Cursor acquires Graphite to unify code writing and code review as AI agents reshape developer workflows

Speaker 3: at that. But Without further ado. We have

Speaker 2: some very special Tell us more about all this. We have Michael Truell and Merrill from Graphite and Cursor. Great to great to meet you, Michael. Great to see you, Merrill. Good to see you too. How are you doing?

Speaker 1: Amazing. It's a it's a fantastic and exciting day for everyone at Graphite. We're we're thrilled about about today's announcement and super excited to work with Michael and team.

Speaker 3: Yeah. It makes so much sense. Yeah, we're excited to have you guys break it down. So, yeah, when did when did the conversation start?

Speaker 1: Yeah. So we started chatting. I guess we've known each other for, like, six years almost now. We've yeah. We've been Yeah. Yeah. We've been we we both went to there's this startup camp program that one of our shared investors did did, like, six years ago. We're in that for the first time. And then our teams have kind of always known each other. There's been a lot of overlap. Cursor was a a big user of Graphite. We're a big user of the Cursor. We started talking kinda back in the summer when we were building we started thinking about building integrations with background agents and thinking about how we let our users, call background agents from Graphite so you could create, review, and merge PRs all in one place. And, we started chatting with the Cursor team. It, you know, quickly became obvious that we shared a lot more than just our, you just know, our biggest investors. We're you know, when we think about the world the same way, we have a super similar vision for where DevTools is going. Their New York office is literally across the street. I can I can see their window from right here? So it's it's it just made so much sense.

Speaker 2: Yeah. That's great. Yeah. Yeah. Michael, please.

Speaker 5: I was just gonna say as we got to talking, like Merrill mentioned, we both think about the future pretty similarly, where we both believe that the way people build software over the next five, ten years is gonna change radically. A lot of coding as we know today will be automated. And we think very similarly about the ways in which code writing will change, but also the ways in which teams collaborating will change.

Speaker 2: Mhmm.

Speaker 5: And Graphite has focused really intensely on the team collaboration problem and how you help people review each other's code. We focus really intensely on the single player experience of how you develop software as a, you know, as an individual programmer. And so we're excited to kind of marry the two together and pull across.

Speaker 2: Michael, I I would love to get a year end review for Cursor or even more broadly just the state of of of software development. Quantitatively, qualitatively, how can you explain the way writing software changed in 2025?

Speaker 5: It's changed in a big way. I think at the highest level, agents became useful in a professional setting, and that really expanded the demand in the market. And I think we're still early. Like, I think it can be really easy to underrate just how far away coding is from being automated. Mhmm. And still, building professional software takes so many people over such a long period of time, and there's lots of issues we need to contend with as AI coding becomes deployed more broadly. But it was a big year where you went from being able to just, you know, ask some quick questions to an AI about your code base and how to kind of help you out with the next thirty seconds to five minutes of your work to being able to hand off whole tasks to an AI and have it do hand.

Speaker 2: And and and Merrill, like, the shape of Graphite, obviously, we know that you're growing quickly. Like, how did how did you perceive the changes that happened this year? If you look back on 2025, obviously, you know, this deal is gonna be something you remember forever. But more precisely, how do you think that the developer experience

Speaker 3: Every time I catch up with Merrill, he'd be like, there's a lot of code to review. So we're busy. That was that was the view your own. Mike that's in a big in a big way is Michael's fault. So

Speaker 1: No. That's that's the funny part about this. I I think Cursor has just so dramatically changed the the rate at which we can build features and, how much code that engineers are able to generate. And, what's happened consistently, the bottleneck has now just shifted to the rest of the process, what we call the outer loop, where, now we need tooling to help every team review and validate and merge changes at the rate that you can now generate them with tools like Cursor. And, that was basically our our 2025 has been how do we both, apply AI to this problem? How do we use, like, more, know, more traditional or deterministic methods like merge queues and, stack PRs and other workflows and tools, to make that process more efficient? But, you know, how do we just unblock this bottleneck that that is now it's kind of like, you know, preventing teams from really realizing the the true potential of tools like Cursor, and, that's that's been our mission this entire year pretty much. And, part of why I think we're so excited for for this partnership is that now you can put, you know, the surfaces where you you write code and where you review and validate and merge it together and just have that seamlessly integrated. Like, you shouldn't have you shouldn't have to, like, jump to a different tool for, your editor, for for code review, for your PRs, for CI. Like, all this should just be, you know, one nicely integrated surface. And, that's kind of always been the the dream for for Graphite in our vision. I think this, you know, now that can become a reality.

