Operators Ep 23: Nik Koblov (Ramp)

  
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Nik Koblov is the Head of Risk and Financial Engineering at Ramp.  Prior to joining Ramp, Nik spent three years at Affirm working as the Head of Bank and New Markets Engineering, and 18 years at Goldman Sachs.

In this episode I talk to Nik about the engineering culture at Goldman and how it set him up well for the startup world, why Affirm’s innovative model was such a breath of fresh air, and what got him so excited about Ramp. He shares about the uniqueness and ambition of Ramp’s holistic approach, how the company works to empower its employees, and some benefits over the past year of being remote.

I hope you enjoy the show.

Full transcript available.

Operators Ep 23 Transcript

Delian Asparouhov:

Hi, everyone. My name is Delian and I'm a principal at Founder's Fund, a venture capital Affirm based in San Francisco. This is Operators where I interview non-VC, non-CEO, non-founder operators that make the startup world go around.

            Today, I'm interviewing Nik Koblov, head of risk and financial engineering at Ramp. Prior to joining Ramp, Nik spent three years at Affirm working as the head of bank and new markets engineering as well as 18 years at Goldman Sachs before that. I hope you enjoy the show.

            Sweet, Nik, excited to have you on. You're going to be the first person on the podcast who's had to let's say, get to know, or at least deal, with another Asparouhov.

Nik Koblov:

That's right. Yeah.

Delian Asparouhov:

Hopefully, my brother's entertaining.

Nik Koblov:

He is. He's awesome. He's awesome. Pleasure to be here. Thanks for having me.

Delian Asparouhov:

Cool. So yeah, the way that we normally structure these conversations is before diving into what you're currently working on in the world of Ramp and some of your prior work in startups, I like to always sort of go back in time and talk a little bit about how you sort of started your career in tech, which was you started studying physics and then, studying computer science and then, getting into the world of sort of just startups back in even the mid '90s. And so, I would love to kind of hear what sort of interested you in computer science, why that out of all things in sort of the early '90s. And then, sort of what go you over to K2 Design, that sort of first startup that you joined?

Nik Koblov:

Yeah. It was a wild trip, man. It was also science. I was studying theoretical physics. I was born into a family of scientists. My father was a physicist. My mom was a research chemist. And I always wanted to be a musician, but my parents prohibited me from pursing that. And there I found myself in the university studying physics. And to be honest, I didn't want to be a scientist. I dreamt of music. I skipped on lectures and went to play in a jazz rock band.

            But somewhere around my senior year or my junior year, I think it was my junior year, we started doing lots of modeling in turbulence and high rate dynamics. So my school was known, and it's still known in Europe as one of the premier schools of theoretical high rate dynamics. There's lots of big names came out of, like Professor [Dushuney 00:02:39] and Feynman, even in the '30s. So it's a good old school. It predates Soviet times. I think it was founded in 1902.

            And the approach typically with Soviet science, is that you sit with a stack of papers like this and you analytically solve partial differential equations till you basically cannot hold your pen anymore. At that point, you take all of this. There's no personal computers anywhere. We're talking about '90s. You go to a research institution somewhere. So my mom worked at a research chemistry lab and she was like, "Yeah, come on over. We have some computers. You can have it." And usually spend all night basically sitting and coding it.

            And after one night of debugging, it sort of clicked. I was like, "Oh, my God. This is fascinating. This is what you can do with that." And yeah, so kind of got there through physics. And it was more enjoyable than writing stacks of paper with your pen at that point in time.

            So my family moved here in '94. I transferred to Grant Institute at NYU and switched over to computer science. Although I probably should have went into physics quickly finish it, because I just got so many credits in physics. But I was like, "You know what? I had enough of pure science." I actually wanted to do coding at that point.

            So went to the job database in college. And there was a startup literally on 11th and Broadway. And Ramp is on 12th and Broadway. So it was one block away that was looking for a founding engineer. And it was basically a traditional designer, a former actor from Hollywood and a Wharton Business grad, three partners, decided to go online. They were a traditional print shop and there was like, "Well, we need some engineers. We have designers, but we need some engineers to bring this online."

            And they came over. My English was so bad, they wouldn't let me pick up the phones when they rang. And I was just sitting down, head down. We IPOed eventually. I didn't even know what IPO was. I was like, "What is academics doing there? I don't know." I was just sitting coding and doing my job.

            But it was fascinating, kind of do everything from working on accounting team servers and setting up silicon graphics workstations for designers, working with... We had our first hosting service down in Texas and I was like, "Oh." We run stuff on somebody else's computer, pre-dated the cloud. And but yeah, I was just so focused on work, I kind of almost missed IPOs. I was like, "What's happening with the company here?" I was like, "Okay, why is there's all this excitement there?" But yeah. No, it was a wild experience. It was really, really fun.

Delian Asparouhov:

It sounds like you had some kind of interesting projects that you worked on there, like the two that you at least list on LinkedIn that are kind of cool. You were doing the live web coverage of the IBM Deep Blue versus Kasparov Games and then, also the Toys"R"Us e-commerce website, RIP to Toys"R"Us. But yeah, I guess, I don't know. This sounds cool. Do you have some fun stories from that?

Nik Koblov:

Definitely. So yeah. So K2 Design was specializing on sort of live events in the early day e-commerce. So two super cool projects we got was the Bring in 'da Noise, Bring in 'da Funk. So my most purely fascinating memory was around the opening gala at Urban Plaza, where I was standing with a spark laptop. Literally, this thing was like 20 pounds with a microphone connected into it and interviewing Susan Sarandon when she showed up. I was like, "Oh, my God." There's all these celebrities coming in.

            And we basically built what now you call a blog. At the time it was called [Buet&Bork 00:06:38]. People were chatting about the event, "Oh, the show is going to go to Broadway." It's so big. There's all these actors coming in. And so I built a blog. We built a live video feed. It was all over 56K modem speed. It was pretty fascinating all the compression we had to get out of it. We had a lot of help from MIT scientists.

            And actually, we built a relationship that went into the next project which was the Kasparov versus Deep Blue. I think it was one of the first, if not the first, live covered events in the history of the internet. For a split second, we had the highest traffic in the world, or so we've been told. MIT servers that hosted the website went down when the match started. We spent the whole night moving all the resources over to the IBM servers. And then, IBM scientists were helping us out to get the website up.

            So at the end of the day, there was no load balancer, so we had a page where we had 10 links to 10 servers. So basically, just go to the landing page, like, "Okay, we'll just rely on people randomly clicking on this thing. And then, we'll go in and get to their version of the website on server three. And that will hold through the duration of the games."

            So I coded live commentary. So there was IBM speech-to-text software. We streamed in the commentary. We parceled off files from Deep Blue. I was physically sitting in the Philadelphia Convention Center during the game in the same room with the IBM scientists. And there was a backup Deep Blue. So when I walked in, there was this big cabinet in the corner. I was like, "Oh, is this Deep Blue?" And they were, "No, no. This is the backup. The real one is in West Chester in the IBM center."

            And then, the scientists, when they got to the end game, Deep Blue, I think it was the second game, it was a notoriously bad at End Game. End Game is hard. And you could see at the end of the match, the scientists literally pacing around like they are playing chess. It's like, no. I think at this point, it's these guys versus Kasparov. And I guess, I know who's going to win. But they're all nervous and the computer is not coming up with the good moves. So that was just eye-opening. It was absolutely fascinating.

            The best part of the story is I go back to school, so I was still studying at NYU, and second semester of my network class an IBM dude comes in. The professor invites him. And he talks about load balancers on network routers and he said that, "We built this product that I could describe so we could all take notes. It's fascinating architecture. We can now do load balance as part of the network appliance. It's pretty cool, especially for the '90s." And I raised my hand. I was like, "What made you guys build it?" He was like, "Oh, there was this event, Kasparov versus Deep Blue, and the website went down." I was like, "Oh my God." After class, I went to give him a hug. I was like, "That's amazing work on this project."

            So it was great. It was great to see stuff that you study and stuff that you work on just all come together. That was fascinating to me. It's not so dry and academic. It's like there's real life. There's real events run through real internet. It was pretty cool.

Delian Asparouhov:

That is so, so cool. Wild. Yeah, so I guess, after that, you kind of made a transitioning career that stayed maybe somewhat consistent sort of since then, which was you kind of shifted into a world of sort of mixing let's say computer science plus sort of financial services. And that's basically sort of what you've done in every step of your career sort of since then. And so, I guess, yeah, maybe walk me through sort of how you moved over to Alliance Capital and then, Goldman Sachs. And was that an intentional hey, I want to sort of go into this world of finance plus computer science? Or sort of what motivated that shift?

