# GitHub's AI-Driven Scaling and Enterprise Context Strategy

**Podcast:** Latent Space: The AI Engineer Podcast
**Published:** 2026-06-02

## Transcript

Okay, we're here with Kyle Bagel, CEO of GitHub.
Welcome.
Thanks for having me.
You're not just CEO of GitHub.
People know you as that.
Yeah.
You have a new role.
Yeah, so I have an expanded role now.
I mean, we've been working at GitHub for 13 years and doing all things developer, joined as a developer myself.
And now I'm also responsible as the CMO of developer for Microsoft.
And so all the kind of learnings and passion for...
developers and how we work with them and how we communicate and, you know, how we bring our products to market.
We're also bringing that expertise, you know, to the broader Microsoft ecosystem and helping every developer that uses a Microsoft, you know, product or would like to, to have a sort of similar experience that they've had with, you know, GitHub over the years.
So it's a big different role in some ways, but it's also just building on the experience that, you know, I've had at GitHub of just sort of, Tell the truth, be authentic, show people how to use it, and then let the products speak for themselves.
Not just doing that with all of Microsoft.
Yeah, and we'll be releasing this in conjunction with Build.
You've got lots of stuff planned, and we can sort of touch on that whenever it's appropriate.
I think one of the interesting things is I rarely meet a COO who's also a CMO.
I think you're very outward-facing, and you're very confident publicly.
um that's rare like do you actually view yourself as COO like what's yeah I mean what is your thing I think for me like it's been funny the titles have always been uh like always felt a little strange to me I mean I joined GitHub as a developer you know I mean I wrote so much of the let's bring that up yeah yeah you wrote the back end yeah I was going through like uh I was going through uh some old photos uh when you know folks were talking about you know how things were being built or how others would build GitHub.
I built webhooks and worked with teams building the API, built the platform layer, anything that integrated with GitHub.
Up until really 2018, I was built or ran the engineering teams.
And that's kind of where my, like the beginning of my passion always was, was helping people build things.
deliver them to their customers.
And so being a developer, building for developers was always super unique.
And I think as my role expanded, it became my ability to talk to not just developers, but also enterprise customers or business leaders and have this translation layer.
And then through all those years, GitHub has always operated pretty uniquely.
Post-pandemic, working remotely was...
Not as novel as it was when GitHub started in 2008.
But all that expertise of running remote teams, doing it well, became this sort of bigger role, ultimately turning into the COO role of how do we operate GitHub in the way that GitHub's always operated after the Microsoft acquisition.
And kind of so on from there.
So I mean, like for me, I think I still code.
I love coding.
But the problem has always been, like, people.
It's a much harder problem to both support our own employees, harder problem to communicate to developers and enterprise buyers what we're building, why it matters, because those are two very different messages.
And so getting to work in the mix of COO, CMO, also just being a dev, I think is what's kept me at GitHub for so long.
Yeah, apparently you have, your commits have gone up.
Yeah.
What's this?
What's going on?
Yeah, I mean, Reese called me out pretty aggressively.
So, I mean, you know, I think, I mean, as you can imagine, right, like you can see my like normal era of being a dev in the 2013, 2014 era and then moving into management and then ultimately the COO role.
I think what you see there is me like really getting back to coding thanks to AI.
You know, I.
Similar to attaching problems between how to market and how to operate a business and how to code, I find building agents and workflows that are connecting very disparate problems to be what's driving this.
Some of it's writing software.
A lot of it is connecting a ton of different data sources to help me out.
But that is completely me really, really diving in on the AI side.
in trying out our tools, trying out everyone's tools, like, um, but building for me, building for the like non-technical leader, though I'm technical, you know, and how we're, uh, able to use these tools more than just the simple, like call and response that I think, you know, a lot of the like non-technical, your employers, like you have to get, you have to use AI.
And so everyone uses like chat GPT or copilot or cloud or whatever.
To really get into like, how is this going to help me out?
I find that it's not the, I need to write a blog post.
I need to, you know, those simple examples, helping people find the workflows of like, okay, I need you to go through all the PRs today.
I need you to go through everything that we've posted online.
I need you to go through what we've did the last, you know, three months, go through all of my Obsidian notes for any mentions of this, then go through my.
transcripts at work where we use teams.
So like using work IQ, go call that MCP server, grab all the transcripts, go through all the Slack and then build me out the plan of like what this week's messaging actually was.
That's something that was like impossible because for me, I find AI in like what most of this like launch here is, is actually like less building forward.
It's actually like.
a recursive loop backwards.
I'm always looking at what had happened first, like go back through the week and tell me what we did, what worked, what didn't work, you know, and then tell me in the next, you know, three or four days, what would you tweak based on, you know, this sort of like looking backwards and then looking ahead a little bit.
I find that to be so much more valuable, especially for like non-technical because that retrospection is actually.
LMs are very good at that, you know, like finding all the patterns, pulling them out, and then applying that retrospection to just a couple of days or just like a short period of time is all a bunch of apps that I've built and launched, like a bunch of internal tools.
I use the new GitHub Copilot app, the desktop app with workflows.
Every time I crack open my laptop, it's running workflows for me.
It's just a ton of different stuff.
And of course, it all ends up on GitHub.
Of course, that's where stuff is hosted.
Man, there's so much to ask you.
I was going to leave the how do you run a company with AI thing at the end.
