Girl Geek X LiveRamp Lightning Talks (Video + Transcript)

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Akshaya Aradhya, Angie Chang speaking

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

Transcript of LiveRamp Girl Geek Dinner – Lightning Talks:

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

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

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

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

Allison Metcalf speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Tina Arantes speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Eloise Dietz speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

LiveRamp Girl Geek Dinner

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

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

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

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

Audience Member: Mm-hmm (affirmative).

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

Erin Friesen speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Akshaya Aradhya: Questions for Erin?

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

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

Rachel Wolan speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Akshaya Aradhya speaking

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

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

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

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

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

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

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

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

Akshaya Aradhya: So that’s how that went. 

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

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

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

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

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

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

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

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

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

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

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

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

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


Our mission-aligned Girl Geek X partners are hiring!

This Girl Geek Wrote Her PhD Thesis Arguing For Tech To Support Economic Security For All

This girl geek earned multiple Stanford engineering degrees, worked in Silicon Valley, and then wrote her PhD thesis named “Tech:” The Curse and The Cure: Why and How Silicon Valley Should Support Economic Security.

Sage Isabella Cammers-Goodwin lays out the societal inequality of San Francisco’s Bay Area, and provides some suggestions for change:

We need a clear image of what valuable innovation looks like. Valuable innovation is work that goes toward raising the bottom standard of living and not increasing the distance between the bottom and top. Valuable innovation makes people self-actualize and does not take away from their productivity. Everyone stands to benefit from valuable innovation. Some persistent issues that would be valuable to fix include access to food, fresh water, healthcare, shelter, and education.

There are companies that work to improve the world and determine success primarily through the fulfillment of their users and nonprofit margins. Propel is a service that assists individuals with managing their food stamp balance. Handup allows people to donate directly to verified homeless individuals. Wikipedia, despite its unpopularity with academics due to a lower reliability than thoroughly fact-checked un-editable sources, offers a non-predatory social good. The belief that taxing tech corporations and breaking up monopolies hurts humanity by limiting innovation is a false rhetoric. Society does very little to encourage the kind of innovation that improves humanity by making the world a more livable, healthy, and equal place.

The true heroes of innovation are the creators of tools to assist those most in need and provide open-source frameworks so that anyone—including private firms—can learn from and build off of what they create.

The tech industry cannot be blamed for preexisting conditions. Many young entrepreneurs do not start as homeowners and did not create the systematic privileges that helped them succeed, whether that be affirmation that someone who looks like them is capable of success, having a family that could provide them an education, early access to computers, or an enthusiastic circle willing to invest in their success. Yet, they are still responsible for the systematic injustices they perpetuate and intensify.

The vast majority of U.S. born citizens, especially women and people of color, are not provided with the resources or encouragement to make earning over $100,000 per year coding seem reasonably achievable.

Ideally, the wealth of corporations would uplift local community and not just drive people out. Fortunately, there are a few legal structures in place to mitigate the negative influence corporations have on the communities they move into, one of which is called “impact fees.” The San Francisco Planning website explains, “The City imposes development impact fees on development projects in order to mitigate the impacts caused by new development on public services, infrastructure and facilities”—for example, improving public transport to counteract the added burden on the system.

Author of “Winners Take All” Anand Giridharadas agrees:

Philanthropy does not undo bad behavior. The range of tech philanthropy efforts — from “self-made” billionaires pledging to give away the majority of their wealth, to corporations promising to match employee donations, to those that give grants up to one percent of annual revenue, to corporations that do not find it within their mission to give at all — are insufficient.

This rhetoric is problematic because it distracts from the fact that automation, prior innovation, corporate bullying, and infrastructural advantages account for a large amount of tech wealth. It also frees corporations from needing to fix the problems they advance. Philanthropy is a positive corporate dogma, but is not sufficient to renegotiate the funds tech corporations owe to society.

A possible improvement could be taxing corporations on their employee-to-wealth ratio at increasing rates for corporation size. This tax structure could be applied internationally to lessen tax evasion loopholes. This money should be used for infrastructure that makes life affordable and for wealth redistribution to improve outcomes for everyone over time.


Read more of Sage I. Cammers-Goodwin’s writing at Tech:” The Curse and The Cure: Why and How Silicon Valley Should Support Economic Security, 9 U.C. Irvine L. Rev. 1063 (2019).

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

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

Aurora garage girl geeks

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

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

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

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

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

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

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

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

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

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

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

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

Jessica Smith speaking simulation

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

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

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

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

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

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

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

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

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

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

Haley Sherwood-Coombs speaking

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

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

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

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

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

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

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

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

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

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

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

Elizabeth Dreimiller speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Khobi Brooklyn: Okay. All right.

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

Khobi Brooklyn: Is that pretty good?

Chethana Bhasha: I think so.

Khobi Brooklyn speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Khobi Brooklyn: Jessie?

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

Khobi Brooklyn: And maybe just generally.

Jessica Smith: And generally, yeah.

Khobi Brooklyn: Cool. Chethana?

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

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

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

Khobi Brooklyn: Yeah. Jessie.

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

Khobi Brooklyn: Lia.

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

Khobi Brooklyn: Catherine.

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

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

Aurora Girl Geek Dinner in Aurora garage

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

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

Khobi Brooklyn: Anybody? Top of your head?

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

Khobi Brooklyn: Cool. Anybody else?

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

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

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

Khobi Brooklyn: Great.

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

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

Khobi Brooklyn: Yep. I think go ahead.

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

Khobi Brooklyn: Yep, absolutely.

Xantha Bruso speaking

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

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

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

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

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

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

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

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

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

Lia Theodosiou-Pisanelli: I think I tweeted this.

Audience Member: Thank you.

Khobi Brooklyn: And there we have… yeah.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Khobi Brooklyn: I feel like you two should start.

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

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

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

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

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

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

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

Khobi Brooklyn at Aurora Girl Geek Dinner

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


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women in tech - diverse group of women sitting in the audience, clapping and laughing during a tech talk at the Aurora Girl Geek Dinner in the San Francisco Bay Area, July 2019.

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Women in Tech networking at the Aurora Girl Geek Dinner

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16 Female Infosec & Cybersecurity Executives To Watch

Get inspired by these privacy and information security experts who are leading Fortune 100 companies, running health and non-profits, and impacting the field of infosec today.

Dr. Alissa Abdullah, Chief InfoSec Officer, Xerox

Dr. Alissa Abdullah is Xerox’s Chief Information Security Officer. Prior to Xerox, she was Chief Information Security Officer at Stryker. She served as Deputy Chief Information Officer for the White House Executive Office of the President during the Obama administration. She started her career as a Mathematician for an Intelligence Agency —  a certified cryptologic engineer at the U.S. Department of Defense.

Anne Marie Zettlemoyer, Vice President of Security Engineering, Mastercard

Anne Marie Zettlemoyer is Mastercard’s Vice President of Security Engineering. She was Director of Information Security Architecture and Engineering at Freddie Mac, and Director of Information Security Analytics at Capital One. She has worked in various positions, as a Director of Business Analytics at FireEye, Senior Consultant at Deloitte, Special Advisor for the United States Secret Service, and Principal Strategy Analyst for DTE Energy. Follow her on Twitter at @solvingcyber.

Arlin Pedrick, Chief Security Officer, Accenture

Arlin Pedrick is Accenture’s Chief Security Officer. She was at Disney as Director of Global Intelligence & Threat Analysis, and Director of Global Security at Walmart, and held various positions in the U.S. Government for 32 years.

