec, if you have that then it’s going to be a lengthy design process and also you can’t use the hardware, so… If you use FPGA, then the applications can be adapted… On the same FPGA you have HEVC application be running and also the VP9 application, so FPGAs are adaptable and reusable.

Uma Madhugiri Dayananda: What is happening behind the scenes? How is the video transcoding happening on the FPGA? We have the live video coming in from the host’s CPU and that’s being decoded on the FPGA using H.264 Decoder, and scaled into multiple resolution using adaptive [inaudible] scaler. And these scaled resolution videos are again to be encoded with the better quality encoder, and sent out back to the host.

Uma Madhugiri Dayananda: Here is this video transcoding stack that Xilinx offers. I work end to end on this pipeline. Building FFmpeg applications, XMA plug-ins, testing these applications on different SDAccel boards, targeting different devices. And not just these, I also work on video algorithms, including the quality, for improving the quality, and benchmarking encoders from partners according to customer requirements, so… I guess that makes me a Girl Geek. I work on things that I’m passionate about, video compression technologies.

Uma Madhugiri Dayananda: What I would like you to take away from this talk is FPGAs give you better performance, better adaptable and reusable, and you don’t necessarily have to be a hardware engineer to use FPGA, you can be a software engineer and still use FPGA to isolate your application. Thank you.

Eva Condron-Wells: Thank you so much, Uma, and to all of our lightening talk presenters. Let’s shift gears to our panel of senior Xilinx leaders. Here to lead our panel discussion is Tom Wurtz, Senior Director of Documentation and Program Management. And our distinguished panel.

Tom Wurtz: So tonight we’re going to explore the topic of acceleration. We’ve got a great panel of senior Xilinx leaders here to enjoy the [inaudible] discussion. So we’re going to start with Jayashree Rangarajan. She’s a Senior Director of Software Development. And her Girl Geek power is simplifying solutions to complex engineering ideas. We’ve also got Lori Pouqeutte, who’s our Vice President of Global Customer Operations, and her Girl Geek power is knowing what the customer wants and needs before they know what they want and need. All right. Next up is Jennifer Wong, and she is a Vice President of FPGA Product Development, and her Girl Geek power is optimizing results for both engineering and management. And finally, we have Ambs Kesavan, who’s our Senior Director of Software Infrastructure, Engineering & DevOps, and her Girl Geek power is improving the development efficiency of using tools both in the cloud and on something.

Tom Wurtz: All right, so let’s talk about this acceleration, that’s a pretty wide topic. We’re going to take it in a couple of different directions. First, computational acceleration. And then we’re going to make it a little bit more personal and talk about careers, as well as teamwork. So, we’re going to start with the hard stuff. So we’re going to geek out a little bit on computational acceleration. You heard Changyi talk earlier about machine learning. So this is things like image classification, motion detect, and speech recognition. So Ambs, I’m going to have you go first, and I’m going to have you talk us through some of the bottlenecks and challenges in this.

Ambs Kesavan

Senior Director of Software Infrastructure Engineering and DevOps speaking at Xilinx Girl Geek Dinner.

Ambs Kesavan: Thanks, Tom. I actually view this as an opportunity rather than a challenge. So, I’ll talk about the opportunities here and I’ll explain why I view that way. So we are in an era of big data, and there is a lot of statistics about big data. And I was looking at a recent article that said every single second, we generate about terabytes of data from connected devices and sensors around us, and 70% of this data is video. And that amounts to about 800 million hours every single day or something like that, and businesses are trying to take advantage of this data. They want to mine the data, to be able to look through things. One is for better customer service and also in [inaudible].

Ambs Kesavan: So machine learning applications are getting innovated at that rapid pace, in every single industrial segment, whether it is retail, or finance, or healthcare, Uma talked about video transcoding, speech recognition, name it. Every single industry is going through innovation. And these machine learning applications, they actually have the most algorithms for actually doing the machine learning. And these algorithms, if you run on CPU, that is no longer sufficient. It is not a scalable given the massive volume of data that we are looking at.

Ambs Kesavan: So acceleration is the way to go. And innovation needs to happen both in hardware, also in software, in order to accelerate this machine learning applications and algorithms. And that’s the opportunity, Tom. And Xilinx is well positioned Tom, [inaudible].

Tom Wurtz: Thanks. Lori, maybe you can join in with a few more thoughts.

Lori Pouquette speaking

VP of Global Customer Operations Lori Pouquette talks about opportunities and challenges in supply chain for applying machine learning to the business at Xilinx Girl Geek Dinner.

Lori Pouquette: Sure, and I’ll take this more from the practical application in business. So we’re building a lot of capabilities to accelerate machine learning, but we actually have to apply that too in our business. And in supply chain… There’s quite a bit of opportunity in supply chain for applying machine learning to the business. And it provides good ROI to the business. A couple of the areas that we’re looking at are, what I call predictability or or predictable analytics. And one of the applications would be being able to understand the profile of the die that is coming out of the fab very early on, so you can actually match that to the demand much earlier in the work stream and optimize the use of your materials. Another predictable application is actually in the back end, when you talk about equipment. One of the things that shuts us down is unplanned machine downtime. So if we can anticipate and understand the profiles of the machinery so that we prevent it from going down in the first place, it’ll definitely propel the business. The challenges with all of this, though, are the massive amount of data that you have to gather to really train your models and make sure you have the right algorithms, so you get the ROI out of it.

Tom Wurtz: So there’s clearly a lot of opportunity is this space, so… You see companies like Google and Intel, they’re doing these dedicated AI chips, there’s dozens of startups that are actually going down this path as well. And maybe Jayashree, you can walk us through kind of what you see in terms of where is the market going from here.

Jayashree Ranga: You all heard Ambs talk about the terabytes of data getting generated. And there’s also… She was mentioning about algorithms that need to be developed… And specifically, if you look at the computing today, CPUs generally are meant for general purpose computing. When you talk of AI, and machine learning in particular, you have two types of learning. There is training, and then there is inference, right. And then training, you use all of this data that you have accumulated and we are training certain models to do a particular task, [inaudible] domain, or [inaudible] exploration, or whatever. But then, when you have to deploy that model, actually for doing the inferencing, you want this to be done in such as way that the computation happens a lot faster and the CPUs are not scaling… You probably have heard at many conferences that [inaudible] are not scaling anymore.

Jayashree Ranga: So there is a need for us to be looking at how can we accelerate the solutions that are targeted for these specific applications. So, now you’re seeing companies looking for like… Especially the examples that, Tom you gave about the GPUs and the… That’s primarily because they saw a need for how do I accelerate this? I can’t do it just with software, I need to be building custom hardware. And, it doesn’t just stop the building that accelerator, but you’ll need to have some surrounding support in the system because data that needs to come into that accelerator, and how’s the communication going to happen? So there is a need for these specialized architectures to be built and that’s why are seeing a lot of these startups getting funded to find that next big accelerator architecture that we can build.

Jayashree Ranga: Second thing with machine learning also is you probably are hearing new networks getting created everyday, right. Which means you want an architecture that you don’t build for one network, but two years later you’re not able to use it. So, you want to a hardware architecture that is scalable with the needs. And that’s an area where Xilinx’s provided solution, which is adaptable and reusable, you saw it in the presentations earlier, it provides solutions that people can use for building networks that gets scaled with new models that come in. Especially with the startups that you’re talking about, I’m waiting to see as well, which ones succeed, which ones get taken over.

Tom Wurtz: Yeah. So adaptability, programmability, is part of the Xilinx DNA. So, when we think about programmability, there’s the idea of buying a chip off the shelf and programming it to do what you want. But there’s also the notion of, once that chip is actually in operation, being able to turn off part of it, and reprogram just that part to take on a different workload. And it’s part of the general philosophy of Xilinx, and as we look forward to the next generation of chips, it becomes even more impressive what we’re planning to do, so… Jennifer, maybe you can walk us through what Versal looks like.

Jennifer Wong: Earlier I see a lot of hands go up when we ask “Who knows about Xilinx?” So I saw a lot of hands go up. Then I heard, “How many people are hardware engineers here?” So I do see quite a few hands go up. So I wouldn’t be surprised that some of you here are some of our customers, or you have used our products, it depends… When you were in school… So you must be very familiar with our earlier product lines like UltraScale or UltraScale Plus.

Jennifer Wong: So Versal, it’s a significant step up of UltraScale, UltraScale Plus in terms of performance. So what is Versal? Versal is our first 7 nanometer product, TSMC’s latest process node, and is the industry’s first ACAP. ACAP stands for adaptive compute acceleration platform. But this is truly a platform device, not your old FPGAs. Though I should say this is the really revolutionary architecture. So this revolutionary architecture combines a scalar engine, an adaptive engine, an intelligent engine, to give us this significant performance improvement. The performance improvement can go up to about 20x of today’s GPU, or 100x up to today’s CPUs.

Jennifer Wong: So, now , how do we achieve this kind of a performance improvement. It’s pretty impressive. So, given today’s focus topic is machine learning and compute acceleration, I’m going to talk a little bit about the intelligent engine. Intelligent engine is also known as AI engine. Internally, we have a name called AI engine. So this is specially designed for compute intensive applications, like machine learning and wireless operations. Now go to the next level, what is AI engine made up of? It is really a wide array of integrated DSP engines, which are capable of [inaudible] and complex MAC operations. Now we have all these very very powerful engines. We need to think about how to connect them together in order to take advantage of them in terms of hardware acceleration.

Jennifer Wong: So you have used our products before, you must know MPSoCs. So, in MPSoCs we have a processor subsystem sitting alongside with the FPGA fabric. And these two entities are sitting side by side with some interface in between them, but the bandwidth is relatively limited. So, when they operate, they are operating fairly independently. So the difference between the older generation products and Versal is we added a very powerful NoC engine in between all these powerful engines. NoC stands for network on chip. This is not new in the industry, so NoC is very standard in ASIC. But what we are doing here is applying it to our architecture in order for us to leverage their compute acceleration.

Jennifer Wong: So what is compute acceleration, or hardware acceleration? It is… What it is a design when you can partition the area that are very very performance critical. So you partition it out, and put it into these powerful engines, and use compute acceleration to make the performance improve. And then, after the partition, you can have the slower function continue to run on the processor’s subsystem. And that’s how you achieve the big performance gain. And I’m going to stop right here, there are other innovations in Versal architecture. I’ll be happy to talk to you, if you’re interested, later this evening.

Tom Wurtz: Thanks, Jennifer. Versal is definitely an example of technology escalating at an incredible pace. So I’m going to ask each of you to kind of give some thoughts on where you think the things are going to go in the next three to five years in the acceleration space.

Jennifer Wong: Maybe I’ll just follow up on what I just said. So today’s product, what we have today is pretty big. If you look at our die size, it’s huge, and power is pretty high. So, they’re going to data center, into the cloud. And I see this intensive computation not stopping, because this is in the very early stage and I see that continue to go. But in three or five years, as our process becomes more mature, our technology become more advanced, I see more and more functions going to the edge devices, like mobile phones in your hands today. And I think in future, that’s where it will go.

