⚡ Inside GitHub’s AI Revolution: Jared Palmer Reveals Agent HQ & The Future of Coding Agents

All right, we are here for a very special edition of Lanespace with my buddy, Jared Palmer, SVP at GitHub and VP at CoreEI at Microsoft. Correct. Dual title. Yeah. Twice the fun. Is it weird to have two jobs? You know. I'm only on, I'm only, to full disclaimer, I'm only on day 13, I think. Yeah. So early days. So, so far, so good. So far, so good. We've been trying to get you on the podcast for two years, I think. I think so, yeah. you're a busy guy. We don't do it in person. Yeah, we have to do it in person. Yeah, exactly. It's way better. I should also plug that you have, if Jared Palmer fans should dig into your previous podcast with Ken Miller. No, let that. It's from the inner room. Okay, so, Shout out to Ken. Shout out to Ken. Before that, you were building, I guess like V0 and AISDK, and you were just sort of VP of AI at? At Vercel, yes. Yes, all AI initiatives and vibes. Yeah, and I feel like basically you went from sort of building one coding agent to now being the home for all coding agents. Is that like the general vibe of AgentHQ? I think that's right, yeah. So backing up, I spent the last sort of two years or so building vZero at Vercel and AI SDK. And then the summer took time off and now joined GitHub. And today we launched AgentHQ, among other things here at Universe. and yeah, it's going to be the home, we hope, of not only agents but also developers and it seems like the gravity well of this new collaboration space that we're trying to build. Yeah, what do you think basically that GitHub can do that you couldn't do at vZero? GitHub is an enormous platform, right? Yeah, it's under 80 million developers. It's just the scale is immense, right? And vZero was focused on not only one language but one framework. Right. And a specific problem space with a built-in renderer. And, you know, for those who are not aware of v0, it's like a fault or lovable, but it's built by Vercel. And it's focused on building Next.js apps, specifically Next.js apps. That constraint was rather liberating for the team at the time. And it lets us really, like, laser focus. It does. That's right. Well, that it. I hope. Thank you. I hope so. And obviously, at GitHub, you know, we're the home of all languages and frameworks and developers. And so the scope is broadened. And yeah, it's just a different part of the map, if you will, right? Yeah. So you've been basically covering the entire journey of coding agents from the start. Like, what do you think, what's your personal journey through coding agents, right? Like, we started out with Copilot, obviously GitHub started the Copilot trend. Sure, sure. When, tell us about the origin story of V0. Yeah. and then how that develops and maybe where, like what you want to see next with history. It's funny you ask that. As I've told this story multiple times, I feel like I've unlocked different parts of it in my brain by going back, you know, like, so maybe we'll have to figure out how retrieval memory works. By the way, interesting how memory works for agents. Totally. That's why I brought it up. This is small. Sometimes you discover new paths, right? Yeah. Anyway, the story goes like this. So when ChatGPT first came out, obviously it was incredible, right? Like world-changing, immediately, faster-growing product ever. I looked back at like the timeline and dates and we were very early, like when I was at Purcell, jumping into AI stuff. But the journey kind of went like this. So at the time, actually there was no AI division, there was no AI group. I was actually the director of engineering for all of Purcell frameworks and I was helping Next.js. Svelte, right, yeah. So Next.js, Svelte, Turbo Repo, Turbo Pack, Webpack, and all internal dev tools at Vercel. And I was helping the Next.js team dog food and test the initial implementation of server actions. And instead of building a to-do app, Guillermo, the CEO of Vercel, was like, why don't you build like a playground? And I was like, okay, cool. So that led to the AI playground, which is now just part of AISDK. We'll get there in a second. Which, by the way, iconic for like side-by-side, but also the... Right, so now that's CEO. So G told me that NatDev, I got a DM. I remember because I was at a bachelor party. And Guillermo, internally online, sends me notes like, Nat.Dev is launching on Monday. You have to ship. And I've been working on it previously. So you have the same idea. Yeah, so he got wind of it, I guess. So I definitely had to jump into motion. And I didn't think we didn't even ship chat first. Guillermo sends me this DM over the weekend. I'm at a bachelor party. And he's like, Nat.Dev, this side by side. He sends me the link. And I play with it. I'm like, ciao. Okay, so I spring into gear, ship the AI Playground. What was cool about the AI Playground was it forced me to go through every single model provider's API docs and figure out their quirks of their nuanced streaming. Because at the time, it wasn't like everybody used OpenAI. It was like all little