Coleen Coolidge, Chief InfoSec Officer, Segment

Coleen Coolidge is Segment’s Chief Information Security Officer, having built the Security, GRC and IT org from scratch at the startup. Previously, she was Twilio’s Head of Security and Core Logic’s Director of InfoSec. Earlier in her career, she was at First American Title as an Infosec Project Coordinator, at New Century Financial as an InfoSec Specialist/Engineer, and was a Tech Writer in her early career. Follow her on Twitter at @coleencoolidge.

Flora Garcia, Global Chief Privacy Officer & Security Attorney, McAfee

Flora Garcia is McAfee’s Global Chief Privacy Officer, Privacy & Security Attorney. She discovered privacy law in law school when she read the case of Bodil Lindqvist, a Swedish woman who was the first person charged with violating the EU Privacy Directive. Flora is a graduate of the evening program at Fordham Law School,and Duke University, where she majored in computer science and economics. 

Jacki Monson, Chief InfoSec Officer, Sutter Health

Jacki Monson is Sutter Health’s Chief Privacy and Information Security Officer, where she’s been for six years at the nonprofit health network. Previously, she was the Mayo Clinic’s Chief Privacy Officer, and worked in compliance for healthcare companies. She began her career having earned her JD in health law and healthcare compliance certificates. Healthcare runs in her family — her mom worked at a hospital for 43 years in administration. Follow her on Twitter at @jackimonson.

Lakshmi Hanspal, Global Chief InfoSec Officer, Box

Lakshmi Hanspal is Box’s Global Chief Information Security Officer. She advises Colbalt.io, CipherCloud and HMG Strategy. Prior to Box, she was SAP Ariba’s Chief Security Officer, and a senior leader in information security and risk management at PayPal. She was Bank of America’s Chief Information Security Strategist and Leader for the mortgage line of business, and began her career at Novell as a Senior Security Architect. Follow her on Twitter at @LakshmiHanspal.

Maria Shaw, Chief InfoSec Officer, Varian Medical

Maria Shaw is Varian Medical System’s Chief Information Security Officer. Prior to Varian, Maria worked at McKesson, where she was a Vice President of IT Risk Management & Compliance for over a decade. She led the information security and risk professionals across McKesson’s distributed business units, as well as the enterprise IT risk program (HIPPA, PCI, training, IT Vendor Assurance). She began her career as a Senior Manager at Deloitte.

Mary Prabha Ng, Chief Security Officer, AXA

Mary Prabha Ng is AXA Equitable’s Chief Security Officer. She’s been at AXA for over 7 years. Previously, Mary worked as Vice President of Risk at financial firms and banks. She started her career in security as a computer engineer for the Department of Defense’s Undersea Warfare Center where she led several multi-million dollar government projects through various states of project development.

Mary Welsh, Chief Security Officer, UnitedHealth

Mary Welsh is UnitedHealth Group’s Chief Security Officer. Prior to UnitedHealth, she worked at St. Jude Medical in Minnesota for over 8 years, leading security and strategic projects. Prior to that, Mary spent 9 years working for the U.S. government, from domestic assignments in Washington, D.C., to residing overseas in Europe and Southeast Asia on national security issues. She began her career at Arthritis Foundation working as Director of Health Education.

Noopur Davis, Chief Product & InfoSec Officer, Comcast

Noopur Davis is Comcast’s Chief Product & Information Security Officer. She was Vice President of Global Quality at Intel for over 4 years. Prior to Intel, she spent 11 years at Carnegie Mellon University supporting the Software Engineering Process Management program. She worked at Davis Systems as Principal for over 6 years, and began her career at Intergraph as a Director of Engineering. Follow her on Twitter at @NoopurDavis.

Parisa Tabirz, Senior Director of Engineering — Chrome (Security & Privacy), Google

Parisa Tabirz is Google’s Senior Engineering Director, responsible for the security and privacy of the Chrome browser. At Google, Parisa’s business card has read “Security Princess”, and she’s been promoted several times since joining the company over 12 years ago. She began her career as a security intern at Google after being inspired to pursue infosec from a campus club at University of Illinois at Urbana-Champagne. Follow her on Twitter at @laparisa.

Reeny Sondhi, Chief Security Officer, Autodesk

Reeny Sondhi is Autodesk’s Chief Security Officer. Prior to Autodesk, she spent a decade at EMC, where she co-authored SAFEcode Security Engineering Training — A Framework for Corporate Training Programs on the Principles of Secure Software Development. Prior to that, she spent a decade working in product management before moving into information security where she has been for the past 13+ years now building enterprise scale security programs. Follow her on Twitter at @reenysondhi.

Sherri Davidoff, Chief Executive Officer, LMG Security

Sherri Davidoff is LMG Security’s CEO and co-founder. Her infosec consulting and research firm, based in Montana, specializes in network penetration testing, digital forensics, social engineering testing and web application assessments. Sherri is the co-author of Network Forensics: Tracking Hackers through Cyberspace and is working on another book (coming soon). She studied computer science and electrical engineering at MIT. Follow her on Twitter at @sherridavidoff.

Tarah Wheeler, CyberSecurity Policy Fellow, New America

Tarah Wheeler is New America’s Cybersecurity Policy Fellow, where she is leading a international cybersecurity capacity building project. Tarah speaks frequently on cybersecurity, Internet of things, and diversity in tech, having been the lead author of Women in Tech: Take Your Career to the Next Level with Practical Advice and Inspiring Stories. She has been advising / consulting on enterprise infosec thru Red Queen Technologies for over 17 years. Follow her on Twitter at @tarah.

Window Snyder, Chief Security Officer, Square

Window Snyder is Square’s Chief Security Officer. She is a security industry veteran and former Chief Security Officer at Intel, Fastly, and Mozilla. She previously spent 5 years at Apple working on security and privacy strategy and features for OS X and iOS. Window was a founding team member at Matasano, a security company, acquired by NCC Group in 2012, and co-authored Threat Modeling, a manual for security architecture analysis. Follow her on Twitter at @window.

Raising Up The Next Generation of Women In Security Engineering

Girl Scouts offer 9 cybersecurity badges for girls learn about the inner workings of computer technology and cybersecurity, applying concepts of safety and protection to the technology used. Sponsored by Palo Alto Networks, the cybersecurity badges activities range from decrypting and encrypting messages, to learning proper protection methods for devices, to exploring real-world hacking scenarios every day.

Women in Security and Privacy is a 501(c)3 group creating pathways for folks to get into the field. OWASP has a lot of in depth knowledge and the “Top 10 list”, suggests Salesforce Senior Application Security Engineer Aisling Dempsey.

Conferences include The Diana Initiative (August 9-10, 2019 in Las Vegas).

Books to read include The Web Application Hacker’s Handbook and The Tangled Web – Add a copy of each in your library, or as a coffee table book!

What are some resources we can add to this page for folks who want to get into cybersecurity as a career? Please tweet @GirlGeekX and share – thank you!


“Enterprise to Computer (a Star Trek Chatbot)”: Grishma Jena with IBM (Video + Transcript)

Speakers:
Grishma Jena / Cognitive Software Engineer / IBM
Sukrutha Bhadouria / CTO & Co-Founder / Girl Geek X

Transcript:

Sukrutha Bhadouria: Hi everyone, I hope you’ve been having a great day so far. Hi, Grishma. Hi, so yes, we are ready for our next talk. I’m Sukrutha and Grishma is here to give the next talk. Just before we get started, the same set of housekeeping rules. First is, we’re recording. We’re gonna share in a week. Please post your questions, not in chat, but in the Q and A. So you see the Q and A button at the bottom? Click on that and post there. If for some reason we run out of time, and we can’t get to your questions, we’ll have a record of it and it’s easy for us to find later and get you your answers later.