I have to ask one, double click one thing.
You're looking back at the week, you're understanding what happens.
When you say we, that's 3,000 people.
Yeah.
Yeah.
How?
I mean, I think, you know, When we started rolling out AI internally beyond engineering, right, one of the things that I was really, really passionate about is like we have to do this in a way where no one has to change how they work.
I don't want to have to teach you a tool.
I don't want to have to teach you something new.
And so for us, we tried out a few tools.
Most of them don't work because I got to get you on board.
You know, I got to teach you how to use it.
What we've actually ended up doing is.
We've built like a set of, you know, skills internally.
We have like we each have our set of skills and we've just been distributing even to the non-technical folks, the CLI.
And then effectively, we're just giving it access to like read about everything that we're writing.
So that's for us, that's usually GitHub, Teams, email and Slack.
So Teams for video chat, generally speaking.
Teams and Slack?
Yeah.
I mean, so we use Teams for video communication, but we don't use it for chat.
GitHub for a long, long history, right?
We always talk about chat ops and everything is built into Slack.
Every command, every flow.
Even though you've been acquired for, I don't know, eight years now.
Yeah.
You still use Slack?
Yeah.
I mean, it's a purpose-built tool for us.
so like bluntly expensive you know simply because all the tooling is uh baked in with that paradigm and they both have their pros and cons like but they don't work the same way like at all yeah i mean we still use a bunch of different tools because it's you know the purpose-built tools that uh we need but the same doesn't go for the rest of microsoft presumably i mean like the like you know, various teams like, yeah, various ways, you know, um, I think it just matters what you're trying to like, what you're trying to do.
Yeah.
Um, but we do, you know, we do work across kind of every tool that we use.
And then, uh, by giving everyone access to all of that context and like, um, uh, the new, uh, like work IQ MCP cert, which is quite cool.
If you do live in the M365 like world, uh, I can ask it.
all these backwards facing questions and it's incredibly important for our teams that are working remotely.
You know, there's a lot of stuff you miss when you're not in an office and we are spread out all over the world.
So most of that is looking back.
And then we post, we post either automatically into like GitHub issues or discussions, these sorts of like findings or like our industry reports, like what's happening this morning, today, yesterday.
A little automation gets run.
We'll use the app.
We might use GitHub Actions, like with our agentic workflows, just to go do that run.
And then we push it into GitHub, and we keep having a conversation.
So usually for us, it's about that sort of like looking back, looking forward on the non-technical side.
And then, of course, for a lot of those folks, it's also, you know, building an app, pushing it to GitHub pages, or pushing it somewhere to host it, et cetera.
But it's just like enabling everyone with that power of it's going to take me, a week to figure this out.
Instead, we're going, okay, like, I built a skill, let's put it into a repo, we'll all share that skill together, and then we'll use the CLI or now the app just to run it.
I think we're going straight into, like, the team management and productivity thing.
I think a lot of people are getting various levels of LLM psychosis.
How do you manage the bloat of skills?
Like, everyone has their thing, and they're trying to promote it to the rest of their peers in their org, right?
And obviously, whoever...
becomes a skill influencer internally becomes like an ai leader right yeah yeah sorts yeah uh i assume you have those yeah i mean like i think we have i assume it's a mess like yeah i mean there's like i like i think the reality is there's two pieces like first is i think that we're ending the era of these like massive beautiful perfect skills that are just like not any of those things you know uh Because for a while, right, like every tweet every day is like, go download the skills, the perfectly managed thing to do this entire workflow.
And I think that like what we found in what I was just with my team this week, and we were talking about the skill side, and we're really talking about these like incredibly micro skills that are just doing one thing for us very, very well versus a skill that's going to do, like I said, that full report.
That doesn't really exist on our side anymore.
You know, it's usually like, How do like a single skill that's going to identify the most important marketing information given any MCP server?
Like this is the most important thing.
Less about stitch a bunch of tools together and have it produce this mega output because then weeks go by, months go by, things change and you want to tweak your mega skill and you're screwed.
You know, you can't do that.
And so now we're really just talking about.
like the Legos we're using and letting the instruction book, you know, be something we're all putting together.
Whereas I think a lot of AI skills for a while have been that mega, you know, instruction book style.
Yeah.
I've thought a lot about Postel's law.
I don't know if that's a term that means things to folks.
It's the idea that you should be liberal in what you accept and strict in what you output.
Right.
And I think that's like a good.
framing principle for skills.
This is my skills, obviously, on GitHub.
I feel like everyone should have, like, you know how some repos in GitHub are special repos?
Sure, sure.
I feel like we should sort of reify the slash skills and everyone, like, give it as some kind of special presentation.
Yeah, yeah, yeah.
Anyway, so, yeah, this is one of those, like, download anything, transcribe anything, and then you can string together the atomic skills that do one thing well into, like, some kind of orchestration skill that calls other skills.
I assume, does that match?
Yeah, I think so.
I think that the...
Summarize anything.
Totally.
Like, I think the...
For me, summarizing something for, like, you know, I do communications and PR and analyst relations and marketing and customer activities.
And so my summarize everything is very different for each one of those, like, contexts.
You know what I mean?
Because if I'm summarizing something for an analyst...
That's a very different thing than probably how I'm going to summarize something for a customer meeting or an engagement.