quirks. Some of them kind of were compatible. So that was my first foray. And then launched AI Playground. That shot to the top of Hacker News. And I remember I didn't even implement chat because that chat wasn't actually like a fake, like wasn't as important. It was just like complete completions. So eventually we've acted a chat and that project, out of that came AISDK because I had already looked at all the model providers and all the accommodations. I was like, okay, here's that chunk of streaming code you need. And then AISDK found that sort of niche of like, how do we focus on the part that we're going to be good at, which is like that UI aspect of it, but then also knock it in your way. So that, we shipped AFL-Aground, then AISDK launched. And then, you know, we're always about demos and having great starter templates at Vercel. And I remember writing Gigeru. I was like, you know what would be cool? This guy, Shad Cien. Oh, man, he seems like amazing. And his UI library is doing great. Why don't we team up and ship a ChatGPT clone open source? And we did. We shipped this awesome template, which is now called Chat SDK, but it's great. and what that did though at Vercel was it set us up for like rapid experimentation because we had this really good like pretty full-featured chat GPT ready to rock with all the latest features. So when it came to like rapid prototyping that summer, now we're summer 23, it was so great. It was like liberating. So I remember at that point I had gained some momentum internally and pivoted almost entirely to AI and I had Shu Ding who you're friends with and Max Leiter and Shad Sien now were cooking. And I think at that point code execution had just come out. I think that's my timeline. Yeah, the Cruel Sandbox interpreter. Intercode interpreter. That's what they call it at the time. And I had a very, as soon as I saw this, I had a very ambitious idea and proposal to present to Guillermo, which was like, what if there was some, and mind you, tool calls don't exist. The context window is 4,000 tokens. So there's not much here. What if we had this thing where you could prompt, and sometimes it would do code interpretation, and then maybe we could sort of, sometimes it would do code interpretation, but then other times it would choose to render UI, or then it would render sometimes a document. Inline in the chat. Yeah, it would just have different sort of render. Generative UI. Yeah, and maybe you could pipe them together. So the output of one could pipe. So if we did code interpretation, we coerce it to always emit tabular data. Maybe we could pass that to another prompt that was like a UI. And just some idea there. It's kind of crazy. But if it sounds like these are just tool calls, that's exactly what these are. So it became pretty obvious that I can't be zero-mine. At the time, we just had a sort of security debate. Should we code interpretation with the ability to fetch data? Giving it internet access was kind of... Now, they're like, fine. whatever, do whatever you want, wow, wow, west. But at the time, it was like a little scary. So we kind of said, okay, no to the code interpretation, but this UI thing, it's pretty neat. And so that, this like prompt to UI, that was like the aha moment of v0, but the models were not very good, right? Or relative to where they are now. And it was 4, GPT-4 era? This is just into the GPT-4 era. And now we're probably at a 16,000 token context window. so you can't really do chat. So we had to kind of invent this kind of new paradigm of like fake it with completion. But that forced us to do sort of the click, the initial v0, which launched, I think, in September 23, it would look more mid-journey. In fact, if you like the original tweet, it was like mid for React because it was all very visual And you could click on different components and elements and reprompt but it was again we were kind of hacking this because we didn have chat and we didn have tool calls And then fast forward again, you know, that launches, and then probably like nine months later, it took us like nine months to get to like a million ARR, this little team, but then the models progressed. and from, you know, GBT-4, GBT-432K, the big boy. We never really got GBT-4 Turbo working. I don't know why. It should never happen. And then switch to other Frontier models and then start doing our own models and stuff like that. But fast forward another 10 months or nine months or so, and then we rebased towards chat. And now the models finally could do chat. And the artifact pattern had evolved, so it was time to rewrite. When we launched V0, the chat version or the new V0, whatever I'm going to call it. It's like 14 days, another million MRR, 14 days, another million MRR. It was like a rocket ship after that. And that just proceeded. And we just kept cooking. And so that's been the journey. We just kept perfecting. And what was really liberating for us was actually the focus on just one stack or one framework. When everybody else was trying to do general purpose coding agent, we were like, no, we're just