GitHub's CEO says AI coding is ‘here to stay’

25:11And still huge, obviously. But I'm curious, especially in the year that's lapsed since you've been on Decoder last, I'm wondering if you agree with the sentiment that GitHub Copilot seems to have lost mindshare, at least in the Silicon Valley niche that is obsessed with this stuff and talking about it every day. I'm sure you still have a ton of users, but I'm curious if you feel that and if you feel like that's a pressure on you to evolve the product faster. And yeah, how you look at how competition has changed this year. I think the overall market of artificial intelligence, larger language models, and what is possible with these models, is moving at a really rapid pace.

25:55I've never seen anything like that in tech, and I've been around for a while. And you're right, AI code generation is at the forefront of that innovation. Logically, if you think about it, because all these companies are also employing developers, and so there's an inherent motivation for everybody to make coding easier, because that means I can innovate faster. And if I have a coding tool that lets my developers move 5 % faster than my competitor, I will use that. But since I was on last time at Decoder, that market has accelerated. And I want to be really open to this. This is amazing. Like, I've been a developer for so long and I've never seen so much innovation in software development tools.

26:35And as GitHub, you've always understood us as a part of an ecosystem that is both competing and partnering with companies in our space. Whether it's in AI cogeneration or whether it's in CICD, like how applications are built, We're not making decisions of what open source library you prefer, right? Like most people wouldn't use GitHub if it would only offer you the JavaScript ecosystem but would tell you to go somewhere else to use Python. And nobody wants to watch sports if there's only one team winning it all. And where I don't agree with you is that we lost Mindshare. I think we have won some and lost others.

27:15And, you know, sometimes it's on a week-by-week basis that you see folks posting on their X that now they're back on VS Code because the latest release, and we're doing nightly builds and monthly releases, has something they want. That's something we should, as an industry, be really proud of. Copilot was late on moving from a single model to multi-model choice. But we got there last year in October. You know, we added agentic support. We built MCP, a model context protocol integration. And now all these coding agents are using the GitHub MCP server that we have built and partnered with the topic.

27:52So it's a race. It's a race where we just announced in Microsoft earnings that we now have 20 million users on GitHub Copilot, 75 % quarter over quarter growth in enterprise usage, 90 % of the Fortune 100. I can give you all the stats. Hold on. On the user number, I got to ask you about this user number. Yeah. Thomas, there's something funny going on with this user number. This is lifetime users? This is users that have ever used it? Or is this monthly? Is this daily? Can you give me a little more granular detail here? It's 20 million users that have, 20 million GitHub users that have Copilot enabled.

28:28Enabled. So it matches the 150 million accounts number, same way of measuring it. And we have 50 million users on, 50 is 5-0 million users on Visual Studio and Visual Studio Code. So that gives you an idea of how far we are in activating the users on our OIDs. This post of yours where you announced that new user number stat, you wrote, the true measure of a company is never drawn during its hype wave, but by its resilience when pressure tested. And then you wrote something even more interesting, I thought, where you said, even with all the constraints we faced, we've proved that a little grit wins the game.

29:06What constraints were you referring to there in that post? Because you're the CEO of GitHub. I would think that you guys are not really constrained. You're also model agnostic, whereas the rest of Microsoft seems much more still connected to OpenAI, at least for now. But it seems like you're able to work with whatever model you want. You're still a separate part of Microsoft relative to the other parts. So what constraints were you talking about? Any size of company is constrained. That's the definition of budgets and employees or headcount, what have you. And you can just always add more people and then you run into the mythical person once that adding more people to a team actually slows you down and doesn't accelerate you.

29:46As such, whether you're a 10-person startup or a 3 ,000-person GitHub or 200 ,000 or so-person Microsoft, you have to make decisions. And Apple famously said, a thousand no's for every yes. And so one constraint is that, of course, we have endless number of items in our backlog. and many of the backlog items that GIP has stem from a time before AI. Customer feedback, people wanting a feature in GitHub issues or GitHub projects, you name it. In fact, there is a running joke that for every customer feedback item we get, there's already one there from months or years ago where somebody else had that same idea.