Speaker 3: How are you guys thinking about the integration process and and how, Graphite fits into the sort of Cursor platform family? I think a good first step would be, like, maybe a walkway between the offices in New York.

Speaker 2: Like a Skyway? A Skyway? Yeah. We have a Skyway.

Speaker 1: We've talked about

Speaker 3: the A little string and string and cups, you know, so you can but

Speaker 1: Yeah. We'll we'll put a zipline over Broadway. Yeah. So that people can commute back and forth. No. I think I think that there's there's some really obvious low hanging fruit of things that you'll see us roll out in the coming months together, and then there's a a long tail of, like, even more ambitious ideas that we have that are that are in the works. But immediately, like, I remember earlier this year, a few of us on the the Graphite team were up in Toronto, meeting with, with Toby and some of the Shopify engineering leaders, and, they're one of our our biggest customers and close partners. And the biggest ask that they had for us was how do we get context from, from our IDE or from, you know, from tooling where we're we're writing code with AI into pull requests and have that be seamless and have the same chat history, have the the agent logs and everything show up in the PR and be able to then call out to the agent to fix things again. And, you know, we were like, that's that's an interesting problem. Like, maybe we should maybe we should think about working with with Cursor on this. And I think that's that's kind of the most obvious thing that we can do to start with, and then we can build from there on on many of the other ways that we can kind of connect all those surfaces together and have the agent be able to help you, you know, all the way through from the moment that you generate the code to the moment that it's merged in and out to production.

Speaker 5: Yeah. I'd second that. There are gonna be a bunch of opportunities for some quick ways in which we can make the experience of working together in graphite and cursor better. But then the big thing will be going heads down on on a much bigger build together where we'll have more to share late in 2026.

Speaker 2: Michael, I'd love to get an update on how you're thinking about just growth opportunities as segmented by sort of, like, scale of the customer. We we've we've read some, you know, like, the AI, like, the models are great. The tech is amazing. There's still some odd resistance to adopting AI in certain enterprises. We're not at a 100% penetration with these tools. Is there more opportunity in the near term in large enterprises and transforming the way those businesses work? Or is it just the ground game of going getting every SMB online? Like, how are you thinking about growth in 2026, 2027?

Speaker 5: We've been shocked by the demand across the board. Mhmm. And so on the mid market and smaller company side of things and the self serve side of things broadly, there are all these rules of thumb for when the growth of that business tops out in developer tools or in kind of other comparable markets. And the thing that's just shocked us and shocked all of our investors is that the growth has been compounding really consistently at the same growth rate over the course of course of many years

Speaker 3: Mhmm.

Speaker 5: Into the, you know, the revenue scale that we are now. And that just continues unabated.

Speaker 2: So yeah. And then is that sort of like an IT spend thing where, like, a small and medium a small and medium business might just say, like, okay. We don't wanna spend 10% of revenue on IT spend or or technology, and maybe the new paradigm is actually helping with so much growth that they're able to underwrite a larger investment in technology. Is is that what you're seeing?

Speaker 5: Comes from more people using Cursor

Speaker 2: Okay.

Speaker 5: And people deeper. Yeah. Both ARPU and how we're helping people and how much code we're writing for people.

Speaker 2: Yeah. Yeah.

Speaker 5: And then also the number of people using Cursor within companies and across companies

Speaker 1: Yeah.

Speaker 5: Which has consistently been growing.