going to focus on Next.js front end and ShadCN. And that allowed the team to focus. So that's the story arc. I mean, to be fair, like, because Next.js is so dominant, basically everyone has to be good at Next.js. Right. But being focused on, like, even right down to the UI library and component stuff, like, that actually helps a lot. We also started working with all the Frontier Model Labs to help because it was in our, Vercel's best interest to have them be great at Next.js. Yeah. And also because of the post-trained models, and you can read about this on the Vercel blog, like we can, the post-training like harness that we created, we started sharing and stuff with other model labs and stuff like that. And we had all our data in a very hygienic state to work with them. Did you ever debate internally? And because, you know, from my seat at Cognition, I can also see this, where you should pick the best qualities of every model and string them together in the V0, or you have the model selector and you let customers choose. We went back and forth. And I think, yeah, you know, we launched, we went back and forth on all this. I think at the end of the day, there's pros and cons. Yeah. One of the benefits of having your own branded model or synthetic or composite is that you can stick these things together. Yeah, there's like higher levels of, and now it's a little different with this agentic flow. But even look at what you guys launched recently with ZZRG Rep, right? So, Search, is it going to be a different model than what generation? Yeah, the Genesis. but like, because it's a sort of, but like search and Genesis are two different, like entire subsystems, right? So you can have search evals that are gonna be totally different. And so how do you, so where we ended up now, where are we, where it probably ended up now is like, for a long time, we didn't have model selector and then we had our own models, which were composites, which we talked about. And then like, and that would allow us to, you know, mix match. I think that's probably what... It's also nice because this is like the product app. You get to brand it, right? And you can decouple it from the launch of the Frontier Lab. Yes. How does Cognition even bill for it? They use Cognition. It's a synthetic unit, right? Yeah. So it gets a little wonky. Yeah. We can go on for pricing this stuff. It gets challenging. But the nice thing about having the brand name model is that like you get to co-launch with the provider and they'll hype you up. But your billing needs to then is capped at whatever retail is, right? Or some... Right, right, right. You can't really charge too much of a premium. You can, but... Right, but then people are buying... Sorry, I can't put my own IP. Yeah, I can't put my own IP, right? And it's like, well, then how do we charge you for sweet rep or something? Yeah, yeah, yeah. And so like, I think it's some part of it is the cynical, like you want to create a sustainable business and independence from the model labs. But the other part is genuinely, you actually do get better performance. You string together all these things. Yes, and so it's tough. I think, well, we've switching gears to GitHub. We are all about model choice now. And what's cool is that we also have Copilot, which is our harness, and Copilot CLI, but we also have third-party harnesses like Cloud Code and Codex and Cognition now in Agent HQ. So you kind of get the best of both worlds. And like, I think that's going to be awesome and ultimately what people want. Yeah, I think also the model layer is not the right abstraction to do the switcher anymore. Which is weird because that's where you started with the ISDK. Yeah, exactly. But now it's like the model and the agent have to be strictly tied together, like very, very strongly balanced. You can't loosely bound it and just do a generic interface because then you're just going to have the lowest common denominator of all the models. If you're in Agent World, which may just be better than Chat World. like in general like better agent world is a much better abstraction I'm calling it agent world but I mean by like a loop with maybe compute runtime and like files that's that your definition of agent you're dropping your official definition here no don't put me on stop but um maybe no so my initial definition of agent for AIS because like I actually thought I was dying on this hill because AISDK everyone else is an agent framework and I think maybe they actually went to like this I don't know what it says on the front page now but like who knows but like an agent is uh you know, an agent is orchestrating, you know, an API request with a queue and a for loop. Okay, but a coding agent now has meant so much more. There's like these, you know, coding agent SDKs and you've got sandboxing and file systems and tool calls. And I do think that is a uniquely, I've called that agent world and I'm trying to get coding agents here. And yeah, I think that that seems to be where things are going. And even I believe the Claude Excel agent is basically, I was talking to