30:31Naturally, because our customer base are developers and real developers, there's always going to be somebody having an idea that was already there or telling us how to do something better. And then, you know, have a group on X that says, you know, well, that was a stupid decision for them. You have to make a default. And now they're saying this is the best decision ever. And so we are living in that world where we have way too many input signals and we got the constraints, the grid is to pick the right ones where you're really moving fast and where And nobody in the industry is actually knowing what AI cogeneration or AI in general looks like in two or three years.

31:07I think that if we're all honest to ourselves, that is true. We're like, if ChatGPT was the Netscape moment of the 2020s, then we are like in 1995 now where we have an Amazon and a Google, but we have not seen a Facebook, not seen a Shopify and not seen the iPhone. Right. Like in 1995, it would have been preposterous to predict that those things were happening. And you actually have the confidence that that is true. And I think that's the world that GitHub has been living in ever since its founding. It was ahead of its time leveraging Git to build what nobody called DevOps back then, but what is ultimately now the largest developer platform.

31:44And then it was swinging back and forth of what is the next big innovation and what do others in the industry are doing and where do they actually prefer to partner instead of building it themselves. And I think with Copilot, we have navigated that well. And we had our moments where this wasn't, you know, working. And the strategic decision that ultimately I, as CEO, made wasn't the one that pulled us in the right direction to win this space. And now, I'd say, in August 2025, we're still ahead of the curve and we're still the leader of the market. And as such, we're really proud and happy about, you know, the fruits of the hard work that we're earning.

32:22Speaking of partnering or not, coding has become a thing that affects huge transactions that people read about as it relates to AI. And I'm thinking about Google and Windsurf. Windsurf was this, it still is, very ascendant AI coding tool. And they were going to sell to OpenAI. That deal got called off. And that's where Microsoft comes in here. And I know you're GitHub, but it's all kind of related. And I'm curious, you know, a big thing with that and why Google ultimately ended up hiring that team from Windsurf is that the company wasn't able to sell to OpenAI because there was a concern that the IP from Windsurf was not going to be shielded from Microsoft, that there were competitive dynamics at play given the Microsoft OpenAI connection.

33:06So I'm wondering why was that such an important issue that it actually ended up killing a huge deal that would have been a huge deal for not just the AI coding space, but Silicon Valley in general. This would have been a multi-billion dollar sale to open AI. And I'm curious why, from where you said, I know you probably weren't driving that, but why? Why was that such an important issue? You have to ask the question and I can refuse to answer the question. No, look, you know, obviously I have a conflict of interest of even involved in these conversations as such. I don't have any background knowledge I can share with you on this.

33:40What that actually shows you, though, is something else, which is the fear that developers are soon going to be replaced by AI is actually not justified. In fact, the opposite is true. And teams like the founders and core team behind Windsurf or other parts of the industry, Meta comes to mind, get offers that match professional basketball players. Some of them even have agents helping them to lend a new contract. And that should be something that we should be excited about. How we get to that point is a good question to explore for somebody who has access to all the documents. I don't. But I think as a developer that has been in this industry building developer tools and using them myself, that's freaking exciting.

34:26Because it shows you that the market value of those at the top of their game keeps growing. and it hopefully also motivates kids, teenagers, those that are often first into gaming and then want to build their own stuff, still get into a profession. Because I do believe that we will need more developers than ever if this all plays out the way I hope it does. Let's turn to Cursor specifically, which I think has really taken the mantle as, at least in the Silicon Valley, really early adopter set, like the hottest AI coding tool right now. What have they cracked? What was it that they saw, the insight they had that you think got them such a quick lead in terms of just mindshare awareness?

35:07I know GitHub Copilot is still bigger, but they're growing very fast. And the CEO was actually on Dakota recently with Casey Newton, and he cited you all as inspiration for them starting the company. But what did they crack that you didn't see, and how are you responding? What Cursor cracked was to realize that it's not just about adding AI into the IDE, but about changing the IDE itself and designing what you might call AI-native workflows. I was really thinking about how will developers work if AI is the default and not an add-on. They were the first, you know, it was Claude Sonnet 3.5. So they were also ahead of the curve of saying, okay, multiple models play a role and let's give developers the choice and pick the model that works best for them instead of us making the choice, which was our philosophy a year ago when I talked with Eli.

