GitHub CEO on the AI Coding Arms Race: One Agent, 150M+ Devs | Thomas Dohmke

GitHub Copilot has 15 million users—more than Cursor and Windsurf combined. So why does it feel like they're losing the AI coding race? Last week at Microsoft Build, I interviewed the CEO of GitHub Thomas Dohmke to find out. I wanted to know: Is their huge existing user base a blessing or a curse? And will their latest launch—an autonomous coding agent built into GitHub—let them retake the lead? Watch this episode of AI & I to find out If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Sponsor: Attio: Go to⁠⁠⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠⁠⁠ and get 15% off your first year on your AI-powered CRM. Timestamps: 00:00:38 - Introduction 00:07:40 - Copilot’s place in the AI coding agent race 00:10:42 - Inside the product decisions behind Copilot’s new agent 00:16:18 - How Dohmke thinks about shaping Copilot’s personality 00:20:29 - How GitHub supports both AI-native developers and legacy enterprise users 00:26:57 - Dohmke’s predictions for the future of software development

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

• 0:00Dan Shipper?

  You had the developer zeitgeist in AI the very beginning. How are you repositioning with this agent launch?

• 0:06Speaker 01

  Over the last year, it has clearly turned out to be, you know, that, you know, race between a copilot cursor and windsurf. We believe we still, you know, have the biggest user base across these three. As with every competition, whether it's in sports or elsewhere, you constantly need to keep reinventing yourself. The race is on.

• 0:38Dan Shipper?

  Thomas, welcome to the show.

• 0:39Speaker 01

  Thank you for having me.

• 0:40Dan Shipper?

  Great to have you here. Psyched to get to talk to you about GitHub. You just launched GitHub Copilot Agents, which is awesome. How do you feel about it?

• 0:49Speaker 01

  I feel amazing. It's obviously, you know, the moment after the keynote when everybody in the GitHub team and lots of our friends at Microsoft worked really hard over the past few weeks or days to get everything ready. All the announcement today actually shipped. So there's no waitlist this time around. And so we can just try it using it and the keynote went well. And so we're really happy about that moment. And now, you know, the next phase starts and collecting all the feedback and listening what people have to say and hopefully a lot of positive reactions.

• 1:21Dan Shipper?

  That's awesome. The place I want to start is I remember Copilot as like the first AI application of this wave of AI, even before ChatGPT, where I was like, wow, this thing is awesome. And Copilot actually like quietly has a ton of users. You have like 15 million users or something like that. But when you think about the, or when I think about the ecosystem of next generation AI coding, like the cursors or the windsurfs or the Claude codes or whatever, GitHub doesn't come up as much. So take me through like that evolution and sort of like where we started with GitHub Copilot and, and how that ecosystem has evolved and how you see yourself as part

• 2:05Dan Shipper?

  of like the whole landscape of, of AI coding tools.

• 2:09Speaker 01

  Yeah, absolutely. And you mentioned chat G P T already, but we were before chat G P T, we were not before G P T.

• 2:16Dan Shipper?

  Yeah.

• 2:16Speaker 01

  So the, you know, G P T two was kind of like the first model that had an impact, then G P three came. Um, five years ago at this event, although we weren't uh here in Seattle due to, due to COVID, everything was online, but um. Uh, Kevin Scott and Sam Ortman had a session talking about transformers and large language models and shortly thereafter, we got access to uh. Uh, G P three and we're playing around with it together, you know, on a call.

• 2:41Dan Shipper?

  Yeah.

• 2:41Speaker 01

  Somebody had the keyboard, others were typing, uh, uh, dictating prompts and, and we were seeing candidate's write code and. Uh, uh, in different programming languages and we had these moments where like, holy shit, this is, it actually works and. Can separate Python from, from JavaScript and, and so we had this original idea uh for Copilot, um. Uh, which were actually uh three different uh concepts. One was um. Uh, code to text, uh, I have code explained in, in natural language. We felt this was. Cool, but not good enough. And many developers would try that and say, this isn't working yet. Describe something that doesn't really work.

• 3:15Dan Shipper?

  Like in a chat interface or?

• 3:17Speaker 01

  Uh, well, yeah, it was like um, uh, in a chat like interface where you would highlight things and then say, uh, right click and say, explain this to me.

• 3:24Dan Shipper?

  Okay.