Ambs Kesavan: So, Jennifer let me add a slightly different viewpoint. We talk quite a bit about computer acceleration. Even tn the presentations we heard about computer acceleration, and here what happens is you’re transferring massive amounts of data from storage to compute, doing that acceleration. And then transferring the results back to storage, and there is lot of data movement happening back and forth. And that’s not necessarily very efficient, you’ll run into [inaudible] storage, and networking. And every single data center, whether it is cloud data center or on ground data center, you’re going to have compute, storage, and networking. So, what if you do the computation closer to storage? So you’re actually doing the acceleration closer to storage instead of doing the data transfer back and forth. And that’s the area Xilinx is innovating and that’s… One example that I can give is the smart SSD announcement, that happened couple of months ago, when Samsung had it’s tech day. And that precisely is doing acceleration at the storage itself. And there is also similar innovation happening on the networking with SmartLynq. So it essentially, it’s converge solution with computer acceleration, storage acceleration, and networking acceleration, and that’s where the industry, I think, will benefit a lot.

Tom Wurtz: Maybe you could talk about the software a little bit, Jayashree.

Jayashree Rangarajan speaking

Senior Director of Software Development Jayashree Rangarajan speaks on a panel discussion at Xilinx Girl Geek Dinner.

Jayashree Ranga: So, if you look at where a lot of this machine learning development is happening, it’s happening on the cloud. And they are the software developers. Throughout [inaudible] Niyati’s presentation, data scientists are looking at these massive amounts of data and looking at how am I going to write the right algorithm to solve this problem, right, and they are operating at higher levels. So what I see happening with the software is many layers of libraries being built, where these are libraries probably optimized to work for the hardware architecture that we’re targeting. Not necessarily done by the data scientists, but it’s provided by the company that is also delivering the hardware. Plus, there’s probably going to be AI specific library. For instance, we talked about video transcoding. So if you have open CV libraries that need to be provided for you. If your are software operator, you will understand this, right. Because we don’t… Anymore write string compares and stuff. You use [inaudible] libraries or SDL. So you are going to see stacks of libraries built, which are the highest level the application developer… Whether they are in a Caffe framework or a FFmpeg framework if they’re dong video transcoding. They’re going to leverage these libraries.

Jayashree Ranga: So I see a lot of innovations happening in that realm. And companies will be providing their own libraries. I see open source development or certain APIs that can be leveraged by people who are trying to address a lot of machine learning problems and various [inaudible].

Lori Pouquette: And then, if you take that from the engineering world to “Where is this all going to be used?” Xilinx has long been serving multiple end market segments, from automotive, to communications, tested measurement, medical, but our new focus now is on the data center area. The proliferation of the data, the video, it’s all going to be needing to be stored up in the cloud or on the premises. So we’ve really now got this strong focus on data center. And as part of that, in addition to selling our semiconductor devices, we’ve also started to sell boards. So we have Alveo product, which you heard Eva talk about earlier, you can see it in the demo room. So this is now making the acceleration capability, from just the semiconductor to enabling the customer with a board. So they can use the board and then go on to their design work for their entire solution much faster. They don’t even have to just start with the FPGA.

Lori Pouquette: Now, as we go out into time, what’s going to be really good for everybody is, we’re still serving all these other in markets, and as in markets like automotive really get into advanced autonomous drive or advanced applications, they’re all going to need to store that information somewhere. And they’re all going to need to process that information, and they may need to do that at the edge very rapidly, or they may be able to do that in a central place. But, basically what we’re doing here with acceleration isn’t just going to serve the base acceleration market, but all of our markets.

Tom Wurtz: Well we got pretty hard there to the extent that we pretty much used up most of our time. But I do want to take one moment to ask each of your, if you were to put into one single word, what does it take to actually accelerate a team, what would that be? And let’s start with you, Ambs.

Ambs Kesavan: Communication.

Jennifer Wong: Teamwork for me.

Lori Pouquette: Focus.

Jayashree Ranga: I’m going to go with two words, I would say it’s the winning attitude.

Tom Wurtz: All right. Thank you very much for all of our panelists.

Eva Condron-Wells: Thank you so much to our panelists and to our lightening talk presenters. At this time we’d like to open it up to the floor. And I’ll need to steal a microphone from one of our panelists, so we’ll share. Pardon me. Thank you.

Eva Condron-Wells: So, you’ve heard a lot of different insights, different perspectives. We’d like to hear a few questions. We probably have time for… We’ll take three. So… And we’ll continue the conversation afterwards. So if you’re still burning… You have a burning question in your mind, please know that we are planning to be here until 9:00, and we have plenty of demos to share too. So… And don’t forget to take your gift on your way out, I want to say that before you mentally leave… While I have your attention, that we have a gift for all of you, that we would like you to take on your way out, in the lobby of when you came in. So, please be sure to take that with you.

Eva Condron-Wells: So, that said, I’ve given you a little bit of time to think about your question, and I have a microphone right here. Come on up, let’s have… If you don’t mind saying your name and your question to our panel.

Sara Biyabani: Sara Biyabani, GridComm CTO. So the question I have, for engineering… We talked about acceleration, so I want to start with FPGA is a [inaudible] processors, you know, they’re part of the screen, right? They’re not the… Well, I mean they could be the star, they could be the diva. So then there’s the processor, right, and you’re not going in the space, competing with x86 or R. So what does that architecture look like? What’s your ideal architecture?

Jennifer Wong: I think we have a pretty good… We do have a processor. So we have a… So for the Versal we have the A72 cores, we a have a dual A72 core in the processor subsystem, in the scalar engine, what we call the scalar engine these two processors, subsystem, you a two A72 cores and then two R5 cores in there. So from a processing standpoint, we do have capability of doing that. And now we added a lot of these architecture that we can accelerate functions. So that is what we think were our niches. So we can partition it where very critical functions, we can put it into the more expensive side. We use a lot of silicon area for acceleration hardware. So we would smartly do that, and say, okay, “What is the important one that we can partition out, put it into hardware acceleration, and leave the processor still running?” So that is what we think where the niche. Everything is on one piece of silicon. So think about it, if you’re doing it outside, you have processors and other components. So, the interface takes a very long time. The key is integration for us. Everywhere, the smaller the footprint, the more integration you do, the more performance you… Both performance and power. So, whenever you got our chip, power is a big deal. So, performance and power both are advantage to integration. And that’s where we think we going in future.

Eva Condron-Wells: Thank you, Jennifer. We have actually three questions just popped up, right all in the same area. So we’re going with that energy, and please, your name and your question.

Sylvita: Hi, I’m Sylvita. First of all, thank you to Xilinx for hosting this event. Given all the other Girl Geek Dinners I’ve been, it’s nice to see somebody on the hardware chip design side kind of take a lead here. So my question is related to that. Because most of the discussion in the big data, enterprise SaaS, or AI has been around the software and the algorithms. The first time I saw a focus on hardware was actually a Startup Grind where one of the presenters talked about , don’t write off the chip guys here, because there’s a next revolution coming where we’re going to see a lot of custom built chips for AI applications. And given that we’re talking about… First of all, this is a Girl Geek Dinner, and given that we’re talking about the fact that we need women to be on an equal footing in the way that the AI is going to evolve, what are some of the ideas you might have for some of the younger folks to continue in this space?

Jayashree Ranga: Mic check? Can you hear me okay?

Jayashree Ranga: I can think of a couple of things, right. Computer architecture, ’cause as I was talking earlier about, hey there’s many architectures that need to… They’re probably waiting to be innovated, right, because we are talking of machine learning in many many domains and stuff. So I do think, as young women who are looking to hey, what do I want to do if I want to enter into hardware, I think having a good grounding in computer architecture principles is going to go a long way. And just learning the hardware aspect, alone, is not going to be sufficient. You also need to understand which domain you’re targeting. So you need to know the end customer that you’re going to be influencing. So you need to learn about the software component, also. So I think, if you want to excel in both sides, as you are getting your early education, having good grounding in both hardware principles as well as software programming principles help you better understand the needs on both sides. But as you go further, and you are looking to specialize, then at that point, it’s an individual style choice as to whether hardware attracts you more or software attracts you more. But I think it’s good to keep your options open.

Eva Condron-Wells: Great. Thank you so much. We’ll take two more questions, and then continue with our networking.

Mung: Okay, and my name is Mung. I’m a software engineer working hardware design company. You already addressed a little bit about that, and I just wonder if you can address a little bit more regarding into FPGA application in machine learning and hardware acceleration to win over ASIC in that field.

Jennifer Wong speaking

VP of FPGA Product Development Jennifer Wong speaking at Xilinx Girl Geek Dinner.

Jennifer Wong: I think the jury is still out, but I think everybody is working very hard. This is a very hard space. And I think everybody is trying a very different route. And Xilinx has Xilinx’s niche. And I think what we give here… What our specialty is, is we are reconfigurable. Aside from being able to partition… That’s definitely a big deal, we can allow software to run on software, hardware fabric to run on past hardware… The bigger part, I think, is the reconfiguring part, which I didn’t talk about earlier. So we talked about many many different workloads today. During the day, the data center can be running one kind of work load, in the evening it’s a different workload. So, what we excel, here, is we allow reconfiguration. So even you can… Within the ACAP, you can run different workloads at different times, with the exact same piece of hardware. So we believe that is a very big niche that we can further leverage in this particular space.

Eva Condron-Wells: Thank you.

Lori Pouquette: I just want to add that, beside the reconfigurability, there’s the costs. So the costs of doing ASIC is becoming prohibitive for many applications. So on higher volume applications it’s still an option. But many of our customers who might’ve classically done ASICS, are moving away from it because it’s just not making financial sense. So there’s that piece of it too.

Eva Condron-Wells: Thank you, Lori. And our final question.

Wolfgang: Hello, my name is Wolfgang. I’m a hardware engineer. And I want to thank you that I have the chance to ask a question even though I am not a Girl Geek. So, my question is about reliability. When we have Ultra high speed computations in applications such as control of industrial processes or autonomous driving, it is not only imperative that those computations are very fast, but the results need to be very reliable. And we don’t always have the option to just [inaudible] processing memory because we have a sensor somewhere, a camera, it sends data to some processor, and that processor has to make a decision and send it to some machine that needs to act and do the right thing. So what are your thoughts about reliability, or maybe a hint, it has to do with something with high speed interfaces and a robustness against big errors, but there are also many other aspects to that.

Eva Condron-Wells: Thank you.

Jennifer Wong: Okay, so reliability has always been a big issue for us. In the past, what we do is we allow [inaudible] reliability and we do things very carefully with our foundry. Because foundry give us some specs that we have to follow through. TSMC is pretty well known in terms of it being rather conservative. So, they give us specs and we obviously negotiate with them. There is a little but of push you can do, because everybody is competing for performance and power. The more you can push the foundry, the more you can gain the advantage. So, this is maybe against what you are asking, but what I’m trying to say here is we do a very [inaudible] balancing act in terms of balance versus reliability. We don’t completely ignore reliability. We go for performance, but we always make sure we can meet our reliability. And we do a very very thorough quality QA in the end. And, also, we have qualification… Pretty substantial qualification… Different time, maybe you can add to it.

