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

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

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!

“Unconventional Journeys in Tech” —  Girl Geek X Elevate (Video + Transcript)

Panelists:
Shanea Leven / Director of Product / Cloudflare
Farnaz Ronaghi / CTO & Co-Founder / NovoEd
Rosie Sennett / Staff Sales Engineer / Splunk
Angie Chang / CEO & Founder / Girl Geek X

Transcript:

Angie Chang: Great. Well, we’re all here. Welcome back to Girl Geek X, Elevate. This is our afternoon session. We will be talking about our unconventional journeys in tech, since it seems like that seems to be more common than people realize. The diverse pathways we have found to our jobs, that we get lots of people coming up to us, and saying, “Wow, you’re doing a really good job. That’s a successful career.” We’re like, “Oh, okay.” And people are like, “How did you get there?” So, hopefully, we’ll be able to share some of these stories, and I’m gonna ask each of our panelists to talk about themselves and share their backgrounds and their journeys and tell us their personal stories.

Shanea Leven: Sure, I’d love to start. Hi, everybody. I feel like I’m echoing.

Angie Chang: I think you sound fine.

Shanea Leven: Okay. Okay, cool. Hi. I’m Shanea, I started actually, my career, as an analyst and I was really interested in getting into tech. I actually started a digital marketing agency, way back when. That worked really, really well. I taught myself to code, for a number of years. The thing about myself, is that after starting, doing the entrepreneur thing, I wanted to get into tech in Silicon Valley, and so I ended up taking a job at Google, as a Program Manager.

Shanea Leven: Along the way, I really wanted to get into Product Management, except that the prerequisite at this time was that you needed a computer science degree. For myself, having gone on a ton of journeys trying to figure out how to navigate the tech space, one of the big questions was, am I technical enough? Do I have enough technical skill?

Shanea Leven: In order to get that product management job, I had a few options in front of me, which was to either go to a bootcamp, trying to gain additional technical skill, or get a computer science degree, or possibly get a technical Masters degree, which I know a lot of people face. For me, I ended up going back to school to get a Computer Science Bachelor’s Degree, while working full time at Google.

Shanea Leven: After, I became a Product Manager. I proved myself to gain that technical skill. I went on to work at Ebay, as a Senior Product Manager. I went on to work as Head of Product, at a startup, and now I’m a Director of Product at Cloudflare.

Angie Chang: Awesome. Farnaz, I think you have kind of the opposite story, where you started with the CS degree, you want to share a little about your journey?

Farnaz Ronaghi: Yes, of course. Hello, everyone. Yes, I come from a very traditional computer science background, but I did not start by choosing computer science as a major. They way education works in Iran is that for free. I’m from Iran, from Tehran, education is for free. However, we go through a very detailed, competitive University entrance exam. I was an A+ student, and I was very arrogant. I picked my top major to be double E, and I told everyone else, “I don’t need to pick more, that’s it.”

Farnaz Ronaghi: That was the paper I submitted. But my Mom, out of just being so kind, and out of love, filled out a few more degrees for me, a few more preferences. Her preference, her first preference for me was computer engineering. So that is how I ended up in computer engineering. Yes, I had that training, I had that Bachelor’s degree. However, the training did not make me a software engineer. It did not make me fall in love with writing code, and it did not make me confident that I am gonna be someone who will stay in tech.

Farnaz Ronaghi: But that happened, I came to the US for a graduate degree, and started a company. I learned through fire, by just being on the job, and doing it myself.

Angie Chang: Rosie, why don’t you share your story? I think you are definitely someone who has picked up things along the way, and has a very scrappy attitude to learning.

Rosie Sennett: Yeah. I was a Theater major, a technical theater major and I actually started out building props and costumes on Broadway, and then I kind of got distracted by coding–this is gonna show my age–coding macros in WordPerfect when it was green screen and it caught me.

Rosie Sennett: So, one day, I opened up the New York Times, and there it said, “Seven months. Learn to be a programmer.” So I signed up at Baruch College, and learned COBOL, and assembler language, and I got my first job at Information Builders in New York, answering the phones in technical support. In fact, I answered the phone so often like that, I would do that at home.

Rosie Sennett: “Information Builders, technical support. How can I help you?” I climbed that support ladder, and while I was doing that, the internet was born. So, I taught myself how to make webpages and marketing noticed that I was kind of messing with the website, and they decided I should be over there, and I discovered what marketing was, and what sales was, technical sales, and ended up as a Sales Engineer. I was there for 13 years and then I decided to go back to entertainment.

Rosie Sennett: I went back to entertainment, and I went west, and stayed and did some film stuff for a while. Now, I decided it was time for insurance and a paycheck again. Floated my way back in, and the last six years, I’ve been at Splunk, happy as a clam, doing sales engineering.

Angie Chang: Quick question. I think Sales Engineer almost feels like an insider term in Silicon Valley. Can you explain a little, for some people who may not be so aware, what is sales engineering?

Rosie Sennett: Sure. A sales engineer is the technical person on the sales team. So, sales engineers are the jack of all trades, the technical person who gets to do…. Our technical knowledge is super, super wide and deep, and the last bit that we concentrated on with the last customer. So, you know the products of the company, usually a vendor, that you work with, and then other stuff that you adapt.

Rosie Sennett: So, we’re the most technical really, that there is, ’cause you have to know a little bit about everything, and be able to present, and talk, and interface, and translate for the sales people.

Angie Chang: Cool, cool. What drives you forward in your career over the years? Like, what has kept you … I don’t want to say leaning in, but like, engaged to pull the levers, to figure out where to go in your career.

Rosie Sennett: I would like to say it was determination and a laser-like attention span. But actually, it was sort of distraction and curiosity, honestly. Now, in my sort of elder years, I have some very clear direction, I think. I’m actually really inspired by the young women coming in, and I’m really inspired by all the amazing stuff that’s happening at Splunk. I really landed in the most amazing place. Very lucky and feel really privileged to be working with the people I’m working with, and working in the programs that we’re doing at Splunk. Hiring like crazy, by the way, so come take a look at all the stuff, and apply.

Rosie Sennett: But yeah, I mean, right now, mentoring and being mentored by my mentees. The most amazing thing. No direction until I found direction, by watching all the amazing people who are now coming into the industry, honestly.

Angie Chang: Shanea, what has driven you in your career, and your product?

Shanea Leven: Yeah. So, a few things has driven me. I think from my perspective, I love building products. I like being able to have a lot of ideas all the time, about almost everything. I’ve found that product management is a really great medium for me, personally, between being an entrepreneur and working at a company.

Shanea Leven: I still get a lot of those same feelings that I got when I was an entrepreneur, with a lot less risk. Another thing that drives me is that, at this point in my career, I feel this personal responsibility to help the folks coming up behind, like, the generation that’s in right now. Some of us have to take a stand and stay and push through, so that we can make change for everybody else. So, hopefully our daughters won’t struggle with some of the things that we struggled through. That’s incredibly motivating to me.

Angie Chang: Farnaz, how about you, what do you think has been really driving your career forward, and the challenges? I know once, on the prep call you mentioned motherhood as something that has really changed the way you look at your career and managing your career and life.

Farnaz Ronaghi: Yeah. Well, and moving forward, when I started writing code on my own, the joy of creation was what was pushing me forward. But it was getting a little bit crazy. I was becoming, not becoming, I was the engineer who was taking six shots of espresso per day, and is coding 7 AM to like, 2 AM, and only sleeps five hours, just doing that all the time.

Farnaz Ronaghi: But then, motherhood, yes, it happened and while I was pregnant, I used to talk to my team and say, “Well, it’s no different. It’s just a baby. We will deliver it, and move on to becoming the same person.” Just like that. But when baby arrived, I actually learned that time is limited, there are other priorities in life, and I started prioritizing my work better.

Farnaz Ronaghi: The impact was actually surprising. It helped me make better decisions, because then I was always writing code, or working on something. I always thought time is infinite. So, there is a lot of time to get back to things, or to not close the loop on something. Or to not discuss it for today, leave it for tomorrow.

Farnaz Ronaghi: When baby arrived, I had to be more on point, and I had to make harder decisions to pick one way versus another and to be actually more deliberate about what I learned, what I spent time on, what technology I explore, and what I don’t. It has been helpful in that way to give me depths in technologies that I need to have depth in and leave alone parts of the stack that are not necessarily in my expertise.

Angie Chang: Cool. I also have a question for the panel, which is, what is a challenge you’ve faced, and how did you fix that? Rosie?

Rosie Sennett: Do I look the most perplexed? What was a challenge I faced? That’s a long road.

Angie Chang: Okay, I have another way to put it. How have you learned from a career mistake that you thought was a mistake that has turned out to not be a mistake? I think one thing we hear a lot at Girl Geek dinners is, “How do I know I’m going on the right direction?”

Rosie Sennett: Mm-hmm (affirmative).

Angie Chang: Or Shanea, do you have-

Shanea Leven: Yeah. I fail all the time. I had this conversation recently, every time I start a new job, or every time I start a new thing, it always seems like right at the beginning, there’s always a setback. Always. It came up in conversation, because like, “Is it just me?” Am I constantly getting setbacks right when I feel like I’m taking two steps forward? I don’t think that that’s the case.

Shanea Leven: I had a couple of really big failures, at least I’ve categorized them in my mind as big failures. I took the risk, but ended up, after seeing it through, I kind of failed up and that’s perfectly fine. It’s okay to switch, it’s okay to change direction, it’s okay to move forward. Sometimes you don’t know until you try and completely failed.

Shanea Leven: When I was actually getting my CS degree, I tell this story a lot, which is, I basically cried almost every night. It was challenging. It was one of the hardest things that I’ve ever had to do. It challenged my identity to my core, and I couldn’t be happier that I did it. Every day it felt like the worst struggle ever. But it made me better.

Farnaz Ronaghi: Actually, to build up on that point, knowing what is gonna work and what isn’t gonna work is impossible. We never do. We have patterns that we have seen in life, we have interests and excitements. So, we just go with that, and we push and push and push. There may be a time that we realize, “Okay, this cause is not a cause that is worth pushing,” and sometimes we push and we push, you know, what essentially makes you stronger. You come out, out of fire, feeling like you are unbreakable, because you just did that.

Farnaz Ronaghi: Guess what? Just a few months after, something happens that feels like the worst event of your life, and if we don’t let ourselves feel that we have failed, if we don’t feel ourselves burned and emotionally challenged by something, we will never learn. We will never have any opportunities to grow, because we are always staying in our own comfort zone.

Farnaz Ronaghi: When it comes to computer engineering, and writing code, it’s just everywhere. It’s a very male dominated industry, and as a result of that, in many places, the culture may not be as positive as some of us like it to be. Or, it may not be the culture that we are used to engage with and that by itself used to be a big emotional burden on me. “If I don’t belong here, why am I pushing?” But at the same time, when you push, when you show up, you change the ones around you, and you actually find your own people. Not everyone is the same. You’ll find a group of people who are like you, and you work, and you have fun.

Shanea Leven: Mm-hmm (affirmative).

Angie Chang: That’s a good point.

Rosie Sennett: I saw not too long ago, a cartoon that had two pie charts. One was completely red, you know, a circle, and it is said, “Life ending disaster that it felt like,” another pie chart was a little slice, it said, “Actual problem,” and the white thing, it said, “The thing I will learn from.”