• 3:24Speaker 01

  Um, but that wasn't good enough. And so we figured, okay, we parked that for now. Uh, chat was the, the second idea, same idea, or conversational coding is what we called it back then. Um, which was in the, in the concept paper, uh, but we felt the model is not there yet and. We were very worried about developers trying this out and then uh you have a, you have a negative response or you see the description or the, the. Response in chat doesn't match what you ask.

• 3:49Dan Shipper?

  Yeah.

• 3:49Speaker 01

  Um, and then you stop using it, right? Like, that's always the danger in developer tools, just try something and it's not good enough and then you move on and. You, you always remember that moment instead of what the tool has evolved to and that kind of like gets, goes back in a little bit into the beginning of your question and then. Auto completion or, you know, effectively text to code, like you. Write something in the editor and it provides a suggestion of what comes next and. That worked fairly well and we had a lot of confidence that that use case would work. Because if you think about what developers do every day when they're writing code in editor. Without auto completion is they they also have imperfect code either because they're mistyping themselves because I don't remember what the API looked like.

• 4:27Speaker 01

  Or because they took code snippet of Stack Overflow, of Reddit, of you know, some blog or what they saw in your channel or some open source project. And more often than not, that code snippet that they're taking from somewhere else and putting in their code isn't perfect, right? It might have different variable names or it might be for a different version of the library that you're using. And so still have to make that work. So that's what the initial idea behind auto completion was. We can make that work, you know, close enough to the real developer workflow to actually provide some real value. And that's, that's how this all started five years ago and ultimately, you know, created this market that we are now all in. We have all these developer tools, you know, I've been in developer tools for fifteen-ish years or so.

• 5:11Speaker 01

  I've been a developer for thirty years. I've never seen anything like that, with such an explosion of startups in different spaces. And you already mentioned Curse and Winserve. If you just look at that space of IDE extensions, that's obviously a whole, like a dozen or more other startups. There's all the hyperscalers invested into that space. You know, all our traditional competitors like Bitbucket and GitLab or Atlassian and GitLab. And so there's this one space of competition and that gives developers a lot of choice and they can pick the tool they like. There is things like Bolt New and Loveable and Brussels Zero or Manus.

• 5:49Speaker 01

  At, you know, some part of that spectrum that competing in like you wanna go from a prompt straight to web application. There's open source tools like Kleinen Ru Code and many others that are looking at the evolution of what could that look like? But you have an open source extension and then you bring in your own model. And GitHub plays in all of these. And in fact, you have also plays in continuous integration, continuous deployment, right? Like we traditionally had lots of competitors in CICD that were there before we were in CICD. Because we added actions only in late twenty eighteen when CICD was already a thing for like a decade or so.

• 6:30Speaker 01

  We're in the security space where we're competing against companies that are finding secrets or code vulnerabilities, dependaboard, those kind of things. And so at GitHub, we've always seen ourselves as long as we're part of the developer ecosystem. Where we provide a platform that all these companies integrate with, that all developers come to to collaborate. And now agents and developers collaborate. We are part of, you know, the developer ethos, developer ecosystem. And that's where we see ourselves. And so Copilot evolved from, you know, order completions to chat. We added voice, we added the CLI, we looked into customization, code search, bringing more context into the prompt.

• 7:11Speaker 01

  To know agents, where we have agent mode in VS Code, where you synchronously work with the agent. And where we have the coding agent on GitHub, we assign an issue or task to it. And then it does this thing in the background. You can actually run, you know, ten or so of them in parallel. And where we look at the pull requests and review all that code. And so I think that journey will continue where we provide an end-to-end experience across our platform on GitHub. And across the Copilot experience between the IDE and the DevOps lifecycle.

• 7:41Dan Shipper?

  I think maybe what I'm asking is, you guys, you had the developer zeitgeist in AI the very beginning. And now you're launching this agent, which seems like it's actually like really like right at the edge of what all the other, kind of all those other companies are doing. But for the last couple of years, I feel like personally, I just haven't seen that that much in in my world. I know you guys are shipping like tons of stuff in the enterprise that like has a huge impact. Like internally, for example, we use GitHub all the time. That's like where all of our code is. We have like fifty GitHub repositories or something like that. But most people at the company are not using GitHub AI tools. So I'm curious, like, what do you think happened? What's been going on for the last couple of years?

• 8:23Dan Shipper?