Sukrutha Bhadouria: So please share on social media #GGXelevate and look for job postings on our website at girlgeek.io/opportunities. We’ve also been having, throughout the day, viewing parties at various companies. So shout-out to Zendesk, Strava, Guidewire, Climate, Grand Rounds, Netflix, Change.org, Blue Shield, Grio, and Salesforce Portland office.

Sukrutha Bhadouria: So now, on to Grishma. Grishma is a cognitive software engineer at IBM. She works on the data science for marketing team at IBM Watson. So today her talk is about Enterprise to Computer: a Star Trek chatbot. I’m sure there’s a lot of Star Trek fans out there because I know I am one, and I can’t wait to hear about your talk, Grishma.

Grishma Jena: Thank you, Sukrutha.

Sukrutha Bhadouria: Go ahead and get started. You can share your slides.

Grishma Jena: Okay, I’m gonna minimize this. Alright, can you see my slides? Okay. Hi, everyone, I’m Grishma. As Sukrutha mentioned I work as a cognitive software engineer with IBM in San Francisco. So, a lot of my job duties involve dealing with a lot of data, trying to come up with proprietary data science or AI solutions for our Enterprise customers. My background is in machine learning and natural language processing which is why I’m talking on a chatbot today.

Grishma Jena: I’ve also recently joined this non-profit called For Her, where we’re trying deal with creating a chatbot that could act as a health center, as a resource center for people who are going through things like domestic abuse or sexual violence so I’m very interested to see you know, a totally different social application of chatbot. But for today we’ll focus on something fun. And before I begin, a very happy Women’s Day to all of you out there. So, yeah.

Grishma Jena: When was the last time you interacted with a chatbot? It could have been a few minutes before, when, you know, Akilah was talking and your Alexa probably got activated by mistake and you had to be like, “Alexa, stop.” It could be with Siri. We interact with Siri every day. It could be on a customer service chat or it could be on a customer service call.

Grishma Jena: Basically, there are so many different avenues and applications of chatbots today that sometimes it’s even hard to distinguish if are we talking to a human. Is it a chatbot in disguise of a human? And it’s quite interesting to see where chatbots have come in the past few years.

Grishma Jena: So, this was a grad school project that we did. Our idea was, okay, chatbots are amazing. We really like that they help take some of the workload off humans, but how can we make them seem a little more human, a little less mechanical? Could we give them some sort of a fun personality?

Grishma Jena: And we brainstormed for a bit and we finally came up with the idea, hey, why don’t we, I mean … Well, to be honest we weren’t that big fans of Star Trek, but we did become one during the course of this project and we were like, “Okay, let’s think of Star Trek”. It has a wide fan base and let’s try to not pick one single character from Star Trek but let’s take all of the characters and make this huge mix of references and trademark dialogues and see what kind of personality the chatbot would have.

Grishma Jena: So, like I mentioned, the motivation was to make a chatbot a little more human-like. And we wanted to have a more engaging user experience. So the application of this could be, it doesn’t have to be something related to, you know, like an entertainment industry. It could be also something like a sports lover bot so that would be very chatty and extroverted and it would support your favorite sports team. Or it could be something a little more sober like a counselor bot who is very understanding and supportive and listens to you venting out or asks you about how your day was. So yeah, we chose Star Trek infused personality.

Grishma Jena: So our objective with Star Trek was wanted it to incorporate references from the show. [inaudible 00:05:17] wanted to [inaudible 00:05:20] Spock and live long and prosper. We wanted it to be data driven model, we did not want to feed in dialogues we wanted it to just feed in a corpus and have it generate dialogues on its own. We obviously wanted it to give interesting responses and to have the user engaged because that is one of the things that a chatbot should do, right? So in really simple words, just think of a friend of yours or it could be yourself who is this, you know, absolutely big fan of Star Trek and just transfer that personality to a chatbot.

Grishma Jena: So this is what the schema of our bot look like. We had the user utterance which is basically anything that you say or that you provide as input to the chatbot. And then we had a binary classifier. I’ll delve deeper into why exactly we wanted it, but the main point is that we wanted it to be able to distinguish whether what you’re saying to the chatbot is it something related to Star Trek or is it something a little more general conversation like, “How are you feeling today?” Or “What is the weather like?” And depending on that we had on that we had two different routes which the bot would take to generate a response.

Grishma Jena: So before we begin, we obviously need some sort of data and we decided that we would take all of the data that was available for the different Star Trek movies and the TV series. You’d be surprised at how little data is available, actually. We initially thought of just doing a Spock bot, but Spock himself has very limited dialogues so we just expanded our search to the entire Star Trek universe. And that’s why we took dialogues from movies, TV series. We didn’t want to have any sort of limitations as far as the data was concerned. We ended up with about a little over 100,000 pairs of dialogues.

Grishma Jena: Then we also went and got this database, which is known as the Cornell Movie Database. This database was created by Cornell University, which has a collection of raw movie scripts. It’s just a really good data set to train your bot on, the way how humans interact and what kind of topics they talk about, what are the responses like.

Grishma Jena: And finally, we also had a Twitter data set because we wanted some topics that were related to the ongoing affairs in the world, the current news topics. Because we envisioned that if you had a chatbot then people do like to talk to the chatbot or ask for the chatbot’s opinion on something that’s happening in real time.

Grishma Jena: So the very first component of a chatbot was having a binary classifier. Like I mentioned, we had two different routes for our chatbot. One would be the Star Trek route and the other would be a general conversation route. So we had the binary classifier that would help us distinguish whether whatever the user is uttering or whatever the user is giving as an input is it related to Star Trek or is it general conversation which was getting handled by the Cornell Movie Database. So we used an 80:20, that is the training data set and the testing data set split. And the features that we used were we took the top 10,000 TF-IDF unigrams and bigrams.

Grishma Jena: TF-IDF stands for tone frequency and inwards document frequency. Tone frequency is nothing but how many times a given word occurs in your corpus and inverse document frequency,, it’s kind of a weight that is attached to a word. So think of a textbook or think of a document that you have. Words like prepositions, like the, of, and would occur multiple times. But really words that would be important that would have some sort of conceptual representation, perhaps like the topic of it. Compared to it would be a little rare in occurrence, compared to prepositions, compared to commonly used words, and that’s why they should be given more weightage. So that’s the whole idea behind TF-IDF.

Grishma Jena: Unigrams and bigrams are nothing but you divide the entire document that you have into words. An unigram would be one [bit kilo word inaudible 00:09:17] bigram would be a set of two consecutive words that occur in the document. There’s an example later on in the slide to explain it better. Stop words, when consider stop words are just filler words like I mentioned similar to the prepositions. And we were very happy with the performance of the binary classifier. We were able to get a 95% accuracy on the test set, and we decided that is good enough, let’s move on to the next one.

Grishma Jena: And finally, this is the main core of it, where deep learning comes into play. So with deep learning, we used a model called a Seq2seq which is a particular type of recurrent neural network. So if you can see the image on the right, it is a simplified version of a neural network where you give it an input and it gets an output and that output is also the input for the next cycle, so it’s kind of like a feedback looping mechanism.

Grishma Jena: First, the specific type of neural network that we use, Seq2seq. It was just two recurrent neural networks so just think of a really big component that has two smaller components, which is an encoder and a decoder.

Grishma Jena: So the encoder actually takes in the input from the user and tries to provide some sort of context. What do the words mean? What exactly is the semantics behind the sentence that the user has given? And the decoder generates the output based on the context that it has understood and also based on the previous inputs that were given to it, which is where the feedback mechanism comes into play.