Nik Koblov:

Yeah. Yeah, I'm a little bit ashamed of the answer. I basically just went for the pay. I was graduating and all the businesses come on campus and you get in offers. And someone just gave me 10K more. Back in the day, the engineers were getting like 40K was the going salary. And I got 50 and I was like, "Oh my God. I'm so rich." And I went for this company. Little did I know, I almost ended up hating fintech because of this first job. It was like everything that I didn't want. It was a big company. It was a buy side. It was then acquired by I think, Axa, a French insurance company. And then, you basically cannot sense exactly what you're doing and why you're doing it.

            So I ended up doing personal projects that were just much more interesting in the evening at the job. And I just ran away after a year. If this is what finance is like, I never want to do anything with that.

            But I was in New York City. Where does a programmer go in the '90s in New York City? So again, more banks reaching out to me. And then, I ran into Goldman guys and my sort of aftertaste at this point was kind of like, I'm going to quote of our Ramp founding engineers, Pablo Meier. He has a great quote. Becoming software engineer because you like to code is like becoming a butcher because you like animals. It is not what you think it's going to be. It's not going to be a glorious. I write the most amazing architecture all the time. I solve incredible problems. It's a lot of grunt work.

            So I sort of was getting that first realization. I was like, "Oh, that fun stuff I used to do at K2 Design, they don't do it in finance."

            And then, I ran into Goldman guys and I was blown away. It was a small panel. It was a hard problem. I did not solve it actually. I had a bug. They gave me a benefit of like, "Okay, can you point out where your error is?" I was like, "Ooh, you didn't just turn me around." I was like, "Okay, yeah sure. I screwed up right here." I really appreciated the transparency. And the team was small. It was like, "How big is the team?" It was like, "Well, there's two guys leaving so we're hiring you. It's going to be you and your boss and you're going support $20 billion worth of fixed income funding." And I was like, "Whoa. Are you guys really sure that you trust me with this?"

            In about a week, I had the head of fixed income technology sitting on the back of my desk because I incorrectly parsed the head of positions. And the whole fixed income trading desk were trading off the wrong inventory for a day. And I was like, "Okay, so this is real world now. This is real problems."

            And this whole realization of your love for animals and you're a little bit of a butcher. So you got to balance these things out. And sort of the weight of responsibility of how much ownership Goldman impairs to their engineers was just incredibly sobering and fascinating. We had complete freedom to do all the technical decisions back in the day and I think, up till now. Goldman really operates as a collection of startups in the same building. So I had nine traders, five operations people and my boss and that was Goldman. It wasn't 30,000 people. That was the folks I was talking to on a daily basis. And we decided to try Java. We decided to retire the old X Windows from traders' desktops. And actually went to a talk how to email and started to modernize the environment a bit.

            But I think that kind of scary freedom, I think, was just incredibly, incredibly sobering there. And then, little did I know, the reason I stuck there for that many years is just the amount of problems that are never ending. They're just fascinating and usually, just how sharp people are, how sharp financial folks are. I was sitting on the trader desk on the 26th floor in H5 broad, and was sitting between the two REAPA traders who were literally picking up the phone, calling their clients. And they spent the first 10 minutes talking about their family. Then they called the next client, the first 10 minutes talking about their family.

            I was like, "Why are you guys doing this? Why are you wasting time? You got to trade." They go, "This is how you trade." I was like, "Really?" Wow, if shit hits the fan, and they haven't done business every day with these 10 customers, they're not going to do business with me when the market turns down. So a lot of relation management, a lot of understanding what the traders need. Having funding traders stand up in the middle of the trading floor and start yelling REAPA quotes across the floor. I was like, "Why are you doing this?" "Well, I got tell the prices to them." I was like, "Well, here's the screen. You can just type into this and they will pop in on the salesperson's desk." It was like, "Oh, my God."

            So there was no product managers telling you you have to build a product. You actually have to learn everything for yourself. You need to understand. And it was all internal, right? It was all internal tooling. You built something you can see the trader using it immediately. It was just fascinating. Fascinating still.

Delian Asparouhov:

So yeah. You stayed at Goldman for 18 years, which is a phenomenally long run and especially I feel like and today, Silicon Valley area, people do not stay at companies for nearly that long. I guess, yeah, I mean I love that you got to go. You got to be there through the sort of original tech crash. You got to be there through the '08 crash. I imagine getting to sort of be in those rooms and creating technologies, people reacting to those situations. There must have been some really awesome stuff in particular around those two crashes. Anything? Lessons learned or things you'd want to share sort of, from that period of time?

Nik Koblov:

Yeah. So I think that's a great question. What I found is engineers come up with the most ingenious stuff during the crisis. Yeah, living through this crisis was the biggest learning. Building technology that amplifies your core strength as the company during these times and kind of competing with the off-the-shelf solutions.

            So I remember taking the train with [Anawa Kwantz 00:16:57], who came from Bear Stearns. And I was like, "Hey, so you went from Bear. Bear crashed. You went to JP. You came to Goldman. Why? Why all those moves?" He goes, "Well now, Bear and Goldman are the only two banks that take real risk. It's just boring everywhere else." It's like, wow.

            So there's all this pressure in engineering to support that sort of prop technology. Even servicing, like collecting repayments on the loan, you can do it in a way that it's more competitive. But it was pretty fascinating that engineering can unlock kind of so much business potential.

Delian Asparouhov:

And so, after being at Goldman for obviously an extended period of time, what started to get you interested, or how did this sort of switch over to Affirm happen? What got you sort of interested in jumping ship from Goldman and trying out the world of startups sort of yet again?

Nik Koblov:

So the story goes, I found myself in Gary Vaynerchuk's office. So my best friend worked at VaynerMedia. And I started getting interested in fintech at around 2015. So I mean, it was interesting to see all the sort of alternative sources of liquidity coming up and lending marketplaces coming up.

            But from 2009, 2010 to 2015, there's really nothing new that was created. So there was LendingClub. There was Prosper. There was Earnest. There's LendUp. And sort of it was all about lending. I wasn't super excited about that.

            And kind of had this strong feeling that I wanted to talk to somebody. So I turned to my friend, Dennis [Hospov 00:18:38], and he worked for Gary. And I was like, "Do you think Gary can help me debug this a little bit?" And he's such an inspirational speaker.

            And I found myself in Gary's office. And Gary was like, "Yeah, I know. I hear you. It's kind of all the same sort of blueprint of lending marketplaces. But you should talk to Max." And I was like, "Why?" He was like, "Max [Lechtan 00:19:04], he's doing crazy stuff. He's lending his own money. It's a point of sale. It's a pretty crazy product and they're doing it completely differently."

            I got connected with Lieborg, the CTO, who worked with Max at Slide and they found themselves, after Slide acquisition in Google. And Lieborg just started as a CTO. We immediately clicked on the phone. I flew into San Francisco. And I was like, "Oh my God. This is such a breath of fresh air. This is just unbelievable both on the technical side as well as just simplicity. Like a product that has no fees? You have $100 at 15%. You're giving me 115 after a year. That's all there is to it." And you give the product where it needed most.

            So also, kind of a guy from the B2B institutional finance, so consumer. Even though obviously, the regulatory side is much more stringent. There's FTB regulations and all of that. But I think it was just fascinating to try. And as an engineer, I was in my early 40s and never worked in Silicon Valley. I was like, "You know what? If I don't try it now, then when?"

            But also, having a family, having two kids, I was a little bit risk averse. I kind of want a product that already found market fit that kind of made it so that I don't take that much risk. But I think the stage was just right in 2016 where Affirm came out of sort of wandering, looking for the product fit. And there were Affirm of merchants that were already onboarding. But there was a lot of foundations that were not built in financial technology and this is what my strength was. So we started putting in all the right pillars for the company to scale to where it is now.

Delian Asparouhov:

And can you talk a bit about why you found the underlying let's say, business model of Affirm, where you're doing that sort of point of sale lending as a more attractive or innovative model versus the lending marketplaces? What gave you more confidence in that type of model let's say, sort of working better or being more differentiated versus just a pure lending marketplace or let's say, some of the other sort of fintechs that were starting to rise up at that time?

Nik Koblov:

That's a great question. I think what was very hard to see from the outside, so I didn't know it coming in, it was just an excitement of very more different lending product that kind of had a purpose. Very different. So Affirm doesn't give cash, right? So actually, you borrow money but you're never in the possession of cash. And it took me about a year working at Affirm to realize how powerful that is because you actually not interested in...