  And like, how are you how are you repositioning with this agent launch?

• 8:27Speaker 01

  Well, look, if you, you know, go back a year to last build, 2024, at that time, you know, those competitors were still, you know, in a group of competitors and it was always clear there's going to be a number two and a number three. And with us being the number one that created that market. And we knew that, you know, at some point, as everything in technology, right? Like Windows versus Mac or iPhone versus Android and whatnot. There's always a, you know, two or three players that define a market. And over the last year, it has clearly turned out to be, you know, that, you know, race between a Copilot, Cursor and Windsurf.

• 9:13Speaker 01

  We believe we still, you know, have the biggest user base across these three. And as with every competition, whether it's in sports or elsewhere, you constantly need to keep reinventing yourself. You know, just because you won, you know, the championship or in the season this year doesn't mean you're going to win next year. And so I think for us, the most important thing is that we're able to move really fast. And we shipped over a hundred things, change logs for Copilot just yet now in 2025. And it's only May. And we're going to keep shipping and we're going to, you know, evolve our platform from VS Code, where we announced today that Copilot is going to be open source. But we also have Xcode support and Jetbrains and Eclipse.

• 9:58Speaker 01

  And of course, the old school Visual Studio all the way into our platform. We not only have the coding agent, we have a code review agent. We have an auto fix agent that fixes security vulnerabilities. And you can actually already stitch them together and have one agent create the pull request and the next agent review the pull request and look at security vulnerabilities. And then have the SIE agent monitor your cloud resources. So I think the race is on and we're excited about the competition because we ultimately believe in developer choice. It's great that there's, you know, many tools out there

• 10:31Speaker 01

  and developers have the choice and they can, you know, pick the editor that fits them best. And then, as you mentioned, They're still coming to GitHub and store their code there and hopefully use Copilot as part of that, of part of that journey.

• 10:42Dan Shipper?

  Yeah. Tell me about the Copilot agent you just launched. Like, tell me about the architectural and product and UX decisions that you made? And why you think it's a better agent solution than maybe like, you know, Codex or some of the other more popular agents on the market right now?

• 10:59Speaker 01

  It all starts with GitHub Actions. And I already mentioned earlier, we brought Actions to market back in 2018.

• 11:05Dan Shipper?

  What are Actions for people?

• 11:06Speaker 01

  GitHub Actions is, you know, conceptually, you can understand it as our way of implementing continuous integration, continuous deployment. Or simpler, it's you have a trigger, you know, new commit, a new issue, a new pull request or comment on a pull request. There's lots of these triggers that you can define that then runs a script on a compute instance, AKA virtual machine. And GitHub Actions offers you that integrated into GitHub. And so you can define within the repository a workflow file, it's a YAML file. And you say, okay, on every commit, I want to run, you know, this build script or this test script.

• 11:49Speaker 01

  And this Actions ecosystem, so it's developer automation, if you, if you will, right? Like you can run something on an event.

• 11:57Dan Shipper?

  Every time you push code, it runs something for you.

• 12:00Speaker 01

  Or say this pull request breaks the tests and so you're not allowed to merge that back into the main branch. And that ecosystem has now existed for almost seven years and has over 25,000 Actions within our marketplace. And so then the cool thing about Actions is that you can compose it from other Actions. And so there's Actions for everything that you can imagine, including for what it's worth, also lots of AI scenarios connecting to model APIs. And a lot of open source projects and enterprise customers are using Actions for their, for their engineering stack, for their, for their platform. And so we have that compute layer available and customers are already trusting that compute layer, right?

• 12:44Speaker 01

  Because ultimately what happens is that whenever you run Actions, Cloning your source code, your intellectual property onto something else, right? A virtual machine. And then you're trusting that that virtual machine, you know, exists during the runtime of a script. And then when the virtual machine, when the script is done, then the virtual machine gets shut down. And everything gets deleted. And so you're not having your source code set outside of, you know, your compliance boundary or your permissions. Who has access to the code base? So we think that's one of the advantages of our agent, that we're already integrating it into the existing ecosystem. We're people already running their C I C D. The second thing is that we believe that the best place for agents to exist is where developers already do their work.