Lori Pouquette: Yes. So on the quality side, we have many in markets we serve. So we have commercial grade, we have automotive grade, and we even have an aerospace… So all of those have different levels of quality and reliability qualifications that we go through. So we definitely are very attuned to the upcoming challenges of the technology to be able to respond quickly in those types of situations you’re describing. But we definitely offer a variety, and do quite a bit of different qualifications depending on the markets that we’re serving.

Eva Condron-Wells: All right. Thank you all so much for your very thoughtful questions. And thank you all, our guests, our speakers, panelists, for your insights. We genuinely appreciate you taking the time to share your insights with this team and group. So, that said, we are officially closing our technical talk. But we are not done with our evening yet, and we are happy to stick around and answer more questions. Some of our Xilinx employees are wearing “ask me about” stickers, you’re welcome to engage with them. I will be wearing one too, so find me later. And of course, we have our dessert, and networking, and demos. Thank you all so much. This concludes the technical talk, thank you.

applause

Applause from the girl geeks at Xilinx Girl Geek Dinner after the panel discussion. Thanks for joining us in San Jose!


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Girl Geek X Stitch Fix Lightning Talks (Video + Transcript)

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Stitch Fix Girl Geek Dinner

Hundreds of girl geeks came to Stitch Fix Girl Geek Dinner for the food, drinks, good company and excellent talks from CTO Cathy Polinsky to Principal Software Engineer Erin Dees.

Speakers:
Cathy Polinsky / CTO / Stitch Fix
Emma Colner / Software Engineer / Stitch Fix
Lila Bowker / Product Manager, Engagement / Stitch Fix
Anna Schneider / Data Science Manager / Stitch Fix
Erin Boyle / Data Scientist / Stitch Fix
Bingrui Tang / Senior UX Designer / Stitch Fix
Erin Dees / Principal Software Engineer / Stitch Fix
Angie Chang / CEO & Founder / Girl Geek X
Gretchen DeKnikker / COO / Girl Geek X
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X

Transcript of Stitch Fix Girl Geek Dinner – Lightning Talks:

Angie Chang: Hello! Awesome. Thanks everyone for coming out to Stitch Fix tonight. My name’s Angie Chang, I’m the founder of Girl Geek X. It’s been 11 years of hosting weekly dinners at companies around the Silicon Valley in San Francisco. I want to thank you so much for continuing to come back, and also if it’s your first time, I hope you’ve met some amazing people. I learn something new every time, when I come to another one of these events. This is Stitch Fix’s second time hosting this event, and it’s really great seeing them grow, and I’m really excited to hear them speak again.

Gretchen DeKnikker: Hey, I’m Gretchen. How many of you guys are wearing like your Stitch Fix stuff today? Yes. I made sure that I had on all my stuff, and I feel really cute, and I have to say you guys look extra cute. Like you always look cute at the events, but you look extra cute tonight. I can tell. Okay, so how many people is this your first time? Whoa, a lot. Okay. So we actually do these every single week, so make sure you’re on the mailing list, and the next one’s at Cisco, and there’s a few more in the city, Intuit, like there’s a whole bunch of really awesome ones coming up.

Gretchen DeKnikker: We do have a podcast also, so find that on your favorite station. We just did one on uncommon unconventional career journeys, which is a fun topic. But we do mentorship, imposter syndrome, like all of these, so check it out and give us some feedback. Read it, tell us what you’d like to hear about. Tell us how we can be better. And Sukrutha.

Sukrutha Bhadouria: Thanks. Hi everyone, I actually did try wear my Stitch Fix pants, but they don’t fit anymore.

Speaker: We have maternity.

Sukrutha Bhadouria: You do, you have maternity? Okay. I did not get that notification. Thank you. No, but, anyway, the clothes are really cute and fun, and the last time when Stitch Fix sponsored, they spoke about how they used data to correctly identify the styles and the sizing that you need, and it just really blew my mind, how you think, “Oh, I’m just getting clothes in the mail.” But there’s so much thought and engineering and data that goes into it that shouldn’t go unnoticed.

Sukrutha Bhadouria: Speaking of data, we’re also trying to get a sense, so if it’s your first time, how many of you are going to sign up for our mailing list? That’s-

Gretchen DeKnikker: You can decide later. Like we haven’t proven anything, other than that they can get you good food.

Sukrutha Bhadouria: Yeah, but I do want to say it’s really easy to sign up for our mailing list. Go to girlgeek.io, and there’s like one click and you’re in. I do want to say Cathy is my absolute inspiration. We do podcasts, and we also do virtual conferences, and the first time we did a virtual conference she was kind enough to agree to kick it off and do the keynote. And so even that audio and video is available on our website, you can easily access it, and also on our YouTube.

Sukrutha Bhadouria: So enough from me, because there are great talks coming up, and Cathy is going to kick it off. I know Cathy, because she used to be at Salesforce, kicking butt there. And she’s kicking butt here. I’m going to hand it off to you, Cathy. Thank you so much for hosting again.

Cathy Polinsky speaking

CTO Cathy Polinsky talks about the company’s product, the people, and partnership at Stitch Fix Girl Geek Dinner.

Cathy Polinsky: Thanks. Thank you guys. Great. Thanks for giving us the opportunity to host. I really appreciate the organization, Geek Girl X, and the mission of really bringing together women from all over the Bay Area to connect, and to network, and to share our experiences. So thank you all for coming here, and especially welcome to people who are coming to their first Geek Girl event.

Cathy Polinsky: How many of you have never used Stitch Fix before? Yay, awesome. Well, you all have gift certificates, and so hopefully you’ll give us a try. But Stitch Fix is an online personal styling service, so we’re disrupting how people can find things that they love, and our mission is to help people feel and look their best. The way that we do this is we pair human stylists with data science to help people discover their looks.

Cathy Polinsky: And so, I mean many of you have tried to buy clothes online, it’s a pretty miserable experience, and what we’re doing is first you fill out a style profile, similar to a dating profile, but about things that you like to wear. We then use dozens of machine learning algorithms to get match scores against all the items in our inventory. We send those match scores to our stylists, and we have over 4,000 stylists who work for us.

Cathy Polinsky: These are employees of ours. We feel really passionate about not replicating the Uber gig economy of contractors, but really these are employees of ours who work from home, and are really passionate about serving our client’s needs. They hand curate a Fix just for you. They pick the clothes, they send it to one of our fulfillment centers. We put it up in a nice box, we send it to your house. You get to try it on at home. You keep what you like, you send back the rest. We pay for shipping both ways.

Cathy Polinsky: The great thing about our model is that we get better and better the more we get to know you, and you share data about what you like, and what you don’t like, and that gets fed back into our model. And so we’re an eight-year-old company, and proud that Fast Company named us one of the most innovative companies last year. Woo! Thank you.

Cathy Polinsky: This is Katrina Lake, our CEO and founder, and I feel really passionate about working for a female led company. She is a really amazing entrepreneur and leader, that I really get so excited every day to get to work with her. It’s a very data driven company, led by a very data driven leader. That really goes into the innovation of what we do.

Cathy Polinsky: We’re eight years old, we’re a newly public company, making over a billion dollars in revenue. We’re profitable. We’ve got business lines for women’s, for men’s, for kids, for plus, maternity. We’re just about to launch our first international company in the UK, so look for the announcement soon. If you know anyone in the UK, let them know once it’s launched and we’d love to have them try out our service.

Cathy Polinsky: I really get excited about our business model, and it’s just very interesting to deal with something that has a tangible product, and a huge operational aspect. I’ve worked at companies like Salesforce and Yahoo and Amazon, and this is just a different aspect of how I’m working with technology, with our tech teams.

Cathy Polinsky: It’s also really amazing what a strong engineering culture we have, and company culture. We have what we call the Stitch Fix OS, it’s our operating system for how our teams work together. And I think it’s really great to be able to work for a company where you can see the values that you have, aligned with how we run ourselves as a company.

Cathy Polinsky: Two things that really stand out to me as a technologist, is one is our value around authenticity. When I started my career as a software engineer all I wanted to do was fit in and look like one of the guys. I didn’t want to stand out as a woman. I wore baggy T-shirts and jeans, and just wanted to be treated as a great software engineer, and to be respected for what I did, rather than stand out as someone who is different.

Cathy Polinsky: There’s a lot of overload that goes in your brain to just try to fit in, to just try to fit in the same box, talk like one of the guys, to play the first person shooter games, or whatever it is that we were doing back then. It is a little exhausting to think about trying to fit in, instead of just getting to work, focus on your work.

Cathy Polinsky: Stitch Fix is a company where we are trying to help people look and feel their best, because we feel like that they can go out and lead more confident lives, and just the feeling you have when you’re wearing that great outfit and being able to be yourself really matters. We also have a mission for our employees to do their best work, and a lot of that comes down to being their authentic self. So not having to feel like they have to double check their email three times, or phrase things to seem less emotional, or more powerful, or whatever codified words that it might mean to kind of fit into that mold.

Cathy Polinsky: And so we have authenticity as one of our Stitch Fix values, of letting everybody be themselves, and thinking about the culture additive that brings to the organization, so that people can focus on their work instead of just trying to fit into the mold.

Cathy Polinsky: Then the other thing that we have a really strong value is around partnership, so it’s a complex business model that we have. First it starts with the merchandise. We own all of the inventory in our system, that we’re selling to our clients, and if we don’t buy the right inventory, and the right quantities, we’ll never serve our client’s needs. Then we’ve got this huge workforce of stylists and making sure that they have all the tools that they need to operate at their job every day.

Cathy Polinsky: Then we have a huge operational aspect of how we get those products to the clients in the right way, and manage all of our inventory and our costs. And then we have this whole business with our website, the style profile, and engaging products that want you to come back to our site every day, so that we can get to know you better and better.

Cathy Polinsky: If you think about all those aspects, there’s … I’m always surprised by how little changes on one side of those have deep impact on other sides. We could make some changes to how many items we send in a Fix, and that could change the inventory allocation that we have available for the next person. And so it is one of the most partnership driven companies that I have worked for, in that you really have to think about not just your own area, but how that could have an impact across the company.

Cathy Polinsky: We thought what’s really interesting about our business is how strong of an EQ we have here at Stitch Fix, and how that has really led to our innovation and success as a company. And that we really strive for that when we’re hiring technologists, so people who can think not just about building something to spec, but really thinking about understanding the business model and how they can work together across different lines. Whether it’s a data scientist working with an engineer, or someone of the design team working with our marketing team.

Cathy Polinsky: And so we’ve got a theme today of partnership that we’d like to share with you. Talking a lot about some of the interesting projects, but really leaning into how you can use that aspect of your skills to really be a big success. I’d say one of the things that I learned about partnership came from a big misstep, I would say, as an early engineering manager. So going back to this feeling of authenticity, you only know what you see, and so being in an organization where I saw mostly male leaders, I tried to emulate a lot of them in my leadership style. It didn’t always feel comfortable, but you just try to do the things that you’ve seen to be successful when you run into tough trouble.

Cathy Polinsky: A few companies ago I was working on a project, and my team was getting pulled in different directions, and I felt like, okay, I’ve seen the way that guys handle this, and they pound on the desk, and they really fight for their teams to make sure that they’re not being jerked around, and that they’re getting the staffing and the support that they need. And so I tried to do the same, and I pounded on the desk, and I yelled in meetings, and I said that this was just really unacceptable for how we could get something done.