            So it's apparently a less risky product because of that. People have allegiance to a brand such as Peloton, right? So you're far less likely to default. But also, the most important thing that it does, it creates a network of incentives that otherwise, does not exist, right? So the merchants want to be on the Affirm network because they getting higher [inaudible 00:22:16]. They're checkout volumes are increasing because of that. It's the best use of marketing dollars. It subsidize your APR. So that why run an ad if you can have Peloton pay out for 39 months or 199 a month for free?

            So it was sort of this kind of brilliant combination of incentives that you create in a marketplace, you create in a network where merchants wants to be in because they gain customer. Customer wants to be in because they actually get the best credit product. And investors want to be in because they get in a very well-performing set of receivables and return on their debt.

            So my first project was actually, my first Morgan Stanley debt facility, there was a 100 million to fuel the growth. And that one kind of ran at the breakneck speed with some credits, Moore Capital and all the other partners that our firm now has with over 10 facilities, three securitizations and a variety of finance and debt available. So that by itself is proof that this... It was hard to prove. I remember doing our first securitization. We couldn't explain to the rating agency all our revenue streams. We're making money on this. And we're making money on the merchant. And sometimes, the borrower pays interest, but sometimes it's 0%. And it's like, what kind of product? It doesn't fit into your standard square box.

            But to me, I mean, that's a true innovation when you scare the rating agency a little bit. It's like, yeah, yeah, you definitely did something right.

Delian Asparouhov:

And then, can you talk a bit about just the things that sort of translated well for you from Goldman over to Affirm? It sounds like I'm sure that you were sort of familiar with negotiating $100 million credit facilities, but maybe underwriting loans instantaneously online was probably quite different. And so, yeah, maybe talk through that. And in particular, just how did Affirm think about underwriting this, especially when it's such a sort of unique product?

Nik Koblov:

Yeah. So for first part of the question, things from Goldman that were kind of useful, I think the thing that I was surprised most is that engineering cultural-wise, it wasn't that different. It's probably because kind of Goldman uniqueness within the investment banks, technology, that sort of environment where we were just so empowered to make decisions.

            So when I joined the firm, it was like, "Yeah sure." My team makes all the decisions about how we bill servicing, how we do merchant integrations. So that was very familiar. I was worried about adjusting to the pace, but the pace was the same. It was right. It was fast. There was less support, obviously, less infrastructure. We made a lot of early infrastructure mistakes, underappreciated scale. That probably was the scariest when you realized that you introduce a new state on the payment and you just blew up your date sense model because you didn't invest in building an API in between the data scientist and the financial engineers. It's super, super scary. And the models started marking their own decision. It's like, "Okay, it's going to decline the customers instead of approving it." It was like, "Oh, I just did it with this merge? Oh my God. How do we write a test around it?"

            The underwriting side was... As I was saying, I did run into my good friend, Delian, I think, who ran [inaudible 00:25:59] in Palantir. He is the head of risk, is kind of doing what I'm doing now at Ramp. But the underwriting was fascinating.

            So if you look at your traditional sort of line of credit underwriting, it's actually fairly complicated because of the terms and the open nature of the line. Making underwriting way more transactional for a very well-defined amount or a well-defined term, complete absence of fees, tying this particular swipe sort of Affirm in credit card terms, tied to this particular merchant and the unique incentives that merchant provide in this transaction, all right, actually unlocks a lot of flexibility. And that sort of transactional point-in-time underwriting is still pretty powerful where we always consider sort of the merchant risk and the individual credit risk together. And that combination is pretty unique for each purchase.

Delian Asparouhov:

Nik, can you walk through? I feel like one of the things that most people don't appreciate is the underwriting of merchant risk. How did you guys sort of think about doing that? And then, also, how did that plug into also the work that you were doing in terms of were there certain let's say, merchants that were easier to secure ties, versus not? And how did that relate to the actual sort of larger sort of lines of credit that you would then have to go integrate with? I know it's obviously discussing S1 and it's relatively well known, but obviously, Peloton was an extremely sort of large merchant for you all. And so, I imagine in some ways, much easier to underwrite, versus a sort of SMB longer tail merchant probably sort of more difficult and maybe couldn't be securitized the same way. How did that tension play out?

Nik Koblov:

So I think ultimately, the solution came through sort of diversifying the lending partners where some of the early-day partners came back later once we were going to gain volume on scale and started offering... They basically trusted us so much that they offered us a facility that they could present. So at the end of the day, if a particular forward flow buyer who also were selling receivables outright will have a further constrained concentration let's say, on I don't know, fashion retailers, right? Then we'll always have an outlet where we could place that and sell it off the balance sheet or at least finance it through our facility.

            Ultimately, great merchants bring great risk. And merchants that do after-market auto parts come with their own risk profile. And at the end of the day, I think initially, the focus on the merchant risk was mostly from sort of recognizing the profile of the customer that they bring. But ultimately, we sold it through having unique financing programs for each merchant.

            So merchant be looking at the type of customer that they attract at the AOV and how big the purchases are and the overall risk profile. And then, our risk team looking at the overall risk profile of the business, will offer a certain set of financing terms. So with Peloton, you can go as long as 39 months. But initially, we had no facility that we could pledge Peloton to because it was so unusual and Affirm never did more than 24 months terms. But ultimately, through showing the performance of the return customers and through creating the history of vintages, you do prove to the lender that there's yield in this combination of a customer financing program and a merchant.

            And that actually, was probably one of the deepest investment into technology to build out. We sort of collaborated between our merchant engineering team and the risk engineering team and the bank engineering team that I used to run. So almost the entire organization came together so that we can actually have the right pricing model on the value that Affirm offers to the merchant. Traditionally, the focus was okay, so what APR? Is this all consumer raised? But probably, kind of around 2017, 2018, the organization came that there's a unique value proposition to price.

            And the effect of price on the network effect, right, that I was talking about before of the merchant, the investor and the consumer. And there's a lot of interesting conversation about who should own this piece of code? It's like it came from risk. No, the merchants should.

            Well, we modified it on the merchant side. It was like, no, no, it's super important for the bank engineering team, because we service all that stuff. So in reality, it was such a central piece of code that it kind of where all the secret sauce came together and ultimately, realizing and understanding. And that was unique to Affirm, right? It's probably one the firm and early days Clarion and Afterpay of sort of, you have the B2B value proposition and you have a consumer value proposition and there's completely two separate pricing axes. So that was challenging. That was fascinating.

Delian Asparouhov:

So after three and a half years, or a little bit over that, at Affirm, you then decided to sort of move back to New York and join this very exciting company that I really like obviously, but I'm a shareholder and extremely biased and convinced my little brother to work there too. But yeah, it would be great to hear sort of how you ended up at Ramp. What sort of got you excited about the company? And then, in particular, I'd love to hear you talk about sort of, what about the underlying let's say, business model or financial model, similar to how you saw something spark your eye at Affirm, what sparked your eye at Ramp?

            Given that I think for a lot of let's say, unsophisticated outsiders, it's not always super obvious what's so special about Ramp. I obviously, know why it's special. But I'd love to hear you articulate sort of why you think it's special.

Nik Koblov:

Well, excellent question. Initially, as a conclusion I get almost after exploratory recruiting call, it's like, "Oh my God. I didn't realize, that's what you guys actually after." So I'm kind of happy that's a little bit of a hidden secret until you actually talk to one of the Ramplings.

            But starting with the first part of your question, so I think the main factor for coming back to New York was a little bit of a home pride. So we always wanted to come back after a few years in the Bay Area. I love the Bay Area. I love the nature. Hop in the car and be in Truckee in two hours if you drive 90 miles an hour at 5:00 in the morning. That was fascinating. And being a very outdoorsy family, we were just in love with the West Coast and the mountains.

            But it was time to go home. And the opportunity came up to build out a New York office for Affirm. We were very busy growing the office in nine months from five to 50 people. Now it's over 100. And I was kind of tired after that. So I was a little tired. I decided to take a break. And Karim called me up and was like, "Nik, you got to meet this founder." I was like, "For the first time in 25 years, taking a three-month break. Let's talk in January." He was like, "No, no, no, no. It's time bound. It'll go away. You have to meet it."

            I went for lunch with Karim. Karim pulls out a Ramp card. I was like, "You're kidding me. You just started a couple months ago." He was like, "Yeah, this product is working. Let's go back to the office. I'll show you the demo."