So that's, I think, the difference when we're talking about the tools I might use on Saturday or the skills I might use on a Saturday just for Kyle.
Yeah, those are kind of like they have an atomic actual tool underneath or maybe skill.
And then Kyle cares about X.
But I think when we're talking about work and enabling the marketers, communicators there, it's the atomic.
This is what good summarization is.
And then this is what I care about as for marketing, for communications, for whatever.
And that I think is like the interesting matrix problem when we go from like a developer set of concerns to all kinds of different professions is that what that word means to me is different than it means to you is different than it means to the analyst or the salesperson.
And that's where I think the matrix mess is that we're starting to like still starting to find.
It's not these mega skills, but they're all just slight permutations, but those permutations are really important.
It's the difference between someone reading this and going, today I make this, you know what I mean?
Or like, this makes total sense, and I would expect this when I'm giving a briefing to Gartner or like whatever else.
Yeah.
I think the beauty of it maybe is that you don't have to be that careful about what goes in there.
It doesn't have to exactly fit as long as it like roughly is contained in there.
I used to complain about plug-in hell.
Basically, like when you have a framework and then you have a hundred things that you need to integrate, everyone does like the GitHub used to be bloated full of these things.
And now we don't need them anymore.
It's not easy to see skills.
Yeah.
And like, I think the most magical thing is just that like, I can just also crack it open.
Like, you know, like, yes, I could go like, you know, change the, how the plugin is coded or like I could go, you know, do that now with AI.
But I think there's just something more magical about.
getting a response back and being like, that's not right.
And then you just crack the skill open, you just type English words, you know, and it's different.
That building block is just, I think, very unique.
Once I get everyone to kind of understand how to best, you know, how to best make those changes, you know, to get the most power out of them.
Is there, you know, you have a peer group of people like you.
Is there a common framing for...
Something I'm feeling is just true is that this is a golden age for former developers who are now in leadership, right?
Because you can wield the tools.
You would know the right words.
You are maybe not too close to the details.
Sure.
Doesn't matter.
Yeah.
But like you're more effective than someone who doesn't come from that background.
I think that like the secret has always been your ability to identify patterns and solve problems.
And I think that, you know, for folks that like myself that don't code day to day anymore, that.
has made me successful as a developer, made me successful as COO, now CMO.
And so now that I have access to get and write code, I'm now applying that sort of like pattern finding and problem solving.
And I know enough still, you know, about how to then go and say, oh, I want to make an app and I don't want to, you know, break into jail or create something that's not going to be able to work or to be deployed scale or whatever.
That ability to apply all that additional business knowledge, you know, and.
Still code, I think is what makes that so interesting to me, slightly different than I think some of the other like technical leaders that became business leaders and now are going back to their apps in updating them.
Good for them, you know, but I think that the more, much more interesting thing is, well, now I have this whole new set of expertise over 10 plus years.
Why not take that and use that as a developer with these AI tools?
So I definitely think that makes.
me more powerful, but I think that's true for like every dev as well.
You know, most of the dev friends I still have also have some other underlying skill and passion.
You know, there's really talented, very, you know, kind of linear computer science software devs.
Absolutely.
I just find that the folks that came from a different career, went to school for something else, went off and did this random thing and then became a software dev or where a dev did a random thing came back.
Learning that extra set of information, learning those extra skills, and now having the power of an AI where I can crank up 15 agents on Saturday, you know, while my kids are doing lacrosse, that's, like, really powerful.
And I think it gets me back to that feeling of, like, creation.
And it's very hard to...
like replicate that in most other senses.
You know, that first time you build an app and you click it and you show someone like that's magical.
And so being able to do that, not just in code, but across all kinds of different assets, like that's, that's huge.
We were doing, we're doing our, like every year we do our revenue planning.
You know, we talk about, you know, okay, what is it going to look like for next year?
And of course, as you imagine, there's a slideshows everywhere, you know, talking about what are we going to talk about?
What's the narrative, et cetera.
And so, as you said, you know, I'm like, okay, well, I could probably just, like, build something to build this, and then that way I don't have to go build the whole spreadsheet or I have to pass it to my team.
So we went through this process, and I got all the information and used the skills I mentioned.
I built, like, a little app just to make it so I could look at some of the information in a SQLite database more easily.
And I ultimately built this entire presentation.
Without touching any of it, and I was like, okay, I'm just going to present this to our CRO, the CFO, their teams.
Without mentioning I built it with AI.
I built a skill to make it look very much not AI-driven.
Not pretty, but just very clearly not AI.
Kind of like, don't do anything interesting.
Exactly.
We did the whole thing through.
It used my notes from Obsidian.
It used all the context I mentioned before, the plans.
It never came up once that it was AI generated.
Yeah, because it didn't matter.
Exactly.
It didn't matter.
And so now I can take that tool and go, look, I don't want you to go build slideshows.
They're just helping us share information with each other.
If this thing can do it with a little bit of crafting from you and then we can look at it together, awesome.
There's no value in all that extra work.
I think that the ability to make it look...
humanly bad and you know like build a little app to like manipulate the data I think is part of like that upside for devs that are now in leadership roles because like the thing that I feel like like I said before this that's all a people that's all people problem I know if you've used a co-worker not to build a slide deck unless you spent a bunch of time to to not do it.
I think there's a certain charm to just being blatantly AI.
I think you're just honest about there may be mistakes here that I cannot vouch for.
