GitHub's CEO Says AI Coding Is ‘Here to Stay’  ## Metadata - Author: [[Decoder with Nilay Patel]] - Full Title: GitHub's CEO Says AI Coding Is ‘Here to Stay’ - Category: #podcasts - URL: https://share.snipd.com/episode/f0632a0b-5289-4d04-9d73-5e05699eb270 ## Document Notes ## Highlights - **AI Coding Works for Small Apps** - AI coding is already viable for small apps like games or simple front-end projects. - The complexity grows with system architecture, database, and backend integration needs. Transcript: Alex Heath Me can literally vibe code something from scratch? Thomas Dohmke It all depends what you're going to build, right? Like, I think we are there for small things. I challenge you to use something like GitHub Spark or Lovable, and you can probably build like a snake game or Pong or like little scoped apps. And I think we're already at that point. And then as you get more complex, it requires you to have certain systems understanding, architecture design, databases, and all those kind of things. I think we're getting closer and closer to a point where you get more of these, as we call them, primitives, supported by the web coding platform. So if you take something like GitHub Spark, and when we launched it at GitHub Universe last October, it was only creating front-end applications, something that runs in your browser With a language called JavaScript. So it could do things that work in a browser, and it had a little bit of backend storage. Now the version of GitHub Spark actually generates a full-stack application. So it also has a backend and a database, and it can connect to AI models and those kind of things. And so it got more and more complex over like, what, nine months or so. And I think we will see exponential improvements to what these Vibe coding platforms can generate. The challenge, I think, will remain that it's one thing to create something from scratch. It's a totally different thing to take an existing software system and modify that and figure ([Time 0:04:10](https://share.snipd.com/snip/b0236250-e602-4eb6-9353-5bd33749dc05)) - **AI Is Changing Developer Role** - Software development is evolving; AI is changing how developers work and increasing productivity. - Developers have historically moved up abstraction layers from assembly to high-level languages and open source. Transcript: Thomas Dohmke If I want to summarize it really quickly, AI is here to stay. And I think most developers that we interviewed and most developers in the industry, they have realized that the profession of a software developer is going to change. It's already changing through the use of AI. And as such, the majority of them are in the process of adjusting to that new way of working. And I had another blog post earlier this year where I described this as the odyssey of developers. We moved from punch cards and mainframes to the personal computer, which drastically changed the inner loop of how fast I can dry out something. Because before that, I had to book time on a mainframe. And I remember going to my mom's office, she had punch cards on her desk. And then all of a sudden, everybody had a PC on their desk, at least the nerds had them, and they could just start coding. And then we went from, you know, assembly language and basic and Pascal and to Python Go and Ruby, right? And we went from no internet to millions of open source libraries that I can just pull into my application from my own servers to the cloud. They've always moved up the abstraction ladder. And today, a developer that builds a full stack application likely does not actually know what CPU is running that application and RAM and gigahertz and what have you. ([Time 0:06:55](https://share.snipd.com/snip/ee056a1b-d68c-4fde-8278-f9024c3dac2f)) - **AI as Code Amplifier** - Around 90% of today's code comes from open source libraries and dependencies. - AI will write most new code, allowing developers to focus on innovation rather than starting from scratch. Transcript: Thomas Dohmke Thing that always comes my mind when we have this conversation is that we need to acknowledge that 90% of our stack today is already written by somebody else, aka millions of open source Developers around the world. If you look at the Verge webpage and the backend and all that, I'm sure it's 90% open source. If you count the lines of code, 90% of those are from open source libraries, open source operating system, programming languages, dependencies, all that. And the team, the engineering team is writing 10%. Same for us at GitHub and even the same for our friends at Microsoft. So we're already in a world where focusing on the thin layer on top that defines what makes our business while we're pulling in the work of millions of developers from around the world To accelerate and to innovate and what have you, to secure the ecosystem. And the same will happen with AI, that AI will write nine pieces of code. So I can still focus on my eight-hour workday and have my one piece of code. So it doesn't mean that I stop writing code. It just means that now I have 10 times as much code and 10 times as much functionality and features as I could produce on my own. ([Time 0:09:10](https://share.snipd.com/snip/77bf2e55-33ec-4800-bca9-3c026491f6dc)) - **Need for AI Code Review Systems** - AI increases code output but requires reviewing code quality and security. - Agents can generate multiple code variants and self-assess quality beyond human capacity. Transcript: Thomas Dohmke And now you're mad that I didn't give you a percentage? Alex Heath Well, I was mad that I was actually just asking you for percentages when I'm looking at my notes here and going, well, actually, people take issue with these percentage