36:06That's two different philosophies, right? We ran lots of eval suites, we looked at these models, and then we picked the one that really was best. But that's not a binary choice because each programming language and each test case and generating functional code or testing code and so on has a different score. And so then you have different scores for different rows and then you make a judgment call, okay, this is overall a better model. But we know from the history of developer tools, in fact, we at GitHub know this very well, is that the best thing you can always offer to a developer is choice and have them pick the model that they think is right.

36:37And then they will know from the experience or you may call it craft which to pick. And I think that has changed the market. Today, you cannot compete in AI coding if you're not offering multiple models, if you're not having the best models, quote unquote, the best perceived by the majority of developers. if you don't offer them to bring their own models, if you don't have an agent node that runs within the IDE, if you can't take that agent mode and offload it into the cloud and what we call the copilot coding agent that is actually integrated into the GitHub platform. And so I'm a big Formula One fan, so I like to always think about the world like that.

37:19There's teams that win whole seasons, and the next season they're behind, and they're not taking that as in, well, shit, we lost, and we'll never win again, but they're taking that as an inspiration to say, okay, we need to rethink of how we're doing these things. And I think that's what happened to Copilot in mid-late 2024. And I think now where we are in August 2025, we can win races again. Not every race, and neither does the competition win every race, but we certainly have innovated in AI cogeneration ourselves while also caught up to what has made others faster. This space does seem so dynamic because of that point you brought up, which is that it is so dependent on the models.

38:01Whatever tool is currently leading, the models they're using, their way that they price for those models. And the models themselves, who is leading, changes a lot. It's almost impossible even being in it to keep up with all of these model releases. You know, LLAMA 3 was a good model. You know, LLAMA 4, not really as much. Like, Anthropic right now seems to be the king of coding. Maybe that changes. Maybe it becomes open AI in a few months. How does that change the app layer, right? So I appreciate how quickly the space is changing. So I think to say that you all are for sure lost or cursor is for sure won is way too early.

38:37But as I think about Anthropic, and you've done a lot of work with them, you mentioned the MCP server, and obviously you can access Cloud through GitHub Copilot. A thing I've been asking people is, why is Anthropic so good at coding? What is this secret sauce they have? You know, Dario was on the big technology podcast recently, and he did not want to talk about why they're so good at coding. But it's the billion, I mean, God, it's maybe the trillion dollar question is why is it such a good model at that? I'd be curious as someone who works with them closely, why do you think they've gotten such a lead in coding specifically?

39:12Let me, you know, for a second go back to the first part of your question. And I come to why Anthropic is good in a minute. I think, A, in tech, we have this notion that for somebody to win, somebody else has to lose. And that has not been true for Windows and Mac OS. That has not been true for iPhone and Android and many other technologies. In fact, in developer tools, that never has been true. Because if so, we wouldn't have the dozens and dozens of programming languages today. And everybody would have moved to what is perceived as the best one. And if you look at the competitors of GitHub Copilot, like Cursor, Lovable, Windsurf, Old, Vercel, et cetera, well, where do those people that use these tools actually store their source code on GitHub?

39:58Where do they manage their issues and projects on GitHub? Where do they run their CSED on GitHub? You know where many of those competitors actually run their model inference? On Azure, right? And so as such, we are part of an ecosystem. As Microsoft, we have always been a platform company. GitHub has always been a platform company. And so we can both be competing and we can benefiting from these companies, driving the size of the overall software ecosystem. Because let's face it, software development has only ever grown. It hasn't really detracted. It's not getting smaller. The number of developers are getting bigger.

40:31The value generated from, look at the tech companies on the stock exchange on any given day. they're often outperforming the market. If our competitors are winning, we are winning too. And I think that's the mindset that is really important to keep in mind when we talk about these battles in this space. That's the benefit of being a hyperscaler, Thomas, is that when the competitors are winning, you're winning too. Not everyone can say that. Sure. That's called differentiation. And then on topic, specifically Cloud Sonnet, where Claude Sonnet, if you believe YouTubers and bloggers and experts like Simon Wilson, Zvix and others, where really it outcompetes other models is tool use, like the ability of the model to pick the right tool for the next step of the agent mode.