            I was blown away of how much was built and how thoughtfully the card product and we obviously did virtual cards at Affirm. So we used exactly the same technology as at Ramp, the same processor. And I was very familiar. I knew what it takes to build something like that. And it was live. It was working.

            And the two things that stood out to me instantly on the people side, what Karim said just kind of blew my mind in terms of I was like, "What are you after?" He goes, "I want to build a talent brand that years down the road when these people started their own company, is they look back where they all came from." That was Ramp 2019, Ramp 2020. This is that core. This is the absolutely unique set of talent that engineers seek out.

            So when you say, "I want be in payments in San Francisco," Strike comes in, comes up instantly. If you say, "I want to be in fintech in Europe," it's like, okay, there's this. There's that. There's this San Francisco company. Move their office here. Maybe there's early day Venmo and then they got bought by PayPal and the engineering culture sort of dissolved a bit.

            But even in the way Karim approaches hiring interns, I've noted in the company they hire so many freshman interns, right, so rising sophomores. It was like, "Why are we doing it? It's a lot of work." Right? People barely have any experience. It's like, "What are we doing? It's going to slow our team down."

            And Karim's answer to this, "This top 1% that we hire are going to go back to their class. Their classmates are going to see these people spent their summer at Ramp and they all would want to come here and they will know that this is the first person in the class who just had their internship. And very few of us had exciting first time internships." So this sort of word-of-mouth culture carrier brands, so the people who work here, you don't need to sell the company anymore. It's just sufficient to meet the team.

            And then, on the product side, what was super exciting is the fact that you don't see fintech companies... So fintech company model is usually, it's their own model and making money, right? There's a particular revenue model. There's the services that they offer. Very few companies exist where you... Affirm is also one of them, where you actually blend the value proposition directly to your consumer to a degree that you're not gamifying with points. We actually want you to spend less.

            And it's like, "Eric, how are you going to build a company where you're trying to have businesses spend less money?" He goes, "Oh, we just started this. We're not really after a corporate card." And that's the secret sauce that we tell here in interviews is that on network spend, it's a convenient way to get to the company's cash flow. So you start to understand their spend. We connect to the bank accounts. We understand the cash situation of the company and we can underwrite them better. We don't require any personal guarantees.

            We had this story where one of Ramp investors and customers wanted to put an AWS bill on a card, right? So we put 300K on the card. Amazon calls the business in about two days and was like, "Can you move back to bank payments please? Here's $10,000." And so, the customer calls us, apologizes, "So sorry. We tried." The Wall Street business trader's like, "No, no, no. Here it is. We just saved you $10,000. You got a check from us, right?" So this is value proposition that we just brought. And we're going to get that off-network business.

            So expanding holistically looking, actually not seeing the companies either in sort of A/P stage of network spend, or on-the-card spend, solving those kind of siloed problems, which I understand why they're doing it. They're very, very complicated problems. I have friends and former Affirmers who operate in a similar space. And they're focusing laser sharp on solving a particular niche.

            What's very ambitious about Ramp is it's a holistic approach to understanding the cash flow, the payments, the expenses, the customer payments, the vendor payments, everything that the customer does. As Eric says, we want to be an extension of your finance team. If you sign up to Ramp, you can hire less MBA folks because we do that for you. We're accounting experts and payment experts. We're expense management and invoicing experts. So that is pretty unique and ambitious and hard. But hard problems have been the fun ones.

Delian Asparouhov:

Can you tell me a bit about how you think you guys cultivate sort of both mentorship and sort of ambitiousness within the junior team? I mean, I love my brother, but in some ways, it's wild to me that he's dropped out of school after sophomore year at Berkeley. And yet, the features that he's working on at Ramp, that he's almost owning entirely end to end, are things that other companies would be owned by two PMs and 15 engineers.

            And so, I can't quite tell. I mean, maybe my brother's just a really good engineer. But I'm just like, "It's got to be something about Ramp that's somehow enabling him to be let's say, such a good engineer or to have taught him to be such a great one." And so, I guess, yeah, what do you think enables just the speed and pace that you guys sort of ship products and ship value to your end customers? What about the company really enables that?

Nik Koblov:

Yeah. I think the secret sauce is in ownership and trust. I don't believe in separating, of having product insulate kind of the end consumer and the engineers. That kind of goes back to my early days Goldmans where I was sitting on the trading desk without any PMs telling me what to do. And our head of credit, Srinath Srinivasan, also comes to us from Marcus Goldman, was the head of risk at the Apple Card. We clicked on the interview instantly. I was like, "How do you do [inaudible 00:40:33] on projects?" Because I interviewed everybody in the room. It was like we don't have PM write the spec and then hand it over to engineers. It's like, no, then the engineer doesn't understand what they do.

            So one example with Pablo specifically, is we wanted to automate. We just launched as you guys all heard, the $150 million Goldman facility. And we are automating the draw down, the weekly draw down and receivable sale process completely. Pablo was doing it almost entirely by himself. I sat down with our head of capital markets and we literally we wrote maths for Pablo and we said, "Here's how you balance to borrowing base. Here's what your liabilities are. Here's what the assets are. At the end of the day, this needs to be in balance. You're a smart person. You know the math. Go figure it out."

            I was kind of one-on-one with him a couple of days ago. He was extremely proud. He was like, "Nik, I wrote some incredible comments about what all these functions are doing." But it's sort of this trust that... I mean, the kind of inherent brilliance in engineers is something that we try to suss out in the interviews. But with Pablo obviously having kind of gone through the internship with seeing how incredibly bright he is and how hard he works.

            And then, I'm like, "All right. So why don't you solve this problem entirely on your own? I'm not going to write a spec for you." I wrote something super high level. He went in and just broke it down to the level that, "Okay, you don't need a PM. You don't need Alex and me. you own the space to the degree that when announce at All Hands that we want to hire a capital markets lead," he got very defensive. And he's like, "Nik, I thought I am the capital markets lead."

            I was like, "Yeah, yeah, yeah. But if you want to do it, do it. Sure. It's yours. But we have this new product developed, so let's hire somebody to own federal markets longer term and you can go hop around and learn as much stuff as possible."

            I think it's the exposure and the support network that we create, especially in the remote environment. We just had almost every engineer go through kind of peer programming set of sessions where they observe and experience engineer code and then send the code base. You move a little slower with the code reviews because you can't help in person, so you communicate through the written comments.

            But the extent to which you can do this effectively and you know... I almost call it communicate for code, teaching for code, mentorship for code. It eventually worked. It worked really well. It lend itself very well to the remote environment. And the fact that you can be focused, really be careful with your time here in the day. So the managers that we have, engineering managers, are super sensitive to how much time people are spending in meetings, whether this meeting is needed or not. And as a result, yeah, you get stuff like expense management and three sprints. It's pretty mind blowing this November. We replaced expensive [inaudible 00:44:00] concurrent in only six weeks with three engineers working on it. It's pretty fascinating. I still can't believe it.

Delian Asparouhov:

Yeah, it's almost wild to comprehend of yeah, especially somebody who's an end user, you go and you're like, "This is actually quite sophisticated software." And you look at the public comps. It's like, yeah, you guys have built the equivalent software. Sure, not every single little edge case. Not everything is perfectly handled. But still, a very, very solid MVP that is the equivalent of what a many-hundred person engineering team has spent a lot of venture capital dollars to build out.

            And yeah, I think part of it... I mean, yeah, I can't imagine there's that many startups in the world that are comfortable with a 20-year-old Berkeley dropout moving millions of Goldman's dollars around with code that's entire written by them. Yeah, you guys are probably the only one that are doing that right now. There's probably not anybody else.

Nik Koblov:

Yeah. It's wild. It's wild.

Delian Asparouhov:

Well, Nik, I really appreciate you taking the time today and telling me about all the various experiences you've had and the great stories. Really, really appreciated it.

Nik Koblov:

It's been super fun, super fun, Delian, as always. Thanks for having me, and until next time.

Delian Asparouhov:

Thanks for listening, everyone. If you'd like to support the podcast, please sign up for a paid Substack subscription which we use to pay for transcripts, mics and other improvements. If you have any comments or feedback on what kinds of questions I should ask, who should come on the show, or anything else, please do let me know. Have a great rest of your day.

Operators Ep 22: Dan Wright (DataRobot)

  
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At the time we recorded this episode Dan Wright was the President and COO at DataRobot, and was just last week named CEO of the company. Prior to joining DataRobot Dan was the COO (and before that the General Counsel) at AppDynamics.  He also spent two and a half years at Goodwin Law Firm as a technology and venture capitalist lawyer. 