Rosie Sennett: I discovered in my 30s that I have ADD and what that manifests as is a bunch of blockers, things that will stop you from being able to complete tasks, or keep your attention in places. It’s considered a neuro-divergence, right? It’s things that require methodologies to complete tasks that other folks just do. Paying bills, getting through an exam focused, practicing piano. For me, I don’t necessarily look at things as failures, because hitting walls, or for a long time, getting really crappy grades, for me, was like, “Mm-hmm (affirmative), okay,” and I got used to it.

Rosie Sennett: I would think, “Okay, well, I have to figure out a way around this.” More than having something be a failure, it was like, “Okay, that’s what that is. Now I need a way around something.” Or it was a lesson learned that I hadn’t realized before. Sometimes it was a hurdle I didn’t notice was there, and I went … stumbled over. Having recognized that hurdle, once I knew what was going on, I would then find a way over it, the next time. Right? By like, putting a lot of pillows, you know, and padding it.

Angie Chang: That’s a great way to look at hurdles and failures as ways to tell, this is an opportunity to try something new and figure out a new pathway to what you want. I’m wondering, what is advice you would give your younger self? Like, any resources, or something you would have done differently? A way that you looked at your careers?

Rosie Sennett: Listen to your elders. You can learn from them. Yes. That is good advice.

Shanea Leven: I think one of the things that has really hit home for me in recent years is, “Dare boldly. Take bold steps,” and they are scary. It’s really, really scary to put yourself out there, but ask really bold questions and do bold things, because you can completely surprise yourself.

Angie Chang: Do you have any examples for that?

Shanea Leven: Yeah. A lot of times in tech, we get beaten down a little bit, right? I was just leaving Google, and I was convinced that I could not do product management. So, I decided to go on a confidence kick. I was like, “I’m gonna get my confidence back.” I used to be a very confident person. What happened?

Shanea Leven: One of the things that I read, in, I think, The Confidence Code, was asking bold questions. I went to a product management meetup with all of the female VPs of Facebook, and I stood up, announced like, “How are you guys helping,” I didn’t get into Facebook at the time, but, “how are you guys helping move Facebook forward, because if you guys couldn’t get through the process when you interviewed,” which is what they all talked about, “how are anyone else supposed to get through, today? Like, what are the steps that you’re actually taking?”

Shanea Leven: Before I did that, I had to stop myself, because I think I blacked out a little bit, I was so nervous. But absolutely, it was a starting point for getting my hand raised, getting a good question answered. It started a really great discussion. And then, after, I took another bold step, and I basically just walked up to Deb Liu, and said, “Can I interview for you, again?” And she said yes.

Shanea Leven: I went through the interview process and didn’t decide to go to Facebook, but that step of just asking her for, in front of hundreds of other people, and getting a yes, was my first big step into that, and to this day, I continue to kind of live by that. ‘Cause you never know what the other person’s gonna say, unless you ask.

Angie Chang: That was a terrific point. Is there more-

Rosie Sennett: What’s the worst that could happen? Right?

Shanea Leven: Yeah, yeah. Exactly.

Angie Chang: Does anyone have a story of the time they asked for more? I know this was kind of a theme through the day, we had some people-

Rosie Sennett: That was really cool. That was great, when Leyla that was talking about that. That was amazing. [crosstalk 00:23:08]

Angie Chang: I’m wondering if there’s a specific advice–

Shanea Leven: I ask for more all the time. I actually had a conversation with another fellow woman in product management this afternoon. When I started, I made a certain amount at Google, and I didn’t know, I had no idea what the context was for asking for more, and asking for my worth. I started working there a little bit, and I realized, I’m like, “I think I’m underpaid.”

Shanea Leven: I vowed that I would never ever do that again, because I felt like I had missed my opportunity. In my next role, and the next time that I was able to negotiate for salary, I asked for a lot more, and I got it. The next time, I asked for a lot more than that, and I got that. Because again, taking bold questions and just asking the right question and being prepared, you never, ever, ever know.

Shanea Leven: Sometimes, you ask bold questions, and bad stuff happens. But it’s again, what is, all of the things can be fixed with proper communication. All of the things, if you’re able to kind of dare to, you know, put yourself out there. Then things can be mitigated and things can be fixed. But yeah, and also, as a PM, it’s kind of a skill to keep asking for more, and more, and more, and more all the time.

Angie Chang: It’s a great work skill, definitely.

Rosie Sennett: Yeah, it’s true.

Shanea Leven: Yeah.

Angie Chang: I am curious more, it seems like, there’s different types of people that we meet, that attend Girl Geek X events, some of them are new grads, some of them are doing the mid-career bootcamp career change. Some of them are moms coming back. Is there specific advice, or is it the same advice you’d give them on how to come into tech, or like, people always ask us, “How do I get into tech?”

Angie Chang: It seems like, to me, tech has changed in how people view it over the last decade or two. It’s become a lot more intimidating. Have things really changed that much, and is there any advice you would give to people who are looking to change their job title, or come into a new role?

Rosie Sennett: I did not have a standard background, as we said, in a time when you needed one. I was a total unicorn, and it was spoken of lots of times. The guy who hired me held on to my letter and my resume, and walked around, ’cause he was a character, and if I could do that then … you know. In fact, I gave talks about it at the school I went to, ’cause it was weird, that I actually made it through, to them.

Rosie Sennett: Now, it’s not so weird. If it’s of interest to you, and I said this to lots and lots of women at Lesbians Who Tech, who came up to us last weekend, asking the same question. You know, “But I do this, can I do that?” You will not know, unless you boldly go forward, as Shanea said. You’ve gotta just push through. I mean, we live in a world now, where you can actually just teach yourself stuff, and teach yourself enough stuff to boldly say, “I know how to do this,” and as we learned today, it’s just women who think they need to know all of it, in order to say, “I know how to do that.” Yes, you can do that, by just saying, I know how to do that. Right?

Shanea Leven: Yeah.

Rosie Sennett: And then eventually, you will know how to do that.

Angie Chang: Anyone else have advice for any of these Girl Geek X community people?

Shanea Leven: I think that some advice is, if this is the goal, and you really want this goal, just be mentally prepared that there are probably gonna be some challenges. If I could go back, I would try to have a support system for not doing it on your own, and asking for help when you need it. I read in the book, really recently, Dare to Lead, by Brené Brown, to have like, written on a card, what actually really matters to you? Whose opinion about you actually matters? Because you might get a lot of things …

Shanea Leven: I switched careers several times, and I was doing product management work before I had the title of product manager, and it took me eight months to find a role as product manager, even though I was already doing the job. That one simple, tiny little thing was enough, that no one wanted to take a risk. I’ve heard that it could take a long time to get what you want. Or, being able to test, get data back and user test like, how you craft the story of your transitioning in. Just be patient with yourself and have the support system to vent if you need to, or test some things out, or role play, or just taking those baby steps.

Shanea Leven: But don’t compromise what your goal is, which is why the first part of it, this is your goal, stick to it. A lot of people sometimes think that it’s good to kind of weave around, and “I’m gonna take this job, ’cause it’ll lead to this job,” and sometimes it’s just better to just be a little bit patient and just get the job that you want. I learned that, where a lot of folks said, “Oh, you’re transitioning into product management, you should go take a step backwards and be a junior product manager, because you’ve actually never had the title.” I was like, “Absolutely not, I’m not gonna do that. That’s crazy.”

Shanea Leven: Like, there’s no way that I’m gonna do that, because I’ve already been doing it. There’s something that I’m not articulating, this is not the right company, or something like that, where giving yourself the leeway to try things and then I went from Program Manager straight to Senior Product Manager and I did just fine. It’s just all right, it’s fine. All good.

Angie Chang: I’m gonna move on to some questions from our audience. What types of roles have you seen former educators move into when they transition into tech, and similarly, what advice would you give educators who want to move into tech?

Rosie Sennett: Well, a direct one would be education at a vendor. That would be an easy slide, internal or external. It would be the straight up, “I can do that.” If you want to take your resume and say, “I know how to teach.” ‘Cause trainer education, internal and external, that would be the way in, “I want a job today,” way to go. But any kind of customer facing role is gonna be actually on that. If you can teach and interact, pick up whatever … I’ve been in vendors this whole time, that’s my thing. So, the shortest from point A to point B, to me, is gonna be right in-

Angie Chang: That froze, unfortunately.

Farnaz Ronaghi: Yeah, I actually, I agree with Rosie. For a teacher, there are a lot of tech companies that would have good … not customer support, customer success roles, professional services roles, program management roles that basically are, you are building programs on technology. So, they are very technology oriented, and you will learn a lot of technical things, as if you join us at NovoEd, you will learn. But your core skillset, which is teaching, is critical to being successful in that role.

Angie Chang: That’s good advice. I think when I talk to people who are looking for jobs, a lot of times, people are looking, but at the same big brands, at their roles. But also, there’s a lot of early stage and medium sized companies that we don’t necessarily think about. They can be found on AngelList, or just by browsing on the internet, you can find smaller companies that will take a chance on people with resumes that show more different experiences, work experiences, life experiences. I actually recommend that path, as well. Then, after a few jobs, or years, maybe you will be at that big famed company, with the brand name. But to maybe start, and thinking about the smaller companies, and joining those roles for experience.

Angie Chang: Let’s see, another question we have here is, Shanea, knowing what you know now, would you still do a computer science degree?

Shanea Leven: Yes. Absolutely. For me, I briefly mentioned that it was identity, it went right against who I thought I was, by getting this computer science degree. My options were, the bootcamp, I already have a Bachelor’s in Business, and the CS Bachelor’s degree. What I found was that I’d gone as far as I could, teaching myself to code. I had done literally every online class that I could possibly do.

Shanea Leven: The ironic thing is actually, I actually taught, created online coding training, which is the crazy thing. For me, there was a different problem, that I didn’t realize that I had had, until I went to get the computer science degree. Which was, I grew up in inner city Baltimore, and my school system, I did not realize, failed me. There was a lot of things that with getting a computer science degree, and the way it’s taught now, that they assumed that I knew, and I did not.

Shanea Leven: I needed to go back to school, and I also have a little bit of dyslexia. Who knew? Until I was reading programming documentation for a long time, so I absolutely needed the CS degree to fill a lot of the holes and really, to ground my foundation of the theory, in addition to the actual syntax of languages. I would probably do it again. I don’t think the job that I have now, that I could have gotten it, without having the CS degree, and not having a solid foundation in the theory.

Angie Chang: Thank you. So we have a question here about, was networking a big part of your career pivots, or successes? It seems like everyone talks about networking like that’s the only way, but people feel it’s dirty networking for professional reasons. Can anyone give some thoughts on networking? Or what’s the best way to get a job or promotion?

Shanea Leven: Networking was important for me. When I decided to take the role at Google, it was because I actually kind of stalked a recruiter. Like, a friendly stalking. I called all the time, I was like, “Oh, we have to be friends now,” and we’re still friends to this day, ten years later. But just building relationships with folks, the job that I have right now was actually through a referral from two conferences that I met this person at.

Shanea Leven: I know Angie through friends of friends, and so I think networking is important. You never know what kind of doors we can open for each other, what kind of opportunities, and the mistake that I made was trying to think that I could do everything alone, and you really can’t. It’s about building a community, as opposed to thinking about it as networking, like, I have to go and do this.

Shanea Leven: It’s about building a community and you being a part of a community, as well. ‘Cause we’re kind of all in this together, we’re all trying to move forward together.