41:19And that shows you it's no longer just about the training in programming languages, code and whatnot. It's also training in what are the tools that the agent should use in some fashion as a developer should use. And if that fails in a step, and you see that with some other models where the tool usage is just not as good as Cloud Sonnet, then your agent mode just falls apart. Because it can go through the chain of thought and actually imagine it needs to install an NPM package like a JavaScript dependency. If that doesn't work, then the agent can have the best training set in the world. If it cannot achieve that one thing, the whole thing no longer works.

41:59And I think that's where Anthropic had an early insight or better evolve suites, better testing that led them to have this head start and others are trying to catch up. But, you know, the funny thing is we are recording this and then, you know, by the time it actually gets published, maybe that road has already changed again. That's the fun part of that. I think you're maybe alluding to GPT-5, which may be coming when this episode comes out. Audience, his hands are in the air. We need to take another short break.

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44:01Welcome back. Right before the break, Thomas and I were talking about GitHub's competition. That gave me the perfect window to ask about how things are going with Microsoft and OpenAI. We've touched on pretty much all the main competitors. I do want to end just with, I know you can't say much because this is all being discussed, but Microsoft is currently talking with OpenAI about what the next kind of chapter of the corporate relationship looks like because OpenAI is moving from a nonprofit to a for-profit and Microsoft, is obviously a huge shareholder and currently has exclusive access to the IP.

44:33I'm curious, as a CEO of GitHub, how would you like to see the OpenAI Microsoft relationship continue? What do you think is important for where you sit for that relationship and what would you like to see? For GitHub and for all developers, it's always going to be important that it's a healthy relationship, one where both sites are partnering with each other. That's how the original co-pilot came to be. through a partnership between OpenAI, who had developed GP3 and then the Codex model, Microsoft, who had not only the hyperscaler infrastructure, but also years of experience and responsible AI scaling these processes.

45:10Because look, if you think about the original Copilot, it was a masterpiece on its own, because on every single keystroke, we're running inference against the large language model. That was unheard of at that point in time. And at that scale, you know, of millions of developers in a very short amount of time. And so that, you know, innovation between GitHub, Microsoft and OpenAI created this market that we are now in and that has all these competitors and probably another, you know, dozen to come in the next month. And I think that partnership going forward will create, you know, new such innovations through new models and through new ways of running these models more efficiently.

45:50I mean, a lot has been written about energy consumption of AI and cost and gross margins and those kind of things. And through GitHub, which always has put the developer first, that's what we are breathing. It has always been about human-to-human collaboration, and we're moving into human-to-agent collaboration, and more likely into agent-to-agent collaboration. And all these three layers will stack on top of each other. And OpenAI has the largest, with JetGPT, the largest AI platform today. And so partnering with them, making sure the content that developers generate in JetGPT with the OpenAI codecs complies with the same, we call it the control system, the same security compliance enterprise company standards is going to be crucial for developers to adopt these tools and integrate them into their workflows.

46:44And I think the ultimate battle in AI is going to be fought at the platform layer. Because if all agents are insanely powerful, then what you really care about is how can you integrate those into your other business processes. And for us, obviously, that's the developer lifecycle. Makes sense. Well, let's end on some GitHub, Microsoft-specific questions. It's been a year since your last annual revenue run rate stat. I believe it was$2 billion. why no update? What's the current number? Investor relations team has made the decision what's being exposed in earnings and what's not so as per usual I can only tell you what's in the earnings script and this time we made the decision to not publish the number.

47:28I'm assuming it's higher than that. I'm assuming it's higher than 2 billion. We have published other impressive numbers and we're really happy about the Q4 results of over Microsoft. Neil, I tried this one last year and I'm expecting to get a similar response. But a big question that we have is, does Copilot make money for GitHub? Does that even matter? Is that even a consideration? Because you're running effectively your own P &L to a degree as a separate org within Microsoft. Is this actually making money or is it a cost center right now to gain market share? You're right. GitHub has its own P &L.

48:07and as such we are measured against the goals of that P &L. I think in general, if you look at Microsoft as a business, there's always going to be the desire for these units to make money. The time frame is different and often the bets are really big. As such, I think the better question is, is it going to make money over the lifetime of the customer contract, so-called LTV? And on that, I'm very confident that Microsoft shareholders and Microsoft's leadership team is going to be happy about GitHub's business results. Look, we bought GitHub in 2018, so now a little bit over seven years ago for$7.5 billion at a time when the last published revenue number was$200 million a year before that.