questions. Is this even the right way to be talking about this? Because yes, AI code output is going up across companies and CEOs are using it to brag about their efforts. But are we focusing on good code? I'm curious what you make of that debate. Thomas Dohmke Those two, from my perspective, actually go together. I think the percentage obviously is a bit of a marketing instrument. What really does it matter if it's 90%, 80%, or 95%, whatever. I think what matters is that it's clear that the profession of software development is changing. And that we're moving up the stack and we're moving, you know, from understanding every single line of code to switching back and forth between a specification. You know, human language is inherently non-deterministic. We can both say the same sentence and mean different things, let alone that different languages have different constructs of describing these things. Program language is an abstraction of the processor, right, of the CPU or GPU, what have you. As such, it's nothing else than describing, you know, how the transistors ultimately are flipping from zero to one, right? And we're going to have both because the machines are running on CPUs. That's not going to change. But we're thinking in human language. Okay, so then the question really is, do we want to write more human language or do we want to write more code? And that's not AI determines that for you. That's a decision that you make as a developer. And I think this is going to be the creative freedom for me as a developer to say, I want to write code because I know what I'm doing in this moment. Or I want to use an AI agent. And in fact, if you think then about agents, the first question really is, is it faster to use an agent or is it faster to do it myself? And if I know I can do it myself in like three seconds, I'm wasting time, energy, you know, resources if I ask the agent to do that. It's like, you know, I hope when we're texting, you're not using JTBT to write the response to my text message. Alex Heath I have many reactions like this when I'm using consumer agents where it's like, yes, you can go off and book me the hotel or whatever, but it takes you an hour and it's not really right at The end. I should just go do it myself. It's more productive for me to do it myself. Thomas Dohmke And even, you know, the notification summaries in Mail or Outlook or Apple iMessage are often, for me at least, less helpful than just reading the first three lines of text, right? Yeah. Then the second question is, okay, so now AI is writing all this code. And if AI is writing 90% of the code, as in nine times as much code as I'm writing, am I reviewing all that code for, you know, quality, security, coding standards? Or do I find ways for AI to help me with that as well? Because ultimately, we're going to DDoS, the human developer population, with the agent population, as those agents, sorry, DDoS, distributed denial of service attack. As these agents don't sleep, they don't take time off over the weekend, and you can render them parallel. If you look at OpenAI Codex, they're already generating four variants of every task that you're giving. And then you're effectively helping them with their reinforcement learning by picking the one that you like most. But you could not only generate four, you could generate 40 or 400. And then you could have another agent that looks at the quality of that code and rates that quality. And then you have a feedback loop between those agents. So actually, I think we're getting to the point that agents will generate always better quality than a human can generate because you can just run this at infinite scale. And as such, you know, find all the bugs that a human wouldn't find because they don't have the time to do that. ([Time 0:14:30](https://share.snipd.com/snip/97015cac-7d22-4943-a95d-3195156d20f4)) - **Developers as AI Instructors** - Developers will increasingly manage and instruct AI agents rather than writing all code manually. - Coding evolves to writing human language specifications that get compiled down through AI to code. Transcript: Alex Heath Sounds like you're saying the future of a developer is someone who is just looking at how all these agents are behaving all day long and accepting pull requests or rejecting them or reviewing Code, but not really writing it, maybe giving very high level instructions, but really stepping back from the actual process of coding. Is that what you're saying is going to happen broadly? Thomas Dohmke I think to some degree this will happen. We started this with wipe coding, and wipe coding is already happening. All you do is write a prompt. It's actually also happening with image models. If you use ChatGPG, you create like a whatever, Studio Ghibli image, for example. You're not writing the code to do that, and you're just giving the instructions, and then there's something in the model that does that for you. In fact, one of the hacks is that you can upload an existing image and have it decompose the image into a JSON file, like a data structure, and then you modify that data structure and use That as the prompt to generate an image that has something removed or something modified on that image. So you're kind of acting like a developer, but you're not writing any code. You're just having the model do that. So I think there is going to be a class of developers that will use models and agents to build and verify systems. And I think there's going to be a class of developers that also still love coding and that are mixing up their workday with offloading some work to AI agents, like writing test cases, Documentation, offloading the stuff that they don't want to do, so they have