Grishma Jena: So just to go a little deeper into it. This is a representation of what a Seq2seq with encoder and decoder would look like. So the input over here would be, “Are you free tomorrow?” and the encoder takes in that input and tries to understand what exactly is the context or the meaning of this sentence. And finally the decoders understands, okay, this is something someone is asking about either they want to take an appointment or someone’s availability or someone’s schedule. And that’s where the reply is something like, “Yes, I am. What’s up?”

Grishma Jena: So these are some statistics about how exactly we went on training this on AWS. We used a p2.xlarge instance with one Nvidia Accelerator GPU and then we had the Star Trek Seq2seq. So we had one Seq2seq for just Star Trek dialogues and we had another one, the Cornell Seq2seq which is on Cornell data, which is more for just a general conversation purpose.

Grishma Jena: So we went ahead, we generated some sentences, but then we realized that the ones for Star Trek were really good because you’re giving it Star Trek as input so obviously the output is also going to be Star-trekky. But for the general conversation ones, for things like, “What is the weather like?”, “How are you doing today?”, “What is the time?” it was a little difficult for us because obviously the input is not Star Trek related, right? So the output also wouldn’t be Star Trek related, but we wanted this to be a Star Trek chatbot.

Grishma Jena: So we brainstormed a bit and we thought, “Hey, why don’t we try something called a style shifting?” Which is basically like you take a normal sentence, a sentence from the general conversation, and you try to shift it into the Star Trek domain.

Grishma Jena: And the way we did this was, we went through the entire corpus, the data set for Star Trek, and we created a word graph out of it. A word graph would be, just think of it as you pass different sentences in the data set and each of the words would form a node and the edges between them would tell how they occurred in relation to one another. So if they occurred right next to each other or within the same sentence.

Grishma Jena: And along with the words in the node we also had a part of speech tag. So we indicated whether it was an adjective, or a noun, or a pronoun or a conjunction. So let’s say for example our sentence was, “Live long and prosper.” You break it down into four words which are the four different nodes and then we label them with a different part of speech tag and we connected them because they come one after the other in the sentence.

Grishma Jena: So what we did, was after we built out this really huge word graph, we looked it up to insert what could be appropriate words between two given words in the input. So once we had the sentence we would check for every two words in the sentence and see what are the words that we could insert in between to give it more of a Star Trek feel to it to just, you know, shift the domain into Star Trek.

Grishma Jena: We went ahead and we did that and these were the kind of results that we got. “I am sorry” was the input and then the word graph went ahead and inputted “Miranda” at the end. “I will go” and then it inputted “back” at the end of the sentence because “go” and “back” kind of occur very commonly with each other. And similarly for the start of the sentences, it tried to input names like “Uhura” or “Captain”. So one thing we noticed was it really good at inputting names at the start and the end of the sentence and using the character names from the show did end up giving it a slightly more Star Trek feel than before.

Grishma Jena: So we went ahead and we just randomly tried to insert words that occurred more frequently between two words but then we realized that some of the sentences were ungrammatical. So what do we do? We came up with this idea of let us use the word graph as it is and then let’s take some sort of a filter to our responses. So, like I said, we realized that the word graph was giving a few incoherent and incorrect responses. What we did was we went ahead and constructed an n-gram model.

Grishma Jena: So n over here would be unigram, bigram, trigram. You can see the example over here if n is equal to one, which is an unigram, you break down the sentence into just different words so “this” would be one unigram “is” would be another unigram. If n is two, which a bigram, you would take two words that co-occur together. So in this case the first bigram would be “This is,” second one would be “is a” and then similar for trigram it would be “This is a” and then “is a sentence”.

Grishma Jena: So we created an n-gram model which was just to understand what exactly is the kind of dataset that Star Trek has. And then finally we wanted to get a probability distribution over the sequence of words that we have had.

Grishma Jena: So once we get this, we start to filter the responses and we ran the sentences using the bigram models that we trained on the Star Trek data set. Because of this we kind of got a reference type for seeing that what structures are grammatically correct. We went ahead and we get them and the ones that were a little odd sounding or that didn’t really occur anywhere in the data set we went ahead and removed them.

Grishma Jena: Another metric that we used for this was perplexity. So just think of perplexity as some sort of an explainability metric. We went ahead and used that which would help us tell how well a probability distribution was able to predict it.

Grishma Jena: Finally, we have all of the things in place and we have to evaluate the performance of the chatbot. So we came up with two categories of evaluation metrics. The first one was quantitative metrics where we used perplexity, which was mentioned on the first slide. And the second one was we wanted to see often was it using words that were very particular to Star Trek that you don’t really use in normal day life, you know, like maybe spaceship or engage.

Grishma Jena: And the second category was human evaluations where we got a bunch of, user group and we asked them to just read the input and the output and see how good it was in terms of grammar. If the response actually made sense, if it was appropriate. And finally, on the Star Trek style. Just how Star-trekky did it sound?

Grishma Jena: And, we also came across another bot online which is called as a Fake Spock Pandora Bot which was contrary to the way we had. Our bot was data driven this was rule based so it was actually given an input of human generated responses.

Grishma Jena: We wanted to see how good would a data driven model perform as compared to a human generated one. So this is just what the Fake Spock Pandora Bot looked like. And these were the kind of responses that the Pandora Bot gave. If you said, “I’m hungry, Captain” it said, “What will you be eating?” So it’s giving really good appropriate responses because humans were the back end for this.

Grishma Jena: And then, what we did was we went ahead and evaluated the results. And we saw that our bot was performing better for Star Trek style and it also was a little more coherent. For grammar, Pandora Bot was much better and that’s not surprising because humans were the ones who actually wrote it out. For perplexity, the Star Trek perplexity started dialogues were 65, so that was our baseline number and we figured out that the kind of responses our bot was generating that are 60, 60.9 was a little closer compared to Pandora was like, way far off at 45.

Grishma Jena: So we were pretty happy with our performance. I’m just gonna give you a few examples of what the different bots generated. So the yellow ones are the Pandora Bot and the blue ones are the E2Cbot. So let’s see, if the user says, “Beam me up, Scotty” the yellow one, that is the Fake Pandora Bot, gives, “I don’t have a teleportation device” which is a good answer. And the blue one is, “Aye, Sir” which is also a good answer. A little curt, but nothing wrong with it.

Grishma Jena: In the second example if you see our bot answered, “Bones, I like you.” So the “Bones” part is actually come from the word graph which gives it a little more of a Star Trek feel. And the last one over here is the Fake Bot, the human generated one, just says, “I am just an AI chatting on the internet” which is kind of not the response that you are looking for.

Grishma Jena: A few more examples over here. The user says, “My name is Alex” and then the Fake Spock Bot says, “Yes, I know Christine.” I just told you my name was Alex, why would you call me Christine? But our bot says, “What do you want me to do, Doctor?”, which is a better response. And, yeah, these are the kind of responses.

Grishma Jena: I think some of our human focus group people said that they might be correct, appropriate responses, but they might not be factually correct, which was a challenge for us, as well as for the Fake Spock Bot. We didn’t really delve deeper into it because that would kind of dive more into having a question answering system and trying to check if it’s factually correct or not but we tried to make our focus group users understand that it’s just a bot at the end of the day.

Grishma Jena: So finally, we were able to generate Star Trek style text. We were very happy with that, we were able to use the data driven approach which meant we could automate it. And we did figure that it performed better than the human generated responses that Pandora Bot would give, at least on style and at least on the appropriateness. It still needs a little bit of improvement in grammar but we were pretty happy with it.