Cathy Polinsky: And it didn’t work, and I kind of failed miserably at making the changes that were really needed to work on this project in a way that was getting clarity on the architecture and the designs needed at a large scale. It was like, I don’t understand why this isn’t working, it works for other people, I’ve seen managers do that in the past. But I have to say, I had some self-reflection, it didn’t feel good to yell in meetings. It wasn’t successful and it wasn’t me, and it just made everybody really miserable in the process.

Cathy Polinsky: And so the next time I went to a new company, I was like, okay, never again, I’m not going to try to be someone I’m not, and to try to get through this with anger and yelling. I’d say that I learned a lot in my next role, of really starting to build relationships. So how can I build relationships upfront, build trust, so that when we have difficult situations, instead of it getting to a point of anger it came to a conversation. I found that I really developed my leadership style, because I leaned more into my authentic self and led into building partnerships. Because I think that when you have those partnerships, you can get a lot more done.

Cathy Polinsky: I see that here every day at Stitch Fix and hope you’ll see some great learnings around partnerships that we have here today with some of our speakers. So without further ado, our theme is around technology and partnership, and we’re going to pass it off to Emma. Yeah, Emma, come on up. Where’d she go? There.

Emma Colner speaking

Software Engineer Emma Colner gives a talk on “Mind The Gap: How Our Brains Fool Us into Thinking We Understand” at Stitch Fix Girl Geek Dinner.

Emma Colner: I don’t know if you want your wine that’s up here, Cathy. All right. Hi everybody, my name is Emma Colner. I’m an engineer here at Stitch Fix, and I work on expert use systems. That means I build tools for my co-workers that help them do their jobs more efficiently. But in a previous life I was also a former experimental psychologist, so I really enjoy thinking about thinking, and today I’m going to be talking about how experts think, and how that differs from how novices think, and the different implications that can have for when we are collaborating together at work. Oh.

Cathy Polinsky: I stole this.

Emma Colner: Thank you. I only have two hands. So I’m just going to hold this. Okay. Like Cathy was saying, we value partnership a lot at Stitch Fix, and I think it makes a lot of sense to really try and understand how we can bridge this gap between how experts think and how novices think, and what they know. But also it’s a great opportunity for us to harness each individual person’s expertise. In that way we can kind of learn and grow together as a company.

Emma Colner: To start, I’d like you to think about someone that you really admire, someone whose skills and knowledge you really look up to, and someone that you might want to emulate one day. Imagine that this building here on the left is a representation of all that person’s knowledge about a certain topic. Now, if you were to learn how to do what this person does, how would you do it?

Emma Colner: Well, you could try and just copy what you see, but you could also … You’re not even sure of whether the building is going to be structurally sound, so what we don’t see is that this building started out as an idea, and a series of discussions, and lots of back and forth plans before there was even a foundation built. What I’m trying to say is that basically when we look at an expert we don’t see the path that they took to get to where they are.

Emma Colner: We don’t see all of the hypothesis that they tried and tested. You don’t see all the doubt that they experienced, so it’s just important to keep in mind. Part of what makes being a good partner a challenge, is that it’s impossible to truly know the experience of someone else. We can be excellent observers, and we can infer a lot about someone just by looking at them, but we don’t know everything. Part of the difficulty is that as people we naturally just fill in the blanks. When we don’t know something, we infer based on stuff that we already know.

Emma Colner: In some situations this can lead to some false understanding, so to succeed at partnership we need to work hard to bridge that gap between minds. I included this quote here on the right from Domain Driven Design, by Eric Evans, just because I thought it was relevant to what I’m talking about today. I’m not going to be talking much more about it, but I’m still in the middle of reading it, but it was a really good introduction. I recommend it.

Emma Colner: For now, I’m going to be describing three different scenarios that I have experienced in my software engineering career, and what they can teach us about our brain’s natural limitations, so we can become better communicators, problem solvers, and business partners.

Emma Colner: In scenario one I’m a junior software engineer, I’ve just started at Stitch Fix, and I have a mentor who’s a principal engineer. We pair pretty much every day, and half the time I don’t know what he’s talking about. He’s speaking in a different language, and also I don’t even know how to phrase the questions that I’m trying to ask. I don’t know how to phrase the search terms that I want to put in Google to understand what I’m trying to do. So that’s the first scenario.

Emma Colner: Second scenario is, in this scenario I’m the expert. I built something, I built a new feature, I’m trying to get it to work, but there’s a bug that I just can’t figure out. I’ve spent many hours on this, and finally I decide to ask someone for help. But then as soon as I explain the issue to that person, the answer just kind of pops out at me, and the other person didn’t have to say a word.

Emma Colner: And then the third scenario, collaborating with business partners. So let’s say I’m working on a new feature with my business partner. We’ve met and talked about the project several times. We meet each week, seems like we’re all on the same page, but at some point it becomes obvious there’s been some kind of miscommunication, and the project doesn’t end up as we had expected.

Emma Colner: What do all these scenarios have in common? Well, they all demonstrate a gap between what we as experts think we understand and what we actually understand of someone else’s domain. When experiencing cross-functional teams, this difference in expertise can cause friction and lost productivity. I want to advocate for a solution of adopting a beginner’s mindset. So now the neuro scientist is going to come out of me, and I’m going to have a very, very simplified explanation of how learning works in the brain, and how differences in expertise can lead to different outcomes.

Emma Colner: When we learn something for the first time it’s an effortful process that takes a lot of mental resources and attention, so that’s what those red scribbles represent. Over time, as we change from novices to experts, our brains become more efficient as memories consolidate, and unnecessary information is forgotten. The representation of information shifts from the sensory regions to cortical regions of the brain that operate more heuristically and more efficiently. That’s what all the green squiggles are meant to represent.

Emma Colner: So the more knowledge you have on a topic, the more associations you have built up in your mind, and the greater the network of brain areas that are involved while working on a problem. What do I mean about our brains becoming more efficient? I’ll share with you a study called The Development of Expertise in Radiology, and they basically showed that expertise can reduce the complexity of the environment. They did this by showing chest radiographs to novices and expert radiologists and they tracked their eye movements.

Emma Colner: They were told to detect some kind of an anomaly. You can see on the left that … The red represents more time looking at a certain spot, and green is less time. What we see is that novices are just kind of looking all over the place. They don’t know what they’re looking for. They’re spending a lot of time just kind of lost, whereas the experts, it seems that their attention is automatically drawn to the important aspects of the image.

Emma Colner: So that actually, the knowledge that they’ve had over their experience has helped reduce complexity and made the problem easier to deal with. Novices, on the other hand, are using more rudimentary tools. They might take longer, or it might be harder to solve the same problem. Most of the time being an expert works to our advantage, saving us time and energy, but in certain cases, like in the three scenarios I talked about earlier, it can be a handicap.

Emma Colner: Why might that be? Well, the price of expert efficiency is that the scaffolding, or the context surrounding when you first learned something, has been forgotten, probably by the time you’ve become an expert. So just as your brain actively consolidates memories it wants to keep, it forgets most of our daily experience, so over time we only remember the important stuff. Sometimes the only way around a problem is to work through it from the bottom up, starting with basic concepts and building up your understanding, rather than starting from an existing mental model and working down.

Emma Colner: That way we’re forced to think more deliberately, which helps expose weaknesses in our logic, and in other words it helps to just adopt this beginner’s mindset. Circling back to the different scenarios, on the left, that represents my mentor. He was working with a full-fledged Lego set with pieces that all fit together in a sequence that makes sense. And that’s actually like Legos. Whereas I, on the other hand, was working with a bunch of wooden blocks and playing around, trying to stack one idea on top of another, hoping it doesn’t fall down.

Emma Colner: I think what might have happened with my mentor is maybe like he had lost the scaffolding, he had lost the context of when he’d first learned a certain topic that he was trying to explain to me, and so it becomes harder to kind of connect with someone who has such a different skill level.

Emma Colner: And then in scenario two, I was basically describing rubber ducking, which is a debugging method where you basically explain your code to some inanimate object. It doesn’t matter what you explain your code to, but it’s surprisingly helpful in letting you know what it is that you’ve done wrong. The reason it’s so helpful is because you’re forced to approach a problem from a different perspective. You’re building up and filling in the scaffolding that you had lost previously, and that can help us gain some new insights.

Emma Colner: And then in Scenario three, when I describe how I’m working with my business partner, where we didn’t fully connect on our vision, what happened was we both had like a false understanding of the problem and/or the solution. We’d both made some kind of assumption about each other’s work without even thinking about it, because we were both experts in our own domains, and our brains are filling in the details of things that we might not understand fully.

Emma Colner: So, yeah, really, this picture is a joke, but it just demonstrates how easy it is to misinterpret things that might seem really easy. Lastly, I just wanted to return to the skyscraper and reconstruction metaphor for mental models. So while it’s being built up, there’s scaffolding all over the place, allowing workers to place one brick on top of another, but when construction is done, the scaffolding is taken away and all that’s left is a perfect shining tower.

Emma Colner: It can be hard to remember how we arrived at a conclusion once the scaffolding is gone. The next time that you’re collaborating on a project with someone of a different background, remember that you don’t see the path that they took to get to where they are, and it’s often necessary to spend the time to translate, describing one person’s solution in a language the other person understands. Or better yet, coming up with a common language together. Thank you.

Lila Bowker: Thanks Emma. Hi, my name’s Lila, I think I met most of you when trying to sort out the name tag situation up front. I’m just here to make the transitions less awkward, but there’s no guarantee that that’s actually what’s going to happen, so I have notes. Thanks, Emma, for the reminder of how continuous learning and kind of taking a beginner’s mindset is incredibly important as we work with our cross-functional partners.

Lila Bowker: Next up we have Anna Schneider. She’s a manager on our merch algo’s team, and she’s going to talk about how she partners with experts in merchandising to help make our buying better. I’ll give you that. Oh, you have LaCroix. How are you going to switch slides with LaCroix?

Anna Schneider speaking

Data Science Manager Anna Schneider gives a talk on “Transforming the Way Merchants Find What They Love” at Stitch Fix Girl Geek Dinner.

Anna Schneider: I’m going to put it down, is what I’m going to do. Hi. Yeah, so I’m Anna. As Lila said, I’m a data science manager here. I’m going to talk about a project that I worked on that is very similar to the scenario three that Emma was just talking about, where you’re working with a cross-functional partner, and you think that you’re solving the same problem, and it turns out there’s a whole different kind of problem, and a whole different kind of solution that was needed.

Anna Schneider: So when I say buying better here, I’m not talking about how clients buy better stuff from Stitch Fix, I’m talking about how buyers who work at Stitch Fix buy better stuff to send to clients. So digging in a little bit more, we have a team of people called buyers who are Stitch Fix employees, and their job is to figure out what we should be stocking in the warehouses. That determines the pool of merch that then the stylists can choose from when they’re deciding what to send to a particular client.

Anna Schneider: And upstream from the buyers, the buyers work with vendors to figure out what they should be stocking. So by working with the right vendors and buying the right things from the vendors, the buyers have a huge influence on the end experience that the client’s have, by making sure that we have really good stuff in the warehouses. That’s going to be good no matter who shows up as a client who wants a Fix.

