Inside the Fastest-Growing Category in AI: Scott Wu, CEO of $26B Cognition

Scott Wu, CEO & Co-Founder of Cognition, joins Sourcery in Paris amid the RAISE AI Summit. Cognition is the applied AI lab behind Devin, the autonomous AI software engineer, and Devin Desktop, formerly Windsurf. The company has raised more than $2.5 billion, including a $1 billion round in May 2026 at a $26 billion valuation, while growing annualized revenue from roughly $37 million to $492 million in a year. Devin now writes roughly 95% of Cognition's own code, total code shipped has grown 7x in six months, and customer usage has increased 11x to 12x. We cover Cognition's acquisition of Windsurf, negotiated over a single weekend after Google's $2.4 billion talent deal, why Scott is keeping Cognition independent, why enterprises won't buy coding agents directly from the model labs, AI's impact on software engineering, the six-month singularity debate, and the origin story of Devin, from fixing a MongoDB error in 2023 to deployments at Goldman Sachs, Mercedes-Benz, Citi, Dell, Santander, NASA, the U. S. Navy, and the U. S. Army. Recorded July 7, 2026, ahead of Cognition shipping SWE-1.7 on July 8 and acquiring The Interaction Company (maker of Poke) on July 23. Scott Wu: https://x.com/ScottWu46 Molly O’Shea: https://x.com/MollySOShea Sourcery: ⁠https://x.com/sourceryy 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊 YouTube: https://youtu.be/y1XxtvYll4s 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 • Brex https://brex.com/sourcery—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. https://brex.com/sourcery • MongoDB https://mongodb.com/ai–Millions of developers and more than 65,200+ customers across industries, including ~75% of the Fortune 100, rely on MongoDB for their most important applications. With integrated capabilities for operational data, search, real-time analytics, & AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, & simplify complex architectures. https://mongodb.com/ai • AssemblyAI http://assemblyai.com/sourcery–Millions of developers use AssemblyAI to power their voice ai applications and features. One API gives you access to best-in-class speech-to-text, voice agent, and speech understanding models for both pre-recorded and real-time audio. Granola, ClickUp & HeyGen are scaling with AssemblyAI - get $50 of free credits today at http://AssemblyAI.com/sourcery http://assemblyai.com/sourcery 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Scott Wu, Co-Founder & CEO at Cognition (01:00) The Identity crisis of building Devin (01:42) How Cognition 7X-ed its output in 6 months (02:55) The Metric every AI company gets wrong (04:18) Cognition's 12x growth curve (07:46) The Windsurf acquisition (13:26) Scaling overnight: Cognition's hardest week (15:11) The strategy behind the integration of Cognition products (17:23) Cognition's merger playbook (20:01) Why the DMV is Cognition's next big target (22:59) Why Cognition bet against AI centralization (25:09) Why enterprises refuse to bet on a single AI lab (28:32) Scott's honest take on Superintelligence (32:36) Is Silicon Valley losing its mind over the AI gold rush? (33:26) Devin's origin story (37:17) The question Scott thinks nobody's asking yet (39:59) The poker match that almost closed a deal (41:24) Scott's vision for the next year

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Cognition has raised over a billion dollars.

• 0:02Speaker 01

  First AI software engineer, Devin.

• 0:05Speaker 02

  Microsoft and Cognition.

• 0:06Speaker 03

  Cognition and Mercedes-Benz.

• 0:08Molly O'Shea?

  Goldman Sachs, Mercedes-Benz, Citi, Dell, Santander, NASA, the US Navy and the US Army. We've raised over 2.5 billion to date at a last valuation of 26 billion. In less than three years, you got to 500 million in revenue. That's crazy. Half a billion in revenue in less than three years.

• 0:25Speaker 01

  Our customers in the last six months or so have also grown their usage in the range of like 11 to 12x. Once you've solved AGI, you just take over the entire world. And then there's just one entity that rules the world. I just don't think that's the right future, Brad. There is nothing that humans do that AIs can't do. Maybe you can just have like an AI engineer buddy that can just do work for you. But that was like the very first moment that we believed it was possible. I think the abundance era is real and I think we'll be like this soon.

• 1:00Molly O'Shea?

  Devin, welcome to Sorcery.

• 1:02Speaker 01

  Yeah.

• 1:04Speaker 01

  Great to be here.

• 1:05Molly O'Shea?

  Do you get that a lot?

• 1:08Speaker 01

  Yeah, yeah, yeah. Like I'll be in the elevator in my like building and like I'll just come down and be like, are you Devin? And then, you know, like, well, I'm actually, I'm actually not Devin, but yes, I understand what you're asking me.

• 1:24Molly O'Shea?

  Oh, gosh, damn. Well, Scott, welcome to Sorcery. We are in Paris, which is pretty cool. We're here for the Raze Summit. It's like this huge AI summit. I think this is like their second or their third year. You're going to be on stage?

• 1:39Speaker 01

  Yeah, I'll be on stage tomorrow. I just landed an hour ago and came straight here.

• 1:42Molly O'Shea?

  Well, it's awesome to have you on. I'm excited to talk through the state of cognition and autonomous coding agents today. It's very pressing. Did you know that?

• 1:53Speaker 01

  I did, actually, yeah. I mean, it's, I can't even keep up with it at this point. So, no, things, things have been going like crazy. I mean, even for us internally, like one of the craziest things is, obviously, we use a ton of Devin to build Devin. In fact, we almost exclusively use Devin to build Devin at this point. Like 95% of the code or something is written by Devin.