How much value is there?
The real question I want to ask is you were a chief of staff to Thomas.
In the pre-AI world, that job would have been a chief of staff job of like, can you prep me these?
slides and all that yeah and now you do it yourself yeah i mean like i still i still have a chief of staff because like the difference is like it's sort of the the discussion every time we you know have some sort of technology uh you know evolution is it's not that the The jobs, like the roles don't all go away.
They just change, you know?
And so, yeah, I don't have someone spending all their time building out slides for me and presentations because I don't need that anymore.
But now I need that person that is able to go and find all the different connections between humans in those discussions to help me find out, okay, I should be meeting with this group and this team and they have an opportunity and I'm going to be in San Francisco today.
I'm going to be in Seattle tomorrow.
Those sorts of like.
um human connection uh aspects is still incredibly valuable and has always been a big part of that like chief of staff role um but now just like uh you know chiefs of staff are not opening up like letters to process they're doing emails you know what i mean it's the same thing and now they're they're not building out as many of these presentations because they have the you know the ability to have uh ai take it off uh and share that with me and great, let's keep moving because it's allowing us to go faster and make better decisions more quickly.
Yeah, awesome.
We can dive into more productivity insights as you go.
I did want to do a little bit of a brief history of Kyle, can it help?
Yeah, sure.
Because we started here, and then you also involved the NPM acquisition.
I did want to touch upon that.
And then more recently, I just want to bring up to present day where we're having...
uptime issues which transparently we've already addressed publicly but we'll discuss in the pod.
Sure.
Did I miss anything like any other major highlights?
Obviously it's a lot of years to cover.
Yeah, no, I mean like...
I think one highlight was right before the acquisition closed in 2018, I got to launch the first version of Actions at GitHub Universe.
Is there that young?
Yeah, it was October of 2018, I think.
Yeah, yeah.
Jesus.
Yeah, yeah.
I was an engineering leader on that project and got to launch that.
And then, yeah, we did acquisitions of, you know, NPM, like you said, Semel, Dependabot, you know, Pullpanda, like a whole bunch of things.
Pullpanda.
Right?
Abhi is doing well.
Dx.
Did well on Dx.
You know, that was the big shift after the acquisition.
I had to join the sort of business side.
I need to hit you on some of these things because you were there.
Yeah, yeah.
And how often do I get to talk to someone?
But actions, is that the number one source of security issues?
Oh, I mean, I think that the number one source of security issues is probably like the literal code in everyone's like underlying repositories.
I would say back further than that is if you remember, like I have like in this graph, this is I didn't say this before.
This is ultimately webhooks.
Yes.
Like circa, whatever it was.
I forget.
Yeah, hookshot's in there.
And so like back then, it says GitHub services.
Do you see, it says hookshot, hookshot, FE for front end, and then it says GitHub services.
GitHub services back in the old days, right?
We had a repository that was Ruby code, and you could write any Ruby code in there, and then we would execute that.
on your behalf as a service.
And then that way, you know, if you're trying to integrate with something, we would run it for you.
And of course, no containers.
No, because it was 2014, you know, like, and so there was some isolation, obviously, but it was mostly the separations on the server level.
That's an example as long as the very old version of Pages, which ran on its own containerization infrastructure and not on actions.
Which is an all-time great product.
Pages powers the internet at this point to some degree.
Those were places where clearly there were no issues to my knowledge, but it was those things where I'm looking at and going, okay, we can't be running arbitrary Ruby code on everyone's behalf.
Then containerizing all of that up into actions now where, yeah, the containerization is really good.
The pinning, most folks aren't pinning it to a particular SHA, et cetera, their workflows.
And so that's a big place of paying for folks if they're just doing similar to any dependency management, just V1 or newest or latest, I think.
that journey from that day to like, okay, we're just gonna run all this arbitrary code and like, it'll basically be okay to now.
No, I mean, we have like really good containerization.
We have a new, um, uh, underlying, uh, agent, uh, containerization, uh, uh, service.
It's like through, we're using it under the hood.
It's through Azure.
They recently announced it.
Um, uh, the Azure like dev compute, but it's like very fast, uh, very fast compute to be able to like spin up, uh, your own cloud agents or whatnot.
We're using it under the hood for some parts of the new...
Microsoft DevBox?
No, no, no.
DevCompute, yeah.
Not finding it just yet.
It's in there somewhere.
All right, we'll cut that out.
Sorry.
But with DevCompute, you can run really, really fast.
spin up really small VMs really, really quickly.
So you're doing a tool call, just do it containerized.
Exactly.
So we're using that.
So definitely moving that direction to protect us from every piece of code that we're ultimately running.
Yeah.
I mean, look, that grows into the full SDLC.
Code hosting was just the start, and then it's grown beyond that.
It's more about NPM, maybe, because I think that's also a very major point in the industry.
I do think it was looking for a home.
It was kind of struggling as a business.
I don't know how you would characterize that whole acquisition.
Yeah, I mean, when we were talking to the team, I think the big thing for the both of us was to find a way to keep NPM, which was basically powering the internet then and way more so now to some degree.
running, you know, like keep it going, keep continuing with the scale, was having scaling problems, if I recall, back at that time, they were doing some rewrites.
I mean, that's cute compared to now.