Anna Schneider: If you think about what the buyer’s day would look like, an old school company or at Stitch Fix in the early days, this is what a buyer would do. They would look at a list of things that are on offer from the vendors, and because if you’re lucky to work at a place like Stitch Fix, there’s going to be some performance metrics associated with each one of these items of clothing. And so the buyers would look through a list like this, pick the things near the top of the list, and that’s what we would buy, and that’s what the clients would get sent.

Anna Schneider: This has a number of problems. One of them is that it’s kind of like a standard e-commerce experience for the buyer, so they have to like search through all these lists and hunt and peck, and decide what merch to be carrying. One of the big values of Stitch Fix is that we don’t make our clients go through that experience of doing all the e-commerce shopping themselves, so why are we making our in-house buyers go through that experience?

Anna Schneider: We thought there must be something better. And another more subtle problem with this way of buying, is that by only looking at one single performance metric, you’re only buying for the average client. So let’s dig a little bit into why this problem comes about.

Anna Schneider: Say we have these bunch of clients and we’ve sent them these shirts, and we have some performance metric for each of these. So maybe they all hate the yellow shirt, maybe the gray shirt does really well, and the two green shirts are like, nah, kind of in the middle. If you were a buyer looking at this data, you would think that, oh, the right thing to do is to buy a bunch of the gray shirt, and not buy the others. Seems good. Seems fine.

Anna Schneider: Now, what if we dig into the data and pull out some niche client segment that has different preferences than all the others. The top line shows pretty similar data to before. Those people still like that gray shirt, but the client segment on the bottom likes something else. They like the striped shirt on the end. Now if you’re a buyer looking at this data, the right thing to do is to buy both of these shirts, that way no matter who shows up there’s going to be something that’s really good for them.

Anna Schneider: And this is our mission at Stitch Fix, is to have something that’s going to be good, no matter who shows up. And so it’s really important for us to be enabling the buyers to do the job of buying a really diverse set of merch, that’s going to be really good for a diverse set of clients. So we, on the algorithms team, stepped back and thought about how can we give the buyers this data in order to make better decisions.

Anna Schneider: We thought, well, if giving them one list is bad, what if we give them multiple lists, one for each client segment. So algorithms, and engineering, and merch all collaborated to build a tool that did that. There was multiple lists, so every item of clothing would have how good is it for this client segment, how good is it for this other client segment, and the buyers would go through and choose things from the top of all the lists.

Anna Schneider: This was great. So was it going to be a better experience? We hoped so, but no. It was better at accomplishing the goal of having something that’s good for a lot of different kinds of people, but it made the hunt/peck problem way worse, because they had to dig through a whole separate list for every client segment. They were working harder instead of working smarter to accomplish this goal.

Anna Schneider: And they were like, well, we can do it with a handful of client segments, maybe, but Stitch Fix wants to get to thousands of client segments, millions of client segments, and this was never going to work. Is not a scalable solution. Something really interesting happened as we in Algorithms were talking with the buyers about all of their struggles using this tool. They started seeing some things that should have been obvious, and now that we learned them, it is things that we really care about taking into account.

Anna Schneider: They’re running a real business, and they didn’t give us this feedback in rap battle format, but they almost may as well have. So when they are thinking about what to buy, they have a huge number of other things that they’re keeping in mind, not just this one metric. In addition to having the right diversity across clients, there’s also things like having different price points, having different size and fit preferences.

Anna Schneider: We want to make sure that we really cover all of our bases in those kinds of ways. We’re running a profitable business, as Cathy said. We care about hitting our revenue and margin targets. Buying is something that happens on a seasonal cadence, and so we want to make sure that the stuff we’re buying is going to be good a few months from now. And there’s also other targets around the sort of inventory level management, so are we buying too much and we won’t be able to sell it? Are we buying not enough and there’s going to be missed opportunity?

Anna Schneider: The buyers were thinking about all of these things in their heads while using our tool, and not being able to fully actualize in their role. When we heard all this feedback, we stepped back and thought about, okay, is there a better way that we can be addressing this problem? There’s this performance metric that we want to be maximizing, and there’s all of these constraints that we have on the business. What does that sound like? And we go and like dug around in our algorithms toolbox and said, “Hey, that sounds like constrained optimization.”

Anna Schneider: So we reformulated this as a constrained optimization problem. Our decision variable is the number of units of each item to be buying for each client segment. We choose those units in order to maximize the predicted performance of the whole assortment overall. So we add all that together, as subject to all of those constraints that we talked about on the previous slide. It took a fair bit of work to formulate all of those as equality or inequality constraints, but we were able to get close enough for most of them, through a lot of partnership and talking with merch about like, “Hey, so when you want to meet this margin target what does that really mean?”

Anna Schneider: We were able to get all these formulated. To solve this we’re using a open source Python solver called Pyomo, and it’s been working pretty well for us, even though the documentation is pretty bad. If you’re interested in checking it out yourself, I would recommend googling this blog post by one of our other data scientists who is using Pyomo on a different team within Stitch Fix algorithms. It’s way clearer explanation than like anything else on the Internet.

Anna Schneider: Then in order to make this algorithm available to the buyers, we built a tool that they use to interact with it. So from their perspective, they actually specify values for all of these constraints within the tool, and then press go. And what happens then is that our algorithm, running Pyomo, combines those constraints with a separate algo’s predictions of how well each item is going to perform for each client, and spits back out the recommendations.

Anna Schneider: And so within just a couple of seconds the buyers get the whole assortment recommended returned back to them. This has been a way better experience for everyone involved. So our goal of having something for everyone, this achieves. We’re optimizing over all of the client segments at once. And something that has been really interesting to work on is that it totally changes the contract between the buyers and the algorithms, so the buyers are now responsible for having the right goals for the assortment, entering the right targets, and the algo is responsible for figuring out the best way to achieve those goals.

Anna Schneider: And so it’s almost like the experience of getting a Fix, where as a Stitch Fix client you’ll say like, “Hey, I want a cute dress for a wedding next month,” and the stylist will go off, and the stylist algorithms will go off and figure out the best way to achieve that goal for you. Now, the relationship between the buyers and algorithms is much more like that, instead of the standard old e-commerce experience.

Anna Schneider: Some lessons that I’ve learnt through this that could hopefully be transferable to some other business context, like whatever you’re working on. One is that algorithms are good at tactics, and people are good at strategy. In the old versions of this tool, the people were responsible for the tactics of digging through all the lists, and nothing within the tool was responsible for the strategy. Now we reformulated the tool so that the people are doing the strategy and the algo is doing the tactics, and that’s a much more powerful human-in-the-loop algorithm.

Anna Schneider: One important enabler of allowing people to handle the strategy, is being able to capture that strategy for the tool, and so that’s been the really interesting user experience problem, because sometimes the buyers knew explicitly what their targets were, and sometimes it was all just implicit in their head, and so that’s been a fun partnership experience too, is figuring out a good UX to tease those implicit intentions out of the users, and make them explicit.

Anna Schneider: If we were only working with collect telemetry kind of data, instead of asking like, “Hey, what do you actually want?” it would have taken much longer to figure out what some of these targets were. And last but not least, especially if you’re working in like B2B or enterprise, your users are running a real business, and their jobs are way more complicated than you realize, no matter how much time you spend getting in the weeds with them.

Anna Schneider: So in my experience, at least, it’s really worth getting into the weeds to try to figure out how their processes actually work, and then abstracting it back to something that can achieve their goals even better than they thought and you thought that could be possible. So thanks.

Lila Bowker: Yeah, thanks Anna for explaining how you use data science to make our merch buying process better. I’m going to look at my notes again, sorry. Next up we have a dynamic duo, half of which is already up here. Come on over. All right, so we have product designer, Bing Tang. Oh-oh, there goes my notes. And data scientist, Erin Boyle, and they’re going to explain how we use data to understand client style, and then how we use that to inform stylists to send better Fixes. Take it away, guys.

Erin Boyle, Bingrui Tang

Data Scientist Erin Boyle and Senior UX Designer Bingrui Tang give a talk on “Partnering on Style” at Stitch Fix Girl Geek Dinner.

Erin Boyle: Thanks, Lila.

Bingrui Tang: Okay, hello everyone. My name is Bing, and I work on the UX design team, [inaudible]. And this is Erin, she works on the data science team and working on AI instruments, and today we’ll be … being the dynamic duo, and talk about communicating style together.

Bingrui Tang: I think Cathy already talk about this a little bit, but at Stitch Fix we really have this human-in-the-loop process. We have algorithm empowering the stylist’s work, where a stylist will actually make the call. And if we actually put our foot into a stylist’s shoes, it is a very challenging work. Imagine you have a client who is there in a 50s Fix, and their profile might haven’t been updated for a while, and their style preference has been changing over time. It is really difficult for a stylist to dig through all the things, and do we really want to empower them to use their creativity to really send a delightful Fix to our clients?

Bingrui Tang: So on the backend side, a lot of our work is really to design for the styling platform, so, as you can see here, on a platform we would combine the client data which has some basic information. Their style preference and their Fix history, as well as how the algorithm is recommending the items of a variety of categories, and decides by going through all the information about a client, they would actually be able to pick the items that they think would fit the client well, which might not always 100% fit with how the algorithm sorted out.

Bingrui Tang: So for us, a big part of our work is to make sure the way we present the client data is really helpful for the stylists, so they can really do their job well. Previously, the way we represent a client’s style is more aesthetic, so for those who have been using Stitch Fix before, when clients sign up they would rate outfits of different styles, and we will translate this summarized data into some different formats, to the platform, so that the stylists will see and be able to understand what the client wants.

Erin Boyle: Okay. Cool, thanks. The data science team that I’m on works on contributing to a broad set of problems, kind of in this category, that rely on having some more nuanced definition of style. So we actually built a new platform to try and support this. Can I ask, has anyone in this room played style Shuffle? Got a few hands. Okay. Style Shuffle is a kind of game-like experience that we released a little over a year ago, where clients can rate items in our inventory, thumbs up or thumbs down.

Erin Boyle: It’s been really fun and engaging for them, people really like giving us data like this. We have more than a billion ratings now. You can imagine that, like Bing said, one way that you can represent someone’s style is with these kind of like limited number of static questions that we used to have in our style profile. But you can imagine that there’s a few limitations to that, like one, it’s just not very much data, so it’s not going to have a lot of nuance, and then like Bing said, it will also get stale over time.

Erin Boyle: So since people can continually play this game, we can keep collecting more information and get kind of richer, and richer, and up-to-date information about our clients. It’ll come as a surprise to no data scientist in this room, that one way you can deal with data of this format is with an algorithm called matrix factorization. If you want to come up with descriptions of a client’s, what we’ll call, latent style preferences, one thing you can do is you can treat the ratings coming out of this system as kind of sparse observations in this user item matrix, where every row is a user, and every column is an item.

Erin Boyle: You can decompose this matrix into a lower rank co-representation that is composed of the product of this lower dimensional user embedding matrix, and lower dimensional item embedding matrix. When you’ve done this, what you have learnt, you’re learning the coefficients in these two matrices on the right. What you’ve learned are what we call latent factors, that describe client preference. So the kind of columns in this user matrix and the rows in this item matrix are going to describe … they’re going to be kind of like hidden underlying variables that describe a big sources of variance in the preferences that we see from our clients.