• 2:12Molly O'Shea?

  Really?

• 2:12Speaker 01

  But the crazy thing is even in the last six months, you know, if you ask people, oh, like AI coding, yeah, it's been going on for, you know, three, four years now, which is true, it has been. But even in the last six months, I think the number for us was like, our total amount of code shipped is roughly 7x in that time. And so it's like the number of PRs we've shipped, the amount of code. And obviously, literal output, you know, like there's different ways in terms of how you actually measure the productivity that you get out of it. But I think in practice, like, we're just able to do so much more and get so much more leverage in even this, this period of time. Like the models just keep getting better. I think there's more and more that's been kind of fleshed out, I would say, with the product experience. And so, yeah, no, things are, things are flying. It's crazy.

• 2:55Molly O'Shea?

  So how do you measure the productivity of it?

• 2:57Speaker 01

  Yeah, it's a great question.

• 3:00Speaker 01

  So a couple of things I'd say on this, first of all, I think, obviously, literal token is just not the right answer.

• 3:06Molly O'Shea?

  Really?

• 3:07Speaker 01

  I mean, lots of people talk about the, you know, I think the token, you know, I kind of, I say the token max in the era, you know, lasted from January to May of 2026, roughly.

• 3:17Molly O'Shea?

  R I P.

• 3:17Speaker 01

  Yeah, R I P, you know, it was a fun time. But, but no, I mean, I think we were now at this point where obviously, you know, what you care about is outcomes and like what you're actually delivering. And so, you know, we see how much we're shipping, we're seeing how much we're doing. Obviously, what do we care about is like, you know, where are we getting to with the products? Like, what are we actually delivering to our customers and our users? And I think that's roughly the same for every business. There's, there's, there's no kind of like secret trick or there's no kind of like easy way out in terms of measuring actual ROI, productivity and so on. But, but a lot of it comes down to just actually looking to each of the outcomes that you're driving. And so for us, it's, you know,

• 3:58Speaker 01

  obviously, we have all the KPIs, the business that we, that we track and that we kind of follow. And, you know, when we think about our output, like a lot of what we think about is obviously it's like, you know, how quickly are we growing those numbers? As opposed to anything that we actually, you know, look at in terms of tokens or spend or something like that.

• 4:18Molly O'Shea?

  Did you ever think you'd be growing this fast?

• 4:21Speaker 01

  It's a good question. So what I always think about with this is, I think on the one hand, I think relative to businesses, and by the way, it's, it's not just us. It's like our customers have seen this where similarly, our customers in the last six months or so have also grown their usage in something in the range of like 11 to 12x. And of Devin. And the way I'd say it is, yeah, on the one hand, I think you, you just like think about businesses in the past. You think about the growth of all these tech companies in history and obviously, it's pretty crazy. On the other hand, you know, when I kind of asked the question, like the first principle of the question, okay, how many people are using coding agents now? How much are they using it for? How much are they getting out of it?

• 5:06Speaker 01

  Versus like, what do we think they're going to be using? And how much of it are they going to be using in, you know, three years or something? I think the rough answer, especially if you look, you know, if we rewind a bit like a year ago, the rough answer a year ago was roughly zero. And the rough answer for, you know, two, three years from now is roughly every software engineer in the world and probably a lot more than all the, just the software engineers, because I think a lot more people will be able to produce code and produce products and so on, right? And so then when you, when you take those two points on the curve and you just extrapolate out what has to happen, you know, it's, I, I, I think there has to be massive adoption, massive growth. I think what that looks like in practice often is like, of course, you know, there's, there's the virality itself.

• 5:50Speaker 01

  There's like, you know, there's, there's a ton of great content that I think a lot of different folks are putting out in terms of like educating people and showing people how to use the tools effectively. And then there's, you know, real organizational change that has to happen, all of these companies to make that happen.

• 6:03Molly O'Shea?

  It's insane. Like of all the categories, there was an interview I did way back when with Naveen from Mayfield. And he laid out the three fastest growing categories. And I know it's like, it's really, obviously, it's quite easy to kind of forget about these things when you're in it and like when the whole market is moving with it. But it's insane how fast this new category, in less than three years, you got to 500 million in revenue. That's crazy. Half a billion in revenue in less than three years. That's insane.

• 6:33Speaker 01

  Yeah, no, it's, I mean, it's, I think we're very fortunate. And I think the, the like, obviously, I mean, AI as a whole has moved like crazy in the last few years. But like the way that we think about it is just like, we have to move this fast. It's like, if we, frankly, if we only 3x the year over year or whatever it is, you know, we'd be, we'd be lagging the market, right? In terms of how fast all this adoption is happening. And I think it's, I would say it's more a reflection of just how meaningful the technology is. You know, it's like everybody in enterprise or everybody, you know, just building products in general, like the hardest part about building any product, selling a product, all that is just like, explaining to people why they should care. It's like, hey, I've got this like, you know, payroll optimization thing.

• 7:18Speaker 01

  I've got this usage based billing thing. I've got this whatever. But like, here's why this is like, you know, really meaningful. And here's why you should be thinking about this, right? The nice thing about this with, with, you know,

• 7:30Speaker 01

  AI that can write code by itself and build self-driving products for you is, you know, it's, I think it's kind of obvious why you should care, right? And so a lot of it is just like figuring out how you solve all the practical problems of like getting the technology there and then getting it out to, to people.

