Will: And got a text from Patrick saying, Hey, do you want to be CFO? Weird. What a strange proposition. And I, you know, sort of replied rather impulsively saying, I think that's a very bad idea. Welcome to the Logan Bartlett show.
Logan: On this episode, what you're going to hear is a conversation I have with president of Stripe, Will Gaybrick.
Will has had a very interesting career going from an early job at Blackstone while working on his math PhD to Yale law school. So working as a software engineer before ultimately joining Thrive, where he was a general partner and led the investment in Stripe before going over to Stripe, where he initially started as CFO, then became chief product officer, and now works as president.
Will and I talk about a number of different things, including his career arc and how he made each of the decisions along the way. As well as what he looked for in his time as a venture capitalist and what ultimately led him to making the decision to join the Stripe team today. We also then talk about artificial intelligence and where they're using that within Stripe and also where he sees it going forward.
Finally, we talk about the motivations and the things that keep him going today and what makes his job at Stripe enjoyable. Really fun conversation that you'll hear with Will now.
Will: Well, thanks for doing this.
Logan: My pleasure. Thanks for having me.
Will: Uh, so you've had an interesting career path. Uh, I want to make sure I get this, this right. So you study math at Harvard, then you went and you were doing a PhD in math.
Logan: I was, yeah, I was actually at Blackstone, uh, working in private equity at the same time and then, uh, twice a week I would come down to the Kron Institute at NYU and take classes and then go back to my cube and, you know, work all night. And, uh, yeah.
Will: I I, time management maybe will be one of my questions in a second, but, uh, then you were a software engineer, uh, and then from there you went to Yale Law School.
Logan: Yeah. Actually. Fun fact. My, uh, first boss is a software engineer. It was Chris Dixon
Will: How funny. At hunch. At Hunch, yeah. Yeah, yeah. Chris Dixon, uh, of, of Crypto Web3 Fame these days. Yeah. Um, then. Did you finish Yale law school?
Logan: I did. I'm actually a proud and completely incompetent [00:02:00] member in the New York Bar even today.
Will: So then thrive and now Stripe,
Logan: And now Stripe. Yeah.
Will: um, as you're making these professional career decisions along the way.
Will: Um, how did you, how did you think about like what to do next? I'm
Logan: So I'm a big believer in, uh, career construction, uh, via induction. Uh, you know, I think there's like a lot of career engineering you can do, like, I want to get to here. And it's a classic sort of MBA approach of, if I want to be here when I'm 45, then what do I need to do, uh, today? Uh, at every point, just you meet people, you see opportunities, you, You know, work your butt off and when something seems really interesting and you're really compelled by people, you can jump on it.
So Thrive, uh, uh, Josh and I did, Josh Koshner and I did not know each other in college. We were one year apart and I was, uh, going to work as an engineer at a startup, uh, during the summer of, I guess my second year of law school and just got a cold, uh, email from Josh saying, Hey, I'm sort of doing this venture thing.
You want to get together? And incidentally said, uh, I need a CTO. And so my original job at Thrive was to be CTO of the fund, and we were three people. It was, you know, a 5 million fund working out of just a random tiny office, uh, in one of the Kushner buildings. And it turned out Thrive didn't actually need a CTO, it needed, you know, someone who could do deals.
And so pretty quickly pivoted to doing that. And that was awesome. Uh, love to Thrive. Uh, just, uh, Amazed by what that crew has done. So my best friends over there, um, and, uh, and, and I left Thrive to go to Stripe, you know, similar, just because of, you know, it just sort of landed on my plate as an opportunity.
Uh, I'd been at Thrive for about five years. I'd led an investment round in, in Stripe. I think it was a Series C or something like that. It was a 3 billion valuation or three and a half. And, uh, maybe six months later, [00:04:00] um, I just got a. I was out at like a bar in the East Village with a friend of mine and got a text from Patrick saying, Hey, do you want to be CFO?
And
Will: Weird.
Logan: a strange proposition. And I, you know, sort of replied rather impulsively saying, I think that's a very bad idea. Um, but you know, Patrick is very often a couple of steps ahead of me. So we talked about it for a while. I remember his, uh, uh, because I was, you know, being vulnerable and saying, Hey, Patrick, I, I'm not, you know, I've never worked in finance besides being a, you know, a briefly an analyst in private equity.
Um, and he, uh, he said, well, John and I think we could do it. And maybe I just took that as a challenge or something like that, but jumped over to CFO and now it's been going on nine years.
Will: funny. Some of those things that take a long time, uh, of like Yale Law School. That was no short period of time. And, uh, I mean, I'm sure Blackstone was a very consuming thing to be doing.
Also taking a PhD in math on the side.
Logan: Yeah.
Will: both of those decisions to do that incremental thing, were you thinking, Hey, this will come in handy to some career end, or were you doing it for the ends of itself that it was like something that you actually just found fascinating?
Logan: Yeah, really the latter. I get pretty excited about things and I can't really sort of get, get, uh, get myself to stop thinking about them.
Logan: So when I was at law school, for example, uh, I kept my apartment in New York city and was going back and forth. I was at Yale for law school. So I was in New Haven and, uh, by my third year, I was mostly just going because I had started something called hack Yale, um, first couple of years of law school, uh, some like Yale undergrads had gotten wind of the fact that I was an engineer.
And when I was an undergrad at Harvard, it was like this, you know, early boom time of building startups at Harvard. None of that culture was at Yale when I was there for law school. So this is late 2000s, you know, five years after, um, you know, Facebook had been [00:06:00] started. And, um, I started getting these like cold email pitches from undergrads saying like, Hey, I have this idea.
Do you want to like found this company with me and so on. And, uh, you know, sort of thinking to myself, No, like, I don't know you, like, maybe, I don't know. But, uh, what I decided was, hey, what if I taught these kids to, well, these, these, you know, young people to build things, you know, I've been an engineer for a little while.
So I decided to start something called Hack Yale, which initially was just me and a whiteboard and like, you know, five kids who sort of had written to me just teaching them like full stack JavaScript. You know, if you're going to teach them one language, HTML, you can do things on the client, do things on the server.
And, uh, you know, the second class, it was sort of like standing room only in the classroom. Couldn't hold a third one because it was just Two packed. So I opened applications at Yale, uh, to sort of join this class. And in a week, a third of the student body applied to take it, which was sort of, I think, an incredible signal of the demand for sort of like learning on campus, uh, learning computer science on campus.
So I got really excited about that and actually spent like most of my third year of law school just doing that. So just, you know, I don't know, get excited and spend time on these things.
Will: you ever try to use your law degree in, I mean, you, you actually took the bar exam, which I I'm told it's not a, uh, a small endeavor.
So did you, was there ever a thought that, Hey, I should use this in some capacity
Logan: Never really. Um, you know, I dropped out of my math PhD program. I just had this itch to, you know, I don't know, do some more school. I, I really liked it. I mean, it was, you know, freaking expensive. I remember, you know, working in the library to sort of, you know, make sure I could, uh, uh, you know, uh, buy, buy dinner for myself, uh, during law school, but, um, never thought I'd use it.
It was a great loophole where as long as you're not practicing, you don't have to do the [00:08:00] continuing legal education, uh, work. So I don't think I'll ever use it, but I, I loved law school. I learned a lot.
Will: any of those experiences that you think have been most helpful to your,
Logan: It's probably a good fit with my background to some extent because Stripe is a very polymathic company. You know, as a venture capitalist, I, you know, had the opportunity to sit on a bunch of boards of SaaS companies. And I remember thinking, you know, wow, we got to like build all this stuff for the company to be successful and they have to ship this new feature and this new thing and so on.
And wow, it's so cool they're making all this progress. Uh, and when I think about how simple it was just to ship software at a SaaS company, uh, I feel very jealous at Stripe, because at Stripe, it's sort of like, okay, we're kicking off this initiative. We need to think about what are the financial crimes mitigation implications here?
Are we creating credit risk? Are we licensed in the ways we need to be? Do we have the partners lined up, you know, partnerships like financial institutions will take many quarters to line up. So you know, This sort of polymathic background of being able to dig in on
Will: you know,
Logan: anything from the shape of the product and technical designs all the way over to very high level sense of the legal framework has, I think it's paid, paid dividends.
Will: you think about learning, uh, things that benefit you with Shripe as well as, um, I don't know, I mean, being able to learn as well as you have across a bunch of different fields.
Will: Do you have any interesting techniques or ways of, of learning and getting up to speed in, in new areas? I was listening to. Yale talk you did in 2015. And at that point you were talking about AI as a, as a field, uh, almost 10 years ago. And so I assume you were doing things back then to realize the opportunity that artificial intelligence could present.
So I'm curious, are there any techniques or ways of learning that you think are interesting?
Logan: I'll tell you a new one for me, which I'm behind the curve on is, is YouTube. [00:10:00] Um, like I was just, uh, spending a bunch of time trying to understand how the heck transformers work. And I don't mean like, how do they work? Cause no one knows how they work. There's some sort of, you know, black box alien technology, but just like literally the architecture of it.
And it is amazing just like what you can learn from watching a few 10 minute videos. Uh, besides that, you know, as an engineer, I, Just really like to take things in, you know, uh, via reading just, uh, you know, back in the day learned a lot of, uh, just how to do like actual sort of like commercial programming via stack overflow and things like that.
Yeah, I read a ton. Oh, actually a good one. Um, uh, so my partner, Emily and I have a two year old now, just audio books, you know, when I had to walk around with her sleeping on my shoulder forever, just like ripping through audio books. And that's been great.
Will: Yeah. It's amazing. I, I, I also think YouTube for everyone knows it, but I still think it's underappreciated for how powerful of a medium it is.
I had a friend asked me like what the best books were and getting up to speed on real estate investing. Just go Google or go YouTube search it for the next, you can spend six hours and you'll get it to still down in a much easier way and sort of presented
Logan: Yeah. And structurally, it makes sense because you watch these videos and you're like, this is clearly a great business for these creators because I'm sitting through those ads and I'm just like riveted waiting for the next section, you
Will: Yeah. YouTube subscription, by the way, the premium is actually some of the best money I spend on avoiding those, those ads, just, I spend so much time on it. And, uh, that benefit I think is well worth whatever I pay. I don't, I don't know what it actually even costs. Um, looking back on your career, I guess, uh, and then we'll, we'll move off career, but were these decisions, uh, Like calculated risks in how you were thinking about them.
Like, were you building pro and con sort of, uh, uh, trade off, you know, T charts or thinking through probabilities of [00:12:00] outcomes and whether or not it was going to be successful? Were you just moving forward into what felt right?