Mike Krieger backstage, I think it's related to Clock Code. It could be. I actually don't know how I should implement it under a hood. It wouldn't surprise me if it was. They see you very all in on skills, which is kind of an interesting... What do you think of skills? It's kind of... DXT, which is like the sort of bundled version of MCPs. Okay. The reason you don't know about it is because it wasn't very popular. Okay. So skills is kind of like the second shot that is very... LLM pills. It's like, just read my markdown and just read this directory of files and go nuts. As long as I can understand that you have the capability to run code, to read files, you're good. And actually, that is the universal interface, which is a file system. Right. Back to agent file system. Yeah, which is kind of cool. Yeah, so I mean, I think what you're hitting at is this philosophy of our understanding of what coding agents, the minimum bar is over the last two years. you've lived this journey and now you're basically the kingmaker I don't know about that you run AgentHQ and I imagine you have other projects too but AgentHQ is the big one that we're talking about here what are you seeing from the different agents? what do you want this to become? such a good question I think that AgentHQ and GitHub itself needs to co-evolve. And, you know, one of the things that Microsoft has done really well is by putting things that are alike closer together. And so you think about the new core AI organization, you've got Visual Studio, Visual Studio Code, GitHub, and parts of Azure all in one. And obviously the GitHub team and the VS Code team have been working closely together for a long time, but now we're really close together. And I think for me, one of the cooler things that Agent HQ can sort of offer is this seamlessness, this fluidity with your workflow, right? So if you saw in the demo today, we saw a demonstration of you use AgentHQ, you fire off a task, and it creates a PR, but you can also open that PR up in VS Code in one click. And that's awesome. And I think the vision for GitHub as it evolves is to look at those touch points where AI can be sprinkled in, you know, salt-based style, into the native workflow, whether you're assigning an issue or maybe some new stuff that I think we should focus on. Maybe it could be like, how do we resolve a merge conflict? Oh my God. Right? Like, how do we maybe pop open an action or like get in, right? And so- I think solving a merge is my definition of EGI. Totally. But like you get that error on an action and you like we all been in that sort of flow where like actions kind of don work or is that tool act If you trying to I don have that setup on my machine I haven done this in a while So you're pushing up and you're this like, okay, what if we could just put, like, you know, comment or kick off a task to solve this for you or do things there. I think what I'm trying to describe is this like this workflow where it's just like seamless and fluid and you can stay in a flow state across whether you're across, like across all devices, mobile, web on github.com or in your local editor. And I think that's where my focus is going to be in the next six months or so. Just a side tangent on this. One of the things that Microsoft also owns, I don't know if it's Microsoft or GitHub, is dev containers. And I think a very important concept for sandboxing environments, whatever you call it, it is kind of a light version of what Docker containers are. kind of. Do you see that as a standard that we should invest in as like a thing? Because it's supported in VS Code. I don't think it's just that popular outside of VS Code. Yeah. It's used internally at GitHub too for like development at GitHub. Oh yeah, yeah. Which is cool. Yeah, I think they were so far ahead almost. But now there's like sandboxes, there's so many these days, right? So I think Cloudflare just launched theirs. Yeah, there's Daytona, there's here, Rissell, modal, which I think Lovable uses. I mean, you probably have your own. I don't know. What do you guys use? Just some Kubernetes pods. Okay, you guys are rolling it yourself. I think that's maybe the runtime. But there's work and discussion about what that runtime should be, even internally at Microsoft. We've got a couple different competing things, so we'll figure it out in the next cycle here. There's a great point. There's a lot of cool stuff that is in a dev container. You've got VS Code loaded, you've got a file system, you've got a sandbox, you've got the security protocol. It's also wired into GitHub Enterprise and ready to be packaged. So there's lots of goodness there. Yeah, I see the number one pain points that Comission has, but also Codex, also presumably the other guys, is repo setup, which is effectively what dev containers and a Docker file does for you. It's like, run this thing, then that thing, set this up, do that thing. Why is it so hard? Why haven't we solved it? I don't know. I think it's hard because you can't predict what's in the, what's in the repo. Right. So it's like, and you don't know