• 7:46Molly O'Shea?

  You're at half a billion in revenue.

• 7:50Molly O'Shea?

  And you have customers that entail, I'm going to list them out because these are some pretty big customers so far. Goldman Sachs, Mercedes-Benz, Citi, Dell, Santander, NASA, the US Navy and the US Army. And you've raised over 2.5 billion to date at a last valuation of 26 billion. I want to go back in time because cognition played a pretty big role in redemption story of a company called Windsurf. So can you bring us back to that moment and how M and A has played a role in the growth?

• 8:26Speaker 01

  Yeah, it's a fun time. Maybe it was all of 11 months ago. But so we, and by the way, it's kind of topical because I think recently, you know, there's similar news with Cursor.

• 8:39Speaker 01

  You know, we at the time kind of heard this news roughly around the same time as everyone else that, hey, this company Windsurf, which was building a really great IDE that a lot of folks used, individuals, companies and so on. The, some of the team was going to Google, right? And so there was kind of like a, you know, acqui hire deal almost where a number of the researchers on that team were going to Google, right? And there was a company kind of behind.

• 9:03Speaker 01

  That still had all the customers, that still had a ready to go go to market team, a lot of the platform engineering, the product itself, all the details there. But obviously, it was trying to figure out what to do. And that was announced that Friday afternoon. And we at Cog, at Cognition, we were talking about that internally. We were kind of joking about it first, like, kind of interesting. Like, is there... And then, as we actually thought about it seriously more, we were like, actually, this is really interesting for us because if you think about where we're at, we've always been focused on, obviously, the research, the product itself, like really making progress with the agent product.

• 9:45Speaker 01

  I think as time goes on, it's become more and more clear that the really good coding IDE products, the tool that you're kind of like sitting in and using to look at the code itself versus the agent product, which is kind of almost the engineer that you can delegate, you obviously want this to be very hand in hand. Like, a lot of the same information on understanding your exact code base. Obviously, you want the same knowledge to persist across. A lot of how you even go and do your work and manage sessions is very common. You're looking at the code yourself, and then you figure out there's something you want to go do, and so you hand that off to like a remote agent, right? And so, tons of synergies in the product.

• 10:24Speaker 01

  Similarly, in terms of go to market, Winserve had amazing enterprise traction already, had a team that was really, had a lot of expertise in going and selling to these folks and kind of like figuring out how to actually deliver and so on. Like, a really, really amazing deployed engineering motion, all the pieces that you would need, basically. And so, we got in touch with the Winserve team that evening, so it was Friday evening. And then, basically, over the course of that weekend, we worked out the entire acquisition together. So, by Monday morning, we had the announcement ready to go. It was a fun announcement, both myself and Jeff, and honestly, our entire team. We all got very little sleep that weekend.

• 11:08Speaker 01

  But we put everything together, and yeah, it's great that we were able to do that. I mean, I think it made a lot of sense for us as a company. I think it was also, obviously, like a really great team that was just kind of figuring out what to do. And I think over the last year, there's, I remember saying this, it's like peanut butter and chocolate, honestly, for us. It's been a lot of fun. And at this point, it's like, I think the first few months, a lot of little details, as you can imagine, to figure out, like, some of the same customers or companies. It's like, yeah, we had somebody on the Cognition side who had a relationship with them. We had somebody on the Winserve side who had a relationship. There's tons of stuff to figure out, right? All the product stuff. It's like, we're talking at the high level about what the synergies are, ton of detail

• 11:52Speaker 01

  involved in actually going and plugging that in and making billing work and thinking about how you actually hand a session off from the local environment to the remote environment and all these other things. And then, similarly, even like the teams, the offices, all of that stuff to figure out. But today, I would say it's like, it's all one product, it's all one kind of clean. You come to see our office, and it's like, you wouldn't know at all, like, okay, is this person from the old Cognition or the old Winserve, or do they join after that time? And it's kind of like, it's been really nice in that time.

• 12:27Molly O'Shea?

  This episode is brought to you by Brex, my favorite. You become what you spend on, and I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes. The companies building what's next, from Versel, OpenAI, Anthropic, Granola, and Deepgram, all made the same call. They all run on Brex. Brex is the intelligent finance platform that combines cards, expenses, and banking into a single stack with agentic finance built in. AI agents that handle expenses automatically, enforce policy before spend happens, and close your books in minutes. That's why Sorcery runs on Brex, so I can spend time on building and not busy work.

• 13:12Molly O'Shea?

  It's time to get Brex AF. Learn more at brex.com/sorcery. That's B-R-E-X dot com slash S-O-U-R-C-E-R-Y. Bye. What was it like merging the teams together?

• 13:28Speaker 01

  Yeah. No, that was a real process. And by the way, one of the things that was tricky about that process is Cognition at the time was all of 35 or 40 people. And we had a meaningful business with real traction. We were doing in the range of 70 or 80 million of revenue run rate at the time, but it was a very small team. Winserve, on the other hand, because it had kind of like scaled up go to market and set all that up, was around 200 people at the time. And so, a lot of details to figure out, obviously. And so, for a few months, I mean, the immediate day of or week of, all of us were just like, okay, let's just like right the ship. Let's make sure folks know, customers know that we're going to be there for them, we're going to be shipping, we're going to be like, taking care of both sides of the product

• 14:13Speaker 01

  and doing that well, right? And let's just go and deliver. Over the first few months, obviously, a lot of it was just like figuring out how we kind of get into a good state. And then, as with all things, it's kind of like, it's much easier to go build these things and do all this with some time. And so, we had a lot of little, kind of like fun offsites, which helped, I think, for people getting to know each other. Ton of strategy sessions, obviously, like working out all the details and so on. And then, pretty soon, like end of last year, we got to kind of like, we were looking for like a bigger SF office space, obviously, like as soon as possible, just as like a tactical matter, because we needed an office that could fit everybody, right?