Logan: know, last time I made a big move like this, I guess I was 29. Um, you
Will: And that would be straight.
Logan: be Stripe. Yeah. Or I guess, yeah, just turning 30 at the time. Um, and so it didn't have that much to lose at that point. You know, it was hard to walk away from Thrive mostly because of the relationships and just, you know, we, we were building something really fun together,
Will: But
Logan: but no, nothing has been, you know, too sort of, um, I don't know.
Uh, forecasted or risk weighted
Will: Just getting to dip your toes in so many fields was amazing. And a second ago, I was like, what's going on with nuclear these
Logan: Yeah. Uh, so what did I miss? Okay. So, um, you know, on this thread of being sort of polymathic, just getting to dip your toes into so many fields was amazing. You know, you and I were talking a second ago about like, what's going on in nuclear these days?
I'm like, I don't like, you know, I get to every now and then read a little something about it, but you have this license to just learn so much as a venture capitalist. You know, flip side of that was. You learn a lot, but you don't actually get to sort of drive results. And, you know, sometimes I just would really want to get my hands dirty.
And, uh, with Stripe, for example, I was like, you know, kind of getting jealous of they're building this awesome stuff. And, you know, I'd love to get, you know, um, get to do something like that. And, you know, ended up getting the opportunity to, um, I know there's lots of things at lots of firms, like internal firm politics and things like that.
Fortunately, we didn't have that at Thrive. Such a tight, tight partnership. Um, and I guess maybe the other one, venture capital, you get to meet a lot of people. Um, and that's great. You know, you get to, everyone wants to talk to a venture capitalist. Uh, it was my experience.
Will: So, Stripe, I guess, you, you, you came in as CFO and the company was about how big? How many people?[00:14:00]
Logan: I think I was employee 290 something and probably net of, you know, attrition, probably 250 people at the company.
Will: And so, uh, then you stayed on as CFO for, uh, longer than I think was originally planned. I guess when you originally joined with CFO, always going to be the, an on ramp into doing product related stuff. Or was that something that you decided along the way?
Logan: Yeah, you know, I've never actually directly asked Patrick this, but I think CFO is kind of the job he had to give that I might take. Um, and, um, yeah, so I took it, um, uh, uh, when in 2015 and then in 2018, uh, became chief product officer
Will: Along with CFO.
Logan: Yeah, along with CFO. And you know, it's funny, um, back then I was more fashionable and wore tighter jeans.
And one of our employees used to joke, CFPO, Chief Fashion Pants Officer, that stuck around Stripe for a while. And then, you know, about two years ago, I moved into this
Will: um, uh,
Logan: president role.
Will: you did the dual for a while and then president happened after you shed CFO, is
Logan: Oh, yeah. Sorry about that. Skip to step. Uh, we then hired a CFO, uh, about four years ago. And then, uh, now we have a different CFO as of about a year ago.
Will: Okay. And, and so, um, from a, from a functional standpoint, what rolls up into the president? I don't now.
Logan: So, um, from a functional standpoint, uh, a lot of just day to day running of the company. So product engineering, uh, we have a separate infra engineering, um, group under our CTO. Um, uh, Company operations, you know, from GTM operations to product operations, uh, risk partnerships, professional services, um, a lot of things like that.
And then, you know, so the job description day to day is just make the business successful. Uh, you know, John and Patrick run the company and I think day to day, and [00:16:00] they look to me to do a lot of just sort of running the business.
Will: Got it. So, um, I guess over the course of the last, uh, I don't know, 18 months, two years, like when is this shift sort of happened from more growth to the balance of growth and profitability?
Will: When did that happen?
Logan: 2022
Will: 2022.
Logan: Yeah.
Will: there Things you did, uh, as a part of that process that you would recommend, uh, just as good operational hygiene for companies that maybe think they're operating at, I don't know, 90 percent skinny as they should be, but, you know, sort of thinking of the other knobs that they can turn?
It's
Logan: Yeah. Well, so it's interesting because up until the COVID bonanza, um, we ran on a principle that we would always be cashflow positive. Now, I actually don't think that's wise advice for a lot of companies, you know, particularly if you are sort of a classic, um, Uh, you know, enterprise company and you have very good foreseeability and you're sort of like, you know, uh, two to three year LTV on sales and marketing, um, um, or return on, um,
Will: LTV
Logan: LTV to CAC, uh, over two to three years on sales marketing, you know, in that case, you actually might want to dip into, um, you know, spending a bunch of cash, burning cash.
Uh, but we always decided to run the business actually cashflow, um, positive. Now, along came COVID and. You know, there was a sort of a harrowing moment where, you know, it looked like the company was going to just stop growing altogether. And then growth just went, you know, through the roof and, you know, I don't know, you know, drank the Kool Aid or whatever analogy you want to say around sort of really investing at that time.
And it was the first time we dipped into burning cash. Um, uh, you know, interestingly to date, we've still never burned a dollar of investor money. Because we had accrued so much cash from operations to that point that even with our burning cash, you know, our cash pile never dipped into like needing outside capital.
But, um, two things happened at that point. One [00:18:00] was, uh, the median average, uh, tenure of employees sort of fell off a cliff. Uh, you know, when you're growing year on year, like 100%. Uh, headcount. That means the median person at the company has been there for six months or less.
Will: Yeah. And probably less when you factor in
Logan: Exactly. And, and that's just sort of, uh, you know, terrifying if you think about it. Uh, and the other was, you know, we just, and related, we didn't see the productivity gains that you would think of like we're adding,
Will: you know,
Logan: Uh, uh, as much capacity as we already have, we should be able to go faster. And it just didn't play out that way.
I think there's something pretty deep points around capital allocation in this. Like there's some kind of dangerous correlations or dichotomies that people make. Uh, you know, there's the classic one around, um, you know, uh, speed and resourcing, like, uh, or features and resourcing. Like I can give you A, B and C if you give me more people.
And I think you just find that, uh, You're really great leaders, uh, self solve so much more, uh, than, you know, uh, than others. And so, you know, you stack something on the top of the, uh, of, of the stack rank and something else will pop out and you won't care. You won't even know that something else popped out because they just have reallocated so thoughtfully.
Uh, and then another one is sort of, you know, speed and quality. You know, we added all these people and there's a notion that, you know, uh, you can either go fast or build things that are high quality. And in fact, you know, it's sort of interesting because I think they're strongly correlated. Just the teams that go the fastest build the best stuff and, uh, and the teams that go slower, like almost never build good things.
Um, so, you know, uh, I think just really scrutinizing your spend, particularly in, um, Product engineering, where you spend the most money, uh, is, is a good exercise to do. Um, we actually don't institutionalize this where every single year when we do budgeting, the first thing we do is we [00:20:00] squeeze. And so we say, what you're getting for next year is you're actually netting down your OPEX spend.
Uh, so you're going to spend 10 percent less. What are you doing? And then we sort of reclaim that spend and then reallocate it,
Will: It's interesting. It's like a different zero sum budgeting, but
Logan: Exactly. And you just, you know, it's like building a muscle group, you know, you, we want people to leave Stripe, uh, and, uh, you know, they get hired to their next job and, you know, sort of bring in the Stripe way of driving efficiencies and allocating capital.
And so we think of this as something we do it every single year. Our leaders will get better and better at it.
Will: better.
Will: In terms of, um, hiring now, the incremental person, I assume it's, there's, there's a lot of scrutiny put on bringing new people into the organization. Um, are, are there certain. I'm sure you guys have your set of values and, and all the things that you hire for, but are there traits that you found in, are they stripers, what do you, what are stripe
Logan: Uh, stripes. Stripes.
Will: Uh, are there certain, the, the most successful stripes, uh, that have spiked and risen quickly and taken on a bunch of, uh, leadership, are there certain qualities that you found just sort of risen above the noise and really solving for those is more important than anything else in a hiring process?
Logan: Yeah, there, there's a few. Um, So one of our operating principles, uh, elevate Ambitions. Um, and you know, I think, uh, one of the reasons why people get excited to come to Stripe and stay at Stripe is it's sort of like an infinite, um, problem space. Um, and actually, you know, uh, I always looked for those when I was a vc.
Like, you investing in a company that's gonna sort of solve a thing and be done, or it's just like always gonna be more roadmap. Um, and you know, for Stripe it's like, you know, we have at least a decade more things that. We want to build right now that we'll get to, uh, over the next, uh, a couple of years.
And so, you know, this notion of just like the bigger vision and where we're going long term and just believing in the company really being able to have macro impact, [00:22:00] uh, that sort of aligns with the mission of growing the GDP of the internet. Um, so this elevating of ambitions, this thinking big about really being able to do something that's sort of You know, systemic, uh, and its impact is one.
Um, second one, I think there's an Amazon operating principle around this, but, uh, leaders are often right or something like that. I can't remember how it's phrased, but judgment, you know, it's, it's amazing that you sometimes find that you're sort of micromanaging way down in the org. And then you realize like, okay, I have sort of a problem.
Like right below me. Um, obviously this person's not a good leader, but you know, why am I having to sort of go around them or so on? And a lot of people who rise quickly are coming up because they're just, you know, without a whole lot of coaching, doing the right thing over and over and over again. And that sort of just, um, entrepreneurial, uh, uh, you know, ambitious and just high judgment execution, um, really helps.
Uh, and then interestingly, um, I would say, uh, there's something around just, uh, a desire to create something beautiful. Uh, which sounds a little bit hokey, but a lot of our best leaders are just galled to no end when they see, you know, in our documentation that the, uh, string formatting is like different between two different pages.
Like, you know, here we use, uh, a floating point number with two decimal points and here we're using, you know, one and that's like drives them crazy. And I think this is like a, something that sort of. Drives a lot of our best users is we want to, you know, create something truly great for our users
Will: Are there ways in which you can tease out the judgment, uh, thing, or I guess the The design appreciation in interview processes, or are those just, Hey, those are learned qualities that you see once people get into the organization.[00:24:00]
Logan: So on the design side, um, we've actually since changed this, but something I kind of like to bring back, uh, our, uh, one of our interview questions for PMs joining Stripe was to choose one of several integration paths, um, uh, for Stripe and just do an end to end integration. Um, and, and this is kind of table stakes, you know, I think you can be a product manager at a lot of companies and not really know how to fire up the command line or, or, or sort of, um, let alone just making sort of like curl commands, like build a real, um, integration and have them write, you know, what we call friction log, which is just what went well at every stage, where'd you run into trouble and so on.
