The Exchanges

Q Uh, what, what'd you do? How, what was your invention or experiment or submission that won you young scientists of Ireland?

A Well, as we sort of touched on, I'd gotten really into programming, and in particular, I'd become interested in this programming language called Lisp, and I was kind of fascinated by Lisp because it had been invented in the late fifties, like really early in sort of the history of technology, but it had been kind of forgotten and ignored. The thing I worked on was sort of a new version of Lisp, trying to kind of update it, making it really straightforward to build sort of complicated web applications and things like that. And, you know, it's funny, it's only kind of looking back on it that this sort of becomes clear. I mean, from a very early stage, I was interested in sort of working on tools or just kind of building things that created leverage for others, and that basically the whole point of working on this programming language was to provide a tool that would make it easier for others to build things. And so I, you know, I didn't consciously think about it this way at the time, either kind of when starting Stripe or whatever, but basically all the things that I've worked on kind of Somewhat seriously have in some ways been kind of tools for creation.

AI assessment note: “The thing I worked on was sort of a new version of Lisp”

Q So, okay, so Here's what I don't get. You guys were obviously super smart and very good at coding. But what made you think that you could solve these big, enormous problems, like regulation and dealing with banks and developing relationships and credit card companies that, you know, Google and Apple clearly felt that they could not resolve?

A In large part, a healthy dose of the naivete of youth. Um, but, uh, you know, we didn't just leap into it. Uh, we built the first prototype back in October of, and then we basically spent kind of eight or 10 months trying to sort of map out what would actually be required to have this work at sort of, you know, any material scale, what sorts of people we'd have to hire, which sorts of entities we'd have to partner with, and, you know, what that would look like. And so we realized, well, we need to hire, you know, very senior and experienced partnerships people to make sure that we can get sort of first-tier relationships in place with banks. And it really was apparent to us that kind of wouldn't be easy. Like, it was not going to be possible for it to be some sort of, well, you know, we code furiously for two months, we launch this thing, and then it's off to the races. Like, from when we started working on it full-time to when we publicly launched was almost two years. That's how long it took us to kind of Orchestrate all those details that, sort of, you're describing. But I guess, yeah, what we got a sense for, sort of, after, again, this kind of investigation was, yeah, gonna be hard, but it is actually possible.

AI assessment note: “In large part, a healthy dose of the naivete of youth.”

Q you had already started and sold a business, and a lot of investors love that. They love to see that experience. Um, but did they ask you, were you asked tough questions by potential investors? Like, for example, you know, you guys are really young. How are you gonna manage people? Or, um, you don't have any connections or involvement in the financial industry? Did you get questions like that?

A Surprisingly, no. Uh, I think people are used to that in Silicon Valley. I mean, by the time people become famous, uh, because, because the thing they worked on succeeded, they tend to be older. But that means the mental image we have Uh, of people who do successful things is like 10 to 20 years, maybe even more, older than the ages at which they tend to have actually done them, right? And, uh, VCs and investors and just people in general in Silicon Valley, I think, are sort of unusually sort of attuned to this fact and recognize and realize that sort of, hey, really significant work not only can be done by people in their twenties, but is very commonly done by people in their twenties. Uh, and so, you know, I think that's kind of to their Great credit, and you know, we really benefited from it. Uh, the, you know, the thing that has, I mean, this is not to suggest that sort of investors, you know, rushed with enthusiasm to invest in Stripe. Most investors said no, but the reason was much more, or reasons were much more because they just thought it was a bad idea, uh, rather than the kind of, uh, bad people to execute it. Well, You know, a whole host of reasons. It was going to be a developer-oriented service rather than going and sort of, um, uh, trying to, you know, run this big kind of expensive sales and marketing campaign.

AI assessment note: “Surprisingly, no. Uh, I think people are used to that in Silicon Valley.”

Q guys know that this was huge? I mean, you know, it was going from this idea that you have in Cambridge, Massachusetts, to raising two million, to- Being valued at 20, and then a hundred, and then a billion, and then today, uh, more, almost ten billion. When did you, did you ever have a moment where the two of you sat back and said, wow, look what we built?

A There's never really been time for that. Um, and there's nothing like a young company to every morning remind you that there's so much left to be done, so much that's not yet working the way it should be, I mean, it's really quite visceral. You wake up in the morning, and there are 20 emails in your inbox that are sort of somehow all related to things that you're doing badly or wrongly. There's never a moment when it feels successful. And there's a quote that I kind of often think about from Greg LeMond saying, of course, the cyclist, um, it never gets easier, you just go faster. And I used to kind of Cycle quite a bit, and there's a lot of sort of, uh, you know, painful truth to that, where as you cycle more, as you practice more, as you get fitter, as you get faster, as your form gets better, sure, you start cycling faster, your times get better, but the experience of being on the bike never gets easier. The pain that you feel on the first bike ride, that's the same pain that you're going to feel on your 500th bike ride. You'll just be going much faster on the 500th bike ride. And it kind of feels like that in the startup, where every day now, the problems and challenges are, and, you know, visceral pain is just as acute as when we were starting out. The problem is just of a different form. It's, it's this kind of Relentless process of trying to shift what it is that exists a…

AI assessment note: “There's never really been time for that.”

Q Did anybody try to stop you or make life difficult for you, banks or regulators? Because you're dealing with intricate financial regulations, and I mean, and big banks presumably have a big interest in this. This could be a revenue stream for them. Like, Did, were there people who tried to, or was it just, once you started, you just, the momentum was, the wind was behind you?

A Well, in this department, we really tried, tried to approach things differently to, I think, how technology companies often tend to. Uh, technology companies, I think, often have a sort of go it alone mentality. We'll build it all in-house. We'll do it all ourselves. We can do things better than ever in the outside world. Whereas we thought that Stripe would only be possible, and it would only be possible to do it well. If we partnered closely with people who had deep expertise and experience in industries that we ourselves were less familiar with. And so from the very beginning, even before we launched, we partnered closely with banks, and now we work with banks in, you know, many different countries. And not just banks, but sort of other financial institutions besides. But we really wanted to build Stripe as sort of a, you know, multi-decade thing.

AI assessment note: “we partnered closely with banks, and now we work with banks”

Q I mean, I mean, essentially, your competitive advantage was Was you guys?

A I think it's, um, an amorphous combination for any of these products, and I don't mean to single stripe out, for any great product, some amorphous combination of sort of the ethos and the culture and the people and sort of the work style and kind of a fingertip sense for the priorities and all these things that are just like very hard to copy. I mean, it's, There's sort of a continuum, uh, where at one end, you know, you're, um, you're manufacturing steel, and at the other end, you're, you know, you're manufacturing novels. And in steel manufacturing, sure, you can turn capital into more, better, cheaper steel, and at the other end, it's very hard to know how you, how you turn the money into kind of better writing. And software is, is somewhere in between. And I think this is kind of constantly the challenge of For people looking to analyze and make predictions in the industry, where again, Google should have beaten Facebook.

AI assessment note: “some amorphous combination of sort of the ethos and the culture and the people”