Grishma Jena: So that’s me. Live long and prosper. And feel free to reach out to me on Linkedin or on Twitter if you have any questions about this. Thank you.

Sukrutha Bhadouria: Thank you, Grishma. This was great. So just to close I just wanted to mention to everybody that you actually sent your speaker submission to us and that’s how we got connected. So thank you for doing that. We got a lot of comments from people who are Star Trek fans, but yeah, what inspired you to build this project?

Grishma Jena: Yes, so this was actually a grad school project. We were taking a deep learning course so all of us had to build a chatbot as an Alexa skill. We brainstormed a lot, and we actually thought that Spock because Star Trek has a really huge fan base so Spock would be a good idea to do. But Spock had very little dialogue in all of the movies and the television series and then we were like, “You know what, let’s not stick to just one character, let’s have the entire Star Trek universe.” And, the bonus was that during my semester, I could continuously binge watch Star Trek and say that, “Yeah, I’m doing research because I want to see how well my chatbot works,” but I was just binge watching to be honest.

Sukrutha Bhadouria: Nice. That’s awesome. Well, thank you so much, Grishma, for your time. We really appreciate it and for your enthusiasm in signing up through our speaker submissions.

Grishma Jena: Thank you so much, Sukrutha.

6 Ways You Can Be A Stronger Leader and Make Better Hires

Nupur Srivastava, VP of Product at Grand Rounds

Long before she ever started obsessing over product features and worrying about design deadlines, Nupur Srivastava spent her days — and evenings, weekends and holidays — obsessing over her jump shot and running drills in her hometown of Qurain. Her hard work and dedication to the sport took her all the way to the Kuwait National Basketball team, where she played from 1999-2002 and learned the value of teamwork and how fun it is to win!

After earning her Electrical Engineering degree from the University of Michigan, Nupur began her tech career as a Wireless Hardware Design Engineer at Cisco. She then pursued an MBA from Stanford and transitioned into product management, finding her passion in the health tech space. Over the past eight years, she managed teams ranging in size from 5 to as many as 50 people. Driven by her upbringing and desire to help people, she launched Impactreview (acquired by MaterNova), a community for reviews of maternal and child health products for the developing world.

Today, Nupur is the Chief Operating Officer at Included Health in San Francisco, where she leads the company’s product management and design teams. As Nupur explains, “the company is on a mission to raise the standard of healthcare for everyone, everywhere. The team goes above and beyond to connect and guide people to the highest quality healthcare available for themselves and their loved ones. By leveraging the power of data and technology, we create products and services that make it easy for everyone to get the best possible healthcare experience.

When the Girl Geek X team sat down with Nupur during our ELEVATE 2019 virtual event on International Women’s Day, we wanted to pick her brain and hear her biggest mistakes and learnings as a health tech product leader and people manager. She shared some great advice:

1. Hire slow and fire fast.

Nupur confessed that she made a lot of classic hiring mistakes with her first hire. She was at a small startup, strapped for resources (we’ve all been there!), and there was a lot of work to be done. Feeling stressed for help, she hired very quickly without thinking through the long-term impact.

“Basically, I hired the first person who I thought could do the job from a technical standpoint,” she shared, “…but one thing that I didn’t focus on was whether there was strong alignment with the company’s values and where we were  growing. Unfortunately, a year later, I had to let this person go because it was a mismatch. I really wish I had spent time understanding upfront whether they were a good fit for what the company needed at the time.”

The classic saying that you need to “hire slowly and fire quickly” rings true here.


2. Ask the right questions.

“A lot comes down to the types of questions you ask in the interview process as well as what you get from the references.” Finding the right fit is less about technical proficiency, and more about who they are as a person, why they have made the decisions they have in the past, and what they are optimizing for in their upcoming role.

You want to ask questions about how they’ve made decisions in their career to date, what drives them, what motivates them. What wakes them up in the morning? When they’re put in a difficult situation, what value system is driving their decision-making?

Nupur stresses that what you’re looking for in a team member will be different for different stages of the company, and for each company’s unique values and mission.

It’s important to tailor your approach to your individual situation, because the perfect hire on paper might actually be a perfect hire for a different environment, but a poor hire once your own values and needs are considered.

3. Hire for impact: seek out people who are hungry, humble and smart.

Many of Nupur’s favorite hiring and interviewing strategies came from a book that CTO Wade Chambers recommended, called Ideal Team Player. “It focuses on this notion of hiring people that are hungry, humble, and smart, and that concept has really resonated with me.”

“We want to raise the standard of care for everyone everywhere, so we need to make sure that people are hungry for that impact,” she explained.

“The humble component is self-explanatory. People that are low ego and prioritize the company above self are great to have on the team. In addition, if you’re hiring someone to work in healthcare, you need to be sure they appreciate that the patients we serve are suffering through things that we may not totally understand. They need humility to empathize with that struggle and build the right products for those patients.”

“And then smart is not actually what you think it may be. It’s not IQ smart, but rather people smart. There’s a base level assumption that you’ll be able to do the job, but it’s incredibly important that you do it in a way that brings people along — that makes you a teammate that people actually want to work for and with.”

One of the things Nupur has been using in her recent interviews is simply asking everyone, “What’s the hardest thing you’ve ever done?” Their response typically gives you a sense of their work ethic and insight into what they consider difficult. Sometimes they’ll even answer with a personal response, and it offers a good window into who the person is, and whether they’re someone you want on your team.

4. Accept that your top performers will always eventually leave.

“As painful as it is, top performers will leave you at some point. With all members of my team, I try to develop trust, care deeply about their career, and truly understand where they want to go long-term. This way, when they eventually decide to pursue another opportunity, I’m not surprised because there’s openness and transparency in the relationships.”

The week before we sat down with Nupur, someone she’d worked with for four years left the company. She was an extremely high performer, and she let Nupur know of her intentions to leave four months in advance because they were actively talking about where she wanted to go and what drives her. The team member had joined a 50-person company. With headcount now over 500, she was ready for something different.

“I think the most important thing is to have that level of trust with your team members, such that you understand what their career goals are and you’re together making the decision about when is the right time for them to leave. If you adopt this approach, you can prepare for their departure in a way that is not disruptive.”

“It can feel like a painful punch in the gut when someone tells you they’re leaving,” she lamented, “but I think the least we can do is just not be surprised by the decision. At some point, maybe for their own career growth or evolution, or other things that they are optimizing for in their lives, you want them to leave. And as long as you are open and honest with each other and there is trust and transparency, it’s not the end of the world.”

Nupur’s general philosophy is one we could all benefit from adopting: “Everyone has different goals in life. The most we can do is be an advocate and great manager for our direct reports when they work for us, and help influence what they do next, so that you and the business are prepared for employee departures.”

5. Create an environment that welcomes diversity of thought and personality types.

“One of my biggest learnings as a leader over the years has been … beyond diversity based on race and gender, there’s tons of diversity in personality types and the way people like to do work.”

The Head of Data Science asked various team members to take a StrengthsFinder questionnaire, then put everyone into groups of people that are alike so they could discuss things they wanted to teach other groups who were different from them.

The entire product team has also used the DiSC assessment to better understand their behavioral differences. “This exercise gives you empathy for how different people want to show up, and how they want to debate ideas.” 

“Not everybody is comfortable being presented a problem and immediately jumping in and giving their thoughts. Some people want to think about a problem, spend a day organizing their ideas, and come back with their thoughts prepared.” 

“For me,” Nupur admitted, “the first step in improving my communication and collaboration with others is simply awareness. Where do people fall either in the DiSC profile or with StrengthsFinder? What do I need to be aware of as their leader so that I’m creating a comfortable environment for them to speak up?”