Yeah, well, that's the thing is like, you know, when I'm talking to folks now, like there's, you know, there's so many more underlying uses of NPM than there were, you know, back when we had them join in with GitHub.
But that was ultimately the goal.
It was really like, okay.
We used to have pages.
We have, like, the world's code.
Let's make sure that we can keep NPM running well, you know, for the world.
And we put a bunch of time and investment into fixing some of the underlying backend changes, some of which we talked about, like some of the manifest work, et cetera.
And then now, like, really trying to bring the, you know, the security posture of NPM up to speed.
But, like, it is a unique challenge in that.
Every move that we make to make it more secure will break a lot of people.
And security is paramount.
And also, we take it very seriously.
Anytime that we have a problem with GitHub or we make a change that makes us more secure, there's a snow day for developers or a really bad fire that they have to go put out.
have changed the 2FA policies.
We've changed the way the tokens work.
When we find tokens that have been exposed or potentially exposed, we invalidate them.
I love that feature of GitHub.
That creates issues, but that's the thing is we're trying to push the community forward without necessarily doing something that is going to break the contract that's been for 15 years or some amount of years on NPM.
I think the, so now we're talking about open source and publishing.
And I think there's something here with what people are calling slop forks, which I think Malta from Vercel is doing.
And part of me thinks like, well, the way to get past any like vulnerabilities, we just, let's just get rid of the concept of NPM.
And we only publish source code.
And anytime you want to import it, you have your coding agent look at it.
and then adapt whatever subset you're going to use into your, like, vendor it, but, like, the AI vendor it.
Is that realistic?
I don't know.
Will that solve all our security issues?
I don't know.
I mean, I don't think it will solve, like, so Mitchell was just talking, and Mitchell Hashimoto was just talking about this today, and I think that, like, in some ways, it's all...
you know, all things, uh, uh, old or new again, you know, like, yeah, absolutely.
Vendoring everything.
Like, you know, I do, I do remember 2013, 2014.
We must return.
That's what I mean.
It's like, we were vendoring everything.
We were having actual discussions around like, or at least I remember we were like, should we take this full thing?
Like, why is this so big?
We only need this one file.
And so I do think there's something true there where having like, Either taking only what you need or the dependencies just getting incredibly small over time, I think will help to some degree, but it's not going to solve the fundamental problem, I don't think, because the vulnerabilities like in an agent looking at them, there's time and time again, there's a million different ways in which we can convince an agent that this thing is like.
secure or not and pull it in, or we can do, you know, uh, static code analysis or, you know, runtime testing to say whatever the code works or not.
That is, I think the step that needs to continue to be like invested in.
The question is just on like how much scope should it be this enormous project that I'm pulling down or should it be this piece either way?
Uh, you know, most companies are running some amount of, you know, security checking on the, on the, um, uh, the packages that they're bringing in or vendoring.
That I think won't change.
That's what advanced security does to some degree.
Socket does to some degree.
Everyone is doing a piece of that.
How we each do that, especially when we're talking to enterprise customers, is just very, very different.
There's no one wants one single way to do it.
And I think that's always been GitHub's unique position in the world.
I talk a lot to maintainers.
I talk a lot to folks about this.
We rarely start a process and a practice and push it onto the community.
We usually wait for the sort of RFC process socially or literally, everyone agreeing, and then we'll cement something in.
Because otherwise, we're GitHub.
We don't want to shape the whole thing.
We want it to be figured out.
But how do you balance that sort of...
role in the industry to keep everything as secure as possible and make sure that you're, you know, you're not going to be compromised as a human because that's usually how it all happens.
And not, you know, not create a process or lock us into a flow that, you know, you're not going to like or like Mitchell's not going to like or other open source projects aren't going to like.
That's always been a tricky balance for us.
And I think that's something that we haven't talked about enough, you know, is.
We're not going to be able to fix everything for everyone in a way that everyone is going to like.
So help us.
Tell us what is working.
When Mitchell was talking about the upvote.
I forget what it was.
Yeah, I mean, like when he's talking to us, I was chatting with him and talking to him about this.
And I put it on Twitter and we talked also over DM.
I was like, we're going to keep working.
But I think the important thing is I do actually want to hear what isn't working for you.
And it's be as specific and clear for your project as is possible.
And to every piece of credit over the many years that we've known each other through the industry, he's always done that.
And I appreciate that because there are places that we need to fix up and we hear from him and we'll fix up just like we do all other kinds of maintainers.
But that like.
That process between making those types of improvements and being more secure and creating – I forget what he calls it.
It's not the proof process, not the claims process.
You know what I'm talking about?
He has that – his projects have a way for you to kind of like – Vouch.
Thank you.
Yeah, he has like the vouch system for saying, hey, you should accept my PRs.
Yeah, I just built this into GitHub.
I don't know.
Well, see, but that's the thing is that you say that and he and his community really likes us.
And then I'll go talk to other maintainers and other maintainers globally.
And they're like, no, this doesn't work for me.
And that is the tension.
But also the kind of beauty of GitHub, depending on which way you look at it, is we want to help maintainers.
So we create all these tools to let you have more control over how much you take in from AI and PRs.
But you can also use this.
You know what I mean?
You can go use this project.
And if it takes off and becomes the kind of mostly standard, then yeah, we probably wouldn't enforce it, but we would add it in because that's the flow that we tend to do.
I hear a lot of people don't know the history of the pull request.