• 14:56Speaker 01

  And so, like, by the end of the last year, we got that office space, and then kind of were able to put everyone in one space and all kind of like work together. And those were, I would say, the kind of the big milestones that like made things super, super smooth.

• 15:11Molly O'Shea?

  How did you work through the product integration?

• 15:15Speaker 01

  I mean, it was, it was a lot of steps, for sure. No, I mean, I think the, one way I'd put it is like, not trying to overly force it. And so, for the time being, it was like, there's a Winserve product, there's a Devon product, both those are great. Let's work on both those and kind of do the obvious, like, next steps on each of these things. And then, as we kind of had pieces of overlap, just like naturally building them in together. And so, it wasn't like, one month later, Winserve is gone, and that's it. It was like, over the course of the last year even, we've been building all these things. And now, it's kind of like, Devon Cloud and Devin Desktop are like super, super nicely paired together. You can start sessions from one and hand them off to the other.

• 16:00Speaker 01

  You can work with them all in the same systems, whatever, right? But it was much more of a gradual thing. And I think one of the things that was interesting for us was a lot of the users of either product were kind of already naturally looking for the other side, right? And so, we had a ton of people, for example, who were on the IDE framework. And obviously, right around this time, they were talking about late 25, early 2026, is right around when these asynchronous agents were really starting to get big. And so, all these folks were thinking about, okay, well, what should my strategy be? And obviously, it's great to be able to work with like a single team and somebody that already like understands your code base and has all the details kind of like figured out and deployed, right?

• 16:45Speaker 01

  And so, that was nice. And then, on the reverse side, obviously, similarly, for a lot of folks who were like adopting the cloud agent, it's very nice to say, okay, yeah, like the local side of it is there too, for any of the developers who still want to use the local form factor and who want to have that, right? And so, I think it's kind of like, maybe the simple way to put it is like, rather than force it and say, okay, over the next 30 days or 60 days, like we have to integrate these products, it's much more of like letting the actual usage and the new features that we're building, the kind of next paradigms that we're getting to, like letting those like pull the products together more gradually rather than forcing it.

• 17:23Molly O'Shea?

  How were you getting advised during this? Were you just making it up as you go? Or were you, like, who were you turning to?

• 17:29Speaker 01

  It's a good question. A lot of making it up. And I think for us, I mean, it's, one of the things about Cog, honestly, is like, we, we've talked before about how like a lot of our team are former founders. Our first, like, 56 people, I think like 30 of us were, had founded a company before this. And so, obviously, like, a lot of us together were people who liked being ambitious and entrepreneurial and thinking from first principles. But yeah, also, I mean, I think the...

• 18:03Speaker 01

  No, I mean, it was a real like team effort. I specifically remember that weekend. There was a point, so there was the initial kind of discussions, which were with like myself and Russell from our side, and then Jeff and Graham, you know, from the Wind Surf side. But then, obviously, as soon as we got past like the very first initial discussion, there was a question of like, okay, but like, what are we actually gonna do? And so then there was like every single kind of like part of the business that that Saturday. It was one of my favorite, like honestly, one of the funnest days of my life.

• 18:37Molly O'Shea?

  Really?

• 18:37Speaker 01

  Was like, and because, you know, we had our kind of like, you know, technical team. We had Steven and Walden and so on, who are like, you know, engineering product leaders, like my co-founders, going and like, you know, sitting with their team to understand, okay, what's going on with Wind Surf? What do we do to get out Wave 11? What do we, you know, what are the things, what were the specific features which we need to make sure to deliver on time? You know, the things that we've promised folks that we obviously wanted to live up to. What are the next first steps on how we would start kind of getting towards an integration? Similarly, like on all of the, you know, on all the go-to-market stuff, we had our folks there, kind of like working with, across teams, like making that happen.

• 19:17Speaker 01

  There's just kind of a feeling, I think, for all of us of like, we just love figuring this kind of stuff out, you know? I think sometimes people kind of describe it as like, oh, like, I just want to like, build my product and P's and everything else about building a company is, you know, that's just like, I'll put up with it, but it's not my cup of tea. I think for all of us, like, yeah, like, you know, the experience of building the company is like, is a lot of the fun of it. And so it was a really fun weekend for us.

• 19:47Molly O'Shea?

  Wow, yeah, I would imagine. I'm sure it's something else every week, so.

• 19:51Speaker 01

  Yeah, yeah, I know, it's fun. I mean, we've had all sorts of, yeah, we've had, we've had a lot of more fun weeks since that one, too. And so it's always a mess.

• 20:01Molly O'Shea?

  Well, speaking on the backdrop of M&A with Cursor and their deal, their $60 billion deal with SpaceX. M&A is floating around and there's all those kinds of like fun stories that are happening, but cognition remains independent, so much so that you spent Independence Day at DC, in DC?

• 20:21Speaker 01

  Yeah.

• 20:22Molly O'Shea?

  So why were you guys in DC for Independence Day? And what's the DC play here?