In this episode I talk to Dan about how lawyers can get involved in the startup world, some of the mentors he leaned on when deciding next steps in his career, and the value of listening when you’re new to a company. He also shares about the importance of building great teams, the partnership dynamics between CEO and COO, and why he believes DataRobot and AI is changing the world.

I hope you enjoy the show.

Full transcript available.

Operators Ep 22 Transcript

Delian Asparouhov:

Hi, everyone. My name is Delian. I'm a principal at Founders Fund, a venture capital firm based in San Francisco. This is Operators, where I interview non-VC, non-CEO, non-founder operators that make the startup world go round. Today, I'm interviewing Dan Wright, President and COO of at DataRobot. Prior to joining DataRobot, Dan was a COO and before that, General Counsel at AppDynamics. He also spent two and a half years at Goodwin Law Firm as a technology and VC lawyer. I hope you enjoy the show. Cool. Well, Dan, thanks so much for taking the time on the podcast. Excited to chat today.

Dan Wright:

Yeah, thanks for having me.

Delian Asparouhov:

So, before we dive into all the interesting stuff that you're doing at DataRobot, with these types of conversations, I like to actually dive all the way back. You're one of the few, let's say, lawyers in the world of Silicon Valley that's managed to transition from being a lawyer to getting really involved on the business side of things. So, yeah, I guess we'd love to hear why you decided to study law and how you decided to make the transition over from being a VC-focused lawyer to actually transitioning in-house and eventually, obviously, making a pass just to the legal side of in-house staff, but obviously, a much broader set of responsibilities now.

Dan Wright:

Yeah, sounds great. Well, yeah. So, to bring it all the way back, I started to think about going into law around my senior year of college. The thing that was interesting to me about it is it's what underlies every part of our society. I also thought, I just learned some interesting skills that translate into a bunch of different things. So, I decided to go do that. Pretty quickly, though, during my first year of law school, I realized I didn't want to be a courtroom lawyer. I didn't want to be hashing out in litigation and that thing.

            The way I realized that is I actually was clerking for one of the most senior judges in the State of Massachusetts. I went to law school at BC. I clerked for this great Mass supreme court justice. Only the most interesting cases get there. So, this is as interesting a career as you could possibly get in that side of the house. I just didn't think it was for me. So, I decided to start thinking about, "All right, well, what can I do that might be within the law but still working with companies to help them navigate things?" That's how I got into VC and startup law.

Delian Asparouhov:

Yeah, interesting cases, I know. Obviously, clerking, at least for the Mass Supreme Court, I'm sure there's at least something that came across that summer, maybe if it wasn't the thing you decided to do long term. Any favorite court cases for that summer?

Dan Wright:

There were some wacky cases. Yeah, I'm trying to remember. It was a while ago. So, I mean, there were always interesting cases with people somehow getting hurt in the most bizarre ways. A lot of times, it wasn't obvious whose fault it was, but you'd have to figure out, "All right, who is legally to blame for this?" So, that was very interesting. The ones that make it up to that level of the court, there oftentimes is not a clear answer. So, you had to figure out, "All right. What is all of the precedent? What's every case that's ever been seen on this one very unique, totally bizarre fact pattern?" And then sometimes extend that out and say, "All right. Well, based on the policy underlying the law, what makes most sense in terms of the outcome?"

Delian Asparouhov:

Yeah, I guess, how did you end up deciding to go over to Goodwin Procter? You stayed there for a little under three years. How'd you come across them? How'd you decide to stay there for that period of time?

Dan Wright:

So, I was pretty sure I wanted to go into the law working with startups and VC firms. I actually got an offer originally from Gunderson Dettmer, which is another Silicon Valley firm. The partner who I was close with ended up leaving and going to Goodwin and starting their West Coast tech practice. So, I decided to follow him. The reason I did that is I figured, it's a mini startup within a law firm. Also, as a result of that, that I'd be able to take on a lot more responsibility early on.

            So, from day one, I had hundreds of these companies that I was just managing all the way from just somebody with a deck and idea to large public companies. So, that was great experience, worked like crazy, drink from the fire hose, but learned a lot in a short amount of time and also saw a lot of great companies. It's funny, a lot of the companies that I worked with, the founders that I worked with, I'm still in touch with now. A lot of them have taken those companies public or been acquired. So, it's really cool to see the whole lifecycle over a period of time.

Delian Asparouhov:

And then yeah, I guess, what was the decision making process around it? It sounds like you got to be in a more startup legal environment. You'd obviously made your way over to Silicon Valley. Yeah, I guess how did you go from Gunderson to then joining AppDynamics in a more legal focus role, but obviously, different than what you've been doing up until then given that you are now in-house? What was that process like? Why did you end up making that decision?

Dan Wright:

Yeah, so I was working with lots of different companies, including VCs. I did a bunch of work with Sequoia and some of the other VCs. I had a really good vantage point to say, "All right, I think that this is doing very well. It's in an area where I'm seeing a lot of companies come up. I'm able to see what's happening with their valuation and their growth and what investors are involved. I'm able to get to know the founder." So, this is one that had all of the right signs. It had Greylock and Lightspeed involved from the very beginning. And then I got to know Jyoti, the founder. It was in the space of application performance management.

            I could just see how software was exploding and that companies were going to need the ability to monitor and manage all of their apps as that continued to grow. I really thought Jyoti was a special founder. So, he asked me to join and I decided to make the jump. I think that that is one thing, I would say, for anybody who's considering that, lawyers are naturally a little bit risk averse. So, I don't think jumping at the first startup you see is the right approach, but actually, looking at the market and saying, "Hey, was there a real special opportunity with the company and the right market, the right investor base, and a really special founder that you could go work with?" So, that was how I thought about it.

Delian Asparouhov:

Yeah, how did you think about your background in law? When and how it applied to some companies versus others? Were you particularly focused on, "I want to join something in this more enterprise space," or were you considering a wide variety of opportunities? Was it based at all on what you'd studied in law before?

Dan Wright:

Yeah, I mean, I'd studied a lot of law that was applicable more, I thought, to B2B. So, I was looking for something there. I also was looking not just at the type of company, but the stage of company. When I realized that I didn't want to be a partner at a law firm, which was pretty early on, I have lots of friends who do that. That's great, but I just knew it wasn't for me. I was thinking that I wanted to transition into an operating role at some point down the line. So, in my mind, if I could go to a company that I felt pretty confident was going to be successful but if I could get in earlier, I knew that there'd be more opportunity for me to broaden my role over time. So, that was part of how I thought about it as well.

Delian Asparouhov:

So, I guess, speaking of broadening your role, you started off in a very, obviously, legal focused area in AppDynamics and steadily expanded and grew beyond that. I guess, first, what were some of the legal challenges that you were helping with? Is it a lot of contract review and things like that, or what were the primary responsibilities when you first joined? And then how did you even get people comfortable? I feel like a lot of lawyers as they join an operating company for the first time, it's harder to convince the organization to trust you to operate in, let's say, non-legal areas? So, I guess, yeah, how did you build up and navigate that trust? What were the areas that you first expanded to and started to broaden that scope?

Dan Wright:

Yeah, I mean, the funny thing about these large law firms is that everybody specializes, and then there's a group of generalists. So, I was in the generalist group when I was at the law firm. And then you had a specialist to do software licensed contract reviews, right? You had a specialist to do your tax analysis. So, the interesting thing about that is when I joined, I owned all things legal. I had to pick up things like, "How do I negotiate a license agreement?" I remember in my first month, I'm just getting a stack of those and calling lots of friends saying, "How exactly do I do this?" I just had to learn it on the fly.

            That was a great experience, but then pretty quickly after that, I said, "Well, where are there other opportunities where there's just something that's important to the company that nobody owns and nobody knows how to do it?" Because there's a lot of things that in a startup people don't know how to do, but somebody needs to do it. I would always be the first one to raise my hand and just say, "Hey, I'll do that." So, it started with things like M&A, running mergers in random countries. We acquired companies in Germany and Switzerland.

            So, just raise my hand and say, "I don't know, but I'll figure it out. I'll own the outcome." And then from that, it just expanded to other things and just naturally broadened. I think that's the great thing about a startup company, is that everybody's learning. Most people are stretching themselves all the time. That's a necessity because the company is growing so fast that they have to do that. So, as long as you are willing to take a risk and then be accountable to drive a great outcome, then you'll continue to take on more.