Sure.
And that's something that GitHub standardized, basically.
Yeah, yeah.
It was a very messy process beforehand.
And now we have the benefit of it being the process.
Now we have to go and figure out the next best process or what adaptations change or what does a pull request look like when 80% of your PRs are just coming from your agents and not from other devs.
Do you like the prompt request idea from Peter?
I mean, like, I think that for each, like, each idea, I think, has its merits.
Like, I'm not avoiding saying anything good or bad, but I feel like I've seen a version of, you know, we have that, we have, you know, entire, you know, Thomas's, you know, startup, take all the assets of what you've built and put that in.
I think that's got great ideas.
Like, there's all these various permutations of the PR flow.
But I think the reason why there's not a single answer is ultimately we're trying to codify trust.
We're trying to say like, okay, if Sean reviews this, I'm going to trust it because you're Sean or you're the senior dev or you're the whatever.
And right now when we are working in a flow where an agent writes code and another agent reviews code and then Kyle goes and looks at it, the trust is kind of diffuse.
And most of the tools that we're talking about are talking more about verification flows.
We have more assets to look at, so I can probably say whether this is a good PR or not.
But that still doesn't solve, I think, the human problem of I'm looking at a PR and I want to know if I can trust it.
And we still tend to use human signals for that, you know, Mitchell approving it or Kyle approving it or whatever.
And so I think that's why most of these options haven't really solved it is because it's a social problem.
Ultimately, it's a human problem to review it and agree.
Or you fully trust the tool and you're imbuing that tool with full trust, which I think in some cases that absolutely exists.
So like, you know, in the same way that there will be a tipping point in society when we don't allow humans to drive anymore because machines are measurably better than humans.
I'm looking for that tipping point, right?
Yeah.
Mythos is ridiculously expensive.
Someday we'll have Mythos on a desktop.
I don't know.
Does that change the equation?
I think it's more like I took a Waymo here and I was on my phone and not looking around at all.
There are other self-driving vehicles that I would not trust while staring at the road.
And I think that that trust is something that is a Zooks thing.
Like, I think that is both.
I think that is both.
You know, like, that's it.
Well, I mean, depending on what level of self-driving, you know, but my point is sort of that.
I think part of that is, you know, I strongly believe that that's like a mixture of verifiable proof, you know, like how many accidents, how much data and so on.
And the human aspect of how I.
feel when I'm in this car, what it tells me, et cetera.
And so that's why I think some of the, like, uh, some of these, uh, uh, some of our AI tools tend to, um, imbue me with more of that feeling of trust.
Even if the data says this is 100% accurate, you know, like, I feel like it takes more time for us to go.
Should I trust this or not?
And that's in the soft sense of like startups with high agency, weekend projects and open source.
And then there's enterprises and regulated industries and everything else.
And that is an even harder problem to go solve because even when it is fully verified, not only do you have to have trust from the humans on the team, you probably have to have trust from multinational, multigovernments around the world, you know, regulating agencies.
And so that's where I feel like until we tip over to your point, like on the sort of like.
human eq side of it like i feel okay like this feels okay like i've been proven enough uh then the ball will start to roll a lot faster uh where we'll end up getting to the okay we can trust this and feel good about it in the most difficult cases you know if human trust is the thing that matters uh i feel like github as the developer social network could maybe do more there like vouches one system but like we have star counts and then we have contributor rights and that's it and like I feel like there should be more in that space.
I don't know if there's any other design decisions.
I mean, I think that like one of the places that we don't really expose right now in this sort of way is...
like some degree of like hard trust and support, which would like for me is like sponsors is a good example of that.
It like costs you something, you know, to prove that I believe in your project and I like trust you to some degree.
I want to support you at the very least.
Okay.
Self payments for open source.
Why not?
I think that as we keep moving forward, right, there's more and more projects where I'm like adding more and more dollars into sponsors personally because I want to like support them.
But I also like know.
of you know i probably never met them in person but like i know of enough of their work that i want to support them i think the thing that i don't love about stars or commit counts or anything else is like ultimately even with all of the various like abuse and de-spamming and deduplication work that we do or anti-abuse you know work that we do these are all like not active social signals they're passive ones that are ultimately gamifiable and You may trust me, but another open source maintainer may not.
And on what heuristic should you be trusting me?
That, I think, is kind of where some of our thinking is right now.
What signal from me is most important to you?
If you can define that.
potentially, honestly, in an agentic workflow.
That's what we see some of these open source projects do, where you have GitHub Actions, and then you have an agentic workflow that's calling AI, and you're setting these rules.
If Kyle has submitted and gotten accepted PRs across any given project, and has a social handle tied to his account in GitHub, and that social account's older than a certain amount, really complex measures that matter to you, because most open source projects have that heuristic built into their heads, if not written down in the contributing guidelines.
You could take that and then go apply that and then just say, oh, we're not going to accept this PR.
Building something that is, I think, malleable to everyone's needs is a little bit better rather than going, hmm, this account's too young.
Because what happens?
The attackers just go and create a multitude of accounts and they wait.
Until it ages up.
Needs to have a certain amount of stars.
That's how star inflation happens.
Need to have a certain amount of repos with PRs.
They all just create repos and submit PRs to each other.
And then they come in and do something nefarious.
And so it's hard.
It's hard to find the measure.
So I think we're looking more at how can we provide you tools so you can kind of choose what's best for you.