Angie Chang: Definitely. Farnaz, have you found networking to be important in your career?

Farnaz Ronaghi: I know it is important, however, that’s why I’m staying quiet, because I cannot be the one recommending people to do networking, ’cause I am the worst at it. I’m actually the one who will sit behind her computer for as long as possible, the introverted of introverts. Don’t see me talking like this, we are behind a computer, just … we can’t see each other in person, and we’ll see. But I do agree that it is about–just going through the startup experience, founding a company, and six years into it, I actually even, I look back, and every single people that we raised money from, people who became our customers, those relationships that I basically had to build because of my work, for advancing the actual work that I was doing, not that I was at that–

Farnaz Ronaghi: They are the ones that I go back to for, “Oh, I want to look around, where should I look?” Or, I’m looking for a partner, I’m looking for an engineer, so it is very important to be able to build that network. However, many of us have challenges with the concept of going out and talking to what feels like strangers. I don’t have any medication to help with that. But I do recommend everyone to go out there and just practice it, because I was very, very introverted. Now, at least when I take tests, my extroversion is more than introversion. So, it changes and you start doing better.

Angie Chang: Rosie, do you have anything to say about networking?

Shanea Leven: I do. I think in general, it helps to have, it’s interesting, having sort of kind of bopped back and forth, I mean, over long periods of time, between the software industry and the film industry, building a network of people who, I guess, in essence, they are acquaintances. They’re people who you know from cocktail parties, in the film industry, or conferences in the tech industry, who you see at just these things, and you recognize them visually and you don’t necessarily have anything to give or take from them, but you see them and they’re familiar.

Shanea Leven: You do, one day, get to call them up and say, “Hey, do you know this person? I’m looking at their resume,” or, “Well, how’s it going over there?” You get to actually make that, pull that ticket. It’s a good thing to have. So far, it’s been where people say, “Hey, do you know this person? They seem to be connected to you, do you actually know them?” And I’ve helped people get jobs.

Angie Chang: Okay. All right. We’re gonna be wrapping this up, just, I think we’ll take one more question. I think we have a few more minutes. I think this one may be good for Farnaz. We have an attendee who’s found that it’s hard for former educators to move into edtech, as many of the roles require sales experience, or highly technical skills. Even hard to get PM and customer success roles, any advice?

Farnaz Ronaghi: Even customer success and PM roles?

Angie Chang: Yes.

Farnaz Ronaghi: Well, I think, first of all, try sending your resume my way, and then I think, my advice would be, it would be good to look for instructional design or product, or program management roles in smaller companies, in startups that are more willing to invest in people who may not have the track record of success, but who will be able to be there and put their heart and soul in owning the results. We actually do that, with people who are in our customer success and professional services team, they come right from being a teacher to being in a position of working with our customers directly and building programs for them.

Farnaz Ronaghi: It’s actually very interesting. Like, with a bit of onboarding, they do such amazing work. I have no doubt that it works. However, try smaller companies.

Angie Chang: Okay, one final question. This’ll be a fun one. What’s your advice for bouncing back when you do ask for more and it backfires? Like, what is your coping mechanism, self care, how do you get back up?

Farnaz Ronaghi: Well, I think, the thing is that first of all, I think when you want to ask for more, just ask it with data. Meaning, when you feel like you are underpaid, there are Glassdoor reviews that give you average salaries and top of the market, below of the market. There are job descriptions from all sorts of companies with salaries on them that you can use as a data point that, for example, you are underpaid.

Farnaz Ronaghi: Or if you are asking for resources, like just go with data that backs your story, and if you really have a point, but you get the push back, for no reason, what seems like no reason, I actually think in those situations it’s good to just get it out of your system, talking to friends, getting coaching and mentorship. If you actually reiterate the conversation with a mentor, with someone who has, not just a mentor, but someone who has asked for a salary change before, and you feel like you had the right, and you feel like they also agree with you, that your argument was good, your manager didn’t have anything good to say in response, I actually think that it is fair to not think of yourself as just a disposable resource that can be treated in any way.

Farnaz Ronaghi: Just go out there and interview and look for other jobs, and then bring them an offer. You know? Push as hard as you want to push, just as long as you are doing it logically, you have data, and you are sharing your experience with someone else, in the role.

Angie Chang: Does anyone else have last feedback for how to bounce back from a potential rejection?

Shanea Leven: I think Farnaz is totally right. Doing data, and having the conversation. I think that moving, or separating in your mind the emotion of the rejection from the actual negotiation, or the thing that you’re asking for, is something that I really struggled with. They’re two different things. Right? Like, maybe there’s a reason, maybe there isn’t a reason, or maybe there’s a reason that someone isn’t telling you. But that doesn’t necessarily mean that you shouldn’t deal with your emotion around it.

Shanea Leven: That could just be, for me, it’s talking to someone, it’s venting. It’s reminding myself that they didn’t reject me personally, but they rejected the thing that I proposed. Or, it’s maybe not … it’s a no right now, but not a no forever. Or, like Farnaz said, get another job. Just separating those things out is helpful.

Farnaz Ronaghi: You know, I have one more thing to add. You made such a good point. I personally, I find having cheerleaders in life, very, very helpful. I have one cheerleader. One best friend, who rarely tells me I’m wrong. So, whenever I’m going with my emotions high, so angry at the whole world, because of the unjustice that they just did to me, for whatever reason, he will tell me that I was right, that I’m smart, but I have to work on saying it better.

Farnaz Ronaghi: Or, “Why don’t we say it this way?” Like, I just empty the emotions somewhere, and we get to problem solving together. I think finding yourself a friend, a cheerleader would be very, very helpful to deal with the emotion, because it’s very hard not to feel the rejection. But you need to move on.

Rosie Sennett: Yeah, yeah. I think being really clear that your argument, if we take it out of the salary area, broaden it for a second. Being really clear that you know that whatever argument you’ve brought for this decision was delivered to the person you’re delivering it in a way that they can hear it. You’re gonna deliver it to that person, in a way they can understand. If it’s somebody who can understand an emotional argument, then go ahead and deliver that. But if it’s somebody who can not, do not deliver an emotional argument, because it will fall flat. If it’s someone who needs statistics, then show up with statistics. If it’s someone who rejects whatever it is outright, and you feel that you have presented it, you know that this is a logical argument and you’re being dismissed, then yeah, you have a bigger decision to make.

Rosie Sennett: If you’ve been waved off, that’s a whole ‘nother ball of wax. Don’t confuse that with your proposal being rejected. Two different things, really. I think that’s the clear thing, is that one thing is personal, one thing’s not and none of it, in the end, is really personal. As Shanea said, 90 percent of the time, that decision, especially if you’re an individual contributor asking for something that is directly affecting only you, you may have no idea how or why that decision was made, and it may never come to you. So, that information should never necessarily turn into us and them. It should never then go out and become announcement of us and them, that has to be processed, because that’ll mess with you, too. That was what I was thinking while everybody else was kind of talking.

Angie Chang: Okay.

Shanea Leven: I’d also read Crucial Conversations. It’s super helpful.

Rosie Sennett: Yes, yes. Very good, very, very good.

Shanea Leven: Very tactical of like, how to go about these things and some of the tactical things we’re talking about, splitting emotion and like, the actual execution of the conversation. Changed my whole life. I’d recommend starting there.

Rosie Sennett: Super cool.

Angie Chang: Thank you all for joining us today. I know it’s Friday. Thank you so much. We’re gonna be … just tweet at us ggxelevate and we are gonna be moving into our next session, so thank you so much for joining us. See you later.

Rosie Sennett: See you.

Farnaz Ronaghi: Thank you all, bye.

Rosie Sennett: Bye.

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.


Our mission-aligned Girl Geek X partners are hiring!

“A/B Testing Cheap & Easy with Open Source”: Dena Metili Mwangi with Sentry (Video + Transcript)

Speakers:
Dena Metili Mwangi / Software Engineer / Sentry
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X

Transcript:

Sukrutha Bhadouria: Hi, Dena, how are you? You’re muted, so you need to unmute. So, hi everyone. I’m Sukrutha. A couple of housekeeping notes as we’ve been doing through the day. We’re recording all these sessions and we’re going to have the videos ready for you in a week. I saw some of you asking questions about the previous sessions. We will also have the slides for you to be able to view. Please share the fun that you’re having, whether it’s through the content, or selfies of your viewing party, or you watching at your desk on social media using the hashtag GGXelevate.

Sukrutha Bhadouria: We’re going to do Q and A at the end if we have the time. So, please post your questions. At the bottom, there is a button for Q and A. If we don’t have time for it, we’ll do it over social media, and I’m sure Dena would be willing to do that for us. Also, we have a job board on our website, GirlGeek.io/opportunities. So, please check it out.

Sukrutha Bhadouria: Now our next speaker is Dena. I’m super excited. She’s a software engineer at Sentry where she works on the growth team. Fun fact, she graduated from Hackbright where she learnt–did a ten week program studying Python. Before that she was a graduate from Duke University and was working as a research analyst at World Bank. Her talk today is about A/B Testing: Cheap and Easy With Open Source. And I’m sure everyone is excited to learn more about this.

Sukrutha Bhadouria: So, thank you so much, Dena, for taking the time.

Dena Mwangi: Hey, thank you so much. I’m going to go ahead and bring up my slides. Can you hear me okay?

Sukrutha Bhadouria: Yes, we can hear you.

Dena Mwangi: Excellent. Okay. Hi, guys. It’s so nice to be here with all of you. Happy International Women’s Day. Today we’re going be chatting a little bit about A/B testing and specifically how to do it cheap and easy with Open Source. You can find me on Twitter as Dena Mwangi, or on Linkedin. Feel free to connect.

Dena Mwangi: So, before I jump in, just a little bit about me. As was mentioned, I’m a software engineer at Sentry.io on the growth engineering team. I did go to boot camp, and that’s how I got into tech. I went to Hackbright and I think there are few Hackbright grads in the audience today. So, hi to all of you. I’m also a data enthusiast. I am into quantified training. So, I really like thinking about data and-

Sukrutha Bhadouria: Dena, sorry to interrupt you, they are soft on your volume. Can you speak up or move the mic over.

Dena Mwangi: Yes.

Sukrutha Bhadouria: You may need to start again.

Dena Mwangi: Okay.

Sukrutha Bhadouria: Yeah, this is better.

Dena Mwangi: This is better? Okay.

Sukrutha Bhadouria: Yeah.

Dena Mwangi: Thank you so much for the heads up.

Sukrutha Bhadouria: Thank you.

Dena Mwangi: Awesome.

Dena Mwangi: Yeah, so software engineer, bootcamp grad, studied economics. So, I really like thinking about the world in terms of data, which is how I ended up in the role that I’m in now. I also really like thinking about diversity, and inclusion, and how to do tech for good. So, I really liked the talk that we just had about AI. So, if you want to talk about any of those things, feel free to connect as well.

Dena Mwangi: Our agenda for today, we’re going to go through what and where is A/B testing? We’ll talk through the general MVP requirements, if you want to build your own. And then we’ll talk a little bit about PlanOut, which is an Open Source framework that you can use to help you out.

Dena Mwangi: So what is A/B testing? Simply put, it’s just a way of comparing two or more versions of a thing to determine which performs better. And the magic sauce that lets us do that is we are able to randomly assign samples of people to each variation and use statistical analysis to evaluate how legit our results are. If we do this correctly, we’re able to take the insights that we get from our small samples and say something meaningful about our larger population, which is what we’re really interested in. You’ll also hear this called split testing or bucket testing.