48:55And you mentioned last year we published$2 billion. So the revenue has 10 times increased in seven years. And it's safe to assume that that number keeps growing. You mentioned the business numbers from Cursor. given that we are very open about that we believe Copilot is bigger than Carissa, you can forecast what our number might be. And so as such, we are really, really happy as Microsoft about this acquisition. I personally put it into the top three of deals that Microsoft has ever made. I think Satya Nadella and Amy Hood would agree with me on that one. We are really happy about that we have grown the platform in a sustainable way because we haven't left open source behind.

49:40You know, I may say we haven't fucked it up. GitHub is still GitHub. GitHub is still like the most beloved brand in the developer ecosystem. It is adopted by almost any enterprise company in the world. Not all of them have it for all the developers, but most of them have it for some of the developers. And it has, in that age of AI, reinvented itself. We have reinvented itself because just as we used Git to build GitHub, We used large language models and GP3 together with OpenAI to build the first ever co-pilot and to lead that market. Yeah, that's a good response. I'm sorry there was a lot for me to unpack there.

50:20So is there a big goal where you all see this all flipping and this becomes super profitable if it's not right now, like the co-pilot stuff? Is it the market gets to a certain size or there's bundling that happens with other Microsoft products? Or what is the if this, then that that you're seeing that makes this all worth it? We have a version of Moore's Law, maybe it's Jensen's Law now or whatever, where the GPUs get faster and cheaper. That's like, you know, you mentioned the Valley a bunch of times. There's like a dozen startups that are trying to invent processing units for transformers that do that more efficiently.

51:02but I believe in scale. You could have asked the same question to Jeff Bezos like what, 15 years ago and so on and look at where the hyperscalers are today in terms of profitability. And so I think we will have the necessary patience. We will drive efficiencies. Caching, prompt caching plays already a huge role for agents. We will see an evolution of business models for sure. And we will see our own developers being more productive with AI. And as such, it's not only that you're optimizing gross margins, whatever those may be, but you're also optimizing the way the software is built in our own company.

51:41I actually strongly believe that those companies that are still doubting the use of AI, they're going to put themselves in a position that ultimately lets them fall behind in innovation. And whoever is not using AI should have massive FOMO, fear of missed opportunity, that everybody else in their space, in their industry, is already on AI and have their developers 10 % more productive, 20%. And look, these numbers are always like, why is it only 20 %? Couldn't it be 30 %? 20 % is a massive productivity gain compared to what a software developer costs, how long it costs them to go through higher education, to ramp up in a company, what have you, or to move from one project to another.

52:26And as such, whoever is not using internally AI to make their own processes more efficient, not only for developers, for everything else, support is another great example, sales, lead generation, all these things are going to ultimately fall behind. And whether they have positive cause margins or not won't matter to them. What will matter is that they're no longer being able to compete in the market. That brings me to a memo one of your colleagues recently wrote internally at Microsoft, where it was instructing managers to evaluate employee performance based on the use of internal AI tools, saying it's, quote, no longer optional.

53:02It's core to every role and every level. I'm sure you can appreciate the angst that people feel about this shift. People who are farther along in their careers and feel like they're set in their ways, or even younger people who are just coming in and are overwhelmed by all the change. I feel everyone's overwhelmed. And if you're a mid-level engineer at Microsoft, you're probably wondering, am I going to get left behind in this shift? And is the company actually going to be able to even evaluate this correctly? Do you feel as the CEO of GitHub, do you feel that the management team at Microsoft has an actual measurable way to determine productivity gains internally with AI?

53:40And if that's actually going to be something that employees can know in a real way? The memo was a bit more nuanced. The memo talked about AI learning, AI usage in what we call the connect, which is a conversation between the employee and the manager. And at GitHub, we have a similar process. And it's about the employee, you know, writing up what they have achieved in the last year. You know, what could they have done better to have more impact? What are they going to do in the next year and how they're growing? That's kind of like the framework. And I think in 2025, it's totally fair game to say you should reflect on your AI usage.