“I can remember the first realization I had when I recognized, ‘Oh, everybody doesn’t like coming into a room and talking loudly about their ideas? That’s interesting. I thought everyone was exactly like me!’ and that’s obviously not the case.”

“Using some of these frameworks has been incredibly important because it not only helps you understand others, but it also helps you realize how your type may be showing up for that person and what things you may need to temper, especially as a leader, because you’re setting the tone for the team.”

Nupur has a team member opposite her on the DiSC profile, and she’s started running ideas by him to make sure that he can offer feedback and criticism before she takes it to the team, because as she says, “I’m just hyper-excited and trying to tell everybody everything as soon as the thought occurs.” And that freaks some people out. It is important to understand where others in your team sit in the DiSC profile so that you can personalize your leadership style with them.

6. Let people know where you want to go!

One of the questions we hear asked at Girl Geek X events time and time again is about how to get ahead or move into a management role when you don’t have previous managerial experience.

Nupur’s advice is to make your manager aware that you want to be a manager, and make your goals explicit. “If someone wants to be a manager, you need to make sure that there’s an opportunity and a business need, and an opening in the company for a manager. Have open conversations, and make sure that you have the skills, training, and support of your manager.”

“The biggest thing is raising your hand and making it clear that that’s the path you want to go. Then hopefully if you have a good manager, and you are ready, they’ll make that opportunity for you.”

If you’re having open conversations about your goals regularly — say once per quarter — and you find yourself in a situation where the promotion doesn’t feel like it’s ever going to happen, or you start to feel like you’d be better off somewhere else, you’ll be in a better position to move on gracefully and with a reference you can count on time and time again.

For more hiring and people-management advice from Nupur Srivastava and other Girl Geeks, check out the full video & transcript from her panel on “Building High Performance Teams” at Elevate 2019, and subscribe to the Girl Geek X YouTube channel!



About the Author

Amy Weicker - Head of Marketing at Girl Geek X

Amy Weicker is the Head of Marketing at Girl Geek X, and she has been helping launch & grow tech companies as a marketing leader and demand generation consultant for nearly 20 years. Amy previously ran marketing at SaaStr, where she helped scale the world’s largest community & conference for B2B SaaS Founders, Execs and VCs from $0 to $10M and over 200,000 global community members. She was also the first head of marketing at Sales Hacker, Inc. (acquired by Outreach) which helps connect B2B sales professionals with the tools, technology and education they need to excel in their careers.

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

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Gretchen DeKnikker, Sukrutha Bhadouria

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

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

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

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

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

Gretchen DeKnikker: Did you guys see it?

Sukrutha Bhadouria: You did?

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

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

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

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

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

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

Shawna Wolverton speaking

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

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

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

Swati Krishnan

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Erin McKeown speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Eleanor Stribling speaking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Audience Member: I will find you. Thank you.

Shawna Wolverton: I have a feeling–

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

Audience Member: Oh no.

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

Audience Member Thank you.

Shawna Wolverton: Heard one up here.

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

Shawna Wolverton: Lovers and haters of Python.

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

Audience Member: Talk to me more about it.

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

Shawna Wolverton: Question.

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

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

Shawna Wolverton: For the record, blameless accountability.

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

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

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

Audience Member: [inaudible].

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

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

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

Audience Member: Got it. Thank you.

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

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

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

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

Shawna Wolverton: One in the back.

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

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

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

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

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

Eleanor Stribling: Sure.

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

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

Audience Member: Yeah, yeah, yeah.

Eleanor Stribling: Great.

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

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

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

Video Speaker: Oh okay, one word.

Video Speaker: One word to describe her? Badass.

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

Video Speaker: Badass.

Video Speaker: Is badass one word?

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

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

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

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

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

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

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

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

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

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

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

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

Video Speaker: So, thank you.

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

Zendesk Girl Geek Dinner group picture

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


Our mission-aligned Girl Geek X partners are hiring!

“Coding Strong at Age 60”: Akilah Monifa with ARISE Global Media (Video + Transcript)

Speakers:
Akilah Monifa / SVP / ARISE Global Media
Gretchen DeKnikker / COO / Girl Geek X

Transcript:

Gretchen DeKnikker: I’m so, so, so excited about our next speaker, Akilah Monifa. She is the SVP at ARISE Global Media, which is a digital media platform for LGBTQ folks of color and their allies. And she made an Alexa skill called Black Media–or Black History Everyday, which I really want to just make it Black History Errryday. But not everybody’s gonna put all the Rs in it.

Gretchen DeKnikker: I’m very, very excited for this talk and you guys are gonna love it. Please, welcome Akilah. All right.

Akilah Monifa: Thank you, Gretchen.

Gretchen DeKnikker: All right, thanks.

Akilah Monifa: Welcome, everyone. It kind of reminds me, the start kind of reminds me of in eighth grade watching a science film and the film broke, but it is 2019, so we did get it together. I am Akilah. I’m gonna talk today about my Alexa Skill Black History Everyday.

Akilah Monifa: Even though you can see me, just wanted to share a little about me and the skills. This is me. This is my wonderful headshot. One of my favorite shots of myself. This is me and my children. my son Benjamin who is 15 and my daughter Izzie who turned 18. This is Raya Ross who is my intern and is a high school student, and helps me work on the skill. I just wanted to show a picture of her. This is my friend Elan and myself. We are in our Black History is Golden tshirts from the Golden State Warriors, because, obviously, black history is near and dear to my heart. Elan also helps a lot on the site, too.

Akilah Monifa: Okay. Now, this is just a brief little video that I wanted to share with you that Alexa made about my app.

Akilah Monifa: My first skill is pretty simple. It’s called Black History Everyday.

Alexa: Patricia Bath, that first black woman to serve on staff as-

Akilah Monifa: It started to work at 5:00 AM, on April 3rd, 2017, which happened to be my 60th birthday. And I cried when it worked. I cried tears of joy. I want people to know that you don’t have to know the coding to do it. I didn’t know the coding, and I actually now have three skills. I think it’s very exciting. I mean, I don’t think that I can adequately describe just the thrill that all of these skills have, but particularly the first one. And to know that so many people can hear the skill and be as enlightened through sound and knowledge, as I was, it is, I think, very, very profound.

Akilah Monifa: My children jokingly say that that’s my commercial for Alexa.

Akilah Monifa: Why did I start the skill? The first thing was that, as we all know, Black History Month in the United States is in February, and it’s the shortest month of the year, lot of people have complained about that. 28 days, 29 in leap year.

Akilah Monifa: My other big issue was that I really wasn’t learning much in Black History Month. The same facts were being regurgitated over and over. So, what do you remember about Black History Month in general? I mean, we heard facts about Martin Luther King, George Washington Carver, Rosa Parks, and that was really the extent of it. That certainly was not sufficient for me.

Akilah Monifa: The first thing that I did was to develop a website which is BlackHistoryEveryday.com. I was actually amazed that the URL was available, but it was, so I developed the website. My thought was that every day I was going to put a different black history fact on this website.

Akilah Monifa: Here are a couple of examples. The website exists. A few examples of the facts that I put on the website, and they’re very short. I wanted them to be diverse. This is Isis King who is the first transgender model to compete on America’s Next Top Model in 2011. This is the Mobile Edition. This is what it looks like. Mashama Bailey, the first black woman nominated for Best Chef at the James Beard Foundation awards 2018. Glory Edim, she’s the founder of Well-Read Black Girl, an online book club and community.

Akilah Monifa: The other thing that I wanted was the oh wow factor, “Oh wow. I didn’t know that,” or, “I was unaware of that.” So, I really tried to have really interesting things. Since today is International Women’s Day, starting today through the rest of the month all of my facts are going to be about women, about black women.