• 20:27Speaker 01

  Yeah, yeah, for sure. No, I mean, it's, look, I think it's like a really, obviously, it's a really topical thing right now, and I think especially because code is, I think in some ways, like, you know, the most kind of like mature vertical. I think a lot of folks look to code as kind of like a, an expectation of what's gonna happen in the rest of the industry and all these verticals. And, yeah, I think there's been a narrative out there that, oh, like, in order to win, you have to be a lab yourself, or you have to go sell to a lab. And obviously, like, we've just always believed that because there's a lot of value and a lot of power in being independent. And you see that in how we work with folks, like, you know, we're, we're completely model neutral, like, we work with all the different providers, we work with OpenAI, Anthropic,

• 21:10Speaker 01

  you know, Google, so on and so forth. But also, just like in our approach with companies, and so, or with all the orgs that we work with. So DC, DC is really exciting for us for a couple of reasons. I think one, because frankly, it's like, you talk about places that need software and that have, you know, things that they want to build, but not enough software engineers to build them. DC and government in general might perhaps be the single biggest kind of point of that, right? All of these orgs have so many things that, you know, I mean, I feel like the one-liners, like, imagine going to the DMV and it actually worked. And why doesn't it work? You know, it's because there's all this archaic software, it's all these crazy processes,

• 21:53Speaker 01

  it's because the website kind of doesn't really, you know, work, and, or you're not able to kind of see these things and track all these things in advance. And like, government software doesn't have to be that, you know? All these things can be good. And I think it's like, I think it's like a really important thing for us to work towards. I think the other thing, and the other reason why it's so important to us, is frankly, I think AI itself is just going to be a pretty fundamental policy issue over the next few years. And like, you think about the early days of the internet, for example, and there were all these discussions about, okay, what's gonna happen? Is there, are there gonna be a handful of corporations that control the entire internet? Or there can be whatever?

• 22:38Speaker 01

  Obviously, we ended up with the open internet, and now, you know, all the businesses of the world are built on the internet. But there will come a day where all the businesses of the world are built on AI, you know? And I think it's something that we should be thinking about sooner rather than later. And so like, we wanted to give our thoughts to that conversation as well.

• 22:59Molly O'Shea?

  It's awesome to see the new admin just embrace technology so much. The amount that they've done in the last year has been incredible. But from your standpoint of being independent, like, you mentioned a couple of reasons, but why do you think in the long run, it's, it's more important for you to build this company as big as you can independently than under another umbrella?

• 23:21Speaker 01

  Yeah, yeah. No, I mean, I think the, I guess a few things I'd say, I think there's a world that folks sometimes talk about where there's the full recursive superintelligence, and then everything is all owned by like a single entity, you know? Or maybe there's two entities or something, that they're, you know, but they have the, and it's like, you know, everything all collapses. Once you've solved AGI, you just take over the entire world, and then there's just like one entity that rules the world. I mean, I just don't think that's the right, the right future for us. And, and I think AI will get to those level of, to that level of capabilities, and I think we'll see it do even crazier and crazier things.

• 24:03Speaker 01

  Like, I've always felt that there's, in terms of just pure knowledge work, there is nothing that humans do that AIs can't do, you know? Partly because humans are, humans, you know, our brains are just computers, you know? Like, like, like the AIs are too, right? And it's like, I mean, they're literally called neural networks because they were inspired by how our brains operate. And so like, I think we will solve all these problems, but I think we want that to be done in a way that, you know, that people can control their own intelligence, can have access to all these things and so on. And I think more than that, too, I think, I think that it can be done, which is obviously an important part of, of any mission that you want to bet on.

• 24:47Speaker 01

  But like, I think, I think there is a lot of room, and I think there is a lot of appetite from everyone out there, you know, individuals and businesses and so on, for, you know, truly like independent tools that they can use, and, you know, for, for things that really innovate at the product and the value layer, rather than just the pure intelligence layer.

• 25:09Molly O'Shea?

  I mean, so on this topic, Christian Garrett, I asked him for some questions. 137, they're big fans. They talked about you in their interview we just did with them, with Justin Fisher-Wolson.

• 25:19Speaker 01

  Yeah, Justin and Christian also, so.

• 25:22Molly O'Shea?

  They're great. So Christian, Christian asked, why do enterprises want third-party providers or open source and won't solely rely on the labs that's their coding tools?

• 25:32Speaker 01

  Yeah, yeah, I mean, I think several reasons. I think first of all, obviously, the way enterprises work is they want to have long-term partnerships, and frankly, it's just hard to know what's gonna happen in the long term, right? Like, who even is gonna have the best model in six months or 12 months or, or whatever? And, and I mean, I think that's very reasonable, you know? Like, you don't want to teach all of your engineers or your entire team how to use one particular suite and one particular product, and then find out, oh, actually, it's, turns out people aren't using this one anymore because everyone says this other one is better or something, right? But I think the other reason that it's important, too, is because, as we said, you know, I think for every company or for every team, like, what they care about is, is not how many tokens they're using, it's how much value they're driving.

• 26:16Molly O'Shea?

  Right.

