走进 AI 增长最快的赛道：260 亿美元 Cognition 的 CEO Scott Wu

You know, obviously like you want the same, you know, you want the same knowledge to to persist across a lot of like how you even go and do your work and manage sessions is very common. You know, you're 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? Um, and so ton of synergies in the product. Similarly in terms of go to market like um you know Windsor had amazing um enterprise traction already had a team that was really you know had a lot of expertise in going and selling um um to these folks and and and and kind of like figuring out how to actually you know deliver uh and so like a really really amazing deployed engineering motion all all the pieces that you would need basically.

Um and so we got in touch with the Windsor 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. Uh fun announcement both myself and Jeff and honestly our entire team you know we all got very little sleep that weekend. Um but uh but you know we put everything together and and yeah know it's great that we were able to do that.

I mean I think it 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. Um, and I think over the last like um, year, you know, there's I remember saying it's like it's like peanut butter and chocolate honestly for us. Like it's been 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, you know, it's like yeah, we had somebody on the cognition side who had a relationship with them.

We had somebody on the Windsor side who had a relationship. There's tons of stuff to figure out, right? all the product stuff, you know, it's like we're talking at the high level about what the synergies are. Ton of detail 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.

Um and then similarly even like the the teams, the offices, all of that, you know, stuff to figure out. But but today I would say it's like um it's all you know it's it's all one product. It's all one kind of clean you know 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 winds surf or did they join after you know that time and and it's kind of like it's been it's been really nice in that time.

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Um, and we had a meaningful business with with, you know, real traction. We were doing um in the range of 70 or 80 million of revenue run rate at the time. Um, but it was a very small team. Windsurf on the other hand um because it had kind of like scaled out go to market and and set all that up is um around 200 people at the time um and so uh a lot of details to figure out obviously and so for for a few months I mean the immediate day of or week of all of us were just like okay let's just like write the ship you know let's make sure folks know you know customers know that we're going to be there for them we're going to be shipping we're going to be like um you know taking care of both sides of the product and doing that well right and let's just go and ever.

Um, over the first few months, obviously, a lot of it was just like figuring out how we um how we kind of get into a good state. And then, you know, as with all things, it's kind of like it's much easier to go build these things and and do all this, you know, with with some time. Um, and so, um, you know, we had a lot of little like kind of like fun offsites, uh, 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 um you know pretty soon like at end of last year we got to kind of like a uh we were looking for like a bigger SF office space obviously like as soon as possible just as like a tactical matter because you know we needed an office that could fit everybody right. Um and so like uh by by the 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 um and those were I would say kind of the big milestones that like made things super super smooth.

How did you work through the product integration? >> I mean, it was it was a lot of steps for sure. Um, no, I I mean, I think the um one way I'd put it is like, you know, not trying to overly force it. Um, and so, you know, for the time being, it was like, look, there's a win-win product. Both those are great. Let's work on both of those and kind of do the obvious like next steps on on each of these things. Um and then as we kind of had pieces of overlap just like naturally building them in together.

And so it wasn't like uh you know one month later Windsurf is gone and that's it. You know 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 you know Devon Cloud and Devon desktop are like super super like nicely paired together. You could start sessions from one and hand them off to the other. You could work with them all in the same systems whatever right?

Um but but but it was much more of a gradual thing and I think um 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 you know right around this time that we're talking about late 25 early 2026 is right around when these these like asynchronous agents were really starting to get big and so all these folks were thinking about okay what should my strategy be?

Um, and obviously it's great to be able to work with like, you know, a single team and um, you know, somebody that already like understands your codebase and has all the details kind of like figured out and deployed, right? Um, and so that was nice. And then on on the reverse side, obviously similarly for a lot of folks who were like um, you know, adopting the cloud agent, it's very nice to say, okay, yeah, like the the local side of it is there too for any of the developers who who still want to use the local form factor and who want to have that, right?

Um 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 you know 30 days or 60 days like we have to integrate these products. It was much more of like letting the actual usage and the the new features that we're building the kind of next paradigms that we were getting to like letting those like pull the products together more gradually rather than forcing it.

>> 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? It's a good question. Um, a lot of making it up. Okay. >> Um, and I think for us, I mean, it's, uh, one of the things about COG, honestly, is like we, uh, and, you know, we've talked before about how like a lot of our team are former founders. Our first like, you know, 56 people, I think like 30 of us were had founded a company before this.

And so, obviously, like, um, a lot of us together were people who who liked being ambitious and entrepreneurial and thinking from first principles, but yeah. Also, I mean, I think the um um No, I mean I mean it was a real like team effort. I specifically remember that weekend there was a point so so there was the initial kind of discussions were which were with like myself and Russell um from our side and then Jeff and Graham you know from the Windsor side um 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 going to do and so then there was like every single kind of like part of the business that that Saturday was it was one of my my my favorite like honestly One of the funnest days of my life really um was like um 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 um you know sitting with their team to understand okay what's going on with WinSurf what do we do to get out wave 11 uh what do we you know what are the things that what what are the specific features which we need to make sure to deliver on time and you know the things that we've promised folks that we obviously want to to live up to um what are the the next first steps on how we would start kind of getting towards an integration.