Akilah Monifa: Now we go from, I have this website. Two years ago, someone gave me an Alexa, and I had heard about it, but I had not experienced it. I got it. I saw that there were all sorts of skills on Alexa, so I thought I should be able to have my website into an Alexa skill. That was my thought. I thought how difficult can it be. Actually, I thought I don’t know anything about coding, so maybe I can’t do it. But I googled how to do an Alexa skill, and found out there was something called the Alexa skills kit, and that was online.

Akilah Monifa: So, I went to the Alexa skills kit and got information that alleged that one could build a skill in minutes with no coding required. I said, okay, I’ll develop the skill. Basically, when I went to the Alexa skills kit, there were five different entries that I could make to help develop the skill. I suppose theoretically, it could have been done in minutes…skipping ahead. It did not take me minutes. And when I tried to fill out the form or I did fill out the form and I developed my skill, it got rejected. I lost count the number of times that it got rejected. After you submit it, you submit it for certification, and it was not successful. I think I submitted it between 75 and a hundred times. I joined Alexa developers groups to try to figure out what was wrong and talked to people and tweeted…. The shorter version of it is that finally, after all of this, it did start to work. And I just wanted to show you this is just the first page. It was almost fill in the blanks. But the key thing that was missing for me in developing the skill is that I thought that simply by having the website that I could feed the website into Alexa, and Alexa would be able to read out my website, and that in fact was not the case.

Akilah Monifa: It was finally when I, through a lot of research and trial and effort, realized that one thing that I needed was to get Alexa to talk to the website. It was pretty simple. I just had to find a device, and the device that I found is called Feedburner, Feedburner.com. Once I plugged my website into that, then Alexa could understand what my website said and read out the information, which was just wonderful.

Akilah Monifa: As I described in the video, it actually started working on my 60th birthday, which was two years ago, which will be coming up two years ago, so I was very ecstatic. I can also really, if you’re trying to build an Alexa skill, really recommend Feedburner. After that, it was very simple.

Akilah Monifa: I just wanted to show–The skill, I did a definition of the skill. The skill basically says that it is Black History Everyday in about a minute from Arise 2.0. Black history is no longer relegated to the shortest month of the year. A different black history fact presented daily, seven days a week, 365 days a year, 366 in a leap year. It’s prepared. I say, “Invented by the team at Arise 2.0,” which is mainly consisting of me and Raya with some help from a few other friends who give me information. Our mission is to tell our diverse stories.

Akilah Monifa: If you have an Alexa and you go to Alexa, you can enable the skill in the app. And there it is, Black History Everyday, actually with an old logo. Or you can actually just ask it to enable it. I just wanted to at least show you–and hopefully, Alexa will work–how it works.

Akilah Monifa: Alexa, what’s my flash briefing?

Alexa: Here’s your flash briefing. From Arise 2.0 Black History Everyday, Zarifa Roberson, CEO/ Founder/ Publisher of I-D-E-A-L magazine for urban young people with disabilities 2004 to 2015.

Alexa: Toni Harris is the first woman football player at a skill position, non-kicker, to sign a letter of intent accepting a scholarship to Central Methodist University in Missouri in 2019.

Alexa: Akilah Bolden-Monifa, Alexa pioneer, developed Black History Everyday Skill for Amazon’s Alexa in the website BlackHistoryEveryday.com.

Alexa: Dr. Roselyn Payne Epps is the first black woman to serve as President of the American Medical Women’s Association in 2002.

Akilah Monifa: The only glitch was that it was my intent to have one black history fact every day. What I found out with Alexa is that through my website Alexa would read out five facts a day. I had to basically then shift gears and make sure that I had five different facts a day instead of one. That’s my skill. Thank you.

Gretchen DeKnikker: Thanks. Looks like I was still muted. Thanks, Akilah.

Akilah Monifa: You’re welcome

Gretchen DeKnikker: That is so awesome. There’s other people. It’s the same. People [inaudible 00:11:48]. That’s making their Alexas go off just listening to you.

Akilah Monifa: Yes.

Gretchen DeKnikker: Which is awesome, because that’s what happened when we did the dry run for her speaker talk too. And so, we had one question come in. She keeps getting rejected, she’s saying with Google not Alexa. Because I think they don’t want to give me the name I want. It’s frustrating for an indie developer. How many times did you say you had to keep applying?

Akilah Monifa: I lost track, but I believe that I applied for certification between 75 and a hundred times before it was accepted. And I would say that the one thing–that it passed certification, basically.

Akilah Monifa: The one thing that I didn’t do was you can test it before you submit it for certification, and I didn’t do that. I foolishly just kept certifying it and submitting it through certification thinking that it would work, and it didn’t. If I’d tested it, I would have seen that it didn’t work, so I probably wouldn’t have submitted it for certification

Gretchen DeKnikker: Another question. What was the thing that surprised you most about developing a skill?

Akilah Monifa: I think that the thing that surprised me, what most, was how easy it was that I just had the idea. Before people told me that you needed coding to do it or you needed to pay someone to code you, so I thought I can’t do it. The surprising thing was that when I googled how to build an Alexa skill, yes, if you know coding you can build it, but you can build it without knowing coding.

Gretchen DeKnikker: Amazing. I think this is great. What I’m really hoping, this will be my request to you, is that next year you can come back and tell us about building it for Apple and for Google, so that we can all have it, because I do think that American school systems don’t do a great job of giving that information out. It’s amazing that you took the time to just share it with everybody.

Akilah Monifa: Well, and the good thing is that it is available to everyone because even if you don’t have the skill, if you don’t have Alexa, you can get the information through the website. Just go to BlackHistoryEveryday.com, and all the information is on the website, which is good.

Gretchen DeKnikker: Awesome. All right, Akilah, this was great. Thank you so much for taking the time.

Akilah Monifa: Thank you.

Gretchen DeKnikker: All right.

12 Product Design Leaders To Follow In 2019

Love building digital products with amazing user experiences? Product Designers as a job title has blazed a trail in tech for the past decade with the rise of Facebook VP of Design Julie Zhuo leading the industry.

We look to Product Design leaders at companies of all sizes to find insight in their careers and map the rise of Product Design as a profession. Lucky us — many of these leaders speak publicly, tweet and share their expertise and thought leadership.

Here are 12 Product Design Leaders to Follow in 2019:

Christine Fernandez – Stitch Fix VP, Product Design

Christine’s Proudest Moment: “There’s so much work that I’m proud of, but my biggest accomplishment is definitely the teams I’ve built over the years, and helping some of the best designers I’ve had the pleasure to work with grow into leaders. Design now has such an important seat at the table – at the executive level, in boardrooms, and shaping the future at the most innovative companies. It’s been quite a journey, and I’m so grateful to have been a part of leading that change.”

Christine Fernandez is a Vice President of Product Design at Stitch Fix. Previously, she was Chief Experience Officer at Art.com, Head of Design at Uber, and worked as Creative Director at R/GA, frog, Razorfish, Schematic and FCB. Connie holds a B.A. in Graphic Design and a minor in East Asian Studies from University of Pennsylvania. Follow her on Twitter at @ctfernandez and her product design thoughts on Medium.

Connie Yang – Coinbase Director, Design

Connie’s Proudest Moment: “I scaled a team from 3 to 20 in a year – including establishing the functions of User Research, Product Writing, and Brand Design. I did not expect to do that, nor did I think it was even possible. You never know until you actually try.”