Erin Boyle: If you want to get a prediction back out for any of these user item pairs that we haven’t actually observed. If you want to get back out a prediction of how well a user might like some particular item, all you need to do in this framing is simply take a dot product of this user and item vector to recover a kind of score for that pair.

Erin Boyle: In reality, we might actually expand on this, and use a more nuanced algorithm, but I think this is a good kind of framing to understand it. What can we do? So one thing you can do once you’ve trained an algorithm like this, is you can simply pull out the top recommendations for any client. Here I’ve sampled five real clients form our clientele, and I’ve also sampled some of the top items, given this prediction task for these clients, and you can see that you really uncover using this algorithm, like a range of different aesthetics. You can see that these people are all of different style.

Erin Boyle: That’s one thing that we can provide to technical and business partners like Bing, to paint a picture of our clients. But we are interested in also providing something else, so just like from the style profile, you have this set of user features that comes out. We’re also interested in whether the user representation, like just this user vector on the left here, was kind of in and of itself useful and interesting, and whether we could use it as a feature that we could communicate through language as well.

Erin Boyle: One way you can do that is to really think about this kind of style space that you’ve created when you run this algorithm. So let’s say we ran this algorithm with just three latent factors like we’ve done here, just three columns in the user matrix, that means that once we’ve learnt coefficients for this user, they have a location in this kind of XYZ space. They have an address. We’re curious, does that address itself kind of convey information?

Erin Boyle: One way you can dig into that and try and come up with a language to describe this user representation from this algorithm, is you can actually look at these axes, and you can see what they represent. We’ve found these latent factors that predict client preference, but what do they mean? Like what’s going on? One thing you can do, an item that is good for this user … Since our prediction task is done by taking a dot product, an item that is good for this user is going to be an item that is near this user in this style space, and an item that is bad for them is going to be far away.

Erin Boyle: One thing you can do, is you can look at how the items change across some particular axis, to come up with what this axis is encoding stylistically. When we do this for this one X axis, you can see that this is sample of items on the left, and they have this kind of boho style to them. And this is a sample of items on the right, and maybe you would call them more preppy.

Erin Boyle: And you can then go through and do this for the major, what we would call, principle components of this style space in order to really explain what this user’s representation means. There’s a couple little technical details if you want to do this in real life. I actually have a blog post on it, if you want to dig into that.

Erin Boyle: But basically what this gets us to, is that our team can kind of partner with people like Bing, to provide these intermediate data products, that they can plug into whatever their domain is within the company. One thing might be actual recommendations. One might be the client’s representation. Maybe on merch they might care about the style’s representation instead. What we try to do is just provide people with whatever products are going to be useful for their application.

Bingrui Tang: Thank you. Thank you, Erin. I know it’s very magical, isn’t it? I remember when I first got on the project, I was like, “Ooh, look at that.” So, yeah, that’s come back to what I was talking about, designing the styling platform. Once I wrapped my head around this project and going through many meetings with our cross-functional partners, there’s two big questions sitting in front of us.

Bingrui Tang: One is, how to make sense of latent style? Because, as Erin just said, it is a very mathematical model. But we want to make sure it is something that somebody who doesn’t really know statistics, or doesn’t really know much about math, could still understand it in some way. And more importantly, we want to make sure that it could stylists actually make decisions, and with confidence.

Bingrui Tang: So for these two questions we actually conducted two different studies and I will just quickly go through them, and share with you guys. The first one, as Erin just said, and she actually showed these two clusters of clothes too, I think most people would see, “Oh, these two are different styles.” But it’s very hard to say why, or how, or what, or exactly, so this is also how we started the study, because, as a human, when we see a bunch of things sitting together with similarities, we just have this natural tendency to give it a name, a label, a theme, or something like that, so that was how we started.

Bingrui Tang: Let’s use this, two extreme maxis as example. The first moment we saw it, we said, “Oh, the left-hand side looks very classic. The right-hand side look trendy.” Yeah, something like that. But because we thought this is coming from the mathematical model, we should really think about it very objectively. So we say, what is the most visible objective factor? Let’s say, the left-hand side is very less skin exposure, it’s much more covered, and the right-hand side looks more skin exposure, what about that?

Bingrui Tang: And then we show it to the stylists and also other people on the team, and then there has been a lot of voice raised, because everybody’s like, “Yeah, there is skin exposure, but the print seems different, there is seasonal implications. The color scheme is different. The fit is different. There is different levels of embellishment. Which one is the most important? How do we kind of …” Then there’s a lot of debate around that.

Bingrui Tang: At that point, the team and everybody, we actually started stepping back a little bit and think about what is style in reality? This is one quote from the movie The Devil Wears Prada–I still remember when that quote come out in a movie–but I think essentially it is talking about what style was really manifested over time, from the cultural and the historical influence. For us, it is really important to recognize and embrace that instead of trying to invent some new way of talking about style overnight.

Bingrui Tang: At the end we actually come back to our original idea, and actually showed it to stylists, and see how they reacted to it. Do they recognize these words as representative of these clusters? And seems like the old way, the classic and trendy, actually worked the best.

Bingrui Tang: For the second study, I think Erin also showed this image before, now that we know we can get a sample set of items that seems to be into the client’s preference, and we can also get a relevant location of the client preference in this spacial model, how can we display the client’s style representation in the styling platform so that the stylist can actually understand it within a short amount of time?

Bingrui Tang: The goal for us is to find the right way to display each client’s style, to help stylists actually style a Fix. So, again, oops, let’s use this image as an example. Imagine this is client 123, that’s her style preference sample. So we tried a few options again. The first one, we said images only, here’s what she likes, and you can interpret it as much as you want. And we were not feeling quite 100% confident with it.

Bingrui Tang: And then the second option is the more mathematical one, we say, “Her style is 53% trendy, and 28% boho.” And we definitely know it is a little bit too extreme, so we also pulled back a little bit, and look at this, the happy medium. So we would say, “Her style is very trendy, and a little bit boho.” And now we have three options later, we actually ran a quick study, and we are surprised.

Bingrui Tang: We compared a bunch of different factors, from how accurate the stylists are able to find what the client likes and figure out what the client dislike, and also how fast they are.

Lila Bowker: Try that.

Bingrui Tang: Okay. Oh, thank you. And also how the stylists feel about using this feature as an experience, and seems like the image only one actually won all of them. And from the result, seems like, at least during the experiment period, we learned that displaying the images only has the best overall outcome.

Bingrui Tang: So when we look back at the long journey, we realized at the beginning we were trying to display as much information as possible and tried to put massive amount of data in front of stylists, and then we pulled back a little bit, and then we realized we can actually let the information speak for itself, instead of we try to add more things on top of it. Which reminds me of a quote from the very famous designer, Dieter Rams. Her work inspired a lot of Apple products, and he once said, “The good design is as little design as possible.”

Bingrui Tang: I think that really speaks … the philosophy’s really representing how we work here.

Erin Boyle: Awesome. So I guess I’ll add to that, is that … Ooh, hold that thought.

Lila Bowker: Keep talking. Keep talking. Just pretend there’s the lady behind the curtain over here. Oh, no.

Erin Boyle: This collaboration was really interesting for me, too, because A, it was really interesting to learn that it’s hard to summarize aesthetics with language, like I think of language as being very rich, also, but in this case it wasn’t quite up to the task. Our brains are really good at processing images, so that was a good thing for us to learn kind of broadly, even outside of your use case.

Erin Boyle: And then also, I still got the benefit of having language that experts had applied to this space for cases where you really need language, like you can’t always show a collection of images for every kind of use case, and so we do still have language that we’ve gotten from a bunch of the work that Bing’s team did. So, this is an example of one of many technical partnerships that we do here, and thank you for listening.

Bingrui Tang: Thank you all. So I believe most of the teams that are representing here are hiring. Lila will speak more about that, but design team is hiring, so we can talk later. Thank you.

Lila Bowker: Thanks, Bing and Erin. How they takes styles, shuffle data, and turn it into better Fixes for clients is one of the reasons that I joined the company. I love it. Next up I wanted to introduce Erin, she’s a principal engineer on our Fix request team, and she’s going to talk about the importance of giving feedback, and some strategies for how you can give feedback more regularly. Go for it.

Erin Dees: Hi, friends. Is it on?

Lila Bowker: Try this one.

Erin Dees speaking

Principal Software Engineer Erin Dees gives a talk on “Dossiers of Awesome: One Way to Help Folks Get the Recognition They Deserve” at Stitch Fix Girl Geek Dinner.

Erin Dees: Hi friends, how are you all? One more talk on the theme of partnership before we all get some networking time. The focus here now is going to kind of narrow in on the personal partnership, because as strong women we are told that we need to lift one another up. But how? Now part of the answer lies in helping our peers get the recognition and the visibility that they’ve earned.

Erin Dees: It’s about giving meaningful feedback that lifts them up, and also helps you. So this talk will be … The title, Dossiers of Awesome, is just a way to frame these habits and practices. It is not a complete solution to how to lift one another up. It is not a universal recipe. It’s an idea. What I’m really hoping with sharing it, is I get to hear your ideas afterwards. So let’s talk during networking time.

Erin Dees: My name is Erin. I joined Stitch Fix about two months ago as a principal engineer. These are my goats, it’s the day I brought them home in my Kia.

Lila Bowker: I’m so sorry, we’re having … Try this one. I don’t know, I’ve mixed up which one was the good one.

Erin Dees: Can everybody hear me now? Is this better?

Lila Bowker: Is that better?

Erin Dees: Okay.

Erin Dees: Thank you, friend, sorry about that. All right. You didn’t miss anything. Something, something goats. All right. Okay. I really enjoy working on a big thorny systems engineering problems, the kind where you have to reach out across teams, learn from industry, learn from one another, and then package that learning up and bring it back to your team. That’s my jam, like sharing knowledge like that. That’s why I write programming books. That’s why I coach athletes how to race walk faster. It’s not why I have goats, but they are very good listeners.

Erin Dees: This talk came out of a conversation that I had with a former colleague, Liz Abinante, a few years ago. We were talking about this series of stories we’d read, prominent women leaving their posts in the tech industry because of being passed over for opportunities, and being harassed. I said to Liz, “How do I get better at observing, at noticing? I would hate to think that something like this happened to somebody on my team, and I didn’t even see it. How do I catch this happening?”

Erin Dees: And Liz said, “People aren’t going to harass in front of an audience. Right? They’re not going to harass in front of witnesses. So, that’s not the way. If you want to help your teammates, that’s not really a great way to do it.” And I said, “Well, how do I help my teammates? Half my teammates are women, how do I … I like them, I like working with them, how do I hang onto them?”

Erin Dees: And Liz said, “Help them get the visibility and the recognition that they have earned.” The conversation branched out from there, we brainstormed a lot. But I want to pause here for a second, and say that even though this idea came out of a difficult situation and a tough conversation, it’s going to apply in a lot of different scenarios, and I also am aware that a lot of the people in this room are already doing a lot of emotional labor for their teams. The last thing I want to do is give you all more homework.