Dena Mwangi: Now, where is A/B testing? And the answer might freak you out. It’s everywhere. So, as you are using your applications, as you’re surfing the web, tons and tons of organizations are running A/B tests on us all the time. But, for the most part, it’s because they want to make sure that we’re getting the best out of their products that we can possibly get.

Dena Mwangi: So, one example of this is Netflix. So, while you’re Netflix and chilling, Netflix is running tons of experiments. One of these is what image they show when you’re surfing and trying to figure out what show you want to watch. So, they’ve played around with the title they show you, the image that they show you, and they run experiments to see which one gets the most clicks and which one ends up with more people watching it. The quick example of that is with a show that I love called Sense 8. If you haven’t seen it, you should.

Dena Mwangi: So, they ran this when they first had this show out. And this is just three of quite a few variations and buckets of this that they experimented with. So, you’ll notice that they’re playing around with the text, they’re playing around with the image that they’re showing, and they set this through all their markets. So, if you look at this, try and think about which one of these appeals to you the most. And, in the U.S., if you chose the middle one then you’re in the majority.

Dena Mwangi: So, most people in the U.S. ended up picking the middle one. So, most people who saw this ended up clicking on it and actually watching the show, which is what Netflix cares about. But as with A/B testing, you’ll find that, once you start digging into the data, there is often quite surprising insights to be found. So, while the middle one did the best in the U.S., all of these were winners in different markets. So, the last one won in Germany, the right one won in Brazil, and this actually tends to make a big difference.

Dena Mwangi: So, they saw, once they started running these experiments, a 20 to 30% lift in engagement with people clicking on these titles and actually watching the shows. So, you can make a difference.

Dena Mwangi: One more example for that, quick note, this stuff is hard. Computers are really hard. They do this with tons and tons of different shows and this is one where it kind of went awry. If you’ve seen Tidying Up with Marie Kondo, maybe this is the vibe you get, probably not. But this was a case where they kind of mismatched the image that they were showing in their tests.

Dena Mwangi: So, one other quick example of where A/B testing is is an example that’s kind of famous with Google where they weren’t quite sure which shade of blue they were going to use. And I think things like this are why A/B testing actually has a bad rap, because people think, really? Are we going to spend our time thinking about shades of blue? And actually, yeah, we are. Because this actually translated, by figuring out which one worked the best for their users, it translated to an increase of 200 million dollars in ad revenue. So, A/B testing can end up being quite profitable.

Dena Mwangi: So, if I’ve convinced you that perhaps A/B testing is something that could be useful for your organization, what do you do next? How do you even begin? So, let’s talk through some of the MVP requirements. Really, it boils down to two things. You want to think about how you’re going to bucket people and how you’re going to do it correctly. And the second thing you’re going to want to think about is your data, the data that you’re getting out, because you need to know which of your variations performs the best.

Dena Mwangi: So, for the first bit, you want to think about randomization. You’re going to be randomly assigning your users as they come through, but they’re going to come through your website multiple times, hopefully. And so, you want these randomization, these assignments to be deterministic and counting is hard. So, this is a nontrivial task. As you scale out your experiments, you’re also going to want to account for parallel or iterative experiments. So, if you have a user that is going to be exposed to multiple parts of your site, you want to be very intentional about what you’re showing them.

Dena Mwangi: As far as the data, you want to think about how you’re getting the data out for analysis so you can actually decide who wins. You want to think about how you’re linking it to your internal metrics. So, like with the Netflix example that we saw, they really care about people actually watching the show, and they really care about the people who are paying them, how much they’re paying them. So, you want to have a way of linking the success of your experiments to your internal metrics like activation and paid users. And you want to think about how are you going to be seeing this? What does your analysis look like? Do you need dashboards to make that easier for you and your team?

Dena Mwangi: When we thought about this, we had to make a decision between whether we were going to build something or whether we were going to buy something. And there’s pros and cons to both of these situations. So, with buying, of course, it costs money. That’s a downside. These can be pretty pricey. They run up to 40 to 60K sometimes. But, on the plus side, they’re almost ready out of the box. Bit of a negative is you have to do a little bit of extra work to link them to those internal metrics, and you have to also think about do you want to send all your sensitive information about your users out to a third party? If not, which you probably don’t want to do, how do you get that information from the experiments back and connected into your internal metrics?

Dena Mwangi: As far as building it, the downside is, well, you have to build it. So, you have to customize it to your exact use case, which is great, but that takes engineering resources, building and maintaining it. And again, counting is hard, so you have to think about how you’re going to be implementing that correctly and validating the results that you’re getting.

Dena Mwangi: So, when we thought about that at our institution, we decided to use Open Source for the first section, for the first problem of how to bucket people correctly. We don’t want to think about that. We figured if there was someone who has already done the work of implementing that, why reinvent the wheel? So, for the first part we used Open Source, but for the second part, we kind of had our data pipeline already in place. And so, we were able to leverage our existing infrastructure and just hook that into place.

Dena Mwangi: So, what did we use? We ended up using an Open Source framework called PlanOut. It’s Python-based and it’s from Facebook. It’s been around for a few years. So, it’s had various ports from other teams. For example, HubSpot built one for JavaScript. But the best thing about PlanOut, and the thing that really sold us is that it’s low entry but high ceiling. So, you get the bare minimum to get you started running experiments very quickly, but it’s extensible. So, you’re able to scale it out to lots of users, and you’re also able to have lots and lots of add ons.

Dena Mwangi: So, things that you get, you get random operators, you get deterministic assignments for your hashing, you get name spacing. And to do all this, it’s really simple. If you’re familiar with Python, you’re able to create new experiments simply by inheriting from a base experiment class and modifying the assignment logic.

Dena Mwangi: But, what you don’t get is you don’t get a GUI. So, everything is code based and every time you want to create a new experiment you have to write it out in code and write it out in Python. You also don’t get any post experiment analysis assets. So, the nice dashboards to help make your analysis life easier, those don’t really exist, and that’s something that you have to implement on your own.

Dena Mwangi: So, I find it best to learn about a new tool by walking through an experiment. So, we’re to walk through a really quick one with a pet adoption profile. So, suppose you had an app that was trying to get a pet adopted. Suppose it’s this guy. And you think that, if you play around with the image that you’re showing, we’ll be able to have more interest and more clicks on this lovely cat’s profile. You also want to have a blurb with it because why not? So, we’re going to have these two images and these two blurbs, which gives us four options that we’re experiment and randomly showing to our users as they flow through.

Dena Mwangi: If we wanted to run this with PlanOut and actually have an experiment up and running, this is pretty much all that it would take. Put some code, it’s always scary when you see code on your screen, but don’t fear. We’ll walk through it really quick. So, basically what this is is it just pulls from a simple experiment class from PlanOut, and it gives you all your random operators all in this one thing.

Dena Mwangi: What you have to do on your end is tell it the required rules of engagement. So, tell it what you’re trying to do, who you’re trying to experiment on. In this case it would be a user ID. Tell it what your varying. In this case we’re varying an image and a blurb. Tell it also how you want to vary this. And, in this case, we’re going to be using uniform choice. We don’t really care, 50/50 split with each one. And that’s all it really needs to know.

Dena Mwangi: But where does this actually go in your code? So, if you played around with Flask, for example, wherever it is that you’d be using this image and this blurb, regardless of what language you’re using, that’s where this would go. So, in this case, if you have a route, then you just throw in your assignments and you’re able to pull directly from them and put them into your template.

Dena Mwangi: But okay, so you did the thing, but where’s your data? For this, all you have to do is tell it how to do the logging in your setup. So, you tell it where you want to log all the things, what file you want to send it in, whether or not you have a data pipeline or not, you have this option of just throwing into JSON. So, as people are flowing through your website and seeing all the options that you’re showing them as you’re randomly assigning them into particular variation, all of this is getting logged and put into a JSON that looks like this that will make it easier for you to pull from it later on.

Dena Mwangi: And the important bit here is that you’re able to see what the image was that they were assigned and what the blurb was that they were setting. Also who they are and what time it was, but really these are the two main things that you care about. And that really is it. That’s your first experiment, and you’re ready to go forward and A/B test all the things.

Dena Mwangi: But, before you do, I will leave you with a few A/B testing sanity tips that we’ve learned on my team that have made our lives a lot easier. The first being, you really want to have well defined metrics of success before you start running your experiment. I think a lot of teams get really excited and they think, obviously, this is going to be great. I’m sure it will be a success, but they’re not very clear on what success looks like. So, before you run any experiment, be very clear to write this down and know what your metrics of success are.

Dena Mwangi: The second thing I would advise is to make sure that you’re doing all your experiments in small, measurable iterations instead of doing large sweeping changes. Sometimes this isn’t always possible. For example, if you have an experiment that’s being run that requires a lot of design or it’s very greenfield, then you might have to do a lot of front end work, a lot of front end cost work. But, for the most part, you really want to be doing this in small measurable iterations. That way you’re able to attribute what exactly changed to give you the lift that you might be seeing in your data. Otherwise, it gets very confusing. Was it the button color that you changed? Was it the language that you changed? It’s unclear. So, do small, measurable iterations.

Dena Mwangi: The last thing is, A/B testing is not a silver bullet. Data is one thing in your toolbox. It’s not the entire tool box. So, this really should inform your decisions. It shouldn’t be the one guiding light. So, if you see a lift in an experiment, for example, you really want to think about it and look at it in context of the whole picture of your application and what you’re trying to answer. So, with the Netflix one, for example, they could have said, oh okay. This one particular one won in the U.S. Let’s do this everywhere. But instead, they dug deep and they were able to desegregate and see that, actually, they had different winners in different markets. And they were able to leverage that information and go forth with that and be a bit more successful.

Dena Mwangi: Thank you so much for your time. It’s been so great chatting with you. Happy International Women’s Day. If you have any questions, I’m happy to answer them.

Sukrutha Bhadouria: Thank you, Dena. This was amazing. What a fun image at the end. All right. So, there are a few questions. So, let’s roll through them. Susan asks, do the logs include the end action that is the click event of user wanting to adopt the cat?

Dena Mwangi: That’s a great question, and no it doesn’t. So, this really logs the exposure. So, you would have to do the extra step, which is sometimes non trivial, of having to connect the exposure with the actual action of interest. So, what we do is we have lots of different analytics events. So, in addition to the exposure one, we think about what we want them to do, and what success looks like, and we log that as well separately. And, when we run the analysis, then we combine the two.

Sukrutha Bhadouria: Got it. How do you know what is a good sample size of data to test with?

Dena Mwangi: So, this actually, there’s equations that we run. It’s pretty standard like statistical modeling that you can just like put number in, figure out what power you want, figure out what level of statistical significance you want that you’re comfortable with, and play around with that. And that will spit out what sample size you should be going with, at the bare minimum.

Sukrutha Bhadouria: All right. And is there any project too small for A/B testing to be useful? For example, a small app in private data with only 20 users?

Dena Mwangi: Yes, unfortunately. So, with the statistical significance to be able to say something that’s truly meaningful, you would have to run the numbers and see like what the minimum number would be. But I think 20 would definitely be too small. You want something in the hundreds and up.