when they bundled FFmpeg. You just don't know. Right. It's nice when like, if it's just Next.js, you just run PMPM install. Correct. Correct. You, you can like do special, like there's obviously through constraints, you can make optimizations. And I think the general purpose container is just like challenging. That being said though, I think there's probably some work to do on, you know, auto detection and preempting. and stuff that can be done there. But it's just a bigger, it's a broader problem space, right? Yeah. And yeah. So fun fact, when I was at Nellify, I actually wanted to reach out to Rizal to do like a standardized open source auto detection thing of frameworks. Oh yeah. And like we never, we never really got internal momentum on that. It was an idea. I was like, shouldn't this be open source, you know? Yeah. Like auto detection is a, is a common utility that everyone needs. Yes. Yes. I remember that. I'm having a flashback. That's like, have everyone knows their best and yeah probably we shouldn't all build it right now it's and then also like what are your defaults they're not exactly the same which would be better to like just having even the same like a preference stack yeah of defaults yeah is the right yeah would be great because then we can move the whole ecosystem together from like the pmp ever bun right okay so are there other movements or protocols or standards that you're interested in like MCP was a big winner this year. There's other, I don't know, A2A, ACP, all this. That's interesting. I'm not as familiar with... ACP, the payments are one or the Zed one? Oh, no, the Zed one. Okay. And then the payment that was a Stripe or Coinbase? Stripe. Stripe? Yeah, that's very cool. We've had him on the pod. Okay, yeah, that's very cool. It'd be interesting to see if that takes off. I mean, it's Stripe. Yeah, but it's supposed to be adopted by the clients, right? And I think that's It's fascinating. The MCP is huge, it seems. It is the way that a lot of the, especially when it comes to digital transformation or some of our enterprise customers, it's where they're able to add context. In addition to that, we also have custom agents that we announced today too. So you can work with prompts and stuff within your agent HQ and customize these agents for different tasks and those can have MCPs and such. And I think that's going to be really powerful from a platform perspective. It gets me excited. That's what I think is shipping now in the next, but we're always on the lookout for like the next thing. And I don't know, what's on your, what's top of mind for you? For like standards? Standards. Standards? Dev container. Dev container. Look, I think dev container just is a PR problem. It's a great idea. Just no one makes it interesting. I think you can do it, basically. Okay. Add it to my list. But before that, probably you have a bunch of other stuff that I I do want to get to, but just staying on the AI stuff, I think we're actively exploring computer use as a thing because it kind of got going a little bit. People were very excited, and then they found out it was slow and bad and inaccurate. It is computationally intensive, in my understanding. It's getting better. Yeah. Especially with open vision models like DeepSeek OCR and Omo OCR. Like, just give it a few more turns of the scaling. It seems like it's like you need that edge case and primary. It just seems like a modality worth pursuing. I think a lot of people are, on the core gen side, the core agent side, a lot of people are trying to think about, all right, we had this evolution from co-pilot to a more energetic cloud code situation is where I think that the status is. What's next? What's the obvious next step? Making them good? Making them good, yeah. You don't like cloud? No, no, I don't. It's more just like, you know, the devil's in the details. Like, going from 90%, going to like hill climbing, it gets steeper, in my opinion. It gets steeper. And so going from 90% success to 95% to 98% to 99% to nines of success. Yeah. I mean, it's really hard. Paying Mercor a lot of money for expert programmers of open source maintainers to like... Then you realize along the way, maybe the users aren't that good at it. No, but I just think there's a lot of work to do to finish the swing. And there's a big difference between 98% and 99% correct. And that's like noticeable. And this used to hit, you know, if you're working on an AI product, you probably don't realize how, you've probably seen this. Like most people are blind, like living in la-la land about how poor quality their AI product lately is. Unless they're really measuring like the number of error-free sessions, like how many errors are coming from the infra providers how many requests are dropped how fast these things are and so that's something that we cared about for sale quite a bit do you have like a daily review of your dashboard, I don't know daily, daily, slow okay I thought you were going to say daily is too much no, I'm thinking of it like every three hours a roll up of key metrics and stats and like one of