54:16And you should reflect, what did you learn about AI? Did you use GitHub Copilot or Microsoft Copilot, Teams Copilot to summarize a meeting? And if not, why not? And then the manager provides their feedback on that and what they have learned, which often also is a good learning experience for the manager to say, oh, the employee is actually ahead of me in AI usage. Like, I certainly have had those moments where somebody showed me how they did something. I'm like, oh, you know, didn't realize that that actually works. And I think that process is key to Microsoft's culture. And, you know, the term that was coined around this is growth mindset.

54:54Having the mindset of saying, okay, you know, I did something and there's a way of doing this better. And I wasn't born, you know, with all the capabilities I have. I was born with the capability to improve myself. And I think if you see that memo in that context, it actually perfectly aligns with Microsoft's philosophy. The other thing I would say, you know, is like specifically to GitHub is there is no GitHub employee that cannot use GitHub, no matter what function you have in the company. So it's not only developers and product managers, it's also HR and finance and legal and all the GNA functions, all the technical functions, all the sales functions.

55:31They're all using GitHub. There is no world where I would allow for somebody to say, well, sorry, I don't want to use GitHub. And I think, you know, that's fair game if the employee doesn't want that. And then there's tens of thousands of other tech companies out there where they can have that. But it's part of our company culture that everybody at GitHub uses GitHub. And it should be part of our company culture that everybody uses co-parted in AI. That doesn't mean that we're looking at how many lines of code you have written today with AI. In the same way that we never looked at an employee and evaluated them based on how many pull requests have they filed or how many Git comments have they done.

56:10Because these metrics are easily gamified. But it shows a mindset that aligns with our culture if you're using our tools to build our tools. Okay, that's a good answer. I want to end on, it's kind of a heady topic. You can take it wherever direction you want. But this debate about AGI, superintelligence, how we get there. A thing I've heard, Zuckerberg has mentioned this, others have mentioned this, is that AI coding is actually the path because it gets you to self-supervised AIs building and maintaining other AIs. And that the company that wins in AI coding will probably get to superintelligence, whatever you want to call it.

56:52If you have a definition of superintelligence, I'd actually love to hear it. but that AI coding will actually be the way we get there. I'm curious if you agree with that or if you don't and if you actually have a definition of superintelligence, please share it, Thomas. I don't have a definition of superintelligence myself because I think ultimately those definitions don't matter much other than either they are encoded in contracts or like a nice marketing instrument and you can go on stage and say, we are the first to have superintelligence and then next week somebody comes and says, well, no, no, we are the first that have actual superintelligence, right?

57:27These terms are like stretch goals and they're constantly changing. I think, you know, the crucial moment where you may call it AGI or ASI is that the AI can improve itself and make itself better. The model, you're basically jumping from GPT-4 to 5 without, you know, humans in the loop. I think when we get to that stage where all of a sudden AI behaves like a kiddo where your four-year-old moves from laughing about a joke to telling a joke. I think that's when we will talk about AGI. That's the moment where we will say it has happened. And there is now a thing that is able to improve itself and keep going.

58:15That's what we as humans really consider intelligence. It's not what you know just because you've been in trivial pursuit. It doesn't mean you're like the smartest person in the world. It just means that you have, you know, good mapping between the questions and the answers. But, you know, the ability to constantly evolve and improve yourself, I think that's the definition that we should use. When it acts like a kiddo. I like that. I haven't heard that one yet. Thomas, thanks so much for your time. Thank you, Alex. Really enjoyed the conversation. Thanks again to Thomas for joining the show. and thank you for tuning in.

58:52If you'd like to let us know what you thought about this episode or what else you'd like us to cover, drop us a line. You can email us at decoder at theverge.com. We also have a TikTok and an Instagram. Check those out at decoder pod. If you like Decoder, please share it with your friends and subscribe wherever you get your podcasts. And if you haven't already, don't forget to subscribe to The Verge, which gets you access to all of our stories and newsletters, including the one I author called Command Line. Decoder is a production of The Verge and is part of the Vox Media Podcast Network. Our producers are Kate Cox and Nick Stat.

59:24This episode was edited by Xander Adams. The Decoder music is by Breakmaster Cylinder. See you next time.