Delian Asparouhov:

I guess, was there already previously general counsel that you end up stepping into, or was there just an unfilled GC seat and you got promoted into that? How did you eventually step into that role? And then obviously, even more importantly than that, eventually, stepping into COO role like this, I think that it's actually relatively rare to see a GC go from GC to COO. I'd say, yeah, you took on just so much that the organization was just naturally, defaulting to coming to you for a variety of things. I mean, it sounds like you started off with M&A, but I imagine, COO's responsibilities are far more broad than that. So, to understand what were the steps between taking on that first, "Hey, who's willing to take this on?", through GC to then COO.

Dan Wright:

Yeah, I mean, so I joined as the first lawyer right around 150 employees. So, that's usually when you'll hire your first lawyer as a startup company. As a result of that, one, I just had to own everything legal. So, that was a pretty easy transition to eventually just be GC. But two, there just wasn't that many people in the company and the company was growing really fast. So, I was able to take on more as a result of that. I think, a lot of the skills that I learned as a lawyer really helped. I was also able to look at other lawyers who've made that transition. It's definitely rare, but it's not unprecedented. There's people like Belinda Johnson at Airbnb. There's other folks that had made that transition.

            I think things like the ability to take in massive amounts of data, organize it, and then create plans to go drive things, also to figure out what's important and what's not important, because there's so much coming at you in a startup that you have to understand, "How do I take all these things and prioritize what's actually most important and then align people around that and have everybody focus on that until we drive to a good outcome?" Then there's basic stuff like the ability to communicate well. Those things translate no matter what you do.

Delian Asparouhov:

Yeah, it makes sense. I think, that transition for you happened, I guess, either somewhat right after the timing with the Cisco acquisition. I guess, yeah, what was it like navigating, obviously, that type of... You've done some M&A work. But when the M&A is your own company, I imagine it's a different beast. Any big lessons learned from that transaction that you've carried with you since then regarding the Cisco acquisition of AppDynamics.

Dan Wright:

Yeah, the acquisition itself was pretty crazy, because we were two days from our IPO at the time. So, we had the company ready to go public. We were 100X oversubscribed on the roadshow. We actually had sent people out to New York. So, I remember talking to our CMO at the time on the phone. He was surrounded by a bunch of members of our team and a bunch of bottles of champagne for when we were going to ring the bell. I had to break the news to him that "Hey, we have to pivot and get acquired." So literally, we went from a handshake to a signed merger agreement in two days for $3.7-billion merger. So, it was wild.

            I think that the thing that I learned through that is with a startup, you always need to be flexible, right? You never know exactly what's going to happen. The nice thing about it is we were able to, once we got that offer and the board felt like we needed to take it, move very quickly, get it done, and then continue to be successful inside of Cisco. I think the acquisition was a big win for everybody involved.

Delian Asparouhov:

I was going to say, maybe you can't share too many specific details, but how did you weigh or consider that option versus obviously, being lined up and ready to go public? Obviously, the public markets in 2017, especially with enterprise, are a little different than the public markets of 2020 and 2021 in terms of enterprise. Curious how the team thought about weighing those two options, especially it's such a short period of time? I imagine there is a lot of talking and very little sleeping during those 48 hours.

Dan Wright:

Yeah, I mean, at the time, the offer, I think was the highest multiple anybody paid for a software company ever. So, it was a good offer. We looked at it in terms of, "All right. Based on possible scenarios, what's going to happen with the market as well as our own performance, how long would it take us to get to this price?" There's also dilution from the IPO, where all of your shareholders are going to own less of the company after the transaction. So, we actually modeled all that out.

            We had very complex spreadsheets, and then we had a conversation with the board. The consensus was when you factored in both the risk with the market and some risk with our own execution, APM was a crowded space with lots of other companies there, that it really was a good offer and one that is in the best interest of everybody involved. So, we decided to take it.

Delian Asparouhov:

And then you operate as COO within Cisco. What was that like? It seems like they did actually keep the brand and it is still pretty independent. What was easier by being part of a larger organization like, Cisco, versus what were some things you had to navigate as being C-level officer of an entity within a much larger entity?

Dan Wright:

Yeah, I mean, we were able to stay pretty independent for the first couple years. So, it was a great situation, because we had a parent company that had plenty of cash that view this as strategic, that had also some great C-level relationships with the top companies in the world, and that was very interested in helping us accelerate our go-to market.

            So, for the first couple of years, it really worked really well. Especially a company the size of Cisco being in a transition and they were really moving to become more of a software company that was something that Chuck Robbins was driving as CEO, so, there was some complexity associated with making that transition, but overall, things went really well. We were able to, I think, benefit, but also, keep some of the things that made AppD a special place while I was there, so.

Delian Asparouhov:

And then after a couple years of operating post-acquisition, you ended up deciding to come over to DataRobot, which I'd love to dive into. How did that opportunity come across your plate? How did you think through? Given the phenomenal run that you had at AppDynamics, I'm sure there was a lot of opportunities that were coming across your plate. What did you find particularly attractive about the role, the company? Obviously, you're probably relatively intimately familiar with the problems that they were solving. So, why did you find their approach unique or the most appealing to you?

Dan Wright:

Yeah, I mean, for me, I decided to really take a hard look at the market when I left AppDynamics. So, I talked to all of the VCs. I looked at hundreds of different companies, talked to tons of different founders, and really did my homework. So, I had a good sense of the market. I also had some good offers in hand by the time I spoke to DataRobot. The reason that I was so interested in DataRobot was a few things. One is the size of the market opportunity. So, PwC forecasts $15.7 trillion impact to GDP globally from AI between now and 2030. So, huge, huge market opportunity.

            Also, one thing that I really liked about it is that it's a platform versus a product, right? That today includes four different products within our platform, but now, what we're doing is we're able to actually build these AI-powered apps for every industry on top of our platform. We're creating ecosystem around that. I just thought the market opportunity combined with the platform to address that market opportunity created a lot of potential. And then the other thing I looked at was, "Where did I think that I and the team would be able to have a really large impact on what the company could ultimately become?"

            I wanted to do something that I thought could make a really large and positive impact on the world and on the employees that work at the company, as well as our customers. For me, DataRobot stuck out, because it had some of the top data science talent in the world. We had a visionary founder, Jeremy, who's my partner working at DataRobot. We also have just a lot of people who are very ambitious and focused on their own personal growth. So, we talked about 10X-ing our employees lives while they're at the company.

            I thought if you could complement that with some skill sets from people with different backgrounds, but who are very aligned on what we were trying to accomplish as a company and that idea of personal development and developing other people at the company, that you could create something really special. So, it's a combination of those three factors, the market opportunity, the platform, and then the team that really made me want to jump in and be part of it.

Delian Asparouhov:

It was obviously a very different stage, let's say, that when you were joining AppDynamics, not hugely later, but definitely later stage than obviously, when you're joining AppDynamics. What shifted about your mindset in terms of when you were considering your first role, in-house, joining something relatively earlier stage versus DataRobot slightly later stage, or were you pretty focused on this very particular stage? Were you actually looking alongside DataRobot across a variety different stages of companies to join?

Dan Wright:

Yeah, I think it's interesting, because I compare notes with lots of my friends who have either gone through this process before. They were looking for something at the time. A lot of people look at it in the absolute sense. They say, "Hey, the stage is just the stage, regardless of the company." I never looked at it that way. I always looked at it in more of a relative sense, in the sense of, "What is this company in comparison to what it can become, right?" So, even though DataRobot may look externally, a later stage company, we're still early days in terms of what the company can become. That really stuck out to me.

            I'll never forget Jeremy, again, our founder... When I was deciding between the different offers I had on the table, I was really deliberating about the decision, because I thought it was an important decision. He sent me an email. It said something along the lines of, "You can join lots of different companies over the course of your career, but it's not very often you get the chance to actually do something that could change the world." AI, I think, is one of those technologies that really can change the world in a pretty unique way.

Delian Asparouhov:

Yeah, I feel like one of the things that is actually under discussed in Silicon Valley is this type of job search process. Especially once you had a really solid run, the way that that process should ideally go, how long you can take to do it, who you should be talking to is actually quite different than your very first job search, I imagine as you're leaving Gunderson. So, yeah. I guess, can you talk a little bit about how you thought about even just structuring your sort of "search process"?

            Who are the most helpful people that you talked to? How did you think through the opportunities? Did anybody provide the best advice like frameworks? Do you have peers you really found that you leaned on? And then if you were, let's say, recommending somebody else that had gone through a similar, let's say, amazing ride at a company similar to AppDynamics, how they should be maybe structuring how they think about what comes next.