them was like error-free sessions and other things like that that was like really important because you know especially now with agents which are like multi-turn um i have a tweet about this that was like in 2024 which is that like agents will really only work when we get to not only like the more intelligent models but better reliability of the infrastructure providers right these aren't these are not inference is not like a database like update uptime right so there's still differences between providers there's little differences between performance and difference uptimes and that's why you see things like OpenRouter being very successful and different gateway products. Because, like, reliability, you need to switch. They go down all the time. So, long story short, yeah, we would do, like, you know, it was almost like video game style. Like, we'd have, like, all the data coming in all the time. Yeah. And that allowed, I used to joke, it's by mood ring. Like, good day, bad day. So, it was very successful for us. I think other teams should adopt that, like, data-driven approach. I think one thing that's surprising is the lack, the relative lack I still see on data analyst agents where you can sort of chat it, like add a Slack bot for the precise analytics that you want to generate. Because I think we're still in the BI era. Yeah. Isn't that weird? Yeah I totally agree It interesting that that space hasn been like captured as much Yeah Like I guess maybe now Actually I interested in this like shift to a way into like into knowledge work tasks with coding agents. Okay. I wonder... Using coding agents for non-coding tasks. Correct. Do you do that personally? Yeah, yeah, yeah. Yeah, what do you do? Well, like, I was, like, this summer I was doing, like, I was helping, I was trying to automate some of my dad's workflows and stuff like that. And just, like, some of his, he's got some Excel spreadsheets for accounting, financial accounting, or managerial accounting, I guess. And yeah, just point cloud code to that stuff and see what happens. It ends up doing Python and generating some scripts and it kind of got off down on the hairs, but it was like, even he saw that it was better at it than the chat client. Super obvious. It became kind of obvious. Yeah, it felt better. I wonder if he can try Cloud for Excel and see. Yeah, I got you right. And then, of course, you've got the browser, not browser, browser space agents, but not computer use, but browsers with agents. Agent browsers. Agent browsers. For flexibility. Everybody's a commenter. It's like, is that the better? If that's true, then maybe the general purpose injection point is there. Yeah. Have you tried any of the agent browsers? All of them. All of them. I'm currently maining Atlas, mostly because I just want to give ChatGPT a fair go. Okay. but I'm very stuck to the arc and like the vertical tab. Oh, okay. I think any pro user, like I have multiple businesses. How many tabs do you have? I'm context switching. I have hundreds of tabs open. I made an open source tool called Chrome Dump. You can find it on my GitHub where it literally dumps all the tabs open. It summarizes them and I can close it by deleting them on Markdown. That's pretty cool. It's nice to... So you just go on like a... You just go on like a... Like a... Like a bender. Yeah. And then you just dump it. It should be as easy to close as Markdown and Chrome isn't that good at the performance side of things yet. And you were working on some browser comparisons. I was. So I tried to build it in Tori. Tori explicitly doesn't want you to build a browser and I tried to fight it too much. I see. Very cool. So just to wrap things up, we're around about time. There are other side projects, tasks, and things that you've announced here. First of all, redesign GitHub homepage, which a lot of people don't even know GitHub has a homepage I'm legitimately I had a tweet which is Riz's tweet like print it out like you see the tweet like there's a tweet from Riz and it's like no one uses all of this stuff is totally useless I'll pull it up like I quote it out today because we like when we launched let me get it right because I got to do it right hold on was incredible how pretty much the entire GitHub homepage is useless and is 1.3 million views and 19,000 likes. And this was May 2025. So, Hurt, the team made improvements and today they launched a new GitHub homepage. Yeah, which I'm very proud of. And they should be really proud of. It's got tasks at this top. It's got recent PRs. Some stuff is still there, like your recent repositories. I think there's more work to do, but it's really overhauled and they did an amazing job with it. So, they nailed it. But more work to do, never done. and hopefully we can keep iterating with the community and everyone and keep going. The last thing I want to hit you on is Stack Tips. You asked everyone when you joined, what should I work on or something. I don't know if this is your job specifically. It wasn't. But why do people want Stack Tips so much? I think you have some history there. Yes. Anyone