Erin Dees: I really want to talk about this in terms that will help you in your careers as well. How many of us are in a job where we are expected to give feedback on our peers regularly? Right. A lot of us, right. How many people kind of dread that time of year when you’ve got to go write a bunch of peer performance reports, right? It’s exhausting. It takes forever to write, and by the time you’ve done your fourth or fifth one, it’s hard to come up with something that is unique that could only apply to that engineer.

Erin Dees: Like, “Well, you’ve built some great products for us, and keep learning more advanced Ruby skills, I guess.” Like I mean, right, that could apply to everybody. So how do we get feedback that helps that specific person get better in their career? And that’s what we’re going to talk about. So in order to achieve this goal, whatever process we adopt should be lightweight, because we’re all busy and we’re just not going to do it if it’s too much of a burden on our time.

Erin Dees: It should be something that we keep up with in little increments throughout the year, instead of having a big deadline dropped on us. And again, it should be actionable, it should give our peers information that they can use to grow their career. One idea had been sitting right in front of me this whole time, which is an engineering journal. Now, I had started keeping this a few months prior, because we had formed a brand new team, and there was so much learning for all of us, that we really had to capture what we’d learned and what we’d done in some way, and my solution was to keep a journal.

Erin Dees: I tried to do it every day, ended up doing about 50% of days, and here’s something like what that looked like. 4:30 p.m. every day right before the end of the workday, a blank window pops up on my desktop, it’s time to write in your journal. And I spent just a few seconds, literally just a few seconds typing in a couple of bullet points. I implemented this feature. I fixed some tests. It’s okay to get snarky, it’s your own journal. Nobody’s going to read it. And the twist here then, was to realize that there’s no reason I couldn’t put anybody else’s accomplishments in here.

Erin Dees: Sometimes my journals talked about stuff I’d done with my teammates, but it was time to get systematic about it, and use hashtags and stuff. And so that’s what I started doing. So in addition to what I’d worked on, I might add a couple of bullet points that a teammate worked on, and tagged them with a hashtag, which comes in handy later. So then if you’re in a culture that does sort of quarterly feedback cycles, when it comes time to do this, I can click on that person’s tag in my journaling software.

Erin Dees: This is totally real data you all. I did not just type a bunch of this stuff at 1:00 a.m. in my hotel room last night. So then you can either copy and paste, or kind of paraphrase, but you start with a blank document, and you can paste all this data in here. And you start to notice as you do this that these items kind of fall into patterns. These few items seem like they’re about incident response. These couple of items here seem like they’re about tech leadership, and so you can group them. You can start moving them around and you can add some headings.

Erin Dees: Now, then what you do with this information depends a lot about your feedback culture. If you’re in a place where you’re expected to write your own review, for starters, a self-review, you can give your peers the ammo, the raw material that they can use to write their self-review. So here’s what that might look like, you can compose an email, and if your manager is someone who’s supportive, write it to them and Cc your friend or your peer. Well, I hope they might be your friend too. And this now tells them a story. If they’ve been waiting for a great opportunity to write a promotion pitch for this engineer, you’ve just given them all this ammo.

Erin Dees: But the audience is also your peer, because if they’re going to be writing their self-review, it’s going to be a bunch of stuff that they may not remember in the moment that they accomplished that quarter. That said, though, do please let the manager know what they’ve done as well, because there’s a lot of cultural pressure on us not to brag, and we should fix that too. But if this is all stuff that happened, this isn’t bragging. It’s data.

Erin Dees: It’s a good idea to share it with … again, if you have the supportive manager, and with your peer. So how to make this feedback actionable, so that somebody can act on it and grow their career? One way to do this is to work these data points into a story, so it’s not just data, it’s a narrative. What this looks like, for example, if you start noticing this person developing or showing an aptitude and interest in tech leadership, is to call that out, and say, “Hey, maybe it’s time to start handing this engineer larger projects and have them run bigger initiatives. They seem to have a knack for it.”

Erin Dees: So I want to pause, just one second, and say that we’re at a women’s conference, and we’re talking through this originally through the lens of a conversation about women in tech, but there are lots of teammates that we have that are dealing with other marginalized identities, some multiple marginalized identities. So I want us to keep in mind all of our teammates who might be marginalized along one or more axes when we think about lifting one another up.

Erin Dees: That is one way that we can have an impact on our careers and our peer’s careers, is lifting them up. But again, this helps us do our jobs better. If we’re expected to give feedback, and we can do something that gives better and high quality feedback more quickly with less overhead, that helps us too. That makes us recognized for giving good feedback that really helps people, and that’s the impact I’m hoping that you all will have, no matter how you all choose to do it.

Erin Dees: So I’m really grateful to Girl Geek and Stitch Fix for putting together this event. Lila, this has been amazing. I love it. I have loved every talk I’ve watched. The other presenters, you all are amazing. I’m really grateful to Liz Abinante for this original conversation, and Lila and Miriam for helping me, appropriately enough, with meaningful actionable feedback about this very presentation.

Erin Dees: As we prepare to head into networking time, I want to come back to that cultural expectation that we don’t brag, and I want to chip away at that just a little bit tonight. I’d like to invite you all, as you’re introducing yourself to other people, to say something that you’re awesome at, work related, non work related, doesn’t matter. Lead off with something you’re skilled at. And if that’s one notch too extroverted for the comfort level tonight, maybe ask the person what they’re awesome at. Just know that they might turn around and ask you, be prepared for that, it’s okay.

Erin Dees: As we were brainstorming for how to lead into networking time, as a group of presenters, Lila brought up these two articles about the importance of owning your awesome, of owning what you’ve built. I really want to embody that spirit tonight, if at all we possibly can. It’s been hugely inspiring to be in this room full of awesome badass women in tech. I’m really grateful to be up here. I hope you all have a great rest of the event, and cheers.

Erin Boyle: Thanks, Erin. That was amazing, thanks, Erin.

Audience Member: I have a question about the buying process, like particularly more like the supply chain issues you might face. How do you, if you end up with an extra load of clothes that don’t fit anybody, how do you steer away from trying to push product on people just to sell it, and what do you do with your unsold inventory?

Anna Schneider: Yeah. There are several algorithms that help with that, unsurprisingly. So, yeah, we have clearance algorithms that figure out, hey, this thing isn’t performing very well, and then sometimes we will get rid of it through donating it, so that’s one common way that low performing stuff will leave our inventory. Although when we’re doing that, we do want to make sure that we’re not getting rid of stuff that’s like bad for a lot of people, but like really good for someone. We do want to keep that niche stuff around.

Anna Schneider: So with the client’s expectation, like I was talking about, like that’s like something that we’re always trying to figure out how to get better at.

Cathy Polinsky: But I think one of the things that I really appreciate about Stitch Fix is that we separate out the merchandising team who buys the product from the stylist team that sends the product to the right people. So we have intentionally created this firewall between the two, so the stylists are never incented to send bad product out to their clients.

Cathy Polinsky: They don’t know, “Hey, we’ve got a lot of those lime-green shoes out there that aren’t selling, can you just send it out to people.” Instead, we really try to make sure that the stylists are incented to really keep their clients happy, and if we buy bad product, we eat the cost ourselves, and learn from it for the next time, to make sure that we don’t make the same mistake over and over again.

Cathy Polinsky: It is this interesting system where sometimes actually getting rid of bad product helps everybody else up, just making sure that that bad product is not inadvertently getting into Fixes. And so we’ve seen these times where we have changed the dynamics in the model, of how often we’ve gotten rid of bad product, and we’ve now learned that it’s not a good idea to hold onto it, but it’s much better for us to get fresh stuff in. Was a good question, though.

Lila Bowker: Nice. All right. I’m getting my cardio in, you guys, hang on. There you go.

Audience Member: Hi, I’ve a question with respect to recommendations. How do you deal with surprise, because you can learn someone’s style, but often when someone really, really likes something, it might be because it’s a little bit outside their comfort zone, and it’s one item. Do you like work that in by humans or algorithms?

Erin Boyle: Yeah. That’s a great question. And I should say that the exact answer to that might change, depending on what context you’re talking about. So, probably you’re asking about in someone’s Fix, and in that case a lot of that would be done by the human stylist. We do have algorithms that try to think about assortment, but we mostly rely on stylists, or … Yeah? Yeah, stylists would definitely be injecting a lot of that.

Erin Boyle: The other thing I’ll say is another place where you might use recommendations, I mean we have recommendations everywhere, but another place you might use them is like in the stylish level itself. Of course there are recommendations that are fed back to the client, and certainly there is some like assortment logic and experiments and stuff that have gone into like injecting surprise into that experience too.

Cathy Polinsky: But we try to get employees to style, as well as the stylist, and so I try to style a couple Fixes a month, and occasionally I’ll get someone that says, “Stop sending me skinny jeans,” and the recommendations only knows that this client buys skinny jeans, and so the stylist has to think of like, “Well, maybe I’ll send her a boyfriend jean, or a boot cut jean.”

Cathy Polinsky: Our algorithms have no idea what they’re going to want next, based on their previous purchases, but we’ll have to use this … we like to call it the blend of humans and machines. The art and science of what we do is sometimes there is this kind of stylistic creativity that goes into generating a Fix. It’s kind of fun.

Erin Boyle: Well said.

Bingrui Tang: I was also going to add on that, because sometimes there will be clients say, “Oh, I really don’t wear dresses,” and then all of a sudden they’ll say, “Oh, I’m going to a wedding, then I need a dress.” So it’s very important for us, when we design the system, we really keep in mind this kind of flexibility, and people’s preference will change, either occasionally or over time, and we really want to recognize that. I think that’s a really good question, and that’s definitely the fun part of the work, is trying to juggle them both. Yeah.

Lila Bowker: All right, let’s start here.

Audience Member: The question is about the buying process in the old traditional way. One of the reason they’re using that method is because probably the cost optimization, the more you buy, the cheaper it is. But buying optimized by diversity using algorithm, how you deal with the cost optimization to the supplier?

Cathy Polinsky, Erin Boyle, Bingrui Tang, Anna Schneider and Emma Colner

Stitch Fix girl geeks: Cathy Polinsky, Erin Boyle, Bingrui Tang, Anna Schneider and Emma Colner answering audience questions at Stitch Fix Girl Geek Dinner.

Anna Schneider: Yeah, so in the constraints that the buyers will put into the problem, one of them is exactly around that. We know how much we’re going to buy it at wholesale, and we know what our margins will be because of that, and often the algorithm will say like, “Hey, this one has really good margin, buy even deeper into it.” So if that’s something that we want to be … Yeah, yeah, it’s something that’s just rolled into all of our other data.

Anna Schneider: That’s something that we … Margin isn’t the only thing we care about by any means, there’s all these other metrics about making the experience really right for the clients, and so that’s what we are … currently it’s formulated, where we’re trying to give the best experience to the clients as possible, constrained by having a profitable business. Yeah. So the client is really first.

Audience Member: Sure. One of the things I’ve always struggled with with these try before you buy services, is that the things I like aesthetically don’t always match the things that look good on me. I’m curious what you guys think about that, and how you are imagining how the Stitch Fix product addresses that challenge?