Um similarly like on all of the um you know on all the go to market stuff we had our folks there kind of like working with um across teams like making that happen. Um 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 I think sometimes people kind of describe it as like oh like I just want to like build my product in peace and everything else about building a company is you know that's just like I'll put up with it but it's 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 it was a really fun weekend for us. >> Wow. Yeah. I would imagine. I'm sure it's something else every week. So >> yeah know it's fun. I mean we've had all sorts of uh Yeah. We've had we've had a lot of more fun weeks since that one too. And so it's it's it's always a mess.

Yeah. Well, speaking on the backdrop of M&A with Curser 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. Yeah. >> So, why were you guys in DC for Independence Day? And what's the DC play here? >> Yeah. Yeah, for sure.

No, I mean it's um look I I think it's like a real really um 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 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 going to happen in the rest of the industry and all these verticals and yeah I 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 there's a lot of value and a lot of power in being independent. Um and you see that in how we work with fall like you know we're we we're completely model neutral like we work with all the different providers we work with open AI anthropic you know um Google so on and so forth um but but also just like in in our approach with with companies and so um or or with all the orcs that we work with.

So DC um uh DC is really exciting for us for a couple reasons. I think one because um 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 and and and government in general might perhaps be the single biggest kind of point of that, right? Um all of these orgs have so many things that you know I mean I feel like the oneliner is like imagine going to the DMV and 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 these crazy processes. It's because the website kind of doesn't really, you know, work and or or you're not able to kind of see these things and track all these things in advance. and and like government software doesn't have to be bad, you know, all these things can be good. Um and and I think it's like I think it's like a really important thing um for for us to work towards.

I think the other thing and the other reason why why it's so important to us is frankly I think AI itself is just going to be a pretty fundamental um 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 going to happen is is there are there going to be a handful of corporations that control the entire internet or there going to be whatever um 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.

Um, and and so like we we wanted to to to to to give our thoughts to that conversation as well. >> 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 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?

Yeah. Yeah. No, I mean I think the um 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 super intelligence and then everything is all owned by like a single entity, you know, or maybe there's two entities or something that there, you know, but then they have the um and it's like um 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 that that to that level of capabilities and I think we'll see it do even crazier and crazier things. Like I I I've always felt that there's >> in terms of just pure knowledge work. There's there is nothing that humans do that AI can't do. you know, partly because humans are humans, you know, our our brains are just computers, you know, like 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 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. Um, and I think more than that too, I I think um I think that it can be done. >> Uh, which is obviously an important part of of of any mission that you want to bet on.

But but like I think um I 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 for um you know, truly like independent tools that they can use and um you know, for for things that really innovate at the the product and and and the value layer rather than just the pure intelligence layer. >> I mean, so on this topic, Christian Garrett, I asked them for some questions.

137, they're big fans. We they talked about you in their interview we just did with them um with Justin Fishner Wolson um >> Justin Christian also. So >> they're great. So Christian Christian asks why do enterprises want third party providers or open source and won't solely rely on the labs thus their coding tools. >> Yeah. Yeah. I mean I think several reasons. Um, I think first of all, uh, obviously the way enterprises work is they want to have long-term partnerships.

And frankly, it's just hard to know what's going to happen in the long term, right? Like who who even is going to 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 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?

Um, but I think the other reason that it's important too is because as we said, you know, I think for every company, 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, right? And I think it's very important for there to be um a 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 um you know how 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 it's like there's a lot of fundamental questions that you have to think through and work through. Um and and these obviously like require organizational change, right? And so, so like I I think um from their perspective, they want to work with somebody who's thinking a lot about that, who really understands that um and is is is like excited to go help them with all those details.

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You can get started today at assemblyai.com/sourcy and get $50 of free credits to start building voice AI products. That's assemblyai.com ce y. >> So you're based in Silicon Valley. Do you believe the whole 6 months to singularity thing? What's your take on the whole singularity? >> Six months is very shorting. Yeah. Um I mean so so look I the 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, so it's like you know on the other hand I think the question of you know whether um um 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. Um um and and I think there's a few reasons for why that is. 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 uh just purely intelligence soluble right there's just like organizational things that have to be done there's like um uh there's processes that take time that have to be figured out there's like hardware components of like how much G you know how much GPU compute can you get and and so on and so I think all those things obviously exist for two I think we see more and more um that you know in in 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 um benchmark scores for example are obvious every time there's a new model people release benchmarks. The thing that's kind of almost like um 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 it's it's it's incredible how much it works, right? Um 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, um that are super super amorphous that don't really have clear definitions that it's hard to say what counts as success 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? Um and so it's like, you know, if you're if you're asking it to to write a simple program that goes and does a thing, 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? Um, and so I I I think I think we will solve all these things to be clear. And I think we'll we'll >> I I 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.

>> Okay, >> I could be wrong. I don't know. Maybe maybe it is all over but you know it's put if it is all over and say we had we had it we had a good time until then yeah there is a certain I actually think that there's there's a certain nihilism there which is like like >> I 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 um you know we still have desire I think we still will have desire.

