GitHub’s COO Explains Why AI Hasn’t Replaced Developers

Last year, there were 1 billion commits on GitHub. This year, Kyle Daigle expects that number to exceed 14 billion, a two-component explosion caused by more humans—and their agents—issuing pull requests. In March alone, 17 million pull requests on GitHub were created by agents. Daigle is the COO of GitHub and Microsoft’s chief marketing officer for developer products. He’s been at GitHub for 13 years, and is paying close attention to how AI is expanding the platform’s user base. Along with agents, legal, sales, and marketing professionals are building apps with the GitHub Copilot app. The line between developer and non-developer is disappearing. On this episode of AI & I, guest host Mike Taylor sat down with Daigle at Microsoft Build to discuss how GitHub is building infrastructure for an agent-native world: agentic code review, model routers that automatically select the right model for the task, and a philosophy that the most durable advantage in this market is developer choice. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? To hear more from Mike Taylor: Subscribe to Every: https://every.to/subscribe Follow him on X: https://x.com/hammer_mt Timestamps for YouTube: 00:00:52: Introduction 00:03:27: The agentic PR flood 00:04:33: GitHub's approach to helping open-source maintainers manage the surge 00:06:15: What 14 billion commits means for code quality 00:08:03: Moving from per-seat licensing to usage-based pricing 00:09:45: Kyle's dual role as GitHub COO and Microsoft's chief marketing officer for developers 00:13:03: Developer choice as competitive moat 00:14:57: How to balance dogfooding your own tools with staying honest about the competition 00:19:45: Hill climbing, frontier tuning, and solving the model-routing problem 00:24:45: Kyle's agentic communication hack Links to resources mentioned in the episode: Kyle Daigle on X: https://x.com/kdaigle Mike Taylor on Every: https://every.to/@mike_2114 Mike’s piece on building an AI version of Kyle Daigle: https://every.to/also-true-for-humans/i-interviewed-an-ai-version-of-github-s-coo-then-spoke-to-the-real-one GitHub Copilot: https://github.com/features/copilot

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

• 0:00Speaker 00

  Hi, I'm Mike Taylor. I'm the head of tech consulting at Every and I sat down with Kyle Daigle, the COO of GitHub, and talked to him about what is happening on the front lines of coding agents. We have 17 million poll requests coming in every month to GitHub now. It's growing exponentially and that puts them at the forefront of what's happening in this new economy. We talked about how that affects our users as well as how this affects open source maintainers. And we covered a topic which is dear to everyone's hearts. How do I stop my $200 a month coding agent subscription from ballooning into a $2,000 a month usage limit? In this interview, we did something a little bit different, which is I told Kyle I had made an AI clone of him to practice the interview. And he revealed something surprising in return. Here's the conversation.

• 1:00Dan Shipper?

  Every is the only subscription you need to stay at the edge of AI. If you care about being on top of the latest models and using the latest tools, you have to subscribe to Every to separate out the signal from the noise. Go to every.to/subscribe today.

• 1:12Speaker 00

  Hey, Kyle. Thanks for spending some time with me at the conference.

• 1:14Speaker 02

  Yeah, of course.

• 1:15Speaker 00

  Yeah, it was good to meet you as well on the day before.

• 1:18Speaker 02

  Yep.

• 1:18Speaker 00

  And I feel like we already kind of covered a few of these questions.

• 1:21Speaker 02

  Sure.

• 1:22Speaker 00

  But I think it'll be good for the wider audience so they can understand what's going on here.

• 1:26Speaker 02

  Absolutely.

• 1:26Speaker 00

  Yeah, so first thing I think is we were talking about, what's really interesting is that the demographics of the customer are changing, right? Like, a lot of people who previously maybe never used GitHub or never used developer products before are now using them. So how has that changed the way that you decide the product roadmap?

• 1:46Speaker 02

  Yeah, yeah, I mean, you know, I think for GitHub in particular, we've always really had this really expansive view of what a developer is. I started as a developer before I would have ever called myself a dev, you know, where I was just like writing code, but it was just for me. And I went personally like a completely different career path. I didn't go to school for computer science. I was going to art school. I wrote code to pay for art school, which is a very silly decision as an adult now, I guess. But then, you know, that sort of journey of just like, I can create tools with the team and deliver them to people who can have that same experience of like, I just want to build an app that's for me or for my family, maybe as a startup, maybe as a business.