• 26:16Speaker 01

  And I think it's very important for there to be a player that is going and helping them drive all that value and like turning that into reality, right? And I think in practice, it's, you know, how you organize your teams, how you think about planning, how you think about specs or design, how you do user research. All of these things should be different in the era of AI, right? It's not as simple as like, you know, throw the tool over the wall, here's your chatbot, try that out, hopefully it's good for you, right? It's like, there's a lot of fundamental questions that you have to think through and work through, and these obviously like require organizational change, right? And so, so like, I think, from their perspective, they want to work with somebody who's thinking

• 26:59Speaker 01

  a lot about that, who really understands that, and is, is, is like excited to go help them with all those details.

• 27:07Molly O'Shea?

  If you're building what's next in AI, you need to know MongoDB. The database platform developers love and built for the agents you're running. MongoDB stores Searches and reasons over your data in real time with vector search and embeddings from Voyage AI all in the same system. No separate pipelines, no stitching together 10 different tools. It's by 75% of the Fortune 100 and leading AI native startups run on MongoDB. Build and scale from your first user to billions of vectors. Go to mongodb.com/ai to learn more. That's mongodb.com/ai to learn more. Bye.

• 27:49Molly O'Shea?

  Assembly AI is a voice AI infrastructure layer millions of developers build on. They build the industry's best speech to text, voice agent, and speech understanding models that serve as critical infrastructure for companies like granola, Heijen, Ashby, and ClickUp. Their speech to text models lead the industry in accuracy and quality, and their speech understanding models help you go beyond transcription by uncovering insights, identifying speakers, and highlighting key information from voice data. You can get started today at assemblyai.com/sourcery and get $50 of free credits to start building voice AI products. That's assemblyai.com/sourcery. So you're based in Silicon Valley.

• 28:34Molly O'Shea?

  Do you believe the whole six months to singularity thing? What's your take on the whole singularity?

• 28:40Speaker 01

  Six months is a bit short.

• 28:42Molly O'Shea?

  Fear of longering.

• 28:43Speaker 01

  Yeah. I mean, so, look, the recursive thing, here's what I'd say. There is obviously some version of the recursive thing, which is literally, I mean, I even just said that, like Devon writes most of the code of Devon. So it's like, you know, on the other hand, I think the question of, you know, whether, you know, whether humans will be rendered irrelevant and all human, like all science problems and all societal problems will be solved, you know, six months from now with the ultimate intelligence. I don't quite believe that. And I think there's a few reasons for why that is. I think for one, there's a lot of practical problems out there in the world that are not actually, you know, necessarily like purely intelligence soluble, right?

• 29:27Speaker 01

  There's just like organizational things that have to be done. There's like, there's processes that take time that have to be figured out. There's like hardware components of like, how much GPU compute can you get and so on? And so I think all those things obviously exist. For two, I think we see more and more that, you know, in the model training landscape, I think the vibe today is almost like you can teach the model pretty much anything as long as you know exactly what you are trying to measure or what kind of outcome you're trying to get out of it. And so benchmark scores, for example, are obviously, every time there's a new model, people release benchmarks.

• 30:07Speaker 01

  The thing that's kind of almost like counterintuitive is we're kind of getting to the point where you can solve basically any benchmark, right? Because what does it mean to have a benchmark? It means you've already defined the task, you've clarified what success or failure looks like, you've given a bunch of examples of what that task looks like and what the right behavior should be. And the truth kind of is, well, if you do that, then you can teach the model to go do that, you know? It's RL works. It's incredible how much it works, right? But obviously, not all of the tasks of the world today cleanly fit into that, you know, description, right? And then there's lots of things that are, you know, that are super, super amorphous, that don't really have clear definitions, that it's hard to say what counts as success

• 30:52Speaker 01

  or failure, that have like really long time horizons where it takes a long time to find out whether it was the right decision, right? And so it's like, you know, if you're asking it to write a simple program that goes and does a thing, it's super easy to run the program and say, okay, it got the right result or it didn't. You know, if you're asking it to make a 10-year strategic decision, well, it's kind of hard to get the data on whether you did that right or wrong until you've waited 10 years out and seen that, right? And so I think, I think we will solve all of these things, to be clear, and I think we'll, I really don't think that there are like intelligence problems that AI will not solve in the long term. I just don't think of that as like, it's going to be all over in six months.

• 31:34Molly O'Shea?

  Okay.

• 31:35Speaker 01

  I could be wrong. I don't know, maybe, maybe it is all over, but you know, it's, but if it is all over in six, you know, we had, we had it.

• 31:41Molly O'Shea?

  We had a good time.

• 31:43Speaker 01

  Yeah. There's a certain, I actually think that there's a certain nihilism there, which is like, like, like, I agree, there's some point at which there's like, almost like this like event horizon in AI, right? There's some point in which the AI gets so smart that it's, it's hard for us to even kind of like reason about what that world will look like, you know? Will humans still, you know, will we still have desire? I think we still will have desire. We still have passions and things that we want to explore. I think we will, but like, who knows? You know, like maybe, maybe, maybe like AI will just like solve all of those problems for us too or something. But like, so the event horizon, it does exist, and I think past that point, it's hard to predict, but it's just like, you just gotta stay sane, you know?

• 32:27Speaker 01

  It's like, like, you just, you gotta make reasonable decisions, you gotta build, and maybe it all ends in six months, but, but, you know, I don't currently think that's the case.

• 32:36Molly O'Shea?

  By the way, I think most of these people are already insane. I don't know if you read the beginning part of your Colossus piece?

• 32:41Speaker 01

  Yeah.

• 32:42Molly O'Shea?

  But what is up with the rest of the Silicon Valley tech community? Like, I read that and then I commented below and I'm like, what the? I can't unread that. Thank you, Jeremy. What was going on there?