Sukrutha Bhadouria: Yeah, that makes sense. And finally, what did you find most challenging when you transitioned from bootcamp grad to working full time as an engineer?

Dena Mwangi: That’s a great question. That should be a talk all on its own. I think for me it was still like a steep learning curve, but it was getting really comfortable asking questions and asking one more question than you feel comfortable asking, and getting over that fear of being seen as not knowing enough or all the imposter syndrome things that come with being a bootcamp grad and being in your first tech role. I think, honestly, that was the biggest thing is just getting over that and saying, it’s fine. I just need to learn the things. So, I’m going to ask the questions.

Sukrutha Bhadouria: Thank you so much, Dena.

“Office Manager to CPO – Keynote”: Shawna Wolverton with Zendesk (Video + Transcript)

Speakers:
Shawna Wolverton / SVP, Product Management / Zendesk
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X

Transcript:

Sukrutha Bhadouria: Hey, Shawna.

Shawna Wolverton: Hello.

Sukrutha Bhadouria: All right, so gentle reminder of a few things, so I’m Sukrutha. I’m CTO of Girl Geek X. We’re recording these videos. They’ll be available for you in a week. Post your viewing party, selfies of you watching this, and any other learnings that you have on social media with the hashtag GGXElevate. We’re going to do a Q and A at the end, if we have the time. So, use the Q and A button at the bottom to ask questions. If we don’t have time, we’ll answer the questions later tomorrow or later this week. So, please check out our job board on GirlGeek.io/opportunities. Yeah, that’s it.

Sukrutha Bhadouria: So, let’s enjoy Shawna’s talk. Shawna, Senior Vice President of Product Management at Zendesk. Before which she was the chief product officer at Planet. Prior to that, she spent 14 years at Salesforce, going from the first localization manager to growing into being the Senior Vice President of Platform Product. So, that was a great growth, and Shawna is going to be talking to us today about her growth from office manager to CPO in over a thousand steps. Thank you, Shawna, for making time for us. I’m super excited.

Shawna Wolverton: Thank you. Awesome. I will just jump in, since we’re running a little late on time.

Shawna Wolverton: Welcome, everyone. I hope you’re having a great day here. Thank you so much to the Girl Geek X crew for hosting today. I’m really honored to be here. And, as Sukrutha mentioned, I have had quite a career, not always the one I planned. It’s been an interesting odyssey, and I thought I would share a little of that with you.

Shawna Wolverton: And really, this is the only good place to start, because so much of my career really does come down to this. I think there is some myth out here that we can all– we’re self-made, we’ve worked hard, every accomplishment we have came–just sprung forth from our amazing intellect and crazy persistence. And I don’t want to discount that, but the universe is large and we are all very, very lucky to have been born in this place and time. And so many people have helped me along the way, and I’m incredibly grateful to them.

Shawna Wolverton: But really, when I think about career plans, we just heard a little from the good crew of Grand Rounds about planning. And so much of life is really a fantastic stochastic kind of adventure. And we can’t always get all of the steps right for how we want to get there. But, at the end, there’s some really great goals and great milestones that we get there.

Shawna Wolverton: So, in my lifetime, we had an entire industry come and go. We had entire things– dotcom dissolution, number one. We had a grand financial crisis. Entire industries are gone. So, we really have to think about agility. We do it a lot, in terms of how we do our work. But I think we sometimes kind of get a little locked in and forget that we wouldn’t make a solid waterfall five year plan to do anything else in our lives. And being agile in our careers is really critical.

Shawna Wolverton: And there’s no one right way to go, and sometimes things change. I spent the first 20 years of my life assuming I was going to be a physician. It turns out my university transcript and I had very, very different ideas about that future. And there was no product management Barbie set when I was a kid. And coming out of school with my fantastic degree in Russian studies and political science didn’t set me up for anything really obvious. And it took quite a bit of experimentation and curiosity. And I think that early curiosity is what has also kind of driven a whole bunch of my career. A strong desire to learn new things, and an absolute hatred of being bored has been probably the two biggest things that have driven my career to date.

Shawna Wolverton: And I think we think a lot about driving our careers. We hear about this all the time, right? What are you doing to drive your career? What are the activities that you’re doing? I think we get a little lost sometimes and lose the journey. I like car racing, maybe you don’t, but I thought this was a really amazing analogy, right? There is a fantastic race that goes from Paris to Dakar in Africa, and you have this amazing adventure. And you have a whole crew that comes with you, because you assume your car will break down, and you will go the wrong way, and it will take much longer than you anticipated. And it’s glorious. And the sort of alternative is this ring of never ending struggle.

Shawna Wolverton: And I think, when you think about your career and how you progress through it, kind of an adventure attitude and a fantastic kind of see what will happen is a great way to approach things and make sure that you’re not missing out on the amazing experiences that come sort of between those promotions. I think we sometimes put milestones in the ground about where we’re supposed to be at certain points in our lives. And, when we don’t get there, we can be really disappointed. And I always think that’s really unfortunate, because there is so much to learn along the way on these journeys.

Shawna Wolverton: My career was clearly not a straight line. I did start out as a localization project manager. You can see I did that job three times in my career. Sort of moving on from it, finding myself in a position where it was skills I needed to rely on to kind of go back into the job market when things had changed. I certainly didn’t expect to learn much that would help me in my career, taking that nine month apprenticeship as a handbag manufacturer with an Hermes trained designer. But, my goodness, did I learn a tremendous amount about human nature, about satisfying the wants and needs of customers in a way that I don’t think any other technology job would have given me.

Shawna Wolverton: And it was a tremendously long time between that first localization manager job and that SVP of Product manager job. I spent 14 years in the same job–or not in the same job, but with the same company, at Salesforce. And I think it’s another thing we think a lot about is, have I stayed too long? Have I stayed long enough? And I think that a lot of those thoughts are silly. If, like the previous speakers were saying, if you find the thing that matters and that gives meaning for you, then you keep going, and that’s what gets you up in the morning.

Shawna Wolverton: I like to tell people that product management is a job that by all measures is pretty terrible, right? If everything has gone swimmingly well, you’ve reflected that back out on your developers, your sales engineers, your sales team, your marketing team. And, if it goes absolutely sideways and the organization is at a loss, you stand up in front of the room and it’s all you. But what I found is that there was this fire in my gut that was about helping customers help their customers. And I couldn’t imagine doing anything else. And I think that love of my customers and that sort of obsession with helping them is the other sort of huge part that grew my success.

Shawna Wolverton: And then, I think this is a big thing that we don’t talk a lot about and that’s the–well, we do. We talk about it a lot. Who am I kidding? But having it all is a lot, right? You can have a family, and children, and a job and it’s not easy. But I think a lot of the things that we tell ourselves and a lot of the things that the media tells us about what it’s like to be a working mother are really bananas. There is this myth that we’re going to go out on maternity leave and we’re going to come back and we’re going to be distracted and we won’t be as good as we were. And there is this amazingly strong body of scientific research that’s happening about what happens when, not just women, but men and women come back from parental leave or after the birth of their children.

Shawna Wolverton: Amy Henderson, who is the founder of a company called Tendlab that really focuses a lot on sort of parenting in the workplace, has done this amazing research. And the women primarily that she spoke with, the senior women, all with hindsight, were able to look back and find an acceleration in their careers post childbearing. And I think, whether you have children or not is a totally personal choice. But I want everyone to know that it’s not, I think, the horrible, awful, career ending thing that we’ve thought it was for the longest time. And there is a fantastic thing that can happen. That little J curve was definitively, after my daughter was born. And, at 12, we’re having a fantastic time together in a way that allows me to be here and also there, and to be a fantastic role model for her about what it looks like to be a woman who is in the workforce.

Shawna Wolverton: And this one is important to me. It’s, success is not a pie, right? I think oftentimes we think for us to win or to get a promotion or to get ahead, someone else has to lose. And it’s not like there is this finite amount of success where we get our pieces of the pie, and we eat it, and then they’re all gone, right? It is really more of this sort of random, infiniteness that is more pi than pie. And so much of I got to where I am is about the people who put a hand out to me and who supported me in my career.

Shawna Wolverton: You heard from Leyla and Jen earlier. A huge part of my network of support in my career. And it’s incredibly important, I think, for us to think about how we turn around and put our hands up too for the next group of women coming up in the world.

Shawna Wolverton: So, yeah. That’s sort of my journey through my career. I think I went a little fast. I woke up this morning with a cold and I’m on a little cold medicine. So, maybe I’m going a little fast today, but it might leave us with a little more time for Q and A.

Sukrutha Bhadouria: All right. Shawna, that was amazing. My video feed is taking a bit of time. Hi.

Shawna Wolverton: Hi.

Sukrutha Bhadouria: You’re so awesome. I love the fact that you said that success does need to be shared, for sure. Sometimes we’re a little bit hard on each other, right? And we get a little competitive and we don’t help each other out enough. What has been, I guess, for you–I have a question. What has been, for you, the most fun role that you had while you transitioned over the years?

Shawna Wolverton: I think almost every job I’ve had I’ve found the fun. But I think I have a kind of warped sense of fun. Things that are really, really hard are fun. So, at Salesforce, we had a giant project to rewrite the entire front end of a 17-year-old software product. And it was an entire company motion, took me way out of my comfort zone, and it was hard. But, at the end, it was just so fantastically rewarding. And the fun part was really so much about the people and conscripting a sort of unwilling team onto team lightning, and then going out in the world and talking to customers about it.

Sukrutha Bhadouria: Yeah.

Sukrutha Bhadouria: There’s another question. What is a mistake you made in your journey that you could share with us?

Shawna Wolverton: I think one of the mistakes I made was thinking that I could go fast. Like there were times in my career I got a little ahead of my skis. Where I saw other people getting promoted, I let my ego get in the way, and, when I didn’t get a promotion I asked for, I took it really personally. I was devastated. And, in hindsight, I’ve realized that extra year spent in the job before I promoted was important, and I learned a lot. And I wasn’t ready when those things had happened. So, I think–yeah. Getting a little too attached to my own ego and letting some of that go.

Sukrutha Bhadouria: Yeah. It happens to all of us, I bet.

Sukrutha Bhadouria: Okay. We have another question that says, how did you get the opportunity to be a handbag apprentice for Hermes? How does one find additional opportunities like that, Shawna?

Shawna Wolverton: Strange things happen when you take City College classes for fun, and you meet interesting people, and when you’ve been laid off, and you have a little bit of severance, you can say yes to some things that you normally wouldn’t say yes to. I think I probably would have stayed longer, but my husband started sort of like, you know, it might be time, Shawna, this little adventure you’re on.

Sukrutha Bhadouria: So, what do you think kept you going when things were not going the way you meant for them to go? Like how do you keep yourself positive?

Shawna Wolverton: I mean, I think, for me, it’s about what’s always been important to me. And what I found when I became a product manager, and why I’ve never wanted to do any other jobs since I started is that connection to customers. And knowing that, even when things are really hard or things aren’t going great in the office, that the things that I do have impact on real human beings. And I was lucky enough, over the course of my career, to really get to know–I count a number of former customers as friends today. And getting to know how the things I did impacted their lives, and that really is the thing that keeps me going.

Sukrutha Bhadouria: All right.

Sukrutha Bhadouria: So, some more questions pouring in while I’m reading them out. So, what is the biggest leap mentally and leadership wise you think you experienced in moving from director, to VP, to SVP, to C-level?