• 13:27Speaker 01

  And so, you know, we already mentioned the I D E with VS Code. You can just trigger the coding agent from Copilot chat in VS Code and say, add GitHub, you know, create a pull request to add tests, you know, to the method that that is wrote. And then that spins it off in the background and it does its thing on GitHub Actions and it opens a draft pull request and describes what the plan is. And then commits changes into that pull request. And that's very similar to how you would delegate, you know, tasks to one of your coworkers, right? So you're basically taking the exact same workflow that you're already doing with your team and applying it to agents. And bringing those two worlds together. And that also means that, you know, three years from now, you can go back to that pull request.

• 14:12Speaker 01

  And it doesn't matter whether a pull request came from a human developer or from an agentic developer. What matters is that you have still everything together in one place. And it also means that, you know, you have a session log that is stored together in the repo. So again, that session log survives, you know, as long as you'd like. You have ordered logging, so you know when the agent started its work and it stopped its work and lots of enterprise customers, you know, stream that ordered log into their threat intelligence. So they can kind of like monitor, you know, a lot of the questions we're getting is how do you, how do I trust the agents? In contrast, the C I C D, where you have a script and you describe exactly what, what the job does, right? Like download maybe a library, run tests, you know, upload the test results into the log file. With agents, that process is not the

• 14:57Speaker 01

  Right, because it's a model that is inherently non deterministic. And depending on, you know, the time of the day, you get a different, you get a different outcome. And you see that when you're using agent mode and you're following it along in VS Code, how you can give it the same task multiple times and it does different things and maybe calls different tools or finds a different file in your code base to get started with. So we believe this integration of the agent in the same workflow that your team is already doing is incredibly powerful because you don't have to relearn how you're reviewing code, you know, how you're testing code, how you're approving code to get merged into the into the main branch.

• 15:36Dan Shipper?

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• 16:19Dan Shipper?

  Do you think at all about the personality or taste or style of the agent? And if so, like, how did you think about shaping that?

• 16:26Speaker 01

  Yeah, I think, you know, part of that shaping is the reason that we're supporting multiple models. Since last year's GitHub Universe, we no longer have just the OpenAI models, which we still also offer. And a lot of those models got added since Universe. And but in addition, we also have Anthropic's Claude Series. We have Google Gemini. We have Bring Your Own Key, so you can actually just connect to OpenRouter or the Anthropic API, put in your key and connect to these models, including DeepSeek as another example. Because we believe that developers want choice in the same way that they want choice when they're picking, you know, their program.

• 17:07Speaker 01

  Language in the open source library or the JavaScript framework, whether you know React or Next or or or

• 17:15Speaker 01

  you know, whatever favorite framework you have, right? And the same is true for models because the models, they have benchmark, but the benchmark never tells the whole story. It might be better from, you know, from one language than another. It might be better or worse for your personal style. And so developers, you know, by trialing and erroring these models will will figure out what's what's best for them. And some of that is, you know, obviously influenced by by social media and and podcasters and and the news and whatnot, right? Like, you're you're trying things out because you heard about it somewhere else. And but some of it, we believe, is from experience. You're going to gain more and more experience, learning how these models work.

• 17:56Speaker 01

  And just like you know how, you know, you're you're building your craft over the over the course of your, you know, career. And you're getting better because you have been in the situation before and you know how you dealt with it then. And maybe you learned something last time and now you're doing it better. The same is also true for for these models. You know how Claude three point seven sonnet behaves? And so you you pick that because you know, okay, this is the easiest way I can write these test cases. Now, the other part of that is what we call custom instructions.

• 18:28Speaker 01

  You know, you have for all these agentic features, you have a system prompt. Oftentimes, either the prompt is directly provided or leaked and it's in a GitHub just already. And then developers can customize that behavior by creating their own prompt files within the repository. And so we support that across all the different surfaces. And so you can customize the model behavior and maybe tell it, I only want responses in German. And the code, of course, and the comments should all be in English because I'm sharing that with my team. But the interaction with the code with the co-pilot should be in German. And, you know, in in a professional environment here in the United States, that's probably like relatively uncommon.

• 19:12Speaker 01

  Because once you work in the tech industry, you kind of like get to at least, you know, Be very proficient in in English over time. But if you're early in career of your, you know, in in school and you you grow up, you know, like my kids with with German parents, that may not necessarily be the case. And so, but that still doesn't mean that you don't want to share that code with others, right? And so we're democratizing access to computer technology to to software development with with these co-pilots being able to speak any human language, any major human language, not just English. And I think that's tremendously different to the time, you know, in the nineties when I learned coding and when you wanted to engage in the internet, you you had to, you know, have a proficient level of English.