• 32:56Speaker 01

  There's, there's some of that for sure. No, I mean, it's, it's, it's, it's crazy, you know? Obviously, it's like we're saying, like, these companies are growing faster than ever before, and these capabilities are clearly like, I think, I think it's true that the AI paradigm is on another level compared to, you know, the mobile phone or the internet or something. It's not just a technology that people use every day. I think it will like fundamentally reshape our lives, but yeah, to your point, you've just got to stay sane.

• 33:25Molly O'Shea?

  So the first task that Devon did was spin up MongoDB. I want to understand why you picked that.

• 33:33Speaker 01

  Yeah, so MongoDB, it wasn't on purpose or anything, by the way. We were literally, we were playing around with, I guess there wasn't a term for a coding agent back then, but like the idea of like what it would look like to have like a coding agent. This is like end of 2023. So like, there's not, you know, there were not any of these that existed. But, you know, we made these little things. It's kind of funny, you know, one of my co-founders, Steven, another co-founder is Walden. We were all like, okay, we're gonna make the dev version of our cell, like that, the AI debt, right? So there's like a dev Steven, you know, in our Slack, and then there's like a dev Walden in our Slack. And then eventually, obviously, we took all those ideas and like made it into a single, you know, single product, and that was Devon, naturally, as the, the kind of culmination

• 34:18Speaker 01

  of all these. And, but, but yeah, we had each of these, and people were building them and just messing around and trying to get them to do cool things, right? Like, what can you do if you can actually like test your code and not just like LLM completion your code, you know? What can you do if you like hook it up so that it can actually run commands in the terminal or like, you know, have like a basic, super basic like browser use thing, right? And we were messing around with these, and then we actually just needed MongoDB ourselves. So like Walden was, Walden, this is actually what happened, so Walden was setting up MongoDB, and then, you know, it's like sometimes with these, when you're trying to set up a developer tool, it's kind of like this, or like a database or any of these things, where it's like,

• 35:01Speaker 01

  you just like random bunch of commands, you like paste it in the things that it told you to go do, and then it's just like not working, and there's some error, you know, oh, this, this port or whatever. And maybe it's because you, you know, one random dependency package is on the wrong version and that messes up everything. Maybe it's because you have some other process that's open on your computer that's hogging it or whatever. But, but for whatever reason, like MongoDB, like Walden was just like not getting it set up, and you know, you do what you always do, which is you just Google the error message and you see what that says, and then you try that command or whatever this person on Stack Overflow said, it didn't work. You know, back in the days before AI, you had to go do that. And, and he like spent some time on it, and he's just like, yeah, I don't know.

• 35:43Speaker 01

  So then he had his, Devon at the time, basically, and he's like, all right, Devon, just go, just go, just go try and make it work. And it turned out to be like a really great use case because if you kind of think about what do you need? You need, number one, you just need like encyclopedic knowledge of all the different errors that you can run into and what would cause each of them, right? And then number two, you need the ability to actually run and diagnose things, you know? It's like one thing to just like have the error message and nothing else, but it's another thing to be able to go run commands, to go like look at the other running processes, to go and like whatever else you need to go do. And obviously, those two things, like the encyclopedic knowledge and the ability to actually go and run command, I mean, that's literally like what a coding agent is.

• 36:24Speaker 01

  And like Devon just ran a bunch of stuff for a few minutes and then fixed it. And then he like sent Walden a message like, hey, I got it, it's up now. Walden really, he didn't really believe it at first. I think we still have the video recording of that.

• 36:37Molly O'Shea?

  Really?

• 36:38Speaker 01

  It was so unbelievable. And that was like, I remember like, it's like, I couldn't sleep that night. Like, we were just like, shit, like, maybe, maybe it does work, you know? Maybe you can just have like an AI engineer buddy that can just do work for you, you know? But that was like the very first moment that we believed it was possible, I would say.

• 36:58Molly O'Shea?

  That's amazing. Thank you, MongoDB, for giving something engineers can go after.

• 37:05Speaker 01

  Yeah, thank you for the complicated yet solvable documentation pages. That was, that was just right in the cusp of what it needed to be in December of 2023.

• 37:16Molly O'Shea?

  Oh my gosh. What do you think the biggest question people should be asking right now that they're not?

• 37:22Speaker 01

  You know, it's kind of interesting. I think there's actually an important

• 37:27Speaker 01

  Question to ask about what we would do with abundance. And maybe like, I don't actually, I don't actually know what went down in all the industrial revolution. You know, I wasn't there, but

• 37:39Molly O'Shea?

  Really?

• 37:39Speaker 01

  Yeah, I wasn't there.

• 37:40Molly O'Shea?

  What?

• 37:41Speaker 01

  But, but, so I assumed that there was some phase where it was kind of, everyone was farming.

• 37:46Molly O'Shea?

  They were.

• 37:47Speaker 01

  And then there was a point where it's kind of like, oh, wow, we can actually just like mass produce. And obviously in the time since then, you know, we have all like, there's different things that we all want. There's things that we care about. There's like self-expression. There's, there's all of this kind of like, you know, knowledge work and so on, that's, that's come about since then. And I, I think there was like a middle period, obviously, where it was kind of like, the abundance was there, but, but it was like figuring out those things. I kind of think we're about to enter something like that, you know, in AI. And I see this, the reason, the reason I, I say that is because, um, you know, with software, obviously the first thing that people think about is, okay, like, how can I be more efficient? You know, it's like, all this work that I'm doing, now I can do that work in a third of the time. It's true. Like, you can. It's amazing. It's really cool, right?

