00:32:54 · Brian Armstrong, Molly O'Shea
[00:32:54] S0: Yeah. So I think that the average team size will be smaller, but that just means companies can do more things. And so I don't actually, I'm in the camp of people who don't think AI is going to actually cause high unemployment. I I think that employment will be about the same. I think that work will be optional in some sense, in the longer term. I think most people will actually choose to work on something. It just might feel a little bit different. Right now, you're a podcaster, and I'm a CEO going and talking to people on stage. Like, a hundred years ago, this would not have been considered real work. Know? Like, real work is like digging a ditch in a field with like, most of the people in The US economy were working in agriculture with very manual labor, like a hundred years ago, and we don't have to do that anymore. So this is what we call work. I think that in the future, people are still gonna work on all kinds of things, but it may not be what we would consider work. AI is gonna eliminate tasks and toil. It's not gonna eliminate jobs, in my view. By the way, you reminded me of something else on your prior question about how we're shaping Coinbase. One of the next big things we're reaching for to get in place is is recursive self improvement. Right? [00:34:05] S1: So
00:34:05 · Molly O'Shea, Brian Armstrong
[00:34:05] S1: So [00:34:06] S0: we're actually using our apps to collect feedback from customers, whether that's bugs bugs they're encountering or even new feature requests. And we're using AI to aggregate all of this input from customers. And then the next set of agents actually take those priorities. They go plan it out. They draft the code and the pull requests. And then a human being can literally just sit there every day and say, okay, here's like the 100 things that we heard from customers. AI went and implemented them. You a can code review and say approve, approve, approve, approve. And like a 101 person is just reviewing a 100 changes that improvements that went out. And the next day the AI collects another set of 10,000 pieces of input from customers. So the closer we can get to this self recursive self improvement loop, I think we're gonna see really dramatic gains. [00:34:56] S1: Are you having fun with all of this?
00:34:56 · Molly O'Shea, Brian Armstrong
[00:34:56] S1: Are you having fun with all of this? [00:34:58] S0: Oh yeah. Mean, AI is making everything exciting right now. I think we're living in a golden age and, you know, it's part of the really exciting thing is we get to go build the financial infrastructure for this agentic economy. Most people, I think, today think of AI as like, oh, I just talk to one agent at a time, and maybe I ask it a question about my investment account or something. But in the future, you're increasingly gonna talk to one agent. That agent is gonna orchestrate hundreds of thousands of other agents. It's gonna pay for goods and services with companies that it needs to engage with to get work done on your behalf. And so, we need a new financial infrastructure for that. That can do very small amounts, very frequent amounts, where every AI agent can actually have its own financial account that doesn't have to go through a typical AI agents don't have a piece of government issued paper with their identity, and they can't fill out a CAPTCHA and all these things, so they're gonna need a new way to pay and have a financial account, and that's what we've built at Coinbase. [00:36:03] S1: How are you staying on top of everything? Max Levchin said that he's reading research papers. I interviewed Sebastian from Klarna. He's vibe coding and going on demos most of the time. How are you staying on track of everything on top of all the regulatory hot takes for crypto?
00:36:23 · Brian Armstrong
[00:36:23] S0: Yeah. Well, I mean, I have started writing some code again using AI agents. I test out the tools every few months, make sure I can ship a few pull requests and, like, still get in get in the weeds. But the other thing that I'm doing is I'm really just taking we have some of the best tech talent in the world, and some of these folks are I just go around and talk to all different teams. Some of them are creating a brain for their team where all the context of that team is getting updated continuously. So every time, like, a new lesson appears, whether from an AB test or customer feedback or an incident happens or anything like that, it's like the collective knowledge of that team just keeps getting updated in the brain of that team, right, in GitHub. Usually these are in markdown files. And we're gonna start to do that on more and more teams, and eventually you're gonna have be the intelligence of the whole company coming together, like the aggregate of all of these different team pieces of knowledge. Right? And that's what allows the AI agents to get smarter when they go build the next feature. And you have to it's like a shift in mindset where, you know, let's say that it creates a draft pull request for some new feature, and it's not quite perfect. Your instinct typically would be to go in there and actually edit the pull request to make it better. But what you wanna do is actually update the context, the brain that generated it, and say, okay, when you one of these, do it in this slightly different way. Don't forget about this. This is important, and have it rerun itself and generate a brand new one, and only when it one shots it perfectly, then do you ship it, because now you've encoded the thing that it missed in the brain for all future teammates and all future pull requests, and so it's a slight shift in how teams need to think about building the recursive self improvement of that brain over time, and not just editing the work of the AI itself.
00:38:19 · Molly O'Shea, Brian Armstrong
[00:38:19] S1: So I was just in Paris, I was visiting Alex from Deal. He says he loves you, and that you're a great customer. [00:38:26] S0: Yeah. [00:38:27] S1: But he was really curious how you split roles with Emily. [00:38:31] S0: Well, Emily Choi, yeah, she's the president COO at Coinbase for anybody who doesn't know. And I'd say she and I are a really great compliment because, a lot of value gets created in companies, I think, when you have founder energy and a really strong operator. If you have only founder energy, sometimes it's a little erratic and things go wrong. If you have only operators, I think you can have a very well run company, but it might be more incremental or not have as much innovation, and Emily and I, honestly, we can each do both, but we like to play to our strengths, and so, yeah, we really had kind of like a second founding moment with Coinbase, because Coinbase got co founded with Fred Ursson, who's still on the board, and he's hugely responsible for the early success of Coinbase. And we had a second founding moment, I think, with Emily, and that's what's allowed Coinbase to generate a ton of value. She's also just like a talent magnet. I mean, she's really great at just recruiting the best people in the world to all kinds of different functions we have. [00:39:26] S1: She seems like a total badass. [00:39:28] S0: She is. [00:39:29] S1: She seems pretty cool. [00:39:30] S0: Yeah, I think she's the best operator in the industry.
00:39:30 · Brian Armstrong, Molly O'Shea
[00:39:30] S0: Yeah, I think she's the best operator in the industry. [00:39:33] S1: We also just saw Kat. And so like how, okay, this is a fair question on the whole AI lens of things. AI has like a horrible brand right now. People are very pessimistic against it. You built a company in a highly regulated speculative environment, but have made it legitimate and trusted and cool. And like, by the way, your marketing still crushes. Like, I think I tweeted this out months ago because you guys did the Super Bowl ad, which was super fun, and then you did the earnings calls, which had, like, the subway racer kind of things, which were really fun. So how would you take what AI is is kind of branded as today, and, what would you change about that and the storytelling around it?