Dan Wright:

Yeah, I mean, the one thing that I tried to do is just be flexible on my thinking. I really tried to think about, "What are all the possible things I could go do now with my life?" That ranged from, "Hey, maybe I want to go into investing. Maybe I want to go into operating at a very small company. Maybe I want to start a company, right? Maybe I want to join something that's later stage and the whole gamut." And then what I did is I talked to people who had done all those things, especially people who had done something successfully before.

            So, one of the people I talked to was Trae Stephens at Founders Fund. He's a friend. He had had a successful career at Palantir. He decided to join Founders Fund. So, he went on the investing side. Now, he's doing that. He's helping to run Anduril as well. Just people like that, who have some valuable, relevant experience who you trust and won't just sugarcoat things but tell you the good and the bad. That's important, because the grass always looks greener. You need to actually understand what's it like working in these different roles and get the pros and cons and then stack them against each other and decide what you want to do.

Delian Asparouhov:

Yeah, can you give a sense of just what your timeframe was when you first started picking your head up to when you finally made the call? I imagine it wasn't two weeks. I imagine it wasn't a year. Yeah, where did you lay in between that in terms of how long it took you to go from picking your head up to actually deciding the right opportunity?

Dan Wright:

It took me about three months, but I will tell you, those three months, I worked very hard. I had so much analysis, and I did so many meetings. I really was taking it pretty seriously. I think if you wanted to actually relax a little bit between jobs, taking a year would make sense to make sure that you could actually do it fully and feel confident about your decision and maybe get a little downtime, but I was just very focused on it. So, I went full steam ahead for a few months. At the end, the nice thing was I really felt good about my decision, because I knew again, what was in the market. I knew all the pros and cons to all the different options. I knew that I made the best decision I could based on the information I had. So, I was going to live with it.

Delian Asparouhov:

And then yeah, now speaking about your time at DataRobot, can you talk a little bit about how did you hit the ground running? What were the primary, let's say, scope, responsibilities, and maybe also just recommendations for other executives now that you're a year, year and a half in for how to hit the ground running at a company at that scale and what the ideal way of spending the first three to six months to ensure success for years, one, two, three years down the line?

Dan Wright:

Yeah, I talked to some friends who had done this before about this as well, joining a company at a point where it had a large history, a lot of have been tried and failed over the years. Also, there's been lots of victories. And then there's just a lot of people at the company. The number one point of advice that I internalized from that was make sure you listen first. Actually, if you read books about how to be successful in a new job, they'll also tell you the same thing. Listen first and do no harm. And then once you have the context, try to do something. So, that was actually the first thing I was going to do. I actually announced it at our first company meeting the day I arrived.

            I said, I was going to go on a listening tour. I was going to visit all of our offices. Then I was going to come up with a plan that we were going to go execute on. I was responsible for the company's go-to market and operations. So, I wanted to know about the whole company, especially focused on those areas. The thing that happened though was COVID hit. Those in-person office visits, the getting to know people, that had to change shape a little bit. So, it was all virtual. That was a challenge.

            I'm very much a people person. I like to actually meet people, understand people, have longer conversations in person. That just wasn't possible for a long time. So, we had to do it virtually, but I think still the same idea applies, which is doing as many group meetings, individual meetings. Trying to really make sure you have all the context before you just run through walls is important. And then you can move forward in a much more aligned way that's only going to help the company versus maybe doing some harm.

Delian Asparouhov:

Speaking of the go-to market, maybe a two-part question was just one, how did you familiarize yourself with the EDA product? It's a relatively technically complex product and also, wide variety of use cases. So, how did you familiarize yourself with the value proposition to the customer? And then maybe, part two to the question of just how are you thinking about the structuring of your go-to market team? Where are the segments you feel like you guys are doing really well and crushing? Where are the areas that you want to expand into? Yeah, how do you think about the value propositions for the customers across those segments?

Dan Wright:

Yeah. So, I feel fortunate that I joined the company that I joined, because one of the things that we're very focused on is democratizing AI. The whole idea behind the company is that you don't need to be a PhD data scientist to get value from AI. You can be an engineer. You can be a business analyst. Anybody who's used a Tableau Dashboard can use DataRobot. Also, you can be an executive. So, we were able to really appeal to all those personas. Actually, any of those people can use the software. So, that was the number one thing that I focused on was actually understanding how that works, how that's done. And then just seeing it, working with customers as well, you pick it up pretty fast.

            So, I'd say, the number one thing that I tried to do is actually talk to people who've been in the trenches. All of our sales leaders were demoing the software. So, I was like, "Wow, that's pretty unique. You don't see salespeople demoing software very often. Show me how this works." They showed me and then also just talking to customers and seeing how people again who were not data scientists were able to get a lot of value from it. And then from our go-to market angle, what we started out doing was really focusing on just building the machine for the go-to market, things like being really rigorous and accountable around pipeline generation, excellence at every stage in the funnel, really measuring everything and holding people accountable. That has gone really well.

            I think the other thing that I always try to do on the go-to market is just be very proactive. So, a lot of people don't look at leading indicators. They wait until something's wrong, and then they go fix it. We always try to be ahead of where the business is and get in front of problems before they get to become bigger problems. And then what we're focused on now is trying to really match very crisply the value propositions for every different type of person we sell to. So, all the different personas. Whether it is a head of data science, whether it is somebody who might be in risk management, somebody who is maybe your CIO or runs a line of business, or even your COO or your CEO, we talk to all of them.

            So, everything from the slides that you use in your pitch deck to your demos to the next step coming out of that initial meeting, it all needs to be different depending on the situation. Not just doing that, but doing it at scale now is the other thing, because it's one thing for you to be able to do it. It's a whole another thing for a brand new rep who's new to the market, who doesn't have a ton of experience to be able to do it. The other thing that we're focused on is product-led growth. So, we actually recently launched a self-service version of the product for each of those different personas that I mentioned. We're pretty excited about that as a way that customers can get started with us and just get some value and then opt into an enterprise conversation later on.

            The other thing that we're very excited about is this idea of AI-powered apps. So, we recently have been building apps on top of our platform. We launched this last year. That has been really interesting to our customers, because again, it's something that you don't have to be a data scientist. For example, we were very involved working with the Department of Health and Human Services to help with the COVID pandemic response. Those are policymakers that are using the software to make decisions. They're not data scientists. The same thing is true in business where now you can be somebody who has very little knowledge of data science and you can actually understand how this enables you to make better decisions and just do your job better.

Delian Asparouhov:

I think one of the things that is off discussed is, let's say, a tricky area to navigate with a company like DataRobot, where one, let's say, upfront revenue is much less interesting than deeply integrating with your end customer and started to build up more and more use cases and get "more and more wallet share" within the organization. But then, you also balancing that with... I don't know exactly how you guys categorize it, but I imagine heavier services revenue upfront and lots of training, onboarding, getting the customer familiar with it. And then steadily over time, that ideally looks more like product revenue.

            But I guess, yeah, how do you think about your aligning organization where it's not just that upfront sale, but developing that deep relationship with the customer and getting close to them, but then also, in some ways, making sure that you're optimizing the use of your team and economics over time? So, that more and more of that is done via software as opposed to, I assume, customer success type folks.

Dan Wright:

Yeah, the nice thing about our company is that we really did focus on automation and trying to make the process of getting up and running as easy as possible from day one. So, it's not as heavy lift as you might think. So, that helps us. I think the other thing is we were very focused from the beginning on democratizing AI and doing it through two things. One is automation, but the second is we call it relentlessly practical data science education. In other words, how do you use modern tools like DataRobot to solve business problems using AI? There's no sense in AI for AI's sake. I always like to talk about experimental AI, this idea that data scientists should just work on some stuff and it never sees the light of day. That's okay. I think those days are gone.

            Now, AI is really a tool to help you solve a business problem that you couldn't solve before. It just wasn't possible, right? So, with that, we actually developed education. We have the ability to do mass education for large companies, as well as small companies when they say, "I want you to educate all of my people, whether it's an executive, whether it is a business analyst, data scientists, and upskill my people. Teach them how to use this and then really change my culture." That's one thing that we focus on is really telling our customers that this is a cultural change for the whole organization.

            You need to go from just being reactive and, "Hey, the news is this. All right. Now, I need to do this," to actually getting in front of the news and shaping the news by doing all of the different scenario analysis on, "What is going to happen if I make this decision?" And then using your data to make a better decision, which then shapes the news. So, it's a real cultural change, but the great thing is while there is some enablement there and there's some services there, pretty quickly, people can be self-sufficient using a platform like this. And then, as you said, over the long term, that creates a lot of value for everybody.