• 2:29Speaker 02

  We very much have like serious developer tools, you know, like all the largest businesses are using GitHub. But when I look at something like the GitHub Copilot app, I see just as many developers that are using AI every day, running multiple projects, like all kinds of agent sessions at the same time. And I see our legal team at GitHub using the GitHub Copilot app or the finance team, or I was meeting with a customer today and they were saying the same thing. A lot of the folks that the industry would call knowledge workers or just non-bi-trade developers are using these tools to build little apps or assets for them. And so while our focus is very much on developers,

• 3:13Speaker 02

  I think we want to make it easier for people to choose, to try to write some code and make sure there's always an on-ramp into writing some software now with things like the GitHub Copilot app.

• 3:26Speaker 00

  Yeah, and then how do you deal with the, or how do you help developers deal with the burden of all of that extra? There's a flood of PRs now, like open source maintainers I talked to are drowning. Yeah, how do you, like what needs to happen to help them?

• 3:38Speaker 02

  Yeah, I mean, I think for all developers, we're building tools like the Copilot code review. It's now Agentic, so it finds a lot more novel vulnerabilities. And you can just like comment and the agent will take that on and go implement the change if you want to. So I think that code review step is in some ways overlooked as a really great way to get PRs to a place that are much more easily reviewed. I think that the Agentic merge in the app is another place where we see a lot of times internally and in the community, you may comment on something that might have a code review and you might go through and get it almost all the way there. But then there's all those like manual steps just to finish processing the PR.

• 4:22Speaker 02

  Instead, I can go in and set exactly what I want to allow GitHub Copilot to do and say, okay, now go merge this PR and wait for CI and wait for policies and all of that. I think that's a big part. On the open source side, it's a unique set of needs because you don't control who's sending everything in. Or you haven't really historically. And that's been really where we've been focusing is giving maintainers more tools to decide. Well, do you want to accept all of these PRs? Like, who do you want to accept them from? You know, how much work do you need to do to kind of prove that you're going to contribute something that is going to be meaningful to this project? And that's something that we want to provide tools to open source maintainers, but really leave them in control.

• 5:05Speaker 02

  Every community is choosing a slightly different way to approach the problem. And forget how we've always wanted to leave that in their hands. Like, give them tools and enable them. But if a standard comes out of that, or most are using a certain practice, we'll lock that in. But we don't really ever want to be the first to create a standard or an approach. Like, I think, you know, Mitchell Hashimoto shared like the Vouch system that they use. And I was getting questions like, well, why aren't you roll this out to everybody? But there's just as many communities that don't want to use that system because they have their own ideas of how it should work. And so for now, we're focusing on the building blocks of controls for maintainers.

• 5:46Speaker 02

  And then as we all are kind of learning together and as maintainers send feedback in, we'll, you know, we'll cement an entire system if one emerges.

• 5:55Speaker 00

  Yeah, and I feel like you have a front row seat to this like new agent economy where, you know, I think you said publicly on Twitter that you've had more poll requests submitted and like per month than you did all last year. Like, how are those stats exploding?

• 6:12Speaker 02

  Yeah, I mean, I mean, we're seeing way more activity on GitHub. You know, we've always been talking about our users, you know, for many, many years and that growth. But this year, we're seeing obviously the growth of developers having agents building with them. And so last year in October at GitHub Universe, we shared, you know, there's a billion commits on GitHub for the full year. We're on track to be 14 billion if the growth is linear this year, which it will not be. You know, in March, you know, there were 17 million poll requests that were created. By agents.

• 6:50Speaker 00

  Yeah.

• 6:50Speaker 02

  That's just the agent pull request.

• 6:52Speaker 00

  Okay, yeah.

• 6:52Speaker 02

  And so there's so much more code being created. And I think at times everyone goes like, oh, this is all just like slop. This is all just code that's getting pushed up, but and no one cares. It's not like really true. We're all just actually getting to the point where we're no longer in the super early adoption. We're definitely not at the peak, but we're climbing that hill, you know, to see what can we build? When it's not just Kyle building, but it's Kyle in one, two, to N, you know, agents that are using my skills, using my resources, using my context and so on and so forth. And so like we're, you know, investing heavily in preparing for the next wave of growth

• 7:35Speaker 02

  because it doesn't seem to be kind of like growing and plateauing. It's just going to continue to grow because no matter where you're, you know, building or what tools you're using to build, all of that code ends up on GitHub, you know? And or that's where you're sharing it with the world or that's where you're collaborating in a PR. And so we need to be able to support everyone's, you know, sort of agent moment and not just, you know, GitHub Copilot.