• 38:31Speaker 01

  And obviously that's, that's worth a lot already. That means you could do, you know. But, but, but I think the, the real unlock is not in efficiency, but in, um, capacity, right? It's like, what can we do if we can build so much more, right? And obviously, I mean, we gave the example of, okay, maybe the DMV is gonna actually work, you know, in the post-software abundance, or, or maybe, you know, all of your, you know, logging into your bank account or checking your medical record, like, all of this would be like really smooth product experiences. But I actually think there's just so many more things, like, you know, software is eating the world. It's a famous line, obviously. It was true already, you know, here's how we'll look back on this in 2031 or something.

• 39:11Speaker 01

  You know, it's like, it was true already back when you had to go and manually write every single piece of software, every, every line of code that was gonna run. And yet still, it was correct for software to eat the world and to turn all these processes in software. Imagine how good it is and how much more you can do, where you can just generate software on the fly to go do anything. Like, single-use software is gonna exist. Like, self-driving software is going to exist, right? So like, anything that you want to go do or want to turn into reality, like, probably involves doing, you know, that, that, anything that involves using a computer in some form is ultimately some kind of software. And, and when all the software drives itself, like, what do you want to do? What do you want to create? And so like, that's, that's the first thing that comes to my mind, honestly, is like,

• 39:54Speaker 01

  what are we going to create with all this abundance? And I think, I think we're like, starting to get to that question.

• 39:59Molly O'Shea?

  So, last question. What was it like beating Peter Thiel in chess?

• 40:03Speaker 01

  Oh, I didn't beat him in chess, no, no. I would not recommend playing against Peter Thiel in chess. I don't think that's like a good, you know, you gotta, you gotta pick games that you can win. But, but I did challenge Napoleon to a poker match. I, I think there was like, somehow there was like both, but it was just a poker thing that actually happened. There was a round that, it was one of the earliest rounds of Cognizant. So this is like, this is like, this is like the seed, basically. And kind of got to a point, like, we were clear with that, you know, to their credit, by the way, they were always super, super upfront and super hesitant about like, you know, kind of how they negotiated with us too. But, but like, we, we were, we were at the point where like, look, it's like, we wanna go and do this. Here's the numbers that would make sense for us. And they were like, here's the numbers that would make sense for them. And we were kind of like, close enough that you kind of felt like it should work in some form.

• 40:48Speaker 01

  But it was just a question of like, okay, what do we land on? And I was like, you know, it's interesting, you're such a big fan of poker. You know, we can just play a heads-up poker match for that, and we can have the winner decide whose terms we actually sign. It would have been for, in retrospect, it would have been for like 1% of the company or something, which would have been a lot. But, but, um, I put it up with Napoleon. Napoleon was kind of down, and then Peter shut it down.

• 41:11Molly O'Shea?

  Oh.

• 41:11Speaker 01

  Peter, like, you know, I don't really think that's the right way to do this.

• 41:16Speaker 01

  And he said that, you know, and, and so then that didn't end up happening. You know, we worked it out anyway, and we came to a deal, and it was all good. And then we've been, been, been working together since, yeah.

• 41:24Molly O'Shea?

  What are you most looking forward to in the next 12 months?

• 41:28Speaker 01

  Yeah.

• 41:33Speaker 01

  You know, I'm honestly just really excited about us getting closer to this era of abundance. And I think we'll see a lot of that happen in the next, like, not just as somebody, you know, in AI, but like, as like a, like, as a spectator also, like, as a consumer. Like, I, I'm excited for AI to, you know, to, to be there for me, for all of my like tough personal decisions that I had to go make. I'm excited to have AI like handle all these different like little details in my life. I'm excited to have like AI that like, basically just like allows me to like, spend all of my time and focus on the things that I care about and take care, take care of the rest. I think like, I think the abundance era is real, and I think we'll be there pretty soon.

• 42:11Molly O'Shea?

  Amazing. Such a positive, optimistic way to end it. Thank you so much, Scott. I really appreciate it.

• 42:17Speaker 01

  Thanks for having me.

• 42:18Molly O'Shea?

  And, uh, maybe we'll get some hot takes at Versailles.

• 42:21Speaker 01

  Yeah.

• 42:23Molly O'Shea?

  Okay. Thank you so much.

• 42:25Speaker 01

  Yeah, of course.

• 42:25Molly O'Shea?

  Okay, cool. Huge thank you to the entire Raze team for an incredible event. And thank you to Brex, MongoDB, and Assembly AI for making this trip and series possible. If you enjoyed this conversation, you're gonna love the rest of the Raze series, with Tony Kim from BlackRock, Scott Wu from Cognition, Andrew Feldman from Cerebras, Rodrigo Yang from Samenova, Michael Hurlston from Lumentum, CJ Desai from MongoDB, and many, many more, like our hot takes that we did at a secret location that you can find on X, YouTube, and Instagram. Subscribe to Sorcery on YouTube for more conversations with the people shaping AI, and join the free newsletter, you can also do paid, at sorcery.vc

• 43:07Molly O'Shea?

  for weekly insights on AI, robotics, enterprise software, consumer, semiconductors, did I say AI? AI again, and everything that's coming next, like funding announcements and all big things in tech. Thank you. Bye.