And, of course, we'll give you some standards.
But the trust vector gets down to like.
I don't know, some version of like human digital ID like everyone's been talking about.
Like, how do I prove that it's me on the internet?
Give me your eyeballs.
Give me your eyeballs.
Exactly.
I got to keep moving on topics, but obviously I can go all day on this stuff.
I mean, I've been involved in GitHub and open source my entire professional career.
Stars.
Yeah.
Very superficial.
Everyone knows it.
But I think time to 100,000 stars is the fastest I've ever seen.
People just reach that in, I don't know, months.
And then at the same time, I don't trust it.
How many of these are real or bought or whatever.
I don't know how to ask this, but what can we do about it?
Is stars broken?
Is stars fine?
I think that there's kind of two pieces.
Obviously, we're...
constantly like trying to find ways in which like your uh users are you know producing spam which would i would include like be like only doing star gamification when we find them we pluck them out you know and we uh yeah but it's like a whack-a-mole it's 100 like a whack-a-mole now like powered by ai to be helpful but i think more so what i'm seeing is uh a lot of the like fastest time to x you know tends to be because we're now inviting so many more people into like software development on github that like the zeitgeist is just swarming yeah you know it's not just developing it's not you and i like you know like however you want to say like what a developer is you know it's not just folks have been coding for a very long time it's folks that maybe started coding or only joined in since the ai era and now what's the latest octoverse number i know 80 million was my last remember that like a number of developers on github oh we're over 200 million yeah okay once you see yeah yeah yeah like over 200 million developers now but it's not developers right like it's it's people with a github account so like so this is this is the biggest debate that like i would say like everyone loves to have at github at this point from my perspective right i think that there's there's clearly a difference between like professional enterprise developer you know and then developers but i think that i think that the idea that you know We should be like, I don't know, splitting hairs or segmenting developers in the early era of software development is like not worth the time.
Yeah.
You get into gatekeeping.
100%.
Like 100%.
Because I mean, I wasn't a developer when I started writing code.
You know, I was going to.
Oh, no.
I made, I like cloned the thing like seven years before I learned to code.
Yeah, yeah, yeah.
And then I wrote about my learning code journey.
People just called me a fraud.
Yeah.
Because I had a GitHub account.
Yeah.
And I'm like.
Well, no, I just use GitHub, but I don't know.
I remember that.
I remember those sets of posts, and that's bullshit.
So I fight very clearly on the line of if you create code, if you have an idea and you create it into some way of like I'm going to run it and use the app right now, you may still use AI in that moment, but that's okay.
At some point, you're going to do the next thing.
You're going to create a big – you're going to have to learn about this database.
You're going to fix a bug, whatever.
We're all on some same journey.
And those people are also hearing about the great new agent skill package or a new CLI tool or a new whatever.
And those projects are going up because you want to be a part of this moment.
Just like I wanted to be a part of the Ruby community when Ruby was popping off when I started becoming a developer.
And now I can just click the star button.
And so I think that, yes, there's clearly some amount of like, you know, spamming and gamification that we're working against.
But I really think we're just seeing.
This whole new cohort of folks that are moving from technology to technology because they're not working on a 20-year-old software application.
They're working on a side app that they built on the weekend for their friends or for their new idea or whatever.
And that's how you see these enormous charts going up and to the right with stars.
I think something that's remarkable is the persistence.
like GitHub extends to those folks.
Usually when I see platforms go into a new audience, they usually have to like have like a second platform with a different name that like wraps the main platform.
But somehow GitHub has been able to sort of persist and extend and it's friendly and whatever, you know, so it's nice.
Yeah, that's partially why I think as we've tried to move into like...
I don't know, more like low-code-y things.
We started working on Spark as a way to build an app and run it.
I think that the reality is that anytime we try to put even a veneer on top of it without...
When we put a veneer on top of something, we still always show you the code that's kind of like a tenant.
We're never going to hide the code from you ever because what...
Yeah, it's the whole point.
However, I think that what we learned with things like Spark is that really the value of Spark for most devs is like easy runtime.
And you may have a runtime or a host that you're going to use for that, or you just build something and run it.
But like the package of making that like even more simple isn't really needed like for folks that are trying to build software and not just trying to build like an app.
which is like slightly, slightly different, a slightly different goal.
So I want to get you in.
I want to get you comfortable.
I think the best thing for me as like someone that did not like, you know, traditionally come into software dev way, way, way back.
I want anyone to be able to like breach that chasm and not be in the, you know.
I don't know.
I feel like we're still in an era of like STEM, STEM, STEM.
I've got a 12-year-old and an 8-year-old.
And it's like we got to get them into STEM, you know, over and over.
And I do.
I do the things that good parents do.
I was like, oh, we want to do coding.
Yes, I want to do coding, do coding classes.
But now they're just not afraid of doing software.
And that's, I think, the thing that's honestly kept me at GitHub for so long.
Anyone should be able to go and build a thing.
Just like I can go change a light switch in my house.
I'm not going to go into the breaker box because I'll probably kill myself, but I can go change that light switch.
Everyone should be able to go and say, this freaking app doesn't do what I want.
I want it to work like this.
And that, I think, is what's kind of kept us all connected with GitHub through the years and during the easiest of times, during the hard times, because of that opportunity of we're the home for all developers and we want everyone to be able to have that feeling that we've had of...