Shawna Wolverton: Yeah. I mean, I think one of the craziest things is about–I mean, it’s funny, I talk about this a lot–and I noticed it the most when I became SVP, and that’s moving from what I call the person who was sort of, I had this brand as being the person who fought the man, right? I was speaking up for the customer, and I was really adamant, and I was pounding the table, and sort of advocating really hard, often against management. And then, I became the man. And it was a really interesting adjustment for me to understand that, often, there is a toll in this sort of, I disagree but I’m going to commit and go forward that is really required at an executive level. And that adjustment was probably the most interesting of my career.

Sukrutha Bhadouria: Wow. All right.

Sukrutha Bhadouria: Maybe last few questions. I’m curious because a little birdie told me you were best known for getting the customers to fall in love with you. What’s your secret?

Shawna Wolverton: Oh, listening. I think a lot of it was really active listening. And then, here’s the strange thing. I told them no. And I think sometimes we try to please customers, or bosses, or colleagues, and we say, oh yes, all the time. And then, we either can’t deliver, or can’t deliver in a timeline, or people make plans based on that yes. And sometimes a really, really clear, I’m not going to be able to do that is so much more powerful than our sometimes, like, extreme anxiety about wanting to be able to say yes.

Sukrutha Bhadouria: That’s amazing. I didn’t think of that at all.

Sukrutha Bhadouria: Just one last question, and then we should wrap. What was the pivotal moment that helped propel you into senior management roles?

Shawna Wolverton: Yeah. I mean, I think a lot of what I did to get propelled into senior management was taking on projects that no one else wanted to do. I’ve had the good fortune, I don’t know, to work in really fast growing companies where there was always more work on the ground than there were people to do it. And finding out which one of those things was actually really important, and then taking ownership of it, and showing management that I was the kind of person who could take on those hard things was a huge part of my career growth.

Sukrutha Bhadouria: Thank you, Shawna. This brings us to the end of your talk. Thank you everyone who posted questions and the amazing comments. By the way, you got a lot of love for your glasses.

Shawna Wolverton: Thanks.

Sukrutha Bhadouria: Thank you again.

Shawna Wolverton: Thanks, everyone. Have a good rest of your day.

Sukrutha Bhadouria: Thank you too. Bye.

Shawna Wolverton: Bye.

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

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

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.


Our mission-aligned Girl Geek X partners are hiring!

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

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

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.


Our mission-aligned Girl Geek X partners are hiring!

“Creating an AI for Social Good Program”: Anna Bethke with Intel (Video + Transcript)

Speakers:
Anna Bethke / Head of AI for Good / Intel
Angie Chang / CEO & Founder / Girl Geek X

Transcript: 

Angie Chang: Hi, Anna.

Anna Bethke: Hello, how are you doing?

Angie Chang: Good. So we are back. I’m going to … there we go. Snazzy background. So we are recording the videos, this is a common question we get, and they will be available later on our website, girlgeek.io. Please tweet, the hashtag is GGXElevate.

Angie Chang: We’ve been sharing selfies of viewing parties, since it’s International Women’s Day, of women gathered, and allies, in rooms and offices, and coworking spaces around the world.

Angie Chang: Next up is Anna. She will be talking about how she developed the AI for Social Good program at Intel.

Anna Bethke: Cool, thank you. I’m super excited to be talking with everyone. I’m assuming my slides are showing, but let me know if that’s not the case. Awesome. I wanted to get into what does AI for Social Good mean, as well as what are some of the projects that we’ve been doing here at Intel, and things that I’ve seen elsewhere in the space, because it’s one that I’m super passionate about, and love.

Anna Bethke: But just first want to talk a little bit about how I got to where I am today. So I am from Colorado, and I also think of things in a geographic sense. Then I studied aerospace engineering at MIT out in Boston, and started on my career path as a geospatial data analyst in sorts, taking imagery from satellites, taking information from that, and then writing some algorithms to find different patterns of life, and anomalies.

Anna Bethke: Did something slightly different, but also geospatially related at Argonne National Labs, and that was in the Midwest, which was lovely, was really close to my husband’s family, but not quite the right fit for us. Moved over, and was doing a data science consulting type of gig at Lab 41, and landed at Intel doing data science work there.

Anna Bethke: So before I took up this role, I was primarily looking at natural language processing, deep learning techniques. How do we make these faster, what are the different things that we can do, what is the state of the art? It was very interesting, but I just have been so inspired by a lot of different projects, and I’ll talk about some of these groups a bit later.

Anna Bethke: Now I’ve been being a volunteer for Delta Analytics, as well as Data and Democracy, two groups that help pair you with some different projects that you can help a non-profit with, or help move the bar on what is important in the world.

Anna Bethke: That’s sort of how I define, and how AI for Social Good is defined, and it’s easiest to talk about specific projects than to say what this is, because AI is super nebulous. What is good is also something that has some subjectivity to it, but basically, the idea is how do we utilize AI hardware, and software, which is a lot of different techniques, and these technologies to really positively impact our world?

Anna Bethke: The thing that I find really promising and fascinating about this is that we can have a very large impact. This is a smorgasbord of some of the projects, and I’ll go into depth for a few of them. But there’s a lot of different verticals. Healthcare is a large one where we can start to be able to take these image segmentation networks, or object detection type of networks, and say, “Okay, well where is a potential tumor?” Or, “Where is a disease?”

Anna Bethke: “Is this something that looks benign or …” what’s the opposite? “Benign or …” sorry, I can’t say that word today. But basically, “Is this cancerous or not?” Taking these types of ideas from our research areas, and putting them into the field.

Anna Bethke: It’s very wide and varied. For earth or our different types of work there, we can do a lot of things, too. So ways to protect our natural resources, ways to protect, also, our man-made resources, so one of the projects was looking at restoring landmarks such as the Great Wall of China, or how do we map our structures and buildings so that we can have a better disaster response?

Anna Bethke: And then ourselves. How do we protect our kids against online threats, or physical threats? This is some work that the National Center for Missing & Exploited Children has been doing for years, and how can we help them with technology so that they can help protect and find potential perpetrators faster?

Anna Bethke: And then how do we help ourselves create these online communities that are better, so like preventing harassing text online, and even mitigating and stopping it.

Anna Bethke: That’s a high level. There’s more on the website, but the interesting thing is really once we get to dive into these projects. One of the ones that I think is really interesting, because it came from one of our software innovators. So these are basically entrepreneurials, individuals that are external to Intel, and they have these ideas of ways that can really help society, or these different projects, and there’s a link at the end of this presentation that you can get more information on this particular project.

Anna Bethke: Basically, this guy Peter Ma, he was looking at the issue that every minute a newborn dies from infection caused by lack of safe water or an unclean environment. This is worldwide, and it’s a very large issue. This was the World Health Organization, but the current systems that we have there are very expensive.

Anna Bethke: They require manual analysis, so you can’t just take your machine, and bring it from one village to another village, and that’s just not possible. But you want to make certain that the water everywhere in the community, and you’re going to need to be measuring this multiple times, because the water quality can change.

Anna Bethke: So what Peter did with some expertise help from Intel, is he built a convolutional neural network, basically. A computer vision model that is able to take a water sample, and using off the shelf products, as well as this Movidius Neural Compute Stick, which you can buy this commercially from a lot of different sites.

Anna Bethke: Don’t know if I have a link on it here. Oh yeah, if you go to the AI for Social Good website, then you can get to see more information on this product, and that has more information on how you can buy these NCS devices. They’re really low weight, you could actually see one in the image, I believe. That USB stick, basically.

Anna Bethke: He was able to build this entire prototype for less than $500, and now it’s even smaller, and less expensive, and it’s more than 95% accurate. So it might not be perfectly accurate, but it tells you a lot of information, and can really start to help communities know where their water is safe to drink, and where is problematic, which can greatly improve people’s lives.

Anna Bethke: Another really interesting project that I love is with a company called Resolve, and we’re building, with them, Trailguard AI, and the idea here is the camera that’s in the picture is this motion capture camera. Motion capture cameras are great. Scientists have been using them for a very long time to be able to monitor the health of animals, and where are animals located.

Anna Bethke: Park rangers are also starting to use this to be able to say, “Okay, when are there poachers in an area,” and how do we help this poaching epidemic, and really turn the tide on it? Because basically right now, National Geographic has identified that an elephant is poached every 15 minutes, or a rate of 3,5000 a year.

Anna Bethke: This presentation that I’m giving is about 15 minutes long, so in all probability, an elephant could’ve been killed during this, which is just really sad to think about. There’s not a lot of park rangers, it’s a massive area that they’re trying to cover, so what can we do more?

Anna Bethke: What we did with Resolve was embedded also the Movidius Vision Processing Unit, so this is the same chip that’s in that USB stick that was in the last project. But basically, we can run an object recognition network on the Edge, here.

Anna Bethke: Everything that is being processed is being done on this VPU, and basically what happens is an image is taken, that goes to the chip, the chip is able to run this CNN for object recognition, and in this case, we’re looking for people in particular, because this is what the park rangers are very interested in.

Anna Bethke: If there’s a person or a vehicle, then it’ll ping the park rangers, and this is really–

Anna Bethke: –Both reduce false alarms, about 75% of the images that the park rangers would’ve originally gotten, wouldn’t have anything in them. So basically, if a tree moves, then this camera goes off, because you want that to be very sensitive.

Anna Bethke: Now, by just sending the 25% that have a person or an animal, so I think people are only in about five or less percentage, depending on the camera, of course. You can greatly reduce the false alarms, as well as extend the battery life.

Anna Bethke: So we’re expecting these to last a year, which really helps, because then it’s harder for the poachers to find. If you’re always blazing a trail between all of these different cameras, then it’s pretty easy to figure out, a poacher can figure out where they are, and avoid them.

Anna Bethke: It’s really interesting. Something that we already have, both of these last two projects, as well as the next one, these technologies that we already have, like object detection is something that is getting more robust, that we’ve been using for a lot of different applications that we’ve been researching for a number of years now.

Anna Bethke: So how do we use it, though, for these really impactful purposes? One of the last projects I wanted to just mention before going into some of the stuff that I’ve learned while building up a program around these types of projects is the Wheelie. This is a project that we worked with a company called HOOBOX, and basically, they are robotics experts.

Anna Bethke: In the last example, Resolve are conservationist experts, so they bring deep knowledge about what the issue is, and we bring the technical expertise. So what HOOBOX saw, was there are a lot of people worldwide that are suffering from spinal cord injuries, and there’s more and more every day.

Anna Bethke: But the offerings for mobility devices can be expensive, complex, difficult to use, and there aren’t as many options as one would like. We developed the Wheelie 7 with them, and it lets users choose the most comfortable facial expressions to command their own wheelchair.

Anna Bethke: You can basically say, if I smile, go forward. If I raise my eyebrows, go backwards. If I open my mouth, go right. If I stick out my tongue, go left; things like that. This is really nice, because every person has different abilities, so by giving choices that extend the range of people that this’ll be really effective for.

Anna Bethke: And again, facial gesture recognition is built on a lot of deep learning applications that we have already looked at in-house, and so how do we apply it to this? What are the different things that we really need to think about in order to make sure that this product works for everybody in a very safe and reliable way, and that people’s privacy is protected, and all of the things that we really need to be considering while looking at this type of project.