who's interacted with anyone at Facebook knows about Fabric Camera. Just about it, yeah. So can you explain what it is, why is it so hard? Okay, so this concept of pull requests, which we're all familiar with, you write some commits, you open a PR, and then you merge the PR, and you go about your day. So as you scale larger organizations, and you look at your history, and there are people who are very, I'll say, have near religious beliefs about how to do get right. rebase versus merge. There's a crowd that wants to fast forward the repository to preserve all the history. And then there's a crowd that wants to squash and merge into the anime. I'm thinking squash. Anyway, Facebook, and I've never worked Facebook, but in my previous startup, before Vercel Turbo Repo, I did a lot of research on build systems. And at Facebook, they have, not only they have their custom build tools called Buck, they also have a custom file system, and they don't use Git. They use Mercurial, and then now it's sort of custom, and it's all wired together. And at Facebook, they don't use pull requests. They have a different sort of philosophy. You can, it's sort of like the best way to think about this is like, imagine every PR just had one commit in it. You could branch them, and the critical thing is you can restack them. and then if you restack or make a change later, like earlier in the stack than later in the stack and these stacks are just diffs, right? The commits are just diffs and it's the term stack diffs. You can then collapse them and merge the last one and merge them in parts of it and it just gives you a little bit of a nicer workflow. And it's what people, if you work on a monorepo or you work on a very, very large code base, it's a really, really nice way to work. Especially you've got a system that will automatically restack. And then if you think even more deeply about it and get really deeper into the weeds, you can decide which diffs in the stack CI should run against if you get fancy. Okay. Like some kind of commit messages. Yeah, you could decide maybe this one doesn't need it or skip that one or whatever. And you end up getting these groups, these stacks. And it's really nice from a code review perspective because when you go to update or you can update a different part of the stack, It just makes it a little bit more fluid. And so it's what people want. There are a couple of tools out there in the market that do this kind of behavior. One's called Graphite. There are a couple others. There's a few many tools called Graphite. There's another Graphite right here. Yeah, yeah. And it's a great workflow. And so it's been the top pull request, or sorry, the top feature request. Thank you. At GitHub for years. From the community's perspective. I don't know, at GitHub. And as soon as I joined, the first thing I did, I was going to look this up. and uh well that's the first thing i asked how should make it up better and it was the top feature request right uh and then i went to go like okay investigate like any good product person would and there's been multiple attempts at this internally um going back to like 2020 okay and there was one very very very um polished attempt to in 2022 and it just i don't have all the context so but it was it was there was a pretty good implementation all the work was done the client and it reintroduced this new concept called stacks outside the pull request into GitHub and it was a little too risky. It was sort of deemed too risky, too big of a change. That's just what I was told. So anyway, we're we had cold meetings internally already and we're trying to weave it into planning and the roadmap and so hopefully we'll be able to share more updates soon but like it's a top of the list known feature at once. Again, heard. Yeah, and so we're at and like we're working on it. Obviously like something the size of GitHub to support this kind of new feature is not just a walk in the park because of the size of GitHub's Git implementation, but it's something that we're actively exploring. Yeah. Well, I think, you know, just to wrap all that up, I think it's really nice for someone who's so deeply engaged and coming from one of us, literally, that you now run things at GitHub and we can just add you. You can do that, man. And I think like Audrey Karpathy was the other day was saying like every company needs one of these where you can just like, hey, like this really should exist at GitHub. We love GitHub. We use GitHub. But like, come on. Well, yeah. Feature requests. Welcome. Like my DMs are always open. Oh, careful. I don't know. 180 million developers. I like 100. Whatever. I am of the philosophy that like all feedback is a gift. Like it's all a signal. Yeah. And the more signal we can collect, the better decisions we can make. and truly build this really, really useful website and company together. And that's going to be the future. And if we focus just on that, we're going to be okay. Yeah, we're going to be okay. All right. Well, thanks so much, Jared. This is a real pleasure catching up. Yep, likewise. Congrats.