Uh, and you could see, you know, when people were really opinionated and, you know, just This could be better. You know, I ran it. There's a sharp, a pointy edge right there, you know, or I can't believe you didn't do this and almost as I can't believe people, the people you want to hire. So
Will: yeah, the judgment one's always interesting. I, um, I, I find at least when we're hiring, uh, people to be investors or within our organization, there's, there's generally stuff you can tease out in a resume and just have them take you through how they made each.
Decision along the way. And you learn a lot about people's intuition, their judgment, how pragmatic they are in the decisioning. Uh, and if you're, if you're, if you've made a handful of decisions that were, you know, wrong at some point, you're not self-reflecting, uh, and why the inputs are. And so we try to tease out judgment as much as we can
Logan: can. Absolutely. And you want to see that like learning mindset, where if you ask them, can you give me an example of when you were wrong or something you failed at, if they really have to search for it and they can't, you know, give you a good, then that typically means that.
Maybe something's off is too harsh, but you're not
Will: No, I think it's right. There, there's a lack of, um, self awareness or at least self reflection. And at the end of the day, that's sort of all we can do as humans, but maybe [00:26:00] investors specifically is just like continue to tweak our mental framework by which
Logan: we make these
Will: these decisions.
Logan: Yeah. Yeah. To, to, to the point on, uh, sort of, you know, learnings around COVID time. I mean, companies learn by failure or. trauma or whatever. And I really think the same is true, uh, for, uh, individuals. Like I remember, so we, we run a Stripe sessions every year, which is sort of our, you know, uh, our dream force.
It's a little bit different, but it's our, um, our global user conference in San Francisco and, uh, John and Patrick typically open it. And then I sort of MC it and deliver a couple of sections and some of our other leaders, uh, uh, Uh, you know, uh, do demos and, and, and host some of the sections. And we were in our first one.
Um, we had been for a long time, uh, negotiating a deal, uh, with, uh, one of our financial partners that would allow us to geographically expand a lot faster, but it wasn't signed. And in the closing, this was a big moment. We're talking about like next year's roadmap. And, uh, I made a very, very bold claim about, uh, geographic coverage that would be available by the next sessions.
And about a month later, the deal fell through, uh, for a variety of reasons. And so, you know, fortunately, I don't think people cared enough about Stripe at the time to really notice, but I learned then, like, make sure the deal is signed before you
Will: the hay is
Logan: tell the world exactly. Yeah.
Will: you announce it. Um, as you reflect on You're now nine years in, uh, is there something you wish you knew, uh, specifically that stands out that, man, if I had thought about that, uh, you know, 2015 when I was joining, cause Stripe was kind of your, was it your first like company you were at hunch for a little while, but, um, is there something from an operating standpoint that you wish you, you had known in 2015 that, you know, now in 2024,
Logan: I mean, so many things, uh, because just thinking back then, no, [00:28:00] no false humility here, just like knew so little. Right. Um,
Will: Anything that immediately jumps to mind though that was like a light bulb moment when you finally realized it?
Logan: Yeah, one recent one is I think when you are designing organizational systems and processes, you have a tendency to design them for yourself. Or like for leaders. Um, and in some cases that's what that works, but it's almost never the right design center. Um, uh, the two that are most common are one, as I mentioned, you know, second ago, sort of your leaders, like the people who are just sort of, you're leaning on to drive day to day execution.
Or I think the one that people often don't think about is line managers. Because very often, if you want things to get to you, uh, you know, with sufficient granularity, like you want information to cascade up to you, you need them to be undertaking a certain process all the way on the front lines. And if you want them to undertake that process, you know, uh, with, you know, high sort of.
Fidelity, uh, they better like it. And so, you know, a lot of what we do, um, to, uh, you know, make decisions well, and make sure the right decisions are hoisted up in the right ways is figure out what, what are the mechanisms that if you're blocked on the front lines. You'll say, Oh, I know exactly how to unblock myself.
And you do it right there. Or, um, actually a better example. Uh, you know, you, uh, want to do capital allocation really thoughtfully. Well, what do you need to do that? You need observability. You need to know what people are doing. Uh, who knows what people are doing? Line managers. So how do you take what's in their heads and what's happening every single week on their teams and get it rolled up to you?
You need to create the thing that they want to use to run their weekly meetings. And so we spent a lot of time on that. And it's actually part of like spinning up at Stripe. Here's how you do a weekly business review. Here's, you know, what it looks like to operate really well on the [00:30:00] front lines. Here's all the systems and resources we give you.
And then, you know, uh, surprise, surprise, like. Outta that pops all the information that we need.
Will: Have you guys built something internally, like from a codification standpoint? Are there, is there tooling that you guys use that actually rolls up
Logan: Yeah, actually we've, we've really doubled and tripled down on it.
We have a, a project, a product internally called Compass. Um, and uh, it is, um, it was originally built just for product development tracking and actually it was only recently that we made it mandatory. It had a ton of use. Um. Uh, already, but we use it, we use it for like, uh, NPI, new product introduction initially, and then we realized was that it could be so much more.
Um, and so now we run, uh, weekly updates out of it. You can follow projects. It'll send you a digest. Uh, you know, all of our product development processes are sort of institutionalized and systematized in it. Uh, so, you know, we have various gates towards launch. Um, One thing that we do is, um, uh, something called implementation review.
It's like a peer review internal to Stripe. So before you ship your thing, uh, to public preview, it has to run through, uh, another Stripe, a trained implementation reviewer doing an end to end integration, writing up a friction log, saying everything they found. Then, you know, you go through it. You say, what are you going to change?
What are you not going to change? Ultimately, there's sort of a rapid, like a decision making. That's the form of decision, decision making we do, um, where the, uh, the head of the business unit actually says which changes need to be made. So it's this complex process and the whole thing just runs through this tool.
Will: Hmm, super cool.
Um, what's the biggest challenge that you're thinking about today for Stripe?
Logan: You know, there are a lot of them.
Logan: Um, one that is persistent, but very top of mind right now, is, um, migrating users to new versions of our API. Um, we've made, uh, you know, Always made the very user friendly choice, which we're going to keep making to sort of have a very, very generous end of life policy.
So [00:32:00] basically if you're using Stripe, uh, and you're not sort of trying to adopt more of it, it's just going to keep working.
Logan: Uh, right now, Because, you know, we sort of, um, Moved not just like sort of beyond payments, but to this world where we have, you know, this, um, billing suite that, you know, we announced this publicly, it's a half a billion dollar business growing like crazy, um, uh, you know, uh, and we've got, you know, all these products in connect land where you can sort of store money in the cloud, we're having to refactor like all of our abstractions, um, because a lot of the guarantees that our API, um, sort of.
Looked at like, if I, you know, process a payment, then all the settlement will come through stripes rails, um, are being relaxed. Like one of the top user asks for billing is I really want to use straight billing, but I have a four year contract with T SYS or world pay or some other payments processor. Uh, so can you.
Like plug that in. Um, we announced this publicly, uh, at Stripe Sessions. Uh, that's actually now in private preview. So you can do that. But some of these changes sort of run through a lot of our abstractions. Um, so we've actually now cut a V2 of our API, which actually makes, you know, some updates to the API semantics as well.
And, um, We are going to have to maintain backwards compatibility. So if you're a user out there, don't worry. Uh, but we also are going to be able to ship so much value so quickly by getting people into new versions and you know, there are just thousands of lines of Stripe code written into a lot of users.
So figuring out how to do that is a big challenge.
Will: As, as you think about payments and Stripe, I guess, in the next, Five years, 10 years. What are some of the biggest changes that you think are inevitable that might be unintuitive to people just going about their day?
Logan: I mean, I've mentioned it in [00:34:00] passing a couple of times already, crypto.
Will: what way?
Logan: Yeah, I'm so excited about it. I'm so excited about stablecoins.
Will: Um, uh,
Logan: So Stripe's history on crypto, so I think it was before I joined, maybe it was 2014, we were the first, like, the first major payments company or whatever, if we were major at the time, to support crypto PANs, and it was Bitcoin PANs.
Um, and then, uh, we sunset that a few years later, maybe it was 2017 or 2018, uh, because it was just all fraud. It was all, you know, bad actors, um, trying to cheat the system. We lost a bunch of money on it. Uh, and it's not surprising, you know, Bitcoin is not a good instrument, uh, to make payments with. Um, it's a much better store of value or sort of like long term asset to hold.
Um, and we took some heat at the time because, uh, you know, Crypto then sort of started heating up again. And then we sort of jumped back and, uh, back in a couple of years later, uh, building a crypto on ramp, uh, and, uh, and then, you know, we had this next crypto winter, um, and I think a lot of people sort of abandoned crypto and the thing we've just, Seen as a through line that is just compounding and compounding and compounding is stable coins.
Will: Um,
Logan: So, uh, we, uh, we mentioned, uh, recently that we're shipping, um, stable coin pans. So you'll be able to as a straight merchant with no integration changes, except payments in stable coins. I think it's just USDC to start, but we'll be able to very quickly expand that. And, uh, we're now in very recently in private preview, and I think it took two days for our, uh, cumulative volume in stable coin pans to pass our cumulative volume over a year and a half or two years on Bitcoin.
So it is just
Will: And what is the, what is the use case for stable coins? Uh, and maybe, maybe a quick primer for people that don't know what stable coins [00:36:00] are. Um, if, if you could just explain those too.
Logan: So, um, stable coins are just, um, crypto assets that are pegged to, uh, to a fiat currency value. Um, and, you know, there are now, like, uh, EUR, like, uh, EUR rails. Um, I'm sure there's other rails too. I'm sure there's GPP rails, but really, uh, USD rails, um, are, are sort of, uh, winning the day. Um, so there's, uh, USDC, which, um, is a, uh, sort of fully collateralized stable coin, uh, that was started by a company called Circle, um, uh, a big partner in creating it was Coinbase.
And so for this, it's like dollar for dollar collateralized, so in theory it can't lose its peg. Um, you know, fun fact, it actually did briefly lose its peg when, when SVB went down because they're storing some funds there, but, uh, but you know, in theory it's sort of, you know, uh, securely backed. And then there's.
Algorithmic stable coins where via trading algorithms, they maintain their peg. Uh, so tether USDT is, is the most popular stable coin.
Will: Yeah. And so, so then, um, what is the use case that you guys see over time or how would that change, uh, people's experience as you look out 10 years from now?
Logan: it's kind of funny because the sort of, we were all fumbling around for the killer app in crypto for a long time.
And you had the, the ETH world computer, which by the way, it's a beautiful vision and there's like so much, um, value in, um, in Ethereum as, as, as a platform. In fact, a lot of stable coins run on top of Ethereum or L2s on top of them. Uh, you had, uh, you know, all of the speculation that was happening and Dogecoin and all the other fun coins, uh, Dogecoin sort of the GameStop of stable coins, I mean of crypto assets.