Speaker 2: Got

Speaker 5: it. And one big change for us this year is just the upmarket motion has developed Okay. Faster than almost any upmarket motion has ever, where at this point, 64% of the Fortune 500 pay us Wow. In some way. And it's both penetration into digital native companies. So for instance, NVIDIA's a big customer wall to wall Yeah. Adobe, Uber, Salesforce, which I think in a public earnings announcement recently, mentioned that they're seeing over 30% productivity increase in twenty first. Yeah. And it's also it's also companies that aren't digital native too. It's it's shocking how many companies are software companies. So And Starbucks, BWC, Hilton, companies like this are deep customer

Speaker 3: Where where are both of you seeing any resistance to adopting AI specifically in software engineering? Are there any I I'm thinking of, like, the the Japanese soldier on the island, you know, that doesn't doesn't know the the war ended. Are you seeing anybody trapped left on an island?

Speaker 5: I think that well, I think that this is kind of true of how AI tools are bought broadly, but it's really important. I think the way you procure these tools is a little bit different, where the difference between having the best product and the third best product from some incumbent that's, you know, now six months old is really, really big. And then user behavior needs to change, and the way in which your team needs to your team works needs to change. And so you kinda need to you need to teach people within companies how how to work differently. And so we've seen a lot of success in not just pulling out the the tool, but also teaching folks within companies too. But it's really spanned across all types of development. I think that there's still some languages where, there's room for improvement and how much, AI can can help folks, especially some some super legacy languages. But I think where there's resistance, it's mostly a a problem of of teaching and kind of learning new habits.

Speaker 3: That makes sense. What kind of advice are you giving, somebody that's maybe in high school or college that wants to to get into software engineering but is, concerned about just the overall rate rate of change and how good the products and models are getting?

Speaker 5: I think it's actually a really exciting time to get into building things on computers. And probably on a relative basis, especially exciting for people who are new and entering the field just because, you know, it's just quick for them to pick up new habits. And so I told them, yep, to experiment with the tools, to try things out broadly. And, also, I mean, working on a solo project by yourself is very different from building, like, a giant piece of software with hundreds of other people So getting exposure to, like, a real professional development environment, to I think it's it's helpful learning.

Speaker 3: Yeah. And it seems more and more obvious that there's just so so much software that needs to be built. I mean, we've experienced this year where we have built a software tool internally to help us run and and, run the entire show. And we are a business that even three years ago, we wouldn't have been hiring a software engineer because we would have either used off the shelf SaaS or would have just taken so much resources, it wouldn't have been worth it. So there's just so much to build.

Speaker 5: Yeah. It's almost trite now, especially in the Bay Area, to say, you know, software is important. And if anything, I feel like it's kind of, like, reached a point in technological maturity where you don't even really think of software as technology. Just think of it as, oh, it's a website that someone builds. Yeah. But, yeah, it's I mean, it's shocking how much, you know, progress across the world really is just bottlenecked by building things on computers. You talk to people in AI research. What's the bottleneck to making the models better? There's a few, but one of the biggest ones is just building better infrastructure and just the speed at which researchers can code. And it's for another areas too. For instance, I worked at a biotech company at one point, and one of the big bottlenecks making progress there was analyzing data and picking the next set of chemicals that people were gonna try out. And it was dealing with crappy software from off the shelf vendors or building a whole software team to build it yourself. And so, yeah, I think that it's this amazing lever on productivity in a bunch of different verticals.

Speaker 2: What are the research paths that excite you the most or or or that you think might be underrated? Example would be like when when we we talked to Sholto during the Claude four five launch, and he was talking about not image processing, not image generation, but image processing. And that's a that actually makes a lot of sense because a real software engineer needs to look at the web page that they designed and then, you know, interpret that and understand the code that they write, how it feeds into the result. Are there any areas of research or or less obvious, like, it's not just a coding model, research paths that you're particularly excited about in 2026?