I had an idea.
I created it.
And holy shit, like, you know, here it is.
Here it is.
All right.
I'm going to try to do more spicy questions.
Great.
Is it an easy time now or a hard time?
Oh, I get them.
Yes.
I mean, it's a hard time.
Like, I mean, like, it's a hard time.
And also, like, I was just with my team and I said, this is also like the best and most exciting time that I think I can remember.
Like, I get home because.
Best of times, worst of times.
Yeah.
Because we've, you know, like we're talking about Octoverse reports and like.
Usually we do an Octoverse report once a year and we look at the numbers and we say, oh, my goodness, like I was at Universe in October saying this is the fastest year of growth that we've ever had.
Right.
And now we're doing more in a month than we did in a year last year.
You're talking about PRs.
Commits, PRs, kind of like you name it by roughly every measure that we're looking at.
There's some amount of sort of growth is much, much bigger.
And that is breaking our system in new ways.
Not old ways.
Like, you know, webhooks were always notoriously unreliable over the years.
Whose fault is that?
Not anymore of mine, but for a period of time, I'm sure you could pull up a tweet that was like, it was me, I'm sorry.
But like now, like that got rewritten at a scale level that is still working and is not having problems today.
Now what we're finding isn't just the like, isn't the simple stuff that folks are on the, you know, sometimes on Twitter or on the internet are like, hey, like, why is this like this?
Sure.
There's absolutely.
you know, silly problems that shouldn't exist.
But now we're talking about like unique novel permission problems that happen only at a scale across all different objects or whatever, that now we have to go rewrite this underlying system.
And so it's, there are problems that, yeah, caught us off guard, which I think I said, I mean, like the growth is astronomical, but also we're making such material progress in that, that I'm excited.
Once we've kind of reimagined the underlying foundation layer, or pieces of it at least, what's going to be possible when it's not just all of us and all the new people that are being developers and all of their agents and all the tools working together?
Because that'll still happen in that GitHub tool, that GitHub community.
But it's a hard day.
Anytime we can't give you what...
you're looking for.
We have the same problem internally.
I mean, we operate through GitHub.com.
Of course, we have backups when things go down and whatnot for our own operations, you know, but we feel it too, you know, but it's not working.
It's not working for us.
And that's kind of like the promise of dogfooding for GitHub.
It's always been true.
We're using the same tool you're using.
We're not using a super secret version.
And so we also need it to be great for us, for our customers, of course, for open source.
And now.
you know, an exponential growth of agents doing it too.
I wanted to load for audio listeners who maybe haven't seen your tweets, whatever.
So 1 billion commits in 2025.
Now it's 275 million per week.
On pace for 14 billion this year.
It goes and remains linear.
Is that still the pace?
I mean, it's still speeding up.
Yeah, exactly.
This was in April.
All right.
So basically you have 14x growth, right?
Year on year.
And I think that's a scaling issue.
I think I'm going to try to really steel man this thing.
People have experienced 14x growth.
They haven't had your downtime.
And that's like, can we dig into that?
Like, why?
Like, what broke?
What are we doing to fix it?
Like, you know, just anything for the community to reassure them.
Yeah, I mean, so like I was saying, there's a couple different places that we've seen the...
the growth issues.
Some of the growth issues, which is why I was talking about pushing hard on more CPUs is in actions in particular.
More tools, more agents, more PRs mean more builds, more builds mean more CPUs.
And so we are expanding through not just our data center, but obviously we were talking about moving to Azure and adding an additional cloud compute because we simply need more CPUs.
Not as much GPUs.
We definitely need GPUs too, but now CPUs are becoming a factor.
Underneath the hood, when it comes to some of the underlying services, we've been breaking up over the years our database infrastructure.
So that way we have more cognitive separation between the various services.
The place that we continue to have pain is in permissioning.
And so right now, many of our permissioning layers sit into a database that we, like, internally call MySQL 1, and old hubbers will know what I'm talking about.
And so, like, we've been pulling things out of MySQL 1 for many, many years.
Because, like, and we use, you know, we use Vitesse and we use other technologies to shard.
Famously, PlanetScale was born from this.
100%.
Sam, you know, old hubber and friend.
I mean, like, and so finding these opportunities to, like, break this out and then do that globally.
The other thing that I think is interesting in, like.
both a unique opportunity and tricky is we also run everything I just talked about in a like black box container with GitHub Enterprise Server for people that work on on-prem.
So we take everything I just said and we also do it on-prem and we also do all of that and we do it in a data resident setup for customers that need to have their data in a single location.
Each of these has the unique characteristic around how we're sort of storing that data in MySQL or in a permissioning setup.
That's where some of these outages have occurred where you're seeing it more like across the board rather than just like The one piece isn't quite working.
Exactly.
Exactly.
And so part of it is that I think there's been some other places where agents are much more or more projects appear to be moving towards model repo versus we were going the other direction for many, many years in the industry.
Repos were smaller, but there were more of them.
And now we're seeing the opposite.
Repos are bigger and there's not fewer of them per se because there's new growth.
But like.
We're just seeing many more big repos.
Big repos, big monorepos have always had a unique performance problem because each one is slightly different, particularly if the underlying blobs are incredibly big inside the repos.
And so we've done a ton of work that most people haven't probably experienced, unless you're in this case of the monorepo.
But