Um, and it turns out that just the killer app is just money.
Will: It's
Logan: It's just crypto works well as money, as long as you sort of. Stabilize its value. Uh, so many parts of the world just don't have currencies that you can trust. When you look at [00:38:00] Southeast Asia, you look at, you know, I think in Vietnam, the adoption of stable coins is just booming.
And the economy is actually like taking off there. And if you look at the charts, it actually looks pretty correlated, uh, very young population. Very sort of crypto literate.
Will: Um,
Logan: So you know, for us, you know, part of Stripe's mission has always been to increase the pace of like globalization in commerce, like to break down barriers to cross border commerce.
And you know, there's a lot of those barriers that exist, you know, um, that are sort of like written deeply into the existing financial system. And the notion that you could have one globally applicable protocol to program money in the cloud. And you can see how to get there. really excited. So what we're seeing now is that, um, companies that, you know, uh, ship software, you know, B2B SaaS companies, uh, already major conversion uplifts for them when they accept, accept stable coins, because, you know, if you're in Rwanda, you know, it's, you know, pretty hard to sort of, uh, get a, uh, you know, electronic payment instrument, uh, that Stripe accepts.
Um, but, you know, if you can get on chain with stablecoins and you want to buy a piece of software that someone built in Rwanda, India or San Francisco or wherever else, uh, USDC works.
Will: And, and so now you're seeing this in, in mostly international markets that have volatile domestic currencies? Is that the, the primary place that, that this is unlocking?
Logan: I think that's where it'll gestate. And it is adjusting quickly. Um, I think it was something like 4. 6 trillion over the past 12 months in stablecoin transactions. Now there's, there's like a visa report saying that a lot of those weren't actually payments and that's fair. Like, you know, some of it's probably high interest rates and people just wanting to be in stables because they can, you know, you actually earn pretty good interest rates just from holding stablecoins.
Um, but [00:40:00] you know, there's a real exponential curve here. And my sense is that, um, The emerging world will sort of, uh, normalize stable coins and they'll sort of bring all of us who have very stable currencies into the, um, they'll sort of acclimatize us to the notion
Will: that
Logan: it's a perfectly, you know, um, uh, perfectly, uh, Normal and well accepted way to transact and that over time like moving between stables and fiat just won't be a big deal.
Will: And, and you think that the adoption versus Bitcoin, the reason it's growing so much quicker, is it the confidence in the, the price versus Bitcoin is going to be far more volatile or why, why is it seeing such faster adoption?
Logan: I think so and because it's, uh, the performance is a lot better. So a lot of, um, stable coins will run on Fiat. You know, um, L two chains. So these are sort of, um, chains on top of chains that will batch together transactions, uh, to, you know, increase the rate that they're, um, confirm at which they're confirmed, um, and decrease the cost of them.
And so Bitcoin, you know, there is a lightning network, but just Bitcoin in general is pretty slow and expensive protocol. Um, I think, uh, even just on. So on Solana, which is a very popular L1 chain, I think just native on Solana, no L2s. I think it's 400 milliseconds now for a USDC transaction, which is pretty amazing.
Will: Yeah.
Will: Um, artificial intelligence is, is, um, obviously one of the, the topics everyone's talking about. You in prep for this, I went back and listened to, uh, a 2015 talk you did at Yale and you actually said that that was, uh, the technology that you were most excited about.
I think you were even still at Thrive at the, at the time when you were, when you were doing that. I'm curious what, um. Your perspective has been, uh, both as a former investor and sort of looking at the opportunities that are there, but [00:42:00] also as an operator within Stripe of all the AI stuff we've seen over the course of the last two years.
Logan: Well, listen, uh, it's hard to match my enthusiasm about stable coins, but I would say,
Will: yeah, I know. I know.
Logan: I would say that, you know, a lot of what's happening in AI is right up there too. Um, yeah, I mean, I think the thing in 2015 that I was seeing was just deep learning looked like it was really going to work. And so if you believed in, um, in, you know, sort of continued, uh, Moore's law effects, then it just, you know, you would see this sort of exponential, uh, improvement in, um, in, uh, the ability for, um, Um, large, uh, direct, uh, deep neural networks to, to, um, just do powerful things for the world.
And
Will: Well, the video is out there, so, uh, I, I, this is not, uh, some, some hindsight revisionist history. I, uh, the video exists of you saying this,
Logan: But I will say that was the extent of my prescience. It was, it was very basic. Uh, I had no notion of, you know, transformers, even though those were near at hand, uh, or large language models, or just.
The concept of foundation models in general. Um, I think it's all so fascinating. Um, and I can, you know, talk a little bit about the applications at Stripe. Um, so at Stripe, you know, we've been, we've been using, you know, machine learning for a long time and, you know,
Will: I'm sure fraud detection or whatever, it's fundamentals of the business.
Logan: Exactly. Yeah. And you know, we have about something like 100 models, you know, in production to augment our products.
There's 43 that are sort of critical, like sort of in the charge path or doing major risk mitigation things. Um, the first model was shipped in, I think, 2015. It was like a linear regression model, even how it worked, uh, to, to mitigate fraud. So that's how sophisticated we were. at the time. Um, but a flash forward to today, uh, you know, I think we've, we've publicly stated that we've been toying with our own foundation models.
Um, and your foundation model, basically any [00:44:00] large model trained on, you know, large means many different things. You know, for us, it means, you know, order of a hundred million parameters, you know, for the GPT ends of the world, it's, you know, many billions of parameters or, uh, you know, hundreds of billions of parameters.
Um, I guess at this point, um, Uh, and, uh, you know, it was like a sort of self supervision. So there's no sort of, you know, uh, here's the input and here's the output we expect. Um, and it's actually just sort of trying to take, um, concepts and, you know, embed them in context. Uh, and, uh, and then you can sort of run.
Models on top of that, um, and they sort of like, you know, this, this sort of embedding in context, um, you know, it gives rise to this, you know, word embeddings that everybody uses, um, all over the place and loosely, but just to give you a very simple example of like something that's really working at Stripe, um, you know, card testing has been on the rise.
Uh, on the internet, um, maybe correlated with, with, uh, the rise of, of AI and ML. Cause it's just easier to spin up machines, to do basic things like this. So card testing is, you know, steal or buy a bunch of credit card numbers, uh, and then go to just random, uh, you know, uh, websites and, uh, perform transactions, uh, just small transactions to test does this card work?
And then you could tell it yourself or use it for something else or otherwise. And, uh, These used to be pretty easy to detect because they would be sort of one merchant and they would spike. It used to be sort of, Oh my God, you know, um, merchant X is seeing a big card testing attack. You know, we're sort of working with them to mitigate that.
And, and we provide various protections built into radar, our fraud suite and so on. Um, uh, We're now seeing some more sophisticated ones where, uh, card testers are sort of dribbling attacks across like different sites, which is two or three transactions here, two or three here, two or three here. So very hard to [00:46:00] detect because no one merchant is really suffering, but Stripe overall is seeing a huge spike and you know, that can hurt the sort of, you know, integrity of the ecosystem, violate card network rules, things like that. And so we found is actually taking just, um, Uh, raw payments data. So just take like a giant, like JSON blob of payment payments data. Like here's what a payment means to stripe. Uh, stringing it, you know, just turning it into like pure text, uh, like tokenizing it, just slicing that up into tokens, um, and feeding it into, uh, a transform model, um, has led to the ability to embed.
You know, payments in a way that is completely unintuitive to a human. We can't sort of point to any single cluster and say, Oh, this is exactly why those payments are clustering there or these are there. Um, but we've been able to identify just in the clustering that happens, uh, from these payments, just which ones are more or less likely to lead to card testing.
So we just take a new payment coming in. Maybe it's just one of three card testing payments on a site. There's no spike for us to detect. And you know, this model will be able to tell us in a way that no hand curated features ever could have that, Hey, just so you know, that one random transaction that doesn't look suspicious to you is actually a good one.
Very likely part of one of these distributed attacks. So it's been really powerful internally already.
Will: Are you doing that on top of one of the big model providers, or how is that actually, like, technically
Logan: So in this case, no, it's actually just ground up our own model. Um, there are, um, uh, we are toying with, Um, with, um, uh, leveraging, um, uh, some of the existing models, uh, to actually do some multimodal embeddings, which we're excited about.
Uh, there actually are some really cool, like just almost off the shelf applications that have worked very well for us.
Logan: [00:48:00] Um, so one of the things that, uh, is, is a core part of our strategy is to be sort of conspicuously good at risk mitigation and to be, uh, consistent. incredible stewards and sort of guardians of the global financial ecosystem.
We invest just a ton in, in risk management. Um, and you know, we just, you know, there was one of our, one of our leaders once said, uh, risk management to Stripe is like Amazon, uh, logistics is to Amazon. I actually think it's a pretty good analogy. Like we just need to be best in the world at it. And, um, There's a notion that, you know, fintech companies are, you know, play it fast and loose.
And there actually clearly was, you know, some bad behavior with, uh, with, uh, you know, FTX and, and obviously there, this isn't fintech, but you know, with SVB going down and FRB going down, there's been some tightening in the regulatory environment. Uh, and so we've just been doubling and tripling down on risk mitigation at Stripe.
Um, and you know, big banks, you know, Uh, you know, uh, sort of do a very good job of complying with, you know, uh, literally with what regulators want. We always want to do that too. Um, and we want to go a step further and just think how can we be doing this better for the world? And so we built something, uh, called Inspector GPT, uh, which lets us do sort of continuous TOS compliance for users, TOS compliance.
Um, there's a lot of different, um, very, very, very idiosyncratic rules about what you can and cannot sell, uh, coming in from different, you know, uh, financial partners up and down the stack. Uh, so something as a sort of, uh, scary as, you know, AR 15s, uh, maybe that's not idiosyncratic to something as seemingly innocuous as CBD.
Um, or actually even more innocuous, uh, like tarot cards. So, uh, financial partners don't want you to sell tarot cards. Uh, what we've historically done is we've underwritten our users when they're joining Stripe. You know, we use models to do this, like classifier models and so on. [00:50:00] And then, you know, we'll review them again from time to time, uh, you know, different checkpoints of they are now hit.
500, 000 to volume or, you know, 10 million volume or whatever. Uh, but we're actually able to leverage, um,
Will: uh, sort of
Logan: Commercial, uh, chatbots, um, you know, chat GPT or Claude or, you know, uh, Gemini, uh, really any of them have worked so far, feed them our terms of service and just point them at our user's websites. And.