We still have passions and things that we want to express. I I think we will, but but like who knows, you know, like maybe maybe maybe like AI will just like solve all of those problems for RS2 or something. But like um so so the event horizon does exist. And I think past that point, it's hard to predict, but it's just like you just got to stay sane, you know? It's it's like like you just you got to make reasonable decisions.

You got to build and and maybe it all ends in six months, but but you know, I I don't currently think that's the case. 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, 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 like >> I can't unread that. Thank you, Jeremy.

>> What was going on there? >> There's there's some of that for sure. Yeah, I mean it's um I it's it's it's crazy, you know, obviously it's like we're saying like these companies are growing faster ever before. These capabilities are clearly like I I think it's 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 it's just got to stay sane. So, >> so the first task that Devin did was spin up MongoDB. I want to understand why you picked that. >> 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. [clears throat] Um, uh, but you know, we made these little things. It's kind of funny, you know, one of my co-founders, Stephen, co-ounders, Walden. Um, we were all like, "Okay, we're gonna make the dev version of oursel like that the the 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 SL.

And then eventually, obviously, we took all those ideas and like made it into a single um, you know, single product, and that was Devon naturally as the the kind of culmination of all these. Um and uh but 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?

Uh 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? Um 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 um 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 or like a database or any of these things where it's like um you just like run a bunch of commands, you like pasted 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.

Um 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 uh process that's open on your computer that's hogging it or whatever. Um 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 you try that command of whatever this person on Stack Overflow said and it didn't work.

You know back in the days before AI you had to go do that. Um and uh and he like spent some time on it and he was just like yeah I don't know. 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 could 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 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. Uh, 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. Um, and like Devon just ran a bunch of stuff for a few minutes and then fixed it and then like sent Walden a message like, "Hey, I got it. It's up now." R didn't really he didn't really believe it at first. I think we still had the video recording of that because it was so unbelievable and that was like I remember like we I couldn't sleep that night. Like we were just like like maybe it 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 >> that's amazing. Thank you MongoDB for >> Yeah. giving something engineers can go after. >> Yes. Thank you for the the complicated yet solvable documentation pages. That was that was it was just right in the cusp of what it needed to be in December of 2023.

>> Oh my gosh. What do you think the biggest question people should be asking right now that they're not? >> You know what's kind of interesting? I think there's actually an important 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 um really >> yeah I wasn't there but but so I assume that there was some phase where it was kind everyone was farming >> they were and and then there was a point where it was kind of like oh wow we can actually just like massproduce and obviously in the time since then you know we evolved all like there's different things that we all want.

There's things that we care about. There's like self-exression. There's there's all of these 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 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 and it's true like you can it's amazing it's it's really cool right and obviously that's that's worth a lot already that means you can 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 going to 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 this is a famous line obviously it was true already you know this here's how we'll look back on this in 20 31 or something 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 going to run and yet still it was correct for software to eat the world and to turn all these processes and 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 going to exist like self-driving software is going to exist, right? So like anything that you want to go do or or want to turn into reality like probably involves doing you know that 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 so like that's that's the first thing that comes to my mind honestly is like what are we going to create with all this abundance? And I think I think we're like starting to get to that question. >> So last question. What was it like beating Peter Teal in chess? >> Oh, I didn't beat him in chess. No, I would not recommend playing against Peter Teal 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 but it was just the poker thing that actually happened. There was a round that it was one of the earliest rounds of cognitive. So, this is like this is like this like the seed basically. um and kind of got to a point like we were clear with that you know to to their credit by the way they were always super super upfront and super heads up 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 want to go and do this here's the numbers that would make sense for us and they were like here are the numbers that would make sense for them um and we were kind of like close enough that you kind of felt like it it should work in some form there's just a question of like okay what do we land on uh and I was like you know it's interesting you're such a big fan of poker, you know, we just play a heads up poker match for that and we could have the winner decide whose terms we actually signed.

It would have been for in retrospect, it would have been for like 1% of the company or something, which would been a lot, but but um um I proposed that when Napole Napoleon was kind of down and then Peter shut it down. >> Oh, >> Peter, you know, I I don't really think that's the right way to do this. >> >> then he said that you know and and so then that didn't end up h you know we worked it out anyway and we came to a deal and and it was all good and then we've been then been been working together ever since.

Yeah. >> What are you most looking forward to in the next 12 months? >> Yeah. Um, 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 have to go make.

I'm excited to have a 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. Um I think like I think the abundance era is real and I think we'll be there pretty soon. >> Amazing. Such a positive optimistic way to end it. Thank you so much, Scott.

I really appreciate it. >> Thanks for having >> and uh maybe we'll get some hot takes at Versailles. >> Yeah. >> Okay. >> Thank you so much. Okay, cool. Huge thank you to the entire raise 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 going to love the rest of the Ray series with Tony Kim from Black Rockck, Scott Woo from Cognition, Andrew Feldman from Cerebras, Rodrigo Yang from Salmanova, Michael Hurston from Lumenum, 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.

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