Anna Bethke: This all of course is run on the wheelchair too, because you don’t want to be sending this information to the Cloud. That would take a long time, and if you are telling your wheelchair to stop, you want it to stop immediately. So this is run on the Intel NUC, it’s this little miniaturized PC with a customizable board. I think it’s four by four inches, so really small, can fit on the wheelchair, and it also doesn’t pull a lot of electricity, and the facial gestures are captured by this 3D RealSense camera, and that gives more information about the facial gesture than just a normal 2D camera.

Anna Bethke: Again, all these devices are things that we are commercially selling, which is great, because it’s things that are already built, and we can just improve them, make them better by seeing how they work in this new and different environment.

Anna Bethke: This project in particular was supported through a couple different projects. The Software Innovator Project as well, that was that CleanWater example that I gave a couple things ago, and our AI Builders Program. This one’s interesting, it’s sort of tuned for startup companies, and I’ll have a link for that one, too.

Anna Bethke: What does it really mean for me as being the head of this effort? I do a lot of different things. One is research and development, this is a slightly older picture of my cat, is a bit older, but I get to play with code, and do some literature research. That’s a little less now that the program is running, and getting a lot more interest in it, but it’s something that I try to carve out as well.

Anna Bethke: Sometimes I miss doing more of the technical work, but this is something that I am exceedingly passionate about, so I don’t mind not getting to code every day anymore. Another one is Connector. This was a breakfast ideation session last week, or a couple weeks ago, where I talked with a lot of different people like, “What can your companies do? What are the different ways that we can really just raise the bar, even just a little, with our technical expertise, with what our various organizations, or ourselves can offer?”

Anna Bethke: The last is Advocate. Talking at conferences, speaking to all y’all. One of the things I really hope to communicate is that this type of work is really important, and also really interesting and fun, and has a lot of very good business use cases that might not be as prevalent either.

Anna Bethke: I think a lot of us really want to do this type of work, because it’s the right thing to do, but there’s a lot of benefits too. It’s great for marketing, of course, as you could likely imagine, but it’s also really great for hiring and retention.

Anna Bethke: A lot of people want to be doing these types of projects, so the more that we offer them, the more that our companies can hire in this type of talent, and keep us all happy. Then the third for us specifically, being a hardware company, I think I eluded to it a bit, is that we really see a larger number of use cases of how can we apply technology, and then that helps us make certain that we are designing our technology in such a way that it is robust, and that there is a larger user base, basically.

Anna Bethke: So I’ve been learning all these different things along the way, but it’s interesting. There’s some other things too, so I wanted to share a few lessons. Asking for work that inspires you. The role that I’m in now didn’t exist, and I am so grateful for my manager, as well as the leadership here, that they’ve been really supportive in me taking on this position.

Anna Bethke: Helping me get the resources that I need, as well as helping to find what are the things that we can do now, in a couple months, where are the places that we really should be looking?

Anna Bethke: The second is that there are a lot of people who want to help, whether it’s helping plan meetings, whether it is doing the engineering work, being a contact coordinator. A lot of the projects that we have been developing are ones that one of my colleagues, or a colleague’s colleague has a friend who is doing this thing, and they are having this issue. Can we help out with that?

Anna Bethke: Those connections are wonderful. Low hanging fruit are wonderful as well. I say wonderful a lot. It’s very true. A lot of times we really try to go for, I think they’re called moon shots, but what is the coolest and the best thing that we could possibly do?

Anna Bethke: And while those are important too, there are things that we can do today, or in the next month, that are potentially quite easy for us to move the bar a little bit, but can have a really large impact in somebody’s life, or some animal’s life, the environment’s state.

Anna Bethke: Those are important to continue to look at, and to consider. But it’s also okay to say no, and this is one of the hardest things, and it’s really actually necessary to say no sometimes. I have been having to come to terms with the fact that I’m not able to do everything that I want to do, and we’re not able as an organization, or a company, to do everything, to help everybody, and so it’s sort of making sure along the way, that I’m preserving my own health and wellbeing, and sanity, and spending time with my cats, and my husband, and all of that at the same time, too.

Anna Bethke: And then who can help? Redirecting it to other resources, or saying, “I’m sorry. I can’t help at this moment, but maybe this person can.” Doing that redirect. But yeah, it’s hard. Then finally, you’re here for a reason. Whatever position you’re in, it’s awesome.

Anna Bethke: Imposter syndrome is one of my good friends now. I have definitely doubted myself along this way, when I was a data scientist, now as a head of a program, it crops up all the time. This is something that I remind myself of, and I think that we all should elevate each other.

Anna Bethke: I love communities like this, because I really feel like we do that. And then actually last, is that if you’re helping to debut hardware, there’s a high likelihood that they will take a picture of you holding the hardware.

Anna Bethke: This picture, I had no clue was going to be taken. This was right before the holidays, and I had just repainted my nails, and I had never painted them this bright and shiny, but I’ve come to terms with this too, and loving it.

Anna Bethke: I think it’s funny, so I have to laugh at myself a little bit, but I actually really like the super pink sparkly nails. How do you get started in this? Hopefully I have shared enough inspiration, and project examples. There’s more at AI for Social Good, at intel.ai, and this really follows a similar process as most other projects, so getting your ideas, finding the partners.

Anna Bethke: So the partners are someone that has the ability to really implement this into action, and that really varies, and then getting your research together, the data, the compute. There’s some things that could help, like at this AI Developer Program, and that actually gives you links to both the Software Innovator Program, as well as our AI Academy, if you’re a student, but there’s some Dev Compute there, which could be helpful.

Anna Bethke: And then your algorithm development, so how am I actually going to analyze all this data, and make sense of the world? And then testing and deployment. This is really important, of course, to make sure that the system is working before it goes out into the wild. Aibuilders.com is the startup company connector, if that’s something that you’re in, and then one of the really important things as we’re doing this, is to talk about, and think about how do we do project management, project deployment in a responsible way, so there’s a bunch of different resources that are out there. There’s a lot of toolkits, so this goes everywhere from checklists like Deon from DrivenData, which just [inaudible 00:23:00]. These other things you should be considering as you go through, to more algorithmically based mechanisms like the IBMs 360 Fairness Toolkit, or the What If tool from Google.

Anna Bethke: Take a look if you are doing a project. Either for a socially impactful, or anything else, and there’s a large discussion around this right now, which I love. I’ll leave you all this sample of various social good volunteer organizations.

Anna Bethke: This is definitely a growing area of interest, so something in the Bay that I’ve been involved in is Delta Analytics. This is mostly San Francisco, but the other ones are either completely based in the United States everywhere, or also global, so DataKind, Data for Democracy, Code for America, Visualization for Good is really cool if you’re more on the visualization side, and then there’s a lot of different hackathons and challenges that you can join, too.

Anna Bethke: So yeah, that’s it.

Angie Chang: Thank you, Anna. This has been a great, very informative, resourceful talk. There’s been a lot of chatter and questions. I don’t know if we have time for … I’ll send you the questions, and you can maybe answer them on Twitter. I think you’re pretty active on Twitter, and we can get all the questions answered, with helpful links.

Angie Chang: Our next session will be starting soon, so thank you so much for joining us.

Anna Bethke: Thank you, yeah, I’ll definitely answer them there.

“The Gendered Project”: Omayeli Arenyeka with LinkedIn (Video + Transcript)

Speakers:
Omayeli Arenyeka / Software Engineer / LinkedIn
Gretchen DeKnikker / COO / Girl Geek X

Transcript:

Gretchen DeKnikker: Hey, everybody. Welcome back. Our next session here is with Omayeli Arenyeka. Arenyeka, tell me I’m saying it right.

Omayeli Arenyeka: Arenyeka.

Gretchen DeKnikker: All right.

Gretchen DeKnikker: This is important to get people’s names right. So she is a software engineer at Linkedin. She is also an artist and a poet from Nigeria. She submitted her talk to us through our speaker submissions on how she built a gendered dictionary and we thought it was so interesting that we invited her to come here and share it with you guys today, so …

Gretchen DeKnikker: Also, the videos will be available later. Don’t forget to tweet with hashtag, #GGXElevate. We’ve got the Q&A going in the bottom. And just after this session we will give away some more socks, so stay tuned.

Omayeli Arenyeka: That’s good?

Gretchen DeKnikker: Yep. I see you.

Omayeli Arenyeka: Okay.

Omayeli Arenyeka: I’m Yeli. Thank you so much for having me. My talk is about building a gender dictionary. But before we get into all the technical stuff I wanted to play a little word game. And it’s simple, you don’t have to do anything but think really hard.

Omayeli Arenyeka: So the game is, I say a word and you think of an image that’s associated with it.

Omayeli Arenyeka: Okay, here we go. Superhero. Ninja. Hacker. Rockstar.

Omayeli Arenyeka: And then now I want you to consider the images that came up, if they were of humans, whether those images were of a man or a woman or someone who doesn’t exist in those binaries. And this isn’t to shame anybody, it’s just an opportunity to reflect on biases because those biases we have they make their way into things that are supposed to be objective. So when given the option, translating from English to French, machine assisted language translation systems, like Google Translate, code the word nurse as feminine.

Omayeli Arenyeka: So in the Turkish language they use a gender-neutral pronoun that covers he, she, it. So when Google Translate goes from Turkish to English it has to decide whether the gender-neutral pronoun means he or she or it.

Omayeli Arenyeka: So this poem is written by Google Translate on the topic of gender, and is a result of translating Turkish sentences that use that gender neutral pronoun into English, so some of the lines are, he’s a teacher. He’s a soldier. She’s a teacher. He’s a doctor. She’s a nurse. She’s a nanny. He’s a painter. He’s an engineer. He’s a president. He’s an artist. He’s a lawyer.

Omayeli Arenyeka: And so, the algorithm in basing its translations on a huge corporate set of human language, so it’s reflecting the bias, a gender bias that already exists in the English language.

Omayeli Arenyeka: Another example of the effect of gendered language was highlighted be the augmented writing platform, Textio. They found that the gendered language in your job posting can predict a higher … can predict the gender of the person that you hire.

Omayeli Arenyeka: So thinking about this and other ways that our everyday gendered language communicates ideas we might not mean to, I decided I wanted to create something to allow [inaudible 00:03:45] for gender language, and that’s what this talk is about, Building a Gendered Dictionary.

Omayeli Arenyeka: So specifically, I wanted to make an API and a tool where you could find all the gendered words, you could find the equivalent of a gendered word. To be clear, what a gendered word is, they’re words that apply to a certain gender. So, lady/gentlemen, prince/princess, so some of them like lady and gentlemen, prince and princess, they have equivalents and some of them don’t. Some of them, like actor, are not gendered in definition but might be gendered in practice.

Omayeli Arenyeka: So the first question that I had to ask was, where and how do I get this data? So there are some existing data sets of gendered words. One of those examples is from a team of Boston … a team of researchers from Boston University and Microsoft Research. They created a data set that’s part of their work into removing the sexist biases that exist in corpus in data sets that train algorithms, like Google Translate. So they were trying to remove the bias from platforms like Google Translate.

Omayeli Arenyeka: But unfortunately, all the data sets I found, including that one, were not substantial enough. At most they had 1,000 words, and a lot of the words were false positives, so they weren’t actually gendered words. So I decided I would use these methods, API, static data, and web scraping to get the data.

Omayeli Arenyeka: So to start with, I had to determine what a gendered word was, so what I would I tell the computer that a gendered word was? So to start, it was all the words in the dictionary that have at least one of these terms in it, so woman, female, girl, lady, man, male, boy. For example, businessman has the word man in its definition and archeress has the word female, so both of them would count as gendered words.