They just will periodically go and say, Hey, I took your 25 page, like super intensive TOS. And I think I found about a violation on the 26 page of their product catalog. And it's because this spa. Which sells 308 services. One of them is tarot cards and that violates provision like, you know, three, a, you know, triple I, whatever, of no tarot cards, according to this financial partner.
Uh, and just
Will: you know,
Logan: that's, I think the state of the art for this is sort of like sending humans with like the printed terms of service docs and like maybe screenshots and, you know, having them do this in low cost locations. And yeah. It's just, you know, been really, really, uh, impressive and, and really, you know, create a lot of
Will: I think everyone talks about
Logan: the human replacement. Yeah.
Will: side of this, but the, the superhuman element of it is, uh, is super cool.
When you can find that it's not just, Oh, you're making engineering productivity, whatever, this much better. We're automating customer support, so we don't need a. higher people in Manila or whatever it is to do this, but actually being able to do things that humans couldn't do, uh, or, or maybe would be very hard to do as effectively as, uh, as that, like, uh, going over terms of service and being able to catch things on distant web pages.
Logan: I totally agree. And actually one of the things that is, um, that, you know, I've been thinking about a lot on this front is, um, [00:52:00] just the sort of. What are the implications for human knowledge period of the black boxiness of neural nets and transformers in particular?
Just, you know, uh, we don't know how our model was able to tell us that that particular payment was likely card testing and the model isn't able to explain why it was like, you know, there, there are ways in which, you know, we're sort of Getting better at explainability. You
Will: the, it sounds like the accuracy to be.
Logan: Very high.
Outperforming, you know, what we had with hand curated features by a whole lot. Um, and so, you know, there's something deep there about how we need to think about developing our products and enforcing risk standards. If we are virtually certain that the model is right, but we don't know why it is, what does that mean?
Will: yeah, there's, I mean, there's so many moral questions with AI in general, but the, the potential of bias, uh, or whatever, like it's great when it catches the positive, but the false negative in this stuff, when it can't explain how it came to be.
Uh, and it could be
Logan: making
Will: making racist assumptions or like, you don't know what, what the. primitives are by which it's making those
Logan: Yes. Yes.
Will: yeah, is, is fundamentally interesting.
Will: How do you go about, uh, your corpus of opportunity to apply artificial intelligence is gotta be up there for almost any organization.
Uh, and you also uniquely have the competency. internally to, to, to do a lot of these things. Like maybe Exxon has similar, but I don't think they have the competency to go execute it on it right now. Uh, not to disparage anyone from Exxon listening, but, um, how do you guys come up with like, what is worth testing and going after from an artificial intelligence standpoint versus what [00:54:00] falls below the, the line and we should just keep doing it the way it is.
Logan: mean, some of this is cultural. You want to, well, I guess there's a couple of things. So one is from a systems and tooling standpoint, you want to just, you know, give people the agency, like the technological agency to start using these technologies. And so we've made a bunch of investments on those fronts.
Will: And that just means having access to these tools. Yeah.
Logan: So, you know, one of the first things we did after the whole, um, you know, sort of explosion in chatbots with. With chat GPT coming out was we just, you know, um, created a, uh, uh, a go link internally to go slash LLM into a Stripe computer and it takes you right to an LLM interface.
You know, at that point it was just, uh, GPT 3 now you've got, uh, GPT 4, you've got, you know, uh, Cloud, a bunch of others sort of in there. And, uh, you sort of ragged this, um, uh, meaning we sort of, you know, uh, gave it some, uh, additional specific data on Stripe's internal documents. You know, purged any user specific specific data because we didn't want anything, you know, uh, you know, that's sort of native to users to get into these tools.
Um, but, uh, you know, we, Stripe's documentation, it's trained on, things like that, uh, and just sort of gave that to people. Uh, took about 10 days before, uh, usage sort of started to level off. And it's actually kind of stayed there. About a third of the company is weekly active and the vast majority of the company is monthly active.
And it's kind of cool too, because we created a community around it where, uh, Stripes would, uh, sort of share their prompts. Uh, so we actually have a prompt now, uh, that can take any, uh, uh, corpus of text and rewrite it in the Stripe tone. Um, you know, we are, you know, as I mentioned earlier, sort of really motivated internally by creating something beautiful and being, as we say, internally meticulous in your craft.
And so if you're, you know, [00:56:00] a sales, um, a sales rep or an SDR, and you just want to make sure you're writing a good email and that it's sort of done It abides our, um, our style system and our tone and so on. You can just toss it right in and it'll make some changes and shoot it back to you. Um, second step was just, uh, making sure that, uh, from a technical standpoint, we had API endpoints set up to do development with LLMs really easily.
And then the third, which is, I think goes to product development generally at Stripe is making sure that you make room for your teams to, um,
Will: know,
Logan: Um, you know, have, have better ideas than you have and, and, and surface those. Um, so there's definitely ways that we've been sort of tops down prioritizing our investments in AI.
Uh, but we also have seen some really cool bottoms up applications.
Will: Hmm. In terms of like e empowering autonomy, uh, of, uh. Decisioning within the organization and just letting people go do that stuff. Are there any, um, clearly it's partially how you, how you hire and what you incent people to do, but are there any, um, forums or means of facilitation that you guys have done, like, uh, I don't know, hackathon days or, or it sounds like that prompt sharing is, is one, but anything that stands out there.
Logan: so in general, um, you know, uh, I, I mentioned this in passing, but I didn't define it. So we, we actually have introduced a formal decision making framework and to anyone out there who was like worried about adopting one of these sort of very corporate frameworks, I will tell you it has worked so well.
Uh, we use when I think it was developed by Bain called Rapid, where you have a recommender, agreeers, uh, uh, input, uh, performers, I guess, inform, I always say input, but it's kind of both, uh, perform and decide, uh, and particularly given that we don't have titles, this has been very, very valuable. for us. Uh, so basically any material decision is, you know, uh, you define the rapid.
Um, I was worried about sort of the recursive meta decision of like who, [00:58:00] what's the rapid for defining the rapid, but it turns out no one really cares. They just want to know. That there's like a formal way this is being made. We have a decision log we built and decision isn't real. If it's not in the decision log and discoverable and so on.
And so, um, you know, that's how we've like really worked on decision making. It's actually helped a lot. Um, certain decisions go to certain forums, you know, uh, uh, actually, you know, I make every pricing decision personally, just for like pricing consistency across our entire, uh, product base. Um, so we have just like various.
Defined rules and systems for ML. Um, we have maybe, uh, two formal ways we've made decisions about how to invest. Uh, so one is we actually do run what looks kind of like an internal accelerator. Um, it's a bit of an experiment right now, uh, but we've been doing it for a couple of years, um, or a couple of cycles.
So one year it's called, uh, our experimental projects, um, program. And. This is just a program. It, it evolved from what used to be called our crazy ideas program. Crazy ideas program was just, we sent her on a Google doc to the whole company and you could write stuff you thought we should do in it, and then we'd read it.
Uh, Got a little bit big for that. And so now, um, you can apply to just sort of, you know, be seconded onto your own team or a team working on the thing you're proposing, uh, for a period of starting six months and then you, you can keep going if, if things are going well. And we ran one of those, you know, in particular for ML.
Uh, it's just sort of like, Hey, we want an entire batch of teams just saying, I want to do this with MLA. I want to do this. And some of the, um, ideas or things that would be, you know, sort of, um, maybe obvious, you know, uh, docs AI came out of that. So just more AI driven way to, uh, interface with our docs. Um, there's some cool ones that I shouldn't talk about yet, but they'll be coming out soon.
And then the other was, um, actually centralizing, uh, [01:00:00] some of how we operate, um,
Will: in ML and AI. We
Logan: to have a lot of different nodes in the organization. Um, and that's how we ended up with, you know, over a hundred models and, you know, some of them performing well, but no shared features across them. And we've now created, uh, in what we call our information org, sort of a center of gravity and center of excellence.
We hire researchers onto the team. Uh, we actually gonna be announcing soon some, some pretty cool research. areas that we're undertaking, um, at Stripe, uh, and this sort of core group is responsible for this like sort of foundation model intelligence layer where you have the shared embeddings and shared features across everything we do at Stripe.
Will: As an investor at, uh, Thrive, you obviously made a very, uh, significant and successful investment in Stripe specifically, and then you doubled down on it. What were the things that you looked for in companies or founders or teams? Like, obviously the Stripe investment has proven to be, uh, uh, a good one for, for Thrive and for you at a personal level, but was there specific things that you really sought out? Discount all of this,
Logan: Well, I think you're a B2B SaaS investor, so you can just discount all of this. But I can give you my framework at the time. Yeah. Um, you know, when you're, uh, uh, an investor and. It's true. I guess when you're a capital allocator at a company, you're always trying to reduce dimensionality as much as possible.
Like there's just like a million different considerations and what really matters. Um, and so from a market standpoint for B2B investments, I always just thought about a simple two by two of one axis, universality and the other access, just sort of core versus non core. So does everybody need it or do only a few people need it?
Um, and then, uh, for core versus non core sort of the question is like, do people want the best one or are they okay with just any old one? Um, so I used to be on the board of a company, a great company. We use them at Stripe. It's really [01:02:00] awesome. Uh, called Greenhouse and that investment has gone well for us, um, at Thrive or
Will: for
Logan: former, former us now, now the Thrive guys.
I would, that's a sort of a classic like universal non core. Where everyone needs an applicant tracking system, a way to track the recruiting process. But it's hard to get a lot of pricing power, hard to get really deeply integrated into the company. And you know, it's just not sort of a core consideration for senior leadership.
Stripe to me was just like, you know, the top right of that two by two where it's like, What is more core than your money movement? And maybe you needed to have a sense of the vision for Stripe. It wasn't just accept card payments. It was, Hey, we're going to be commerce infrastructure for the world. And then everyone needs it, right?
I'm just going to move money around.
Will: And the pricing power you have because of the best of breedness being 0. 1 percent better could lead to significant pricing power because for an individual merchant that could be material dollars.
Logan: absolutely. And, and, you know, there's the, the, the sociology of, of, uh, payments procurement is very interesting. Uh, I won't sort of, uh, bore you with that unless you, unless you you're keen to understand it. But, um, you know, with, with larger users, the breadth of what you do for them really matters and they want to see the, the precise, uh, the pricing tied Uh, value in each, each dimension, but yes, um, uh, short, short answers.
Yes. And then for, um,
Will: I
Logan: for entrepreneurs and I guess for leaders in general, it's like a good pattern match on when you find someone who just seems to have more hours in the day than, you know, you can possibly believe, uh, uh, that tends to be. Uh, a good entrepreneur with John and Patrick. I just was struck by how prolific they were.