• 19:58Dan Shipper?

  Yeah, one of the, I mean, I think there there's a serious advantage to being able to use GitHub's agent inside of GitHub where you're already collaborating. Um, I feel that pain already, just like if you're reviewing PRs or submitting PRs, there's a separate interface for an agent and then you have to go to GitHub to like talk about it. It sucks. Um, so I'm excited to try this.

• 20:18Dan Shipper?

  And it it sort of strikes me that GitHub, that's a huge advantage for you and it's a huge advantage to be used by millions and millions and millions and millions of developers every day.

• 20:28Dan Shipper?

  One of the things I'm kind of curious about is how you think about making product decisions when you have to satisfy like millions of developers that have a way of doing things that they know how to do it and they like it. Versus like, there's probably this sort of like growing contingent of AI-first developers who maybe were technical before, but like are really just like leaning in or basically like writing ninety to a hundred percent of their code. In a non-enterprise environment, maybe they eventually will be running a big enterprise, but it's mostly just like them in their apartment or in their college dorm, just like using these tools to write ninety to a hundred percent of their code with AI. Those seem like sort of different profiles of users and and how do you?

• 21:12Dan Shipper?

  You have so many big enterprise users and like that's such a big part of part of your business. Like, how do you think about serving both those audiences and doing that well?

• 21:23Speaker 01

  First of all, I would say, you know, while enterprise customers are a big part of our business from a business perspective, like where the revenue comes from. Yeah. At the same time, you know, the larger part of our user base is the open source developer or those that have some form of free account on GitHub. Yeah. With a public repository, whether that's, you know, technically open source under some proper open source license or whether it's just a hobby project where you want to put the code out there for others to use and you're not caring so much about the, you know, thoughts behind open source licensing and whatnot. And both of these audience have historically been equally important to GitHub. In fact, you know, if you go back in the early days of GitHub, it was only public repositories

• 22:08Speaker 01

  first and then private repositories got added and then you can still find those threads. People were begging the founders to actually introduce a payment model. And so they could pay for their GitHub account and earn trust that GitHub will survive and doesn't become, you know, an ad business and things like that. And so I think for the longest time, GitHub actually was very focused on this, today we call it product led growth, you know, on this growing the developers that love using GitHub. And the enterprise came second. And we, you know, encoded this within the GitHub culture of, one of our most important principles is that we always put the developer first. So we're not putting the enterprise first and we're not putting a foundation first.

• 22:52Speaker 01

  We're putting the actual developer first, right? And that actually goes as far as that everybody at GitHub, not only the engineers, but every role spanning, you know, finance and HR and product management, sales, they all are using GitHub for everything. So we have lots, tens of thousands of repositories with all kinds of information that are not necessarily, you know, products that we build or Microsoft services that we run, but it's folks using GitHub issues and GitHub pull requests, you know, our terms of service are in a repo and so you can see every change to the terms of service pull request. So we're using our product every single day. And I think that really helps everybody in the company to understand what is important to GitHub.

• 23:36Speaker 01

  And now, you know, what you alluded to is that the developer audience itself is no longer as as kind of like narrow as it used to be.

• 23:44Dan Shipper?

  That's what I'm trying to say is like, I think what it means to be a developer is changing in certain ways, like.

• 23:49Speaker 01

  I think it's still writing code, like at the end of the day, whether you're using AI to generate code or you knew how to write code without AI and now you're trying to figure out how do I combine, you know, vibe coding with writing code manually doesn't matter as much because at the end of the day, the artifact that you're creating is still code. And as soon as your project becomes more and more complex, you've got to have some fundamental understanding of that code. I don't believe in a world where you can create something like GitHub without knowing what the code actually does. Now, this doesn't mean that low code, no code doesn't exist, right? Like, and has actually existed before AI. And so

• 24:32Speaker 01

  there are going to be scenarios where you just, you know, vibe code a webpage or using manners.

• 24:38Dan Shipper?

  Yeah.