Erin Boyle: Yeah. I mean that’s a tough question. I think there is kind of a fine line between aesthetic and fit. I mean even in this latent style data, which we think of as being largely a style thing, like people are rating whether they like an item and it’s a very visual thing, they’re not necessarily seeing the size of that item that they would actually buy, or the can’t tell the inseam or whatever.

Erin Boyle: And yet we do see fit preferences coming out of that data, like we can figure out some fit preferences too. Yeah, I mean I think we certainly try to collect information on both style and fit in the style profile, and through other means, and then certainly the client has a conversation ongoing with the stylist, where they give the stylist feedback on the details of what does and doesn’t work for them.

Erin Boyle: And then those kind of like subtler pieces of feedback that really take a human to interpret can be acted on by that stylist.

Cathy Polinsky: Anecdotally, I see this. I have some clients that have an Instagram feed, and I’m like, “Oh, they liked this item, we have it in inventory, I’m going to send it to them, even though the match score is really low for the product.” And I send it to them and they hate it, but I’m like, “You said you wanted it.” But there is this notion of what they like stylistically, versus what is good on them, and so I’m really impressed with how these match scores that we have factor that into the recommendations.

Cathy Polinsky: And it’s not like, “I don’t want that navy blazer, I want a navy blazer that looks good on me.” And so how can we take the style things that people are sending us, and pair that with other factors, like fit, to find the exact right thing for you. It’s a hard problem, and that’s why it’s so much of a pain for people to try to shop online and scroll through lists and lists of jeans, to figure out what’s going to fit them.

Cathy Polinsky: So I think that this is a different model that we can use, that can factor in a lot of those different attributes.

Audience Member: I found it really refreshing to see multiple senior female engineers on this panel, and I was wondering what your approach was to sourcing and retaining female engineers. Sort of like what percentages of your teams are female, with regard to engineering specifically? And did that change as Stitch Fix got larger?

Cathy Polinsky: We are really fortunate for the gender representation that we have at Stitch Fix. It helps that we have a female CEO and founder, Katrina Lake, who has started this company. Half of our leadership team is women, more than half of our board is women, and a huge representation of our stylists are women, so if you look at our employee count, which is predominantly stylists, it’s over 80% women who work at Stitch Fix.

Cathy Polinsky: And then our technology organization is really strongly represented. We’re in the high 30s for representation of women in our tech organization. It’s still not 50/50, and still opportunity for us to grow, but compared to every other tech company that I’ve worked at, we are really leading the pack at having a very strong gender diversity in our teams.

Cathy Polinsky: We hadn’t done it through top down quotas or mandates, but really it was generated by teams and managers who cared about this. Of understanding that diverse teams build better products, that we had primarily women as our clients, and to really understand them and understand the products that we’re building, having those diverse teams helps us to make sure that the things that we’re building are really strong and supporting that client base.

Cathy Polinsky: What was great for me to see, as we were scaling out our organization, it’s hard when you’re hiring fast, to make sure that you’re thinking about diversity and all of the different criteria, but we only got better as we scaled. It really came down to the managers who didn’t have that diversity on their teams, were asking the other managers who were doing well, like, “How did you do that?” And, “How can I do that?”

Cathy Polinsky: It came through inclusive language in our job postings, or thinking about sourcing in a different way. We talked about experiences that we had to make sure that we had diverse panels, and then we also look for really product centric engineers at Stitch Fix, and I think that that helps us generate a more diverse pipeline of what an engineer looks like throughout our organization.

Cathy Polinsky: We’re not done. We still really want to hire more architect level senior individual contributors here at Stitch Fix, that’s an area that we don’t have as much diversity. And then we’re also looking to increase our racial diversity, and think that we are really leading the way on gender diversity, but have some more way to go in other aspects of diversity, like racial diversity.

Cathy Polinsky: But I love that we’re a group that cares about this, and we talk about it, and we celebrate where we are doing well, and also understanding that we’re not done.

Erin Dees: May I jump in for a second?

Cathy Polinsky: Yeah.

Erin Dees: I joined pretty recently, and it was one of the things that drew me to Stitch Fix, was seeing that there were so many women in engineering specifically, and then as you look up, senior leadership, in terms of like management, there’s a lot of women in senior management as well. That was something that really shines through, so one reason I think that Stitch Fix has so many women in engineering, is because we’re drawn here. We see like, this is a good place for me. None of us wants to be the only woman on the team, so it’s been awesome.

Cathy Polinsky: Great. Thank you. Glad to have you.

Lila Bowker: Another question over here.

Audience Member: Hi. I have a question on I guess the outlook on how accurate you think your algorithms are becoming over time? Are they becoming more predictive? Do you think that we’ll get to a point where the algorithm can handle both the strategy and the tactics? And if we are at that point, do you think that Stitch Fix would ever move to a model where maybe there is less reliance on human stylists? If yes, why? If not, why?

Erin Boyle: I’ll let Anna speak to the strategy tactics, because that’s definitely your framing. I will say they’re definitely improving all the time. Obviously we can’t give you any quantification of that, but I’ve actually been here almost four years, and it’s shocking how much better we are. You can see it in so many ways. So, yes, they’re improving all the time. I still expect them to improve more, but I don’t expect it to really change anything about the role that people are playing.

Erin Boyle: I think that the role our stylists play is always going to be critical. It’s a critical part of our business model, they play a critical role, and similarly with our merchandising partners, and so many other people, so yeah, I’ll let Anna speak to the strategy and tactics. But that would be my reaction to that.

Anna Schneider: Yeah, one analogy that we’ve started using for the strategy versus tactics, is are we building a self-driving car, or are we building something like Google Maps? I’m mean for a self-driving car that’s just like all about the tactics. It’s like … can be completely automated. There’s no human in the loop there, whereas something like Google Maps, it doesn’t even make sense to think about what that would mean if it was fully automated, because who’s telling it where to go? You need someone giving the instruction.

Anna Schneider: And so there’s always going to be that company leadership and leadership at levels all throughout the company saying, “Where are we going?” And that’s always going to be a human decision, and so we think of it almost more like a scenario exploration engine, where you can say, “Hey, what if we went in this direction? What if we went in this direction?” And then the humans have the opportunity to choose what of all possible futures we want to be going after, and that’s always going to be a human touch.

Cathy Polinsky: So any chess players in the room? Yeah. Was it Kasparov who was the chess player who lost against Deep Blue? So we look at the sense of … At that time it was like this is the end of chess, and the age of the machine, and machines are going to always be better than humans, and what was it? So that was when the first chess game played against a human and won.

Cathy Polinsky: But what’s interesting is after that point, there was a new emerging game that was this freestyle chess. Have you guys heard of freestyle chess? So the freestyle chess, is this idea that it doesn’t matter whether you’re human, or you’re a computer, or a blend of the two, but anybody can play against anyone.

Cathy Polinsky: So they have this competition every year and there’s a freestyle likeness, and the first year that they did this a novice group of chess players won using computers, and they did it in a very novel way, of using a suite of machines to solve the problem. It was this really interesting thing, it was the blend of humans and machines. Humans that had an interesting approach for how to solve the problem, but they were backed by computers.

Cathy Polinsky: And so we use this likeness of what Stitch Fix does. It’s not computers alone, it’s not stylists alone, but it’s this blend of humans and machines that work together in a novel way, to solve a problem in a unique situation. And so we feel really strongly about this model and how it’s helped us, and sometimes we’ll lean a little bit more on the machine side, sometimes we’ll lean a little bit more on the human side, but regardless of where that line is, we feel like the power of the two together is really a magical thing.

Lila Bowker: Awesome. We do want to leave enough time for folks to chat afterwards and brag about themselves and hear what makes everyone else awesome, so maybe one more question, is that all right with you guys? All right, here you go.

Audience Member: Hi, sorry, one of the last questions. A lot of fashion is traditionally geared for women, so I was wondering if you have seen patterns that are maybe encouraging males to be a little more adventurous in their stylistic choices? Just out of curiosity, you know, I think … I mean, I don’t know, but personally I have brothers, that I would like them to be more adventurous, and it’s hard to get them into the space.

Audience Member: I don’t know if you have encountered patterns or had strategies, or even have some vision for even working with fashion industry to sort of expand, that fashion’s not just for women, but also for people who traditionally are not associated with fashion?

Cathy Polinsky: We started out as a women’s only business, and for the first five and a half years we only had women clients, and then about two, two and a half years ago, we launched our men’s business. It’s been really great to see that business growing and thriving. I’d say, I don’t know if it’s specific to gender or not, but we see some clients that start out and they have a specific sense of what they’re looking for, and as they use a stylist, over time, they get to be more adventuresome. And they might try new things and get some of these serendipitous things in their Fixes that they never would have picked off of a rack before, and try it on.

Cathy Polinsky: You know, we see this with our women clients, but I think we see it a little bit more so with our male clients. And I think that that is just kind of a fun thing about our service, is that something that you might never try on, something that you may see in a Fix, we don’t even show you what’s coming, because we don’t want it to taint your view of the Fix before it arrives at your doorstep. And sometimes there’s something that you never would have like wanted in your Fix, that you try on, and I’ve had this happen to me as well, that I’m like, “Oh, this looks amazing.”

Cathy Polinsky: And so I think that that aspect of discovery is a really amazing part of our service, that it works for those folks that may be stuck in their style, whether you’re guys, stuck in a rut, or even a gal, yourself. And so it’s kind of a fun part of our surprise and delayed-esque model. I hope I answered that.

Lila Bowker: Bing had a client recently that was awesome. Bing, you should tell that story.

Bingrui Tang: Oh, yeah.

Lila Bowker: Remember your client?

Bingrui Tang: Yeah. So I had a client who is probably in his 40s and 50s, and I got his first Fix, and he said, “Oh, yeah, so my style is a little bit conservative, really boring, but I want to make my wife happy, so I really want to stretch it out a little bit.” This is his first Fix, and he such high expectation, so I’m really nervous, and I share it with the team, I say, “Yeah, what do you guys recommend?”

Bingrui Tang: And somebody actually recommended a conversational piece, which is essentially pink flamingo prints. Yeah, and zebra prints, and things like that. So I actually sent a bunch of them to him for the first Fix. He returned all of them. I think I definitely went too far, but he said, “Thank you for all the pieces you sent, I think it’s a little too stretched for me, but I really get idea, and I really want to try it again.”

Bingrui Tang: And he actually immediately scheduled another Fix, and so assigned me as his stylist. So for the second Fix, because now I know where he would be more comfortable with, I actually pulled back a little it, and I think he kept all of the five pieces. Yeah, so I think, back to your point, I really think, yes, I’ve sent many, many pink shirts to male clients, and a lot of them end up keeping them, so I think, yes, the discovery part is really the fun part.

Lila Bowker: Awesome. Well I think we want to open it up so everybody has the time to chat and brag about themselves, and hear what makes everyone else awesome. The quick plug of, of course, we are hiring. If you work at Stitch Fix, can you raise your hand? Everybody who works at Stitch Fix, stand up and raise your hand. Yeah, so if you want to chat more about the roles we have open, aim for one of those human beings that just raised their hands.

Lila Bowker: But I’m excited to get to know more of you better. Enjoy. Yeah, and thanks for coming.


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