Um,
Will: Probably reciprocally with you going to law school and Ph. D. and all this. They, they probably were drawn to that on your side.
Logan: failed PhD. But yeah, but, um, yeah, that, that struck me, um, about them. Um, and, and the judgment point, um, that I mentioned as well, [01:04:00] um,
Will: One of your, uh, responsibilities, uh, has been, uh, leading product within Stripe.
Will: I guess I'm curious how, how specific, uh, Stripe's product organized. How do you think about, um, what is the platform versus what are the applications that sit on top or what are the primitives versus, you know, what people get individual decisioning authority over?
Logan: Yeah. And, and, you know, I'll, I'll, I'll sort of give you the, the market texture view and then the institutional organizational view. Uh, cause I really, I really do believe in, in Conway's law. It's, uh, served us very well, uh, to follow it.
Um, so from a market texture standpoint, you know, Stripe started back in 2011, um, accepting card payments in the U S. Uh, uh, evolved a lot, uh, since then, you know, sort of phase two is maybe accepting card payments in other countries and then adding in some local payment method support. You know, in Europe, for example, we expanded to relatively quickly.
Every country has some local scheme that really matters, uh, to, uh, to payments in that country. And if you don't accept that scheme, you lose a lot of transactions. People are just like, Oh, it's only cards. I wanted to pay with ideal in the Netherlands or, you know, swish in Sweden or whatever. So, uh, that was sort of phase two.
Um, phase three, uh, we started dabbling in other ways of like move of money movement. I guess, you know, just pay ins, uh, uh, initially. Uh, but then we had, uh, Shopify, incidentally, sort of asking to white label our pay ins API. This is what sort of has led to the really deep partnership with them. Uh, and around the same time we had a Lyft, you know, we've been working with them on payments.
And I, you know, as, as the story goes, I wasn't at Stripe at the time. Uh, we were in their office and we saw that their finance team was sort of uploading flat files to make payouts to drivers. Um, and we said, Hmm, we can, you know, create. [01:06:00] a better way for them to do that. And so that led to an early version of what we call the payouts API, which is sort of load money into Stripe and send it.
And so this sort of multi party money movement, even though it's sort of two different paradigms, we rolled together into something called Stripe Connect. Uh, and Stripe Connect is been just an enormous driver of Stripe, you know, 13, 000 platforms and marketplaces use it today. Um, and it's, you know, it's a very, very, um, significant driver of, you know, vertical SaaS, you know, on demand economy, things like that.
And so this whole thing, like pay ins, like money storage in the cloud, pay outs, you know, converting currencies in the cloud, is kind of what I would call the core business. Um, we call it like a global payment suite, or sometimes referred to the global payments and treasury network. Uh, just basically saying there's all these different ways to move and store money.
We have one single API, we can handle KYC for you, mitigate fraud, you know, move money in or out of accounts and, you know, send it globally. Uh, and you know, we now support, you know, pay ins across 50 some countries and payouts to over a hundred. Uh, so that's, you know, so the core business, um, that you've probably heard of, um, 2018.
We, uh, uh, create something called Stripe Billing. You, you familiar with billing? Yeah. So billing was originally just this very basic subscriptions API that we shipped, I don't know, way back in 2011, 2012, where you could literally just add a subscription to a customer object in the API and it would just sort of Bill that person on some cadence, some amount, you know, very limited.
You can only have one subscription per customer, you know, was not fit for purpose unless you had the most basic use cases. 2018 we shipped, um, billing, which was just sort of, you know, a small team doubling down on this sort of making a little bit bigger and, uh,
Will: it
Logan: sort of incidentally, uh, I think, you know, B2B SaaS was really booming.
And got like a lot [01:08:00] more pickup than, than we expected. Um, and so this whole area of sort of, you know, becoming your billing system and helping you implement your revenue models, track your customers, you know, um, innovate on your commercial model, uh, has become enormous for us and for our users. Uh, it's now something like 300, 000 users of Stripe billing and actually growing very, very quickly.
Uh, And the sort of adage I have, um, is, and this goes for Stripe as well, everyone has a billing system. Uh, everyone hates their billing system. And it's just one of these things where like, if you've had to work on billing systems, you know, as you hear me talking, you probably feel it viscerally. It's like, you know, your, your, your go to market team says, Hey, we want to, uh, rebundle this in this way, or we actually want to pre bill for this thing or whatever.
And you're like, Oh man, okay, well, we'll give you that in three quarters. And so what we're trying to do is, you know, take that entire team, you know, allow you to repurpose them or at least give them a lot more leverage, um, um, to, to do what they're doing today. And, uh, we sort of rolled this all together with some adjacent services like tax, um, like assessing sales tax, uh, globally, uh, analyzing your revenue, uh, revenue recognition, things like that.
This sort of like area between the CRM and the ERP into what we call revenue and finance automation. Bye. And this is a major, major, uh, sort of bet for us today with, with billing as the core.
Logan: And it's a really fun product space. You know, we sort of stumbled upon it to some extent and sort of can't believe that it's as greenfield as it is.
And digging in, we sort of understand why it's actually really hard. You know, we've had to, um, uh, like re jigger our strategy, you know, several times. Uh, so there'll be a fun announcement on this in the future, but we've now sort of prototyped our own, uh, language that sort of on that will open source at some point [01:10:00] that underwrites all the billing primitives, uh, because we needed to have like, uh, have certain aspects of, uh, static analysis.
We also want it to be pretty simple so that you could. Effectively test changes to your billing system, um, before actually making them. So that's a huge area for us. Um, and you know, there's a, there's a few others as well.
Logan: Um, but these, these sort of two foundational, I guess maybe three foundational orgs core, core payments, the connect org, and then revenue and finance automation.
And they all sit on top of a sort of product platform org. Um, and that org sort of ties it all together. Uh, for Stripe, uh, we used to refer to ourselves as, you know, AWS for money. And I think that was just like a very poor analogy. Uh, and, um, The reason is when you look at sort of, you know, say S3 and Aurora, like, you know, different AWS services, there's no sort of a logical tie between them.
Like how you model data in one versus the other is kind of like your business and how Aurora and AWS work doesn't really need to be, um, they don't need to contemplate each other in any way. Whereas the way that straight billing works, uh, with connect. And with payments is, you know, needs to be, you know, graceful and subtle.
Like if we model Logan as a customer and payments, then how our invoicing API thinks about, you know, a sort of credit balance for you as a customer in a different product line needs to cohere. And so this platform org is very important being sort of the sinews sort of tying it all together.
Will: And so, so are there discrete leaders for each of those functional areas and then the platform underpins it?
Or how does like engineering resources get allocated and like functionally? How does that work?
Logan: Yeah, so each of those are unit organized. Um, Payments. org, uh, Connect, we actually call it Money as a Service, uh, Revenue and Finance Automation, and then we have the platform, also unit [01:12:00] organized, so Product and Engineering, other embedded functions in each of them.
Will: Interesting. And, and is that the way it's been for totality of time? Uh, or like how, how has it evolved?
Logan: So one thing we've done is we have hoisted more, um, technical, uh, unification upwards. So it used to be that you had sort of the classic, you know, Amazon phalanx of, you know, just sort of unit orgs all the way down. Um, that hadn't, didn't work very well for us. Um,
Will: Because of the need for interoperability
Logan: exactly, exactly. Yeah, spot on. Uh, so we've hoisted that upwards.
Uh, so you typically have, you know, one of these very, very, we don't have titles, but you know, Some SVP, EVP level person with a head of engineering, uh, in each of those areas.
Will: And, and, uh, and so then when you're, when you're starting a new project, like you referenced billing was kind of, I don't know, skunk works is a fair term, but in the early days it was kind of a small group that got going similar to the, uh, the connect product sounds like that was smallish in the early days.
How you. How do those things manifest themselves? Like, do you just sort of send some people in the wild and say, have at it and sort of see if there's traction behind it, or is it more top down and telling people to go try these things?
Logan: Yeah, you know, we've, we've had the benefit and, you know, I mentioned this before, like this sort of infinite problem, um, problem domain, um, had the benefit of just vehement
Will: User
Logan: Demands for us to expand into different areas.
Uh, you know, good examples, Stripe tax, you know, just every year we'll Patrick or, you know, someone will tweet out, you know, what do you want us to build next year? And tax was just rising to the top of the list. And so we, um, decided we're going to shoot off a team to go work on that. Um, You have the classic questions of a capital allocation where it, you know, sort of never makes sense from a near term ROI to spend money over there versus shipping the things that your larger users want in the core.
So you have to protect them for a while and so on. But usually we have a [01:14:00] few gates for each of them. Typically they're non speculative bets. They're just sort of like, you know, we need to go execute, um, maybe areas like, uh, You know, when we brought back crypto a couple of years ago, it's a little bit more, uh, uh, at least that time speculative.
Now it feels very non speculative, but yeah, then it was, um,
Will: the, one of the things I heard you say is that companies are, are, uh, often hesitant to force an ROI calculation for early projects. Uh, can, can you elaborate on that point and why thinking about ROI is an important thing in the early days of, of building products?
Logan: I guess my, my more specific push is just that, um, and actually I'll kind of parrot John Collison on this, but we work in an industry where, um, fiscal discipline for the, uh, for the winners. is just not that important. Um, you know, maybe it was very important to Amazon in the early days, but you know, with Meta and Google, you know, soon enough ads money is geysering out of the ground.
And so, um,
Will: you know,
Logan: they're not always the best run companies from the standpoint of just Precision around how many people should be doing this thing. Do we know what they're doing? Uh, what's our observability into the growth there? Um, you know, how can we think about the incremental benefit to investing more?
And then as you grow up as a company, you end up bringing leaders in. from these great companies because of like the survivorship bias of that's where the leaders are. And so, um, this skillset of being really, really, uh, disciplined with your resources and, and thinking about that ROI and self solving just typically, you know, the sort of leader products don't ship with that feature.
And so you want to really.
Will: you know,
Logan: Drive it home.
Will: You made a comment earlier about, uh, titles not having those specific titles.
I guess I'm curious. There's, there's kind of these, there's this Mark [01:16:00] Zuckerberg, uh, view on titles, which is that they're very expensive. And there's this Mark Andreessen view of titles that they're very inexpensive. Um, how do you think about that? Titling, uh, within Stripe and, uh, the cost of giving out titles.
Logan: so I'll caveat this, uh, that I've always had a title with Stripe, so, you know, I'm, I shouldn't be one to talk, but, uh, but we, we get
Will: good, good for me. Not for thee.