Delian Asparouhov:

So, both at AppDynamics and DataRobot now, you've had a COO title. I feel like one of the trickiest parts of COO titles is it can be actually wildly different between organizations and mostly dependent on in some way how the CEO likes to work and where their strengths are versus where they might not be that strong or prefer not to spend their time, their communication styles, et cetera. So, I guess, can you talk a little bit about maybe the differences between your COO role at AppDynamics versus at DataRobot and maybe how that relates to the underlying relationships with the CEO and what their preferences, strengths, attributes are?

Dan Wright:

Yeah, I mean, the blessing and the curse of the COO role is it's very flexible. It means a lot of different things at every different company, right? So, I actually enjoyed that. Because even when I was just at AppDynamics, it allowed me to learn about a variety of areas. So, I started off and I was running all the operations, functions. I was running finance and accounting and all of the G&A and operations. Over time, while I was there, I took on more of our go-to market. That was all great learning for me, because the thing is you really do need to go deep in these areas to understand them. It's also to know, "How do I build my team," right? I think the mistake people make sometimes is that they don't go deep. So, they don't develop that understanding.

            So, I really tried to do that in every one of these areas, and then build a great team. And then I could expand what I was doing. DataRobot from day one, I've also owned our whole go-to market. That, I think, was a natural thing after being at AppDynamics, but I've had to learn a ton, right? I mean, I think you're always learning.

            So, what I would say is really critical for anybody who's looking for a COO role or a President and COO role is you have to have a great partner as your CEO. At AppDynamics, I was fortunate to have a great partner with David Wadhwani, who's still close friend of mine, now at Greylock. And then at DataRobot, I'm really fortunate to have Jeremy, our founder and CEO as a partner. If you have a good relationship there and if you feel like you're complimentary, the rest takes care of itself. Oftentimes, the role will change month to month, then quarter to quarter and year to year, but that's the beauty of being in a startup, right? Everybody's role is changing all the time, and you're constantly learning.

Delian Asparouhov:

If you're giving advice to somebody who's in an earlier stage in their career, maybe just coming out of Gundersen or something like that and trying to get into the operating in-house side of things, what are the best suggestions that you'd have for them in terms of where should they start, how should they think about their career position in order to get into a position like yours, where they eventually want to be, let's say, COO of late stage tech company, ready to go, out on the market and maybe become massive? How do they structure their career in a way that gets them to where you are today?

Dan Wright:

I mean, first thing is to know where you want to go, right? I think it's interesting to me how many people just drift and then think that they'll find themselves in some magical place that they'd like to be. I really encourage everybody and this is actually one thing that we have programs around at DataRobot, try to understand, "Where do I want to be in 5 years, 10 years?" What is your current trajectory related to that? Are you on that track? If you're not, you're going to have to do something differently. And then I think if you're not on the track that you want to be on, just being honest with yourself about that and then being prepared to take a risk. That's one thing, especially for people who may have been trained in the law, they tend to be a little risk averse.

            I always tell people, don't be afraid to take a risk, but make sure it's the right risk, make sure it's risk adjusted. So, for example, when I was choosing AppDynamics, I didn't just jump at the first startup. I really did look at all the different things. I understood the market. And then I decided to join the startup that I felt like was the right startup, the right balance of risk and reward and where I was going to be able to grow in the direction I wanted for my career, right?

            I've continued to do that at every step since then. It's worked out pretty well. So, I think those are the two things I would say is one, have your destination in mind, know where you want to go. Two, don't be afraid to take a risk, believe in yourself. You only get one shot at life. So, why not try to actually make it the life that you actually want?

Delian Asparouhov:

I feel like the thing that I see in Silicon Valley over and over again is the people who consistently take big swings by default almost always end up having the most interesting careers, but the important thing being that they get smarter about which swings they're taking. I think it's hard if you're a total outsider to know how to take risk and how to assess it versus as you've been here for 10, 15, 20 years, it actually gets to be pretty obvious which companies are going to be succeeding, which ones aren't, what the best risk adjusted opportunities are.

            So, I guess, yeah, how do you feel like you've gotten smarter over time about assessing, as you said, the risk, right? You don't want to necessarily just jump at the first startup. So, maybe by being a venture lawyer, you had really broad exposure to a bunch of startups. But I guess, how do you feel like that's progressed over time? Where maybe by the time you were deciding to join DataRobot, you didn't have to rely as much on external advice, because you had so much, let's say, internal knowledge. How do you feel like you got smarter and smarter over time on assessing which opportunities and which risks make sense to take?

Dan Wright:

I think it's like anything else, you just want to get as much data as possible. So, the way that you do that is through networking. Early on, I really tried to make a point of just reaching out to people at other companies and getting to know them, understanding what's going well, what's not going well at their company, and why, and then watching out how things would progress over time. I mentioned those startups that I used to work with back at Goodwin and seeing which ones did well and which ones didn't. That was just more data.

            And then as I've been able to do that, also, investing in companies, getting involved as an advisor or board member in companies, and all those relationships build on each other. You track all these different companies. It just provides all this data that you can organize and say, "All right, these are the common factors that I see that are highly correlated to a great company."

            I think the beauty now is that you don't have to do this as just yourself anymore. There's lots of different ways, whether it's online through different platforms to get a lot of this information. So, you can use that as well, whether it's CB Insights or Crunchbase or going on Clubhouse. There's lots of different ways that you can learn about what's happening in the market and what companies are doing well and likely to do well in the future.

Delian Asparouhov:

I guess, this is the first time I've had Clubhouse show up on an Operators Podcast interview. So, clearly, the app's doing well. I feel like there's two camps, religious camps on when you're in an operating role and focus on building a company, the potential value, but then also the potential downsides of external board member responsibilities if you join, angel investing on the side, advising, et cetera.

            I guess, yeah, can you talk about the value you've seen from that, obviously, in relation to learning about how to gauge risk adjustment, but maybe even value in your actual, let's say, operating role, and then how you think about balancing that without either distracting from the core focus and core goal and how you think about that? How much time do you dedicate to it? How do you think about that balance and whether or not you think more people should be doing that?

Dan Wright:

I mean, I think it's all about balancing priorities, right? I think the idea that's used to be out there that "Hey, operators should just be operators and not invest in any companies," I just don't think that's correct. I think that you get so much insight into the market. What are these different companies that are doing that's allowing them to be very successful? What are the huge mistakes that they're making that's taking the company? It's just more signal that you get if you're tracking these things. So, I think it's hugely value add, not to mention all the networking opportunities that you get out of that, and that can lead to everything from help with recruiting and people make companies. So, that's critical to leads for your go-to market teams. So, I think it's really valuable.

            I think there's a balance though with you need to keep in mind your number one priority as an operator needs to be that role. So, that really needs to be the bulk of your time. Your investing can't get in the way of what you're really focused on trying to build an important company. So, I think, what I would say is if you're thinking about doing it and had the means to do it, it's definitely worth doing. There's a lot of value in it in multiple ways. But at the same time, just keep your priorities in mind and make sure it doesn't disrupt what you need to do on the operating side.

Delian Asparouhov:

Yeah, no, totally agree. I think, yeah, there's ways to balance it. Yeah. I'm maybe the reverse investor now, hopping back into operating, starting a company. There's so much value to having that broad perspective. Yeah, Dan, thanks so much for taking the time today to hop on the podcast. I really enjoyed the conversation.

Dan Wright:

Yeah. Thanks for having me. It was great talking to you.

Delian Asparouhov:

Thanks for listening, everyone. If you'd like to support the podcast, please sign up for a paid Substack subscription, which we use to pay for transcripts, mics, and other improvements. If you have any comments or feedback on what kinds of questions I should ask, who should come on the show or anything else, please do let me know. Have a great rest of your day.

Operators Ep 21: Morgan Brown (Shopify)

  
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Morgan Brown is the VP of Growth at Shopify. Prior to joining Shopify, Morgan was the Director of Product Management at Facebook, COO at Inman News, and Interim Head of Growth at Qualaroo and TrueVault.  He also authored the book, Hacking Growth: How Today’s Fastest-Growing Companies Drive Breakout Success. 

In this episode we talk about his experience at FaceBook and why he chose to leave, what his current role at Shopify entails, and why in retrospect he would have started his career off at a large company. He also shares about his college studies in zoology, his success at blogging, and how his approach has always been to outwork everyone else.

I hope you enjoy the show.

Full transcript available.

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