time for the stuff they actually love doing. Because the question then becomes, how do you spend your eight hours a day? What is it actually that lets you explore your creativity and ship innovation and so on versus just getting stuff done? And I think it needs to be a mix of both. Most developers today in small and large companies code maybe four hours a day, sometimes even less. The rest of the day they do all kinds of other things. They are in meetings and they write emails and review other people's code and update servers. There's lots of other things that developers also have to do. I think most of them will preserve a certain amount of time during the day where they write code or instructions to generate code, which will feel like coding. In fact, if you think about it, I brought this example earlier. We move from assembly language to higher programming languages and open source libraries. I haven't seen many people that are sad that they no longer have to write assembly. They can. It's not like assembly isn't there anymore. It's just that we have a compiler that takes my programming languages and compiles it down into assembly. Now, you could see the AI model effectively like a compiler. It takes my human language instruction and compiles it down into programming language. And then the real compiler takes that into assembly. Your code actually would be the human language, right? Like you wouldn't ever have to look at the programming language, except that all the models today still have hallucinations and they still write code that doesn't exactly do what I Wanted. Or maybe, you know, I do it, ask it 10 times, and each of the 10 times it writes different version of that code. ([Time 0:19:25](https://share.snipd.com/snip/a359c7f5-5f60-4f5b-8572-f05efa97153d)) - **GitHub Copilot Still Leading** - The AI coding tools market is rapidly evolving with fierce competition and innovation. - GitHub Copilot remains a leader with 20 million enabled users and continuous improvements. Transcript: Alex Heath You've actually already mentioned several competitors to GitHub Copilot in this conversation. So that tells me you're open to talking about it. Coding, I think, is safe to say the fiercest competitive corner of the AI world right now. At least that's my read of it. You've got a lot of deals happening, startups being sold. Some of the fastest growing companies of all time, in fact, are AI coding companies. Cursor, Lovable, the Vibe Coding app we've talked about already in this conversation. GitHub Copilot was really the first to this space in terms of being an AI coding assistant. And 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. Thomas Dohmke I think the overall market of artificial intelligence, large language models, and what is possible with these models is moving at a really rapid pace. I've never seen anything like that in tech, and I've been around for a while. And you're right, AI cogeneration 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 tool that lets my developers move 5% faster than my competitor, I will use that. Since I was on last time at Decoder, that market has accelerated. And I want to be really open to this. This is amazing. I've been a developer for so long and I've never seen so much innovation in software development tools. And 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 an 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 you wouldn't, most people wouldn't use GitHub if it would only offer you the JavaScript ecosystem what 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. And 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. A co-pilot was late on moving from a single model to multi-model choice, but we got there last year in October. 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 Anthropic. So it's a race. It's a race where, you know, we just announced in Microsoft earnings that we now have 20 million users on GitHub Copilot, 75% quarter over quarter growth in enterprise usage, you know, 90% of the Fortune 100. I can give you all the stats. Alex Heath 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? ([Time 0:27:23](https://share.snipd.com/snip/550f3b50-58f7-4afb-bd16-4afad1889cf9)) - **Cursor's AI-Native Workflow Insight** - Cursor succeeded by building AI-native workflows, not just adding AI as an add-on. - GitHub responds by embracing multi-model choices and agent integration to innovate further. Transcript: Thomas Dohmke Cursor cracked was to realize that it's not just about adding AI into the IDE, but about changing the IDE itself 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. That's two different philosophies, right? Like 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 roles and then you make a judgment call. Okay, this is overall a better model, right? Well, 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. And then they will know, you know, from the experience, or you may call it craft, which to pick. And I think that has, you know, 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, you know, to bring their own models. If you don't have an agent mode that runs within the IDE. If you can't, you know, 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, you know, I'm a big Formula One fan, so I like to always think about the world like that. You know, there'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, OK, we need to rethink of how we're doing these things. And I think that's what happened to Copilot, you know, mid-late 2024. And I think now where we are in August 2025, we can win races again. Not every race, and neither has the competition win every race, but we certainly have innovated in AI cogeneration ourselves, while also caught