• 8:00Speaker 00

  Yeah, yeah. And how does the business model change? Because I think freemium makes sense, you know, in a human centered world where we go to bed. But the agents are still working while we're asleep now. So does that change like to usage based? Like, is that you see that kind of where things are going?

• 8:17Speaker 02

  Yeah, I mean, like, I don't think we know like yet ultimately. Like, I think, you know, we very much right now, like Kyle's gonna have a license or Kyle's using GitHub dot com for free. And we've always had, you know, API rate limits, you know, and like things like that. And that's usually where folks are seeing this, you know, the agent back pressure, I think. I think the goal is that if you want to be able to do way more, if you want to be able to like, Peter Steinberger says, you know, 150 agents are doing everything all at once, you know?

• 8:50Speaker 02

  That's great. We want to be able to enable that to you, but at the same time, I want you to have a great core GitHub experience, you know? And at the very least, there's some. Round of agent usage is part of that that is necessary. You know, I need similar to how we way, way, way back, right? You'd have free public repos, but you didn't have free private repos.

• 9:11Speaker 00

  Yes.

• 9:11Speaker 02

  You know, and then we said, okay, well, actually like it's fair for an individual to have some code that they don't want to put out into the world and we'll give you free private repos. You know, it's a lot easier to do that. So GitHub is always evolving as the industry and community does. But we're always sort of focused on, I need to make sure you, the dev, have what you need to be successful. You know, and then work with enterprises, you know, to make sure they have what they need to do at scale, which is usually a little bit different than what, you know, an individual dev is doing.

• 9:43Speaker 00

  Yeah, and I guess the business model pricing kind of that all leads back into like the wider Microsoft orbit. And because you have a dual role now, right? A partial responsibility for the wider kind of marketing org. So do you want to talk me through how that's changed and how you prioritize between those two?

• 10:00Speaker 02

  Yeah, I mean, so I've been at GitHub for a very long time, 13 years. And, you know, as a developer myself and leading engineering teams for a lot of that time. And I think what's always been unique about GitHub is we really, really focus on the dev. Like we're building tools for the developers and the fact that people like enterprises are buying them is awesome. And that's definitely great, but we're not building for the buyers. We're building for the developers and 100%. And so in this, and that's like been my focus as the COO of GitHub, which I continue to do. And then now as the Chief Marketing Officer of Developer for Microsoft,

• 10:41Speaker 02

  my goal is to look across all of Microsoft's tooling, their developer tools, their technology that they're bringing to developers and making sure that we're bringing like holistic solutions that you can use that are like authentic, you know, to developer experiences. And at events like this where, you know, we've taken a very different approach to build this year. We're in San Francisco first off, like the vibe is a bit different than, you know. Conference hall setup, you know, really focused on can I go to a session? Can I use the thing? I don't want to be pitched on a thing. I have to be able to use it expo hall, kind of so on and so forth. It's really bringing that expertise and, you know, love and focus on the developer that GitHub's always had

• 11:26Speaker 02

  to have even broader impact throughout all of Microsoft.

• 11:31Speaker 00

  Yeah. And did I hear you say that this is the first build that you've had external contributors?

• 11:36Speaker 02

  It's the first build that I think by intention, we focused on having, you know, speakers, you know, from the community, like in these primary sessions, you know? That includes, you know, in the keynote, we had a bunch of folks like Peter, you know, there's sessions from, you know, SWICS and others as well. I think that it's important, like software development is a team sport, you know? It seems silly to think that there's any one company, one group, inclusive of GitHub and Microsoft and everyone, that can just answer every single question. That's not how software gets made, you know? We're all at least using open source and we're building on the backs of these giant open source projects.

• 12:19Speaker 02

  Let's invite people in that can help tell their part of the story together. Cause I deeply believe that that's what developers want. I know that's what I want, you know? I know that's what my friends that are developers want. And when we look at the events and we hear the feedback, they're excited to see people from Microsoft, from GitHub, and then, oh, I get to see this outside perspective at this event. It's really, it's really meaningful.

• 12:44Speaker 00

  Yeah, that makes sense. And it's a very competitive market, right?

• 12:48Speaker 02

  Sure, yeah.