Speaker 5: Yeah. I think that the capability gains we've seen in our space have actually there's been, like, a lot of details to figure out. Mhmm. But there have been a few really big ideas that have worked just, like, have been levers that people have pulled on continuously. Sure. And so pretraining is one that's been talked about a lot, you know, like Yep. Taking big models, scaling them up, training them on Internet scale data. Mhmm. Another big one that's been really important for our space is curating a set of games for the models to play.

Speaker 2: Oh.

Speaker 5: So for us, that means, you know, collecting a set of or, you know, in our space, it means collecting a set of code bases Mhmm. Writing out tasks, having a set of tests to test if the model actually solved the task, you know, writes a PR. And the big AI companies have have done this really well of getting thousands, tens of thousands of of really hard games for the model to play and then teaching the model to play those games. And in turn, the model then gets better at programming. And so I think that there's a bunch more juice to squeeze both from pretraining and then, you know, RL with this verifiable reward. But I think that there's gonna be, you know, some new big ideas that are needed to really get to a place where you can can hand off end to end most of the professional development tasks we do in in, like, a

Speaker 3: real Does that make you especially excited about some of the neo labs that are that are, I would say, fairly controversial at this point because on one hand, feels like we need new ideas. But on the other hand, it's like

Speaker 2: It's a lot of money.

Speaker 3: It's a lot of money and it's unclear if you just go and try to compete with

Speaker 2: It's always scary when there's a lot of lot of funding, not a lot of revenue. Yeah. Yeah.

Speaker 1: I think Crystal is actually doing a a great job at at this with We got their their own models internally.

Speaker 2: Yeah. I was about to ask, do you think that you're gonna become more of a lab over time?

Speaker 5: No. I mean, we what we wanna do is we wanna build the best way to code with AI. Mhmm. And so we have lots of amazing partners that we're really excited to continue working with over the course of the next few years that are working on things that look like AGI. We've ever since the start of the company, we've kind of picked our spot where we are gonna do our own modeling work. And those have looked different from the places where the big AI companies, big labs do their modeling work. And so for instance, like, all our TAP models, like the things that are looking at what you've done in the editor, breaking the next things you're gonna do, those are our own models. We're on, like, the sixth generation model there. They learn continuously by looking at, you know, what people are doing within, for sure, and figuring out how they how they can get better. And so I am really excited for us to invest a bunch more in research, do lots more ambitious stuff, but it'll kind of be a little in a little bit of a different direction from what some of these these labs might do. And so for instance, we're really excited to build models that are some of the most capable in the world at programming. Not the most capable in the world at programming, but are very fast too. And we think that over the course of the next couple of years or over the course of the next year, agent usage in coding is gonna kinda bifurcate into in the loop or completely async. We're in the loop, you're sitting down, you're, like, working with the agent in a pair programming way. You want it to be very fast and extremely smart. And then async is gonna be you're talking to a colleague. You just hand off something in time. Yeah. And you want it to definitely, definitely, definitely correct. And I think that very soon, we would like to play a really big part in making that human in the loop experience excellent. And I think that there's a lot of useful modeling work to do there. So

Speaker 3: Very cool.

Speaker 2: How do you think about the x for y meme? I feel like Cursor's been very successful in that you there's a certain, like, rite of passage in Silicon Valley where once you become, like, Uber for x, it's like, you're the Uber, it's a good place to be. Good. Cursor for dogs, cursor for bio, cursor for travel, this has become a meme. Is there a where is the line for what cursor will do and what cursor will not do? So when I talk to the Andoril folks, they'll say, well, the Andoril of submarines is Andoril. But if I said the Andoril of stoves or the Andoril of, you know, of, you know, watches, it's like, okay. I don't even know what that means. That's fine. I'm not gonna build that. Like, you actually can go build that company. Where where where's the where where's the line of, like, what Cursor will do over time versus what's something that, like, where where you might like the Cursor four x model, but it's not on your road map?

Speaker 5: Well, we'd like to make it possible for anyone to build anything they'd like on a computer.

Speaker 2: Mhmm.

Speaker 5: And, you know, another way of putting that is we'd like to automate coding.

Speaker 2: Sure. And

Speaker 5: half of that's a model problem, half of that's a product problem.