Omayeli Arenyeka: Then I started looking for some APIs. So I found one of the largest … the biggest online English dictionary by number of words, Wordnik has an online API and it has a free … it has a reverse dictionary feature, which means find all the words that have one of those terms in their definition. So you can see on this screenshot, the reserve dictionary of woman is all the words in the dictionary that have the word woman in their definition. So airwoman would have the word woman in its definition, so it would count as a reverse dictionary term.

Omayeli Arenyeka: So Wordnik has a client for interacting with the APIs, so I just used that to make a call to their reverse dictionary. You can see that happening in line seven. I have all the terms and then I make the call to the Wordnik API in line 10.

Omayeli Arenyeka: So I got about 400 words back, which was kind of confusing because the API said that there were over 3,000 words that were … that had the word woman in their definition. So I had to find another data set, so I stored the 400 words I got from the Wordnik reverse dictionary API and then moved on to the second way of getting data, static data sets.

Omayeli Arenyeka: So I looked on GitHub and I found a dictionary in JSON format and I read that in using Python. So Python has a JSON module that you can just import. So I loaded that in for filtering and I got all the definitions of the word, as you can see on line six.

Omayeli Arenyeka: So, like I said, if a word has one of these terms in its definition, then it’s a gendered word. So how do we check that? With Python you can say, “If string in definition.” So if woman in definition, or female in definition, or lady in the definition, but then you have this long list of conditions. So instead of doing that we can use RegEx. So, for example, my name is Omayeli, but a lot of people often misspell it, so I could use RegEx to create one pattern that matches my name and all the misspelling of my name.

Omayeli Arenyeka: So I created a RegEx pattern for all of these terms, so I could search them in definitions and see if the word was a gendered word. So in RegEx the pipe symbol represents or, so this is saying match woman or female or girl. And then, if you find any of these strings … if you find any of these words in the string, you can see patterned at search definition, it’s searching the definition for one of those patterns. And if you find it in the definition, then we do something. But the issue with that is that it wasn’t looking for whole words, so sub-strings also count. You can see on the right the words that are matched, human, manhole, so these are not gendered words. They have the word man in them but it’s just a part of the word and not the full word.

Omayeli Arenyeka: So I had to use word boundaries, so word boundary allows you to perform a “whole words only” search. So now it’s looking for whole words and not just part of a word. So you can see on the right, it no longer matches manhole and manatee. It only matches man and boy at the bottom.

Omayeli Arenyeka: But then I also want words like grandfather, so what do I do? So word characters, which matches a word character. So anything from A to Z, zero to nine. So now it finds father and all the words that are combinations of father and another word in front.

Omayeli Arenyeka: So going step-by-step through the patterns, these parentheses are for grouping a pattern together as one. This character set says, “Match anything in this set.” So you don’t have to match all of them, but you just have to match one thing in that set. This is, like I said, matching a word character. This is matching a dash. And then this is saying it’s optional, so there can be something before the word but there doesn’t have to be.

Omayeli Arenyeka: And these are the final RegEx patterns. They’re pretty long. So after I finalized the pattern I went through the dictionary and for each entry in the dictionary, if the definition contained one of those terms then I added it to the list of gendered words. So in line eight it’s checking if any of those terms are in the definition, then we add that to our list of gendered words.

Omayeli Arenyeka: So when I add that together, the words from Wordnik and Webster and some other files, it came to about 8,000, which is great. Much more the 400 that I started with. But then when I went through the list there is words that did not belong there, words like lioness. So for my definition of what I wanted this gendered dictionary to be, it was a collection of gendered words for human beings, so not animals. So this was not a word that I wanted in my word set.

Omayeli Arenyeka: So instead … So I decided I would start to look for patterns in the incorrect words, so find … what were the common things in the definitions of the words that were not supposed to be in the set? So one of the patterns of incorrect words that I found was that in some of the incorrect words the definition included the gender term being used as the object of a preposition. So, for example, in the definition of waterfall it says, “An arrangement of a woman.” In the definition of Peter is says, “A common baptismal name for a man.” So it’s not a name that is describing a man. It’s a name for a man, so Peter shouldn’t be a gendered word. And you can see in the other definitions, “Short cape worn by woman,” or, “The position of a man.”

Omayeli Arenyeka: So how would I remove words that fit this category, and the category being the gendered word is being used as the object of a preposition? So first, I had to isolate the part of the string that I wanted to look at, and that was everything before the gendered word. So you can see, the highlighted portion is everything before the word … before and including the word man. So we can use … in Python, we can use RE module, which is for handling RegEx expressions. So the RE search method in line four will search through the text for any of those terms, any of our gender terms in line two. So in this case we have the string definition in line eight, so it’s looking for the word man and it will find the word man.

Omayeli Arenyeka: And then we get … When we get the location of where the word is, you get the end index. So in line nine you can see the search method in RegEx returns the index of where the word was found. So, from there we can get the end index and then we can use that to trim the string. So in line 11 you can see that the word, it’s now a common baptismal name for a man and it doesn’t include everything after.

Omayeli Arenyeka: So after we trim it, remove any punctuation, we use the string class in Python. The string class has a list of punctuations, so we use that to filter in line five and then we return the string without any of the punctuations. So if there was a punctuation it would remove it. So if there was a string in line seven, the return string would be line nine, so, which no punctuations.

Omayeli Arenyeka: So now that we have this trimmed definition we can use NLTK to find where the preposition in is the string. NLTK stands for Natural Language Toolkit. It’s used for processing the English language. So the first thing we do is we tokenize it, so tokenization is the process of chopping up a string into different pieces that are called tokens, and then throwing away certain characters like punctuation. So you can see on the right we pass in … This is an online version of a tokenizer. We pass in a common baptismal name for a man, and then it breaks it up into different tokens.

Omayeli Arenyeka: After we tokenize we can use something called a part of speech tagger, so I load in the part of speech tagger in line … in two, it’s part of NLTK. In line five I tokenize the string. So you can see, in line six, it has … the definition is chopped up into different pieces. And then in line eight we use the tokenizer from NLTK, which gives every token a part of speech. So you can see, common is an adjective, baptismal is an adjective, man is a noun. And I know those because I looked up what the tags were in NLTK. So you can see, NN represents a noun, so man is a noun. JJ represents adjectives, so baptismal is an adjective. And then after that, first of all, we remove the a’s and the and’s and the the’s because we don’t really care about them, so we remove them in line four and then we get … In line nine we get the word before the gendered word. So we know that the gendered word is the last word in the sentence. It’s the last word in the string, so we get the word before that, and then we check to see if that’s a preposition.

Omayeli Arenyeka: So in that case–this case, a baptismal name for a man, the word before man is for, which is a preposition so it returns false and says, “This is not a gendered word.”

Omayeli Arenyeka: Another pattern was that there were a lot of clothing items. So you can see skivvies, pajama, loose-fitting trousers, all of these are not gendered words. So I found a list of clothing items so I can remove any words that has one of these clothing items in the definition. Unfortunately, the website where I found the list, I had to apply for an API key. I did apply like six months ago and they didn’t get back to me, so I decided I would scrape their website. So web scraping is a tool for extracting information from websites that involves grabbing the html that makes up the website. And for doing this in Python there are two libraries I usually use, urllib.request and Beautiful Soup.

Omayeli Arenyeka: So the first thing you have to do is figure out how the data you want is structured in the dom, which you can do using the inspector tab of your browser. So we see that the data I want is in a link. That’s the child of a span element with a class TD. So I open the URL of the page in line two. In line three I add it to Beautiful Soup. In line four, and then in line five I look for the specific elements. So I’m trying to find links that are the children of spans with class TD. And then I get all the texts for them and I have the list of clothing items. So I use that to filter the dataset to remove any clothing items that are disguising themselves as gendered words.

Omayeli Arenyeka: And it came down to about 4,000 words. The last thing I wanted to do was find gender opposites, so I wanted to match words with their opposites, king/queen, father/mother. I can use that … I can do that using something called Word2Vec. So Word2Vec is an algorithm that transforms words into vectors. So back in 2013, a handful of researchers at Google set loose a neural net on a large corpus of about three million words taking from Google News texts. So the goal was to look for patterns in the way words appear next to each other. So you can see in the graph, microwave is close to refrigerator and it’s far from the word grass. Grass is close to garden, is close to hose and sprinkler. So the Google team discovered that it could represent these patterns between words using vectors and vector space. So words with similar meanings would occupy similar parts of the vector space and the relationships between words could be captured by simple vector algebra.

Omayeli Arenyeka: So these relationships are known as word embeddings and the dataset is called Word2Vec. It’s based on the idea that a word is characterized by the company it keeps, so a word is close to another word in space if they appear in the same context. For example, if we give the algorithm this text, since salt and seasoning appear within the same context, the model it creates will indicate that salt is conceptually closer to seasoning than, say, chair. And with that model, and with those word vectors we can do stuff like getting the similarity of words. You can see woman and rectangle are not very similar. Their similarity value is less than 0.1, whereas the similarity value for woman and wife is 0.8.

Omayeli Arenyeka: And word analogies, so you can do it for woman. You can do woman is to queen as man is to king.

Omayeli Arenyeka: In Python, if you wanna use models and the Word2Vec algorithm you can use a library called Gensim. So I mentioned earlier that they used … they set loose a neural net on a model of like three million words, so you can load that model of three million words into Python using Gensim. So it’s called Google News Vectors, so you can see in line two we have a model, Google News Vectors, and we load that in and then we have … we can call the models most similar method in order to get the equivalent of a word. And this isn’t perfect, but I think it works for most of my cases.

Omayeli Arenyeka: So in line nine we pass in woman, wife. So positive, woman is to wife, and then we pass in man, and then the results we get if the score is greater than 0.6 then we say it’s an equivalent. And so, we have …

Omayeli Arenyeka: And that was it. I got an initial word set using APIs and finding static dataset, and then I cleaned and filtered the dataset using RegEx, web scraping and NLTK, and then I used Word2Vec to find the equivalent for words that have them. And then I created a website and an API to house the data. So you can see, woman is to wife as man is to husband. So when navigating the site users can learn what words are specific to a gender, what words have gender equivalents, what words don’t, and which ones significant imbalances exist. And you can see what words have undergone semantic derogation, which is a process where [inaudible 00:20:25] take on more negative connotations. For example, the word mistress was more … was once the equivalent of the word master but over time it’s taking on a new meaning.

Omayeli Arenyeka: So in summary, the words that we don’t and do have matter. They reflect our biases and the ideas that we value [inaudible 00:20:42] risk reinforcing perpetrating those biases if we don’t [inaudible 00:20:42] the words we use and why.

Omayeli Arenyeka: Thank you.

Gretchen DeKnikker: Thank you so much, Omayeli. This was great. I wish you … Go back in and read the comments, because everyone was so excited about how you broke down this search methodology and the test you did at the beginning. Everyone was like, “Oh, I thought of a man, too.” So everyone really, really enjoyed it. Unfortunately, we don’t have time for Q&A and I know we’re missing those a little bit today, so don’t worry everybody. We have a list of the questions and we can go back and do more in-depth interviews with all of the speakers later. So your questions will get answered at some point. Thank you again.

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

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

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!


Our mission-aligned Girl Geek X partners are hiring!