Logan: Exactly. Yeah. We, we get various, um, you know, uh, uh, uh, pushes to introduce titles to Stripe. Um, you know, I think that, um, there's a few reasons to do so. Um, and a fusions not to, and I just think about it very pragmatically in terms of like costs and benefits of it.
And to date, just pragmatically, the costs seem to still outweigh or the perspective costs seem to still outweigh the perspective benefits. Um, culturally, I think it's actually quite good not to have them because it just speaks to a pretty flat, um, culture and, you know, just, they introduce just semantically a notion of hierarchy that, um, as I hear it, at least from, uh, people.
from Stripes. Uh, we don't have, and I think it's part of that. Um, you also, uh, end up, you know, in a situation where, um, you know, it's actually not just titles. We don't expose levels internally. So, you know, um, if you were a level six and I were level five at Stripe, uh, you know, officially, I wouldn't know that you were a higher level than I am.
Now I might know, um, because people talk, but the sort of second order sociological effects aren't there The average person doesn't know that you're a six and I'm a five. So maybe I don't care as much. Whereas if you're a senior director and I'm a director, then that's just apparent and everyone knows it.
And it just sort of, um, you know, I think, um, maybe can lead to bad incentives. You know, a lot of times also, you know, the more [01:18:00] senior title is correlated with a larger scope and a bigger org. And we all know You know, there's very bad incentives related to that. Um, on the positive side, you know, we, we've been a big push over the past couple of years on decision making.
And I do think that it's, it gives you a language for decision making. It's like, this is an SVP level decision. This is a directorial decision. So, um, and actually maybe a subtle benefit of not having them is people don't know how to mine your employee base. People try to mine Stripes and Playbase a lot, but, um, uh, yeah, so some of the considerations.
Will: uh, in terms of like org chart design, then, uh, is the org chart exposed internally? And so are people able to. De facto back in two levels of responsibility. Uh, I realize headcount is not a perfect proxy for that, but
Logan: yeah, we've made a big effort to sort of, um, create divergence between, you know, sort of where you are in the org chart and your level. Um, and so you have Uh, you have some people who are line managers, who are some of our most senior engineering leaders. Um, typically they report in pretty high. Um, so, um, you know, you
Will: there's some ways of
Logan: of back into it.
Uh, but yeah, we do expose the org chart, um, and it's very useful. I actually really believe a lot in org design, you know, far more than I used to, but it Maybe it's a, uh, you know, a, um, part and parcel of, of, growing as a company, but, uh, actually it's came up at a, uh, uh, a Q and a for the whole company on Friday around like, what are we doing to make sure we don't ship the org chart?
And, you know, to me, that question is, um, very little, like we're, we're going to ship it. It better be right. Uh, there are certain mechanisms we have to sort of tie things together, as I mentioned, but, um, but yeah, we are, we're actually, we kind of put the org chart front and center, so, you know, how it's structured.
Will: What have you, uh, what have you learned about, like, org [01:20:00] design, I guess, now that you've reflected on, on it? And, uh, are there any, is there a takeaway or, or, uh, any, like, insights that you wished you had known in the early days?
Logan: maybe the, the thing that comes to mind is not any particular time where it was grossly off, but I feel like I've learned that the, um, uh, the sort of incantation that companies reorg too often is probably literally true, but sort of spiritually off. You know, I, I think there's a.
Will: Toyota
Logan: Toyota design principle or whatever they're called. There's one on continuous improvement, and I really think if you are operating in this continuous improvement mindset, and if you're
Will: ambitions
Logan: growing your ambitions and building new things as quickly as, you know, we want to be at Stripe, there's sufficient change that, you know, you're probably not if you're not changing your org chart relatively regularly, you're probably, um, you know, sort of actually destroying productivity.
So you're sort of like always weighing the. Uh, the benefits, um, uh, of, you know, organizational stability against the benefits of sort of really being organized against your new strategy, your new goals and so on. So I typically think about any org change we make as having, you know, a life cycle of 12, maybe 18 months at the outside.
Um, and then there's obviously like pruning you'll do and gardening, you'll do further down the org chart, you know, on an ongoing basis.
Will: Do you guys still do a metric roulette, uh, within product teams?
Logan: Um, no, not formally. Um, not formally. Um,
Will: Maybe explain for people what it was and what were the, why the, the principle behind it or
Logan: Uh, yeah, so we used to do, um, uh, I think this is a, uh, one of my bad ideas.
Uh, we used to get together at [01:22:00] our, um, sort of leadership team meeting. And this was a 30 person meeting. Um, uh, I think it was every other week. And, uh, we had a little script that would just choose, uh, a team and a leaf node team, like a line managed team. Uh, and it would choose them the day before. Um, and he was just using a, you know, Whatever, some, you know, Unix rand command or something like that to, um, generate a random number.
So every now and then a team would get picked like, you know, twice in four weeks, which was, uh, they did not love. Um, and they'd come in and just, you know, present their metrics of like, you know, here are the four metrics that we run. Our, um, our team on, and here's how we measure success. Here's our targets.
Here's where we are against them. Um, and so on. And so in theory, it was a good mechanism, uh, because, uh, you know, you would know that it could be you on any given day and sort of encourage you to really be on top of your metrics. It's like three things that, um, I think were problems with it. So one is, you know, this sort of, you know, panopticon design of like, you know, you can't tell whether or not we're staring at you.
So you better be on your best behavior. Uh, just, I felt, felt a little culturally off, um, felt a little infantilizing I think to people at times. Uh, two is that, um, uh, you know, we actually sort of were looking at metrics kind of at the wrong level in terms of like the, The leadership team to leaf node teams and what you actually really wanted to happen was your reports or their reports sort of ensuring that they have the right WBRs.
And, you know, those may be cascaded down, um, uh, uh, weekly business reviews. Yeah. Yeah. Yeah. Uh, we did business reviews. Um, and so, you know, you would end up having this sort of, you know, uh, junior team to central leadership team conversation that just, you know, I think kind of disempowered leaders and, um, and didn't really, Um, so have the right types of conversations.
Uh, [01:24:00] and, and then the third one was just, you know, 10 minutes to do that. Um, and it's a team that, you know, you don't have like deep expertise working with, you actually just couldn't give her a very good feedback. Um, and so, uh, yeah, we did that for, for a year. Um, An actual, a different mechanism, um, and one that I think is actually working quite well.
Logan: Um, so are you familiar with a guy named Alan Mullally? So Alan, um, is a leader I find very inspiring. So he was, um, uh, CEO of Boeing, uh, the, um, uh, one of their divisions. I think they're sort of like, um, aeronautics division or I can't remember what the exact name was, but long time Boeing executive. And then he became the CEO of Ford, uh, I think in 2008.
Or something like that. Um, and you know, at this point Ford was, you know, teetering on the brink of bankruptcy already, uh, huge problems with unions. Uh, it was sort of the, the, the laggard of the big three at the time. Uh, I think the stock price in his early tenure dipped down to like one or two bucks a share.
Uh, and by the time he left Boeing, which was, oh, sorry, uh, Ford, which was seven or eight years later, stock price was in the high teens. You know, I think it, Peaked around 24 later. Uh, he had something like a 99 percent approval rate with the, uh, union members, which was crazy. And they were the only one of the three, uh, major car companies that took zero federal money.
Um, so pretty, just incredible guy. And I read this story and I was like, man, I got to figure out how the hell this guy did this. Um, and so he has like a system. Um, he calls it the working together system. And, you know, it sort of, You know, just like with Toyota, other great companies just stolen little, little parts of it.
But one thing we do now, which, you know, I'm just raising him because I have to credit him with some of it is every other Thursday, uh, the top, you know, 80 or [01:26:00] so leaders get together and we run a meeting called the run the business review. Uh, and it's a two hour meeting. Uh, so one hour a week that you're dedicating to this and we go through every single budgetary line item and everyone has a set of initials.
It's the owner, uh, and every single company, OKR, we have about 82 of them and everyone red, yellow, green. Uh, uh, you know, if you are green, you can actually skip it. Get commentary if you want to. Uh, yellow, um, means you have a plan to get back on track, but you're not on track. And we talked about that plan.
Red, uh, means you're off track with no plan. Um, and so we do this together every other Thursday. Um, we do a QBR once a quarter too. Uh, and, uh, what I found is this meeting is sort of the right level for collaboration, uh, among leaders. Um, if you're red for three weeks in a row. We jump out to what we call special attention meeting where the right subgroup gets together to talk about how are we making a plan to get back on track.
And, um, I always find like organizational design mechanisms, like if they're good, they'll be fractal. Like you'll find that, Oh, if this thing is working, I'll start to see it happen down below in various places. And this is actually turned into sort of an operating model for the whole company. Where, you know, the leaders will have their own RTBRs that sort of happen, you know, two or three days before and everything sort of rolls all the way up to this meeting.
So I found this has been much more empowering of leaders, uh, maybe a little less scary for, for, for line managers and, and, uh, yeah, it's been working well for two years.
Will: How many, uh, how many like metrics or things are on that, uh, that graph or actually
Logan: budgetary items that actually have targets is probably about 30. Then we have 82 company KRs.
Um, you know, there's whatever hundreds or thousands of, of KRs that teams track, but there's 82, uh, track centrally. We also have a top 10 among those and 82 seems a lot like a lot, but [01:28:00] it actually works out to be about one per 120 employees. And if you're 120 person company, presumably you'd have more than one.
So, Oh, it seems like a good number. Yeah,
Will: Uh, if you were still doing, uh, venture today, do you think you would have gravitated to doing AI? Like, would that be where you, where you're spending your time or do you think you'd be off doing something totally different?
Logan: I mean, I think you have to be, right? It's, it's just, uh, setting aside whether the current crop of companies are going to be wildly profitable or wildly unprofitable. There's all this sort of, you know, um, uh, obvious jibes at, at inference costs and, and so on. Um, just a lot of things are going to change.
You can just tell. Uh, and so I think whenever the world is on the precipice of changing as much as it is, I think you, you can't ignore it. Yeah. Yeah.
Will: Um, you've worked now with John and Patrick for nine years and I think people hold them in, uh, well, I guess before you made the investment, what, a year before that or two years before that?
A year before. So, so, so 10 years now, uh, nine years as an employee.