up to what has made others faster. ([Time 0:38:13](https://share.snipd.com/snip/6d3e6209-14d2-407b-a0ea-22c62b5fc409)) - **Why Anthropic Excels at Coding** - Anthropic excels in AI coding due to superior tool usage and robust testing methods. - Tool selection is crucial for AI agents to successfully complete coding tasks. Transcript: Thomas Dohmke The 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. Alex Heath 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. Thomas Dohmke Sure. That's called differentiation. And then on topic, specifically Cloud Sonnet, where Cloud 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. And so, and that shows you, it's no longer just about, you know, 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, right? Because it can go through the chain of thought and actually, like imagine it needs to install an NPM package like a JavaScript dependency, and that doesn't work. And the agent can have the best training set in the world. If it cannot achieve that one thing, the whole thing no longer works. And I think that's where Anthropic had an early insight or a better, better evolve suites, better testing that, that led them to have this headstart 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. ([Time 0:43:19](https://share.snipd.com/snip/9c8819bc-7572-499d-b485-a064ddd55b51)) - **Partnership Powers Copilot Innovation** - The GitHub-Microsoft-OpenAI partnership enabled Copilot's success by combining models and scalable infrastructure. - The alliance will continue to drive innovation through new models and efficient deployment. Transcript: Alex Heath What do you think is important for where you sit for that relationship and what would you like to see? Thomas Dohmke For GitHub and for all developers, it's always going to be important that it's a healthy relationship, one where both sides are partnering with each other. You know, 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. Because 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're 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. I 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 collaboration, and we're moving into human-to collaboration, and more likely into agent-to 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. Making sure the content that developers generate in chat GPT with the OpenAI Codex complies with the same, we call this 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. And 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. ([Time 0:48:20](https://share.snipd.com/snip/a061c87e-b9ab-4163-ba9a-f6ed44772cfd)) - **GitHub's Growth and Profitability** - GitHub operates its own P&L and has grown revenue tenfold since acquisition. - Copilot is a significant contributor, and GitHub is proud to remain beloved in the developer ecosystem. Transcript: Thomas Dohmke Right. GitHub has its own P&L. And as such, we're measured against the goals of that P&L. You know, 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 timeframe is different. And often, you know, the bets are really big. And 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's shareholders and Microsoft's leadership team is going to be happy about GitHub's business results. 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. And 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, you know, we are very open about that we believe Copilot is bigger than Cursor, you can, you know, forecast what our number might be. And so as such, you know, 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, you know, 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. I may say we haven't fucked it up. GitHub is still GitHub. GitHub is still 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. ([Time 0:51:44](https://share.snipd.com/snip/1f7250a8-0729-4099-8add-b6e9e4bc28df)) - **Embrace AI for Growth Mindset** - Employees should reflect on their use and learning of AI tools during performance reviews. - A growth mindset embracing AI usage aligns with Microsoft's evolving culture. Transcript: Thomas Dohmke Going to ultimately fall behind. And whether they have positive cost margins or not won't matter to them. What will matter is that they're no longer being able to compete in the market. Alex Heath 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. It'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 a actual measurable way to determine productivity gains internally with AI? And if that's actually going to be something that employees can know in a real way? Thomas Dohmke 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. ([Time 0:56:18](https://share.snipd.com/snip/dfdc3daf-3445-40ff-9ac9-277bb174dd5a)) - **Defining Superintelligence** - Superintelligence could be defined as AI that self-improves without human input. - The milestone of AGI is when AI gains the ability to evolve autonomously like human intelligence. Transcript: Thomas Dohmke 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. But these 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 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 moves from laughing about a joke to telling a joke, I think that's when we will talk about AGI. That's the moment when we will say it has happened. There is now a thing that is able to improve itself and keep going. That'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 a good mapping between the questions and the answers. But, you know, the ability to constantly evolve and improve yourself, I would, I think that's, that's the definition that we should use. Alex Heath When it acts like a kiddo. I like that. I haven't heard that one yet. ([Time 1:00:45](https://share.snipd.com/snip/6cc127cb-a62e-42be-ba4c-36aba7f0d93a))