Speaker 2: Mhmm.

Speaker 5: And we wanna do deep important work across. And yeah. So squarely squarely focused on helping you build things on computers.

Speaker 2: Yeah.

Speaker 5: And that for us, that means an intense focus on engineers. And then increasingly, the Fold's gonna expand too, where lots of technically light personas, like designers and product people, they also work with Cursor too.

Speaker 7: Sure.

Speaker 5: And one of the things we're excited about is that that Fold can broaden as the product gets better, as the technology matures. But I am really excited actually for, quote unquote, cursor for x's to exist in other spaces. And when we started the company, we kind of thought that, like, this this shape of company where you pick an area of knowledge work and you kind of make the cockpit where that knowledge work happens, like the products Mhmm. That people daily drive for that form of knowledge work. You make it you shape it to where the tech's going. You make it great for where AI is. Mhmm. And then you also see where AI is helping people and where it's not helping people, you and use that to make the underlying models better, both by doing a little bit of your own, also by working with partners. That, like, kind of shape of company, we were really excited about. And I think it's gonna exist in in all sorts of different areas of knowledge work, whether it be mechanical engineering or writing or, you know, science, like biological science and other places. Yeah.

Speaker 2: Is graphite the cursor for pull request? Merrill, did you ever think about that positioning? Because I've done I I literally I think I've done 250 ad reads for graphite, and I've never said, hey. It's the cursor for pull request. We said it's code review for the age of AI, of course. But it like, did you do you think that you fit neatly into that that that that framing of the cockpit where the work happens that you improve? Or or is there something that's that's like a different positioning? And I'm wondering how that might change over the next Yeah. Few years.

Speaker 1: Yeah. I think one of our one of our investors, Gokaran, has this framework that we reference a lot where you're you're either building a dashboard company or a pipes company in b to b.

Speaker 2: And Okay.

Speaker 1: If you're if you're a dashboard company, you have to be, like, something where where one type of user, like, single day at work, they're coming in and and doing a certain task and that's just their home screen. Oh. Or you wanna be a pipes company where it's, like, you configure it, you set it and forget it, and it just, does throughput and and prints money for you. Mhmm. And we're very much we've always thought about Graphite as as a dashboard. We've said we wanna be the home screen for developers. We wanna be the place where, where everyone, you know, comes in and checks, like, where are my code changes in flight? What do I have to do in order to unblock my team and keep everything moving? And I think that's that's one of the things that that's so that's so exciting about this partnership is that now, you know, you really can be the the one dashboard for engineering. Like, if you want to if you want to write code, if you want to build something, if you want to move your changes through the rest of the process, like, that can all happen on on one nicely integrated surface now and and really make that that vision a reality.

Speaker 2: Yeah. That makes a lot

Speaker 3: of sense. Well, I'm so excited for both teams. Yeah. I'm incredibly excited for you, Merrill, and the whole team at Graphite as as a as a Graphite customer starting at the age of 25 to a partner now. It's been incredible to see the journey, and you guys pairing up just makes so much sense. And it's been a massive year for you both. I'm sure 2026 will be even bigger, and thank you both for for joining to celebrate with us. We should we should hit the gong again for you both.

Speaker 1: Yeah. I think I think this is the gong worthy moment.

Speaker 3: Definitely. Definitely. And I'm sure I'm sure the two of you guys won't have much of a much of a holiday, but we hope you can enjoy at least a little downtime with friends and family, and can't wait for next year.

Speaker 2: Yeah. We'll talk

Speaker 5: to you Thank

Speaker 2: you so

Speaker 1: much. Thank you, guys.

Speaker 5: We're welcome. Stuff again. Goodbye.

Speaker 3: Incredible.

Speaker 2: What a great partnership. That that that feels like such a yeah. Great Just a match made in heaven. Absolutely.

Speaker 3: Well Let's go over

Speaker 2: to heaven. Dana White and the meta board. This is a match made in heaven. Very funny on multiple levels. Let's play this clip while the team is pulling it up.