• 24:39Speaker 01

  I met the founders last week and they showed me how they used manners to create a page to find an office in Tokyo. And it basically visualized all the available offices on a map. And so that was very specific webpage just for them for that, but that period of time where they're looking for an office in Tokyo, right? So this kind of like micro app or personal software, I think will play a big role in the way we are interacting with those agents because not every answer an agent can give you is going to be effectively visualized with just a text response. Like, the agent is actually more powerful, creates a little bit of piece of software that you can interact with and maybe picking on the flight that trying to book or the the office you're trying to find. And so in those scenarios,

• 25:24Speaker 01

  you might not need the code because it isn't relevant to you, because you're not actually creating software to produce software and sell it, but you're creating software to solve, you know, a task for you. But, you know, the counter example is that you can ask ChatGPT, you know, to whatever, how many airplanes got sold last year and it renders you a chart. And then you look in the code and you realize it didn't actually pull the the source data from some source, but it just filled the source data into like a static variable with some random data. And it might even tell that to you in the text, but you know how it is, who reads all that text? You just look at the chart, it looks cool. And so looking at the code, you know, the simple example shows us that it is still important to understand what this technology does.

• 26:08Speaker 01

  And as soon as you get into like complex software projects, where software is your business, you gotta understand what the code does, you gotta have software developers that review this code, you know, approve it before it gets merged, because otherwise you're going to have security vulnerabilities, you're going to have, you know, functional issues, you might actually delete a feature in a complex application without noticing it. And ultimately, look, you know, businesses, corporations exist, you know, because teams of people are more efficient than a single person. But they exist, you know, to sell products and ultimately make a profit for that group of people. And I think, you know, AI cannot make all these business decisions for yourself. The team has to do them, they have to set the parameters of the business

• 26:52Speaker 01

  to to ultimately return money to the founders, you know, to the corporation or or the shareholders.

• 26:59Dan Shipper?

  I'm really curious, like, if we're back here a year from now,

• 27:04Dan Shipper?

  what are your predictions for where you guys are going to be? Where are you focused? What are you going to ship? What do you think you want to do to sort of like win this future of coding with AI race?

• 27:13Speaker 01

  You know, I think in a TV show, I don't know, I think it was Star Trek, there was like a line, you know, the more things change, the more they stay the same. I feel like it was in Deep Space Nine, but I'm remembering it. And I think, you know, on the one side, a lot of things will dramatically change. And you see that with with agent mode and or white coding as a as a discipline. Although I think Andre also recently had a blog post kind of like saying white coding maybe wasn't as good as an idea as as originally thought. But we're going to have these coding agents, code review agents, security agents, SIE agents. We're going to have those available to developers and those that are on the forefront of the field

• 27:55Speaker 01

  and then know how to, you know, adjust their project to be very, you know, efficient with these agents are going to get a lot of work done. At the same time, you know, we still have lots of companies that have code on mainframes, Cobol and things like that. We still have huge code bases in old school languages like C C plus plus, Perl, and those things don't don't go away. And while there is certain, you know, progress on app migration, you know, we showed a Java and a dot net upgrade agent today as well. There's a lot of work to be done before we get into a world where everybody's just working with agents and no longer has to write code in the IDE. And so I think the IDE will still be there.

• 28:39Speaker 01

  It will be more and more agentic. GitHub will still be there. It will be more and more agentic. And a lot of folks will still, you know, scratch their head and try to find the bug that's, you know, preventing them from going home at night, or they go home with a bug in their head. And then hopefully by the morning, when you have a lot of sleep, you can figure it out. But so I think, you know, we will definitely see a world where you have agents across the whole developer lifecycle. In fact, I think there's going to be a lot of opportunity for small companies to use agents for everything, you know, designing a feature, you know, prototyping it, doing customer research, using something like deep research to do comparative analysis, maybe even write the business model, implementing the feature, testing the feature, deploying the feature, monitoring the feature.

• 29:23Speaker 01

  You know, the full stack builder, I think, will become a thing. But there will be, you know, thousands, if millions of professional software developers that will still write code like we wrote Kill Code this year.

• 29:34Dan Shipper?

  Well, thank you so much for your time. It was great to chat with you.

• 29:36Speaker 01

  Thank you.

• 29:45Speaker 02

  Oh, my gosh, folks. You absolutely positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure, unadulterated knowledge bombs about Chat G P T. Every episode is a roller coaster of emotions, insights and laughter that will leave you on the edge of your seat craving for more. It's not just a show. It's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor, hit like, smash subscribe and strap in for the ride of your life. And now, without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.