Connie Yang is a Director of Design at Coinbase. Previously, she spent six years at Facebook as a Product Designer. Prior to that, she was a UI Director at Twist and PopCap Games, Art Director at ReignDesign and began her career as a Graphic Designer working in advertising. Connie holds a B.A. in Graphic Design and a minor in East Asian Studies from University of Pennsylvania. Follow her on Twitter at @conniecurious and her product design thoughts on Medium.

Erica Weiss Tjader – SurveyMonkey VP, Product Design

Erica’s Proudest Moment: “Landing this role as VP of Product Design at SurveyMonkey 2 years ago – not only because it’s a great opportunity with an amazing company, but also because this role represents a shift in my willingness to take risks, aim high, and flex my leadership muscles.”

Erica Weiss Tjader is a Vice President of Product Design at SurveyMonkey. Previously, she spent six years at Quantcast as the Director of Product Design, where she was responsible for building the design and research functions. Prior to that, she was an Interaction Designer and User Researcher at Move, eBay and Yahoo. Erica holds a B.S. in Cognitive Science and B.A. in Communication Studies from UCLA. Follow her on Twitter at @ericatjader and her product design thoughts on Medium.

Huda Idrees – Dot Health CEO

Huda Idrees is CEO at Dot Health. Prior to founding Dot Health, she was Chief Product Officer at Wealthsimple. Prior to Weathsimple, she was a Product Designer at Wave, an Interaction Designer at Shaken Media Collective, and an UX Designer at Wattpad. She began her career as a Web Developer. Huda holds a BASc. in Industrial Engineering from University of Toronto. Follow her on Twitter at @hidrees and her product design thoughts on Medium.

Irene Au – Khosla Design Partner

Irene’s Proudest Moment: “I had the honor and privilege to build the industry’s most influential and talented design teams over the last two decades. At Yahoo! and Google, we established the gold standard for user experience and design for the internet that continues to shape the profession in this industry today, and we elevated design’s strategic importance in both companies.”

Irene Au is a Design Partner at Khosla Ventures. Prior to Khosla, she was Vice President of Product at Udacity and build and ran design for all of Google and Yahoo! for many years. She began her career as an Interaction Designer at Netscape. Irene holds a M.S. in Mechanical and Industrial Engineering from the University of Illinois at Urbana-Champaign, and a B.S. in Electrical and Computer Engineering from the University of South Carolina. Follow her on Twitter at @ireneau and her product design thoughts on Medium.

Julie Zhuo – Facebook VP, Product Design

Julie’s Proudest Moment: “Helped Facebook scale from 8 million college students to billions of users worldwide.”

Julie Zhuo is a Vice President of Product Design at Facebook. She started as Facebook’s first intern in 2005, was hired as a product designer at Facebook, and has been working at Facebook for over a decade. She published in 2019 “The Making of a Manager: What to Do When Everyone Looks to You.” Julie holds a M.S. and B.S. in Computer Science from Stanford University. Follow her on Twitter at @joulee and her product design thoughts on Medium.

Katie Dill – Lyft VP, Product Design

Katie’s Proudest Moment: “My great achievement and greatest joy has been the teams I have had the pleasure to build at Lyft and Airbnb. Great things come from great teams, and my focus as a leader has been finding just the right mix of folks that can come together as one to build lasting change. A strong culture full of people that inspire each other and elevate each other’s work is the best thing I have ever built.”

Katie Dill is a Vice President of Product Design at Lyft. Prior to Lyft, Katie was at Airbnb as a Director of Experience Design. Prior to that, Katie worked at frog design for five years, where she began her career as a Design Analyst. Katie holds a B.S. in Industrial Design from Art Center College of Design, and a B.A. in History from Colgate University. Follow her on Twitter at @lil_dill and her product design thoughts on Medium.

Kim Lenox – Zendesk VP, Product Design

Kim’s Proudest Moment: “I have had the privilege to nurture a number of burgeoning designers into design leaders. Seeing how they grow their careers, take new leadership roles and bring their own contribution back to the design community is one of my fondest rewards as a design leader.”

Kim Lenox is a Vice President of Product Design at Zendesk. Prior to Zendesk, she was a Director of Product Design at LinkedIn. Prior to that, she was a Senior Manager of Interaction Design at HP Palm. She has held a number of roles in research, interaction design and UX Design, and has consulted and freelanced. Kim holds a B.F.A. in Photography from San Jose State University. Follow her on Twitter at @uxkim and her product design thoughts on Medium.

Kim Williams – Indeed Senior Director, UX Core

Kim’s Proudest Moment: “I have had the honor of orchestrating Design and Brand Systems teams at brands that focus on connection. First at eBay, and now at Indeed, where I am proud to be building a team of talented product designers, technologists, and creatives. My team inspires and challenges me daily, as we work on creating experiences that further empower job seekers during their job search.”

Kim Williams is a Senior Director of UX Core at Indeed. Prior to Indeed, she was at eBay for two years, working in roles from Head of Brand Systems to Creative Director for eBay’s human interface group. Prior to eBay, she was as a Creative Director for Oglivy & Mather, Serious-Gaming Agency, and Weber Shandwick. She began her career as a Designer for consumer goods companies. Kim holds a BFA in Visual Communications with an emphasis in Graphic Design. Follow her on Twitter at @kimwms_.

May-Li Khoe – Khan Academy VP, Design

May-Li’s Proudest Moment: “Despite having worked on so much of Apple’s product line and have a pile of patents as a result, I’m proudest of putting pink hearts and technics 1200s into MacOS, and building a diverse & inclusive kickass design team at Khan Academy.”

May-Li Khoe is a VP of Design at Khan Academy. Prior to Khan Academy, she was at Apple for over seven years, working in roles from Interaction Designer to Senior Product Design Lead. She began her career at IBM as a Research Assistant for three years, and was at MIT Media Lab as an Undergraduate Research Assistant for three years. May-Li holds both M.Eng and S.B. in Computer Science and Electrical Engineering from MIT. Follow her on Twitter at @kayli and her product design thoughts at Medium.

Ratna Desai – Netflix Director, Product Design

Ratna’s Proudest Moment: “My greatest achievement has been to build diverse teams and create the conditions necessary for design to live alongside technology and business strategy. Both at Netflix and Google, I was able to connect individuals to the right opportunities within very different organizational cultures. The key has been to lead with authenticity and adapt my approach to complement the culture and design’s relationship to other functions. The successes have come when open-minded, passionate and hardworking teams selflessly collaborate to do their most meaningful work. I’ve had the privilege of witnessing the best product ideas thrive, transform industries and shape society.”

Ratna Desai is a Director of Product Design at Netflix. Prior to Netflix, she was at Google for four years leading multidisciplinary UX design teams. Prior to that, Ratna was at frog design for six years as a Creative Director, an Art Director at Gap and Korn Ferry, and began her career as a Marketing Associate at the Wall Street Journal. Ratna holds a B.S. in Graphic Design and B.A. in Rhetoric & Communication from UC Davis. Follow her on Twitter at @RatnaDesai1.

Susan Dybbs – Collective Health VP Product & Design

Susan Dybbs is a Vice President of Product & Design at Collective Health. Prior to Collective Health, she was at Cooper for four years leading the interaction design team as Managing Director. Prior to that, Susan lead UX consulting for a few years. She began her career as an User Interface Designer at Microsoft. Susan holds a M.D. in Interaction Design from Carnegie Mellon University and a B.A. in Design, Urban Studies, Psychology from New York University. Follow her on Twitter at @dybbsy and her product design thoughts on Medium.

Product Designers – We Want To Hear From You!

Tell us about your Product Design experience, resources, and nominations!

Thanks to Samihah Azim, Women Talk Design, and Latinx Who Design.

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