Logan: um,
Will: What's something that people don't appreciate or maybe is less appreciated about, um, about those two, either of them, I guess, if you want to call it out separately, although they tend to get grouped together, uh, um, that, uh, you know, that, that maybe people don't appreciate, uh, that aren't working as close to
Logan: Yeah. I mean, there's so much to appreciate. I mean, obviously they're extremely intelligent. I think, um, Uh, maybe it doesn't get talked about that much, but extremely tasteful, like just one of the core, core things that, uh, make Stripe Stripe is, is a sort of level of taste that's hard to teach, but the two that, you know, sort of struck me when I was first getting to know them that have really been borne out over the years is.
One, they're very kind. They're kind, humble people. And I think that keeps people at stripe. [01:30:00] You know, you're just, you're just not working for jerks. And, um, uh, and so we've had a lot of our just senior, most leaders have been around for a long time. Um, and they're very wise. You have great judgment. You're sometimes you just, you know, At least I do.
I think, have you guys seen this before and you're just not telling me? And I think that's probably correlated with them being very curious and just having a lot of conversations who have seen it before with people who have seen it before. But that's what jumps out.
Will: Yeah. Interesting. Um, are there, uh, you mentioned reading Studying, uh, uh, Toyota and studying some of the stuff related to, to Boeing and Ford's turnaround.
Are there, are there other leaders that you've looked up to or been influenced by, uh, outside of, outside of Stripe, like just people in particular that you admire have taken principles from?
Logan: Well, one I know you talked to is, uh, was Claire, Claire Hughes Johnson. And, uh, Uh, Stripe would not be Stripe, uh, without her. And I sort of consider her in many ways to be, uh, perhaps my only like personal mentor . And, uh,
Will: was COO for,
Logan: she was COO. Uh, she started a year before me 20, 20 14. I think she was there until 2020 at some point.
Yeah. Um, and, uh, I think just her understanding of organizations and people and how they work, um, her intuition around, you know, what's really going on and why. You know, something's not working, um, was, was, um, uh, just really, uh, amazing. I encourage anyone to, to, to read her book, um, uh, scaling people, I guess it's called.
Um, so definitely her, um, Marianne Lake, uh, who's now runs Chase, but who was at, uh, uh, JP Morgan, um, Uh, it was a really good, um, uh, sort of mentor in my early days as a CFO. Um, and, uh, just seeing, um, the rigor that she used to run, um, JPM. Yeah, she's sort of bouncing [01:32:00] between talking to regulators and doing capital allocation, doing product reviews.
Um, so, you know, she, she comes to mind, um, trying to think of other leaders I've spent a bunch of time reading about, oh, a good one, actually. Um, Frank Slootman.
Will: Yeah.
Logan: He impresses me so much. Um, and there's just clearly a formula, right? And it works. Um, one of the things he says that I just, I like to repeat a lot internally, particularly being, uh, you know, someone who has sort of grown up on the product and engineering side is, um, uh, that sales is reality.
Will: reality.
Logan: Um, you know, he, he proudly calls his companies sales led companies. Um, and I think in my early days as CFO and CPO, I just spent a lot of my time on all the cool stuff we could do. And then you go sit in the room with the customer and what they want to talk about is completely different. Uh, and the reality of whether or not your product is what they want it to be is right there in the room.
You're talking to them about, will you pay more for this thing? Will you buy this thing? Will you move off of, uh, of XYZ to us? And so I think his approach to being very sales led leads to a customer eccentricity that I really like.
Will: Hmm. Are there any, um, unpopular, uh, opinions that you hold or anything within? Um. They get espoused as Silicon Valley truisms that you, uh, you find to be untrue.
Will: seeds
Logan: I don't know if this is a unpopular opinion or not, but I feel like VCs get a hard time and, you know, take all the politics out of it. You know, just, just, you know, the venture industry, uh, sometimes gets, uh. You know, people talk about how the venture is dead and, you know, it's just a reverse auction now in terms of pricing and no one has pricing power and blah, blah, blah, and so on.
Um, and that everybody knows the hot deals and there's like romantic notion of, you know, how Oracle was discovered by being in the same office park as Sequoia or something. I can't remember exactly what it was, but Larry Ellison was, was, uh, was, was working nearby [01:34:00] and that's how,
Will: how,
Logan: um, Oracle got funded. Um, you know, you look at a place like.
China, uh, where you had this venture boom, I think 2018, you had 50, 000 startups backed or something like that. Uh, I think this year it'll be maybe below 1000, right? It's literally gone down by 98, uh, plus percent. And so, you know, just the. culture of being enthusiastic to back entrepreneurs, uh, I would rather have a system where companies are systematically overvalued rather than undervalued.
And so I feel like there's sometimes this notion of, you know, the persnickety longtime VC saying, Oh, valuations these days. And I actually remember, um, saying the same thing in like 2013, right? When valuations were a fraction of what they are today. And so I just, you know, I think the venture industry, uh, is one of the most core engines of growth for the U S uh, for, for the world.
Um, so maybe it's a, uh, uncommon view, maybe not unpopular.
Will: I mean, I think, I, I agree wholehearted with you. I, I remember there was a very prominent, uh, V.
C. that, that, uh, publicly retired on Twitter. This is now three or four years ago. And the person said, like, valuations are just too out of hand and, uh, I'm, I'm stepping away. It's just not enjoyable anymore. And it was funny if you deconstructed the investments they made implicitly. This person probably made 500 million personally
Logan: yeah,
Will: off of.
low valuations. And I was like, of all the times you should be investing and maybe they were even right with the time. But I was, I was like, you, you, you, in some ways you could say, like, took advantage of entrepreneurs at lower valuations back [01:36:00] then. It's almost like you owe a service
Logan: to
Will: continue playing it through, not taking your ball and going home.
Uh, especially since I think it was the person's personal capital with it. Yeah. I think there's been this meme, uh, that I think was largely true. 10 plus years ago that probably
Logan: some
Will: percentage of VCs were a little tone deaf and, uh, and, and the, the founders came to them and they were masters of the universe because they had access to the purse strings of capital.
And. I think that that whatever that ratio is, is a far smaller percentage than it is today of people just waking up and trying to do their best and best in founders. And it's certainly a lucrative business, uh, if done, if done well. And so no one should feel particularly bad for any venture capitalists out there.
You don't, you don't need to start a hug your venture capitalist campaign or anything, but I, yeah, it does feel like it's, uh, The meme is kind of outs stripped to the reality at this point, uh, which I think is a good thing. I don't know. All the jokes led to self-awareness, uh, which I think, you know, or cancellations this case may
Logan: Yes. Exactly. And that, and that's true in any, in any industry for sure.
Um, and so it's not a, a sort of, like you say, uh, a blanket hug for every venture capitalist, but I just think that we sometimes deride the industry when in fact, I really think it is something that makes, uh, makes the world great in many ways. Um, just, yeah, I remember, uh, Probably 2010 or 2011. You know, one of the VCs I look up to the most Jeremy Levine, I'm sure you, you know, from, from Bessemer.
Will: Did a podcast with him.
Logan: Oh, nice. I mean, I should, I should listen to that one. He's, he's, uh, probably
Will: He's
Logan: saying much more interesting stuff than I am, but he, um, uh, I think we were at Balthazar just up the street and, uh, I remember him talking about Toby, uh, from, from Shopify.
Will: just
Logan: about how, you know, he had this founder who every board meeting just surprised him in a new way.
Um, [01:38:00] and this would have been around the time that Tobii was, you know, getting started with Shopify payments and plugging payment systems into Shopify. And Shopify went public, you know, I don't know, maybe a few years later at a valuation of, 1 point something billion, maybe lower.
Will: was either one, one or 900. It was something
Logan: something like that.
Right. Uh, and now it's a, you know, whatever, a hundred billion dollar
Will: it's amazing.
Logan: so, you know, to that end valuations needed to rise.
Will: Yeah, yeah, for sure. For sure.
Will: What, um, I guess as, as we wrap, uh, what keeps you motivated?
Logan: Well, for one, it's still fun. Uh, and that's the most important thing. Just, you know, does it get you, get you out of bed every day? Uh, I think a lot of people, um, who I've talked to in my career, you know, predicted I would have, uh, founded a company by now, but I, I love what I'm doing at Stripe and, you know, there's just always something new.
Um, back in 2020, uh, we were about a year and a half into Stripe billing, but it was still a bit of a, You know, a toy project with a handful of people on the side. And, uh, we were talking to Atlassian, uh, and, you know, Atlassian, uh, amazing company, uh, you know, coupled together, uh, in some ways via a bunch of acquisitions, almost like a holding company for a bunch of different SaaS services, doing an amazing job of like.
Cross sell, cross subsidy, and so on. As you can imagine, their commerce system was, was tricky because they're billing for Bitbucket in this way, and Jira in this way, and Confluence in this way. And we thought to ourselves, like, what better way to test, uh, uh, you know, billing and its future applicability than to take them on as a customer.
And so, you know, if I just think about the evolution from that moment in 2024, To today, you know, working with, you know, RSIs and GSIs on selling, you know, uh, the billing integrations to hundreds of thousands. Of merchants. It's a [01:40:00] fun, it's a fun four years. And I just see many more in the future for Stripe.
Um, I think people talk a lot about AI as a disrupt, disrupting technology. They also talk about it a lot as a sustaining technology. Uh, as you noted a little while ago, we have some of those interesting data in the world. And I think there's a lot of ways we can leverage that data to advance the mission of growing the GDP of the internet, uh, capital, for example.
Uh, Stripe capital is, we're finding, um. Just that, uh,
Will: when
Logan: when you can get a small business alone, uh, it actually, uh, helps them grow and grow sustainably, which is sort of amazing. So Stripe Connect, uh, as I mentioned, uh, is our product for a complex money movement for marketplaces and platforms. One place we're seeing just really amazing growth is our connect users selling, well, not selling, providing loans to their users via our sort of programmatic capital API.
And so I'm really excited to see what, uh, you know, what, uh, L well, what foundation models. And I guess LLMs is more of a, you know, everyone thinks of chatbots. It actually is really just about autoregressive transformers, but what, what. What they can do for underwriting and can we, you know, 10 X the applicability of credit.
Uh, so I just find, you know, there's a lot more fun to be had and, uh, looking forward to, uh, to, you know, the next, next 10
Will: Yeah. Well, good. Well, thanks for, thanks for doing this. We did a full podcast. There's no question of when you guys are going public, so
Logan: Appreciate that.
Will: Yeah.
Logan: Thanks.
Will: Thank you for joining this episode of the Logan Bartlett Show with President of Stripe, Will Gabryk. If you enjoyed this conversation, we'd really appreciate it if you pressed subscribe on whatever podcast platform you're listening to us on, as well as share with anyone else that you think might find it interesting.
We look forward to seeing you back here with another great [01:42:00] guest on the Logan Bartlett Show next week. Have a great weekend, everyone.