• 12:49Speaker 00

  Like, yeah, the most competitive market probably, maybe the last competitive market, I'm not sure. But, but like, how do you differentiate in all of that, given the pace of change is so quick?

• 13:00Speaker 02

  Yeah, I mean, I think we continue to focus on our roots, which was, you know, we care a lot about like developer choice. It's always been true. We care about building for builders and enabling builders. And so I think we're in a moment that's like really interesting because we've Went from an era of having a ton of APIs, all this access to a little bit of an unintentional walled garden setup. Or you get an affinity. Sometimes I'll say it's a little bit of a mousetrap. And then you realize, oh, this thing's really interesting over here. And then I have to go learn a new thing or a new tool or a new account.

• 13:41Speaker 02

  And I think for us, we always want to enable developers that are building with GitHub to go use these other tools. And we'll partner with everyone to make that as simple as is possible. And while I think that there's other folks that are doing similar things, I think the ability to do that across the entirety of building software, and not just the code gen side, or not just the collaboration review side, but across everything, is a real superpower of ours. And so I think you'll see us invest in our own tech. Like, we talked about the new Microsoft AI models that we'll continue to bring to developers. We're also continuing to partner with Anthropic and OpenAI and Google

• 14:25Speaker 02

  and anyone who's bringing a model to market or a coding agent to market. We'll partner with you and we'll both let you bring that to us or we'll omit it through GitHub and GitHub Copilot. That choice is core. And that's something that I don't think we'll ever back down on. Because if we do, developers will still choose. They'll just be stuck in another mousetrap. And we don't want the world of software to be like that.

• 14:55Speaker 00

  Yeah. And when you're making the decisions internally, like there was a news cycle recently about how cloud code licenses are being canceled. How do you make the trade off between dog fooding your own products, like using the new models you made or using the GitHub Copilot app, desktop app, versus letting developers experiment with other tools?

• 15:18Speaker 02

  Yeah. I mean, we all are using a variety of tools because otherwise you lose track. Or you're too interested in your own. Own work. So like for me, you know, I've been a daily driver of a MacBook for many, many years. I use Windows PCs on the weekends when I play video games. And I got this role and I have my Mac, I have my PC and I have my Omark E Linux box. So I can make sure that every weekend I code most Saturdays. I do my kids' sports activities in the morning. And then in the afternoon I'm coding and I'm swapping between the boxes because I want to understand like, okay, what's that experience? You know, the GitHub Copilot app I only use on Windows because I want to make sure that

• 16:02Speaker 02

  developers who are on Windows also deserve great apps. You know, it's not just the audience that's on a Mac, for example. And that's true across our teams, especially like when we're looking at, okay, what about the coding agents? What about the harnesses? What about the desktop apps? What about memory management? What about, you know, everything? We have this really great culture of just, you know, experimentation. Everyone is building and using these tools. Well, obviously, we're putting most of our energy into our own tools. It's such a blind spot that I think it's happened to GitHub in the past where like, when you're doing something and you're doing it well, you really laser focus. And that's what every piece of startup energy says, right? It's like, look down and just keep moving, keep moving fast.

• 16:46Speaker 02

  And I think that's my optic. You know, I think that while I can't spend every day using every tool, when something comes out, I want to know why this is really great. Why are people having a great experience with this? Not only so I can understand, but so I can figure out, okay, well, for our goals, for our goal of developer choice, I don't need this. Like, I want to focus over here, but I want to know why a dev would pick these tools. And the same thing goes, you know, the same thing goes for our teams.

• 17:18Speaker 00

  Yeah. And how do you, how do you filter? Because obviously, a lot of these ideas are relatively short-lived. Enterprise, the product development cycles are longer-lived. How do you decide?

• 17:27Speaker 02

  Yeah, I think that like, right now, we're in a moment where we're really looking at the like, the short term in capturing the ability to have a multitude of, you know, agent sessions. This idea of just, you know, because that, that seems quite clear. You know, everyone's doing it, how can we cement it? But it seems clear on the longer term path, models are going to continue to get better. The prices of tokens, like token economics, is going to be a bigger, bigger factor in like what models everyone is using. And I do strongly believe that we're not very far off from having serious, the serious ability to use, you know, something above a small language model on a local device, you know, to be able to do some of our work.

• 18:08Speaker 02

  And so if I assume that I have all this optionality when it comes to tokens, you know, effectively, the thing that I think seems to be true from the beginning to open clouds and now is this idea of like personalization or mine or context or fine tuning with context or like, you know, memory, all of these ideas seem to be a truth that's been there since, you know, ChatGPT came out or GitHub Copilot came out. And there's experiments, but not a long-term like vision, I think, for this, like across the industry. So I think it's a good example of like where I need to get you to use agents incredibly well, a lot of them, because like if you're, if you're into using agents, you're not just

• 18:53Speaker 02

  going to be staring at a single agent working, but that's not going to give you a long-term great experience. Using an agent that you feel like is completing a thought for you will give you that great experience, especially if you did not have to personally codify that thought. Yeah. To your agent. Always remember that I insert thing. That's a lot of work, yeah. A hundred percent, like it should, it should be able to intuit that or potentially, again, like, you know, a post-trainer, fine tune or frontier tune, like a model that deeply understands me and how I'm using the work. Yeah. That is, that is kind of how we're looking at it. It's like, sometimes it's short-term and sometimes we got to take a bunch of bites

• 19:36Speaker 02

  of the apple or a bunch of attempts at the long-term. Yeah. To get to something really tangible to help us move forward.

• 19:43Speaker 00

  Cool. And I heard the term hill climbing like 100 times yesterday.

• 19:46Speaker 02

  Yes, yes.

• 19:47Speaker 00

  And I'm a big proponent of that because you know, experiments with DSP, audio research, a few others. Can you talk a little bit about how that's become a big focus?

• 19:58Speaker 02

  Yeah, I mean, you know, I think Satya and Mustafa talk about it a fair bit and Jacob too, leading the co-pilot group. The biggest thing that we've kind of learned is we need to use the, you know, the use of the tools as a core way to improve the underlying use of the models, our own models, et cetera, in just the evals that are necessary to ensure that we're actually improving from things like, you know, using the thumbs up, thumbs down data that comes in to using like whether you're accepting it and how much you're accepting. You know, all of that data is enormous to create that magical type of experience that's

• 20:39Speaker 02

  not just for you, but for everyone. And so every week, we're talking about the hill climbing results, you know, we're looking at the data, we're looking at the improvement, we're looking at both the hard measures and the soft measures because sometimes the hard measures and evals and Rubik's will show that we've made an improvement, but like user sentiment will crash.

• 20:59Speaker 00

  Yeah.

• 21:00Speaker 02

  You know, even with the same latency and performance.

• 21:02Speaker 00

  It's overfitting.

• 21:03Speaker 02

  100%. And so like being able to, being able to really do that loop incredibly quickly. And then I think the main goal is giving everyone one of these hill climbing machines and not have you have to do it the kind of hard way that we've all been doing it. But particularly if you're, you know, in an enterprise and you are using M365, we know so much about that data, or we could know so much about that data because of all the assets, all the documents, the chats. And so being able to, you know, turn on something like Frontier Tuning and using on the, you know, using a MAI Thinking One as the base model, it

• 21:45Speaker 02

  shows real results without having to do all that extra work. And it's been interesting because when I first heard about this, I'll be honest, like I was like, This is like a magic parlor trick.

• 21:54Speaker 00

  Yeah.

• 21:54Speaker 02

  You know, that is not gonna be real.

• 21:56Speaker 00

  It can't really work, yeah.

• 21:57Speaker 02

  Yeah, you know, and I think the reality is that sometimes where the alpha is, is like where it feels like this is too simple to work, you know. You know, we all have all this data and what are we gonna do with it? We have to do all this effort to make it work. But I think so much has come down the pipe to allow us to just use the data and improve, look at the workflow and improve, and just keep doing the hill climbing. That's why I think we say it so much, is that it's not these moonshots or like, oh, hill climb. It is just climb, climb, improve, new eval, improve, new data, improve, and just keep going to get to the point where, you know, we're able to launch these models, seven models for ourselves, and then, you know, allow customers to use the same or similar, you know, tooling to do it.

• 22:41Speaker 00

  Is that the answer to stopping the $200 subscription, becoming a $2,000 subscription?

• 22:47Speaker 02

  I mean, like, I think that the, you know, $200 subscription to $2,000 is really gonna be not only, you know, making these models or, you know, frontier tuning these models so they know you better, but I also think it's really, really gonna be about how can we, particularly for developers, you know, help you automatically choose the models and potentially either have like a model in that step.

• 23:15Speaker 00

  Like their model router in GitHub.

• 23:16Speaker 02

  100%, exactly. Like the, you know, auto model router with task content in GitHub. Microsoft Foundry has a model router as well that can do this, you sort of at an API level.

• 23:27Speaker 00

  Yep.

• 23:27Speaker 02

  The more and more that we can help you, you know, tell us a bit of like where your bars are, like this is an incredibly hard problem and I'm willing to go all the way to the top, or I don't, I just kinda wanna sit, you know, here and let us help choose the models. Because there's a lot of times where a lot of the reasons why tokens are expensive is because we're all going and choosing our model of the day or week or hour, you know, and those models are incredibly expensive. But my train of thought is slipping in and out of a hard problem to like a simple problem.

• 24:00Speaker 00

  Yeah.

• 24:00Speaker 02

  I personally, I feel like I'll, you know, I'll get an agent to do like an enormous amount of work. And then there's always that last. Step that is like a smallish thing, you know, like, oh, I don't actually like change all the naming of this to this.

• 24:13Speaker 00

  Yeah.

• 24:13Speaker 02

  And that's like a find and replace, you know what I mean? But I'm but am I going to actually go and like, oh, I want to save tokens right now. So I'm going to go off a four eight or five five and down to haiku or something, you know, probably not. But the tools could.

• 24:28Speaker 00

  Yeah.

• 24:28Speaker 02

  And I think that will really help us, particularly in the enterprise, but even for, you know, individual developers and, you know, folks that are building like automations and using their copilot, you know, SDK to power that it'll it'll help them too.

• 24:42Speaker 00

  I did something a little bit weird. I hope you don't find it creepy, but I made an AI version of you to practice this interview.

• 24:48Speaker 02

  No way.

• 24:49Speaker 00

  Yeah, and it's actually been pretty spot on so far, and hopefully you think the questions have been good.

• 24:53Speaker 02

  They've been great. Now I want to see what the AI Kyle said.

• 24:56Speaker 00

  And yeah, it's just in the terminal. I didn't have like, I didn't go the full whack and make a video thing, but amateur. But I found it immensely useful. I like, I just wanted to ask, like, what other like weird things are you seeing people do internally or externally?

• 25:10Speaker 02

  Oh, man, so like, it's so funny that you say that because I I do a very similar thing where like I I have both like by the app and then I have a claw that can't talk to work stuff, you know, just so I have like separation of a state where I spend a lot of time having it read everything I write and say, like this interview will get fed into it ultimately. And every day I get a like, like a comms report that's not like what Kyle said, but like, Kyle, you keep saying this.

• 25:45Speaker 00

  Yeah, okay.

• 25:46Speaker 02

  This isn't super clear. Like, you know, based on how you speak, because I I find that I write and speak in like a very particular way that I like, I want to use a lot of metaphors. And so it'll just give me examples of metaphors that are clear.

• 26:00Speaker 00

  Yeah.

• 26:00Speaker 02

  I find that the like self improvement loop as a human from these agents to be incredibly powerful. We used to talk about it way back with Hubot at GitHub, like chat ops. And we used to say like, humans are way more willing to take critical feedback from Robots than other humans.

• 26:17Speaker 00

  Yeah, it's less threatening.

• 26:18Speaker 02

  A hundred percent. And so when my open claw that I affectionately name Baxter, you know, tells me how terrible I did in something like,

• 26:25Speaker 00

  Yeah.

• 26:26Speaker 02

  I feel way better going, tell me why. And then ensure that when I'm writing emails, when I'm writing a script or I'm reviewing details, that you're giving me that feedback. So a lot of my agent loop is really about me and less about like the software side. I still have all those tools too, you know. But it's always looking backwards. It's going, okay, the last seven days, I'm going to read all Kyle's emails, Slack messages, you know, and then give me feedback and then look back at what the agent told me to do. Did Kyle do it? And go back seven days. That loop is like super, super, super powerful. And I think honestly, like the type of personal consumer experience that I want out of AI, you know, to be able to tune these tools that way.

• 27:09Speaker 00

  Yeah, we need to recursively self-improve as well.

• 27:11Speaker 02

  A hundred percent.

• 27:12Speaker 00

  Yeah, thanks so much, man. I appreciate it.

• 27:13Speaker 02

  I appreciate it. Yeah, thank you, thank you.

• 27:15Speaker 00

  Enjoyed that.

• 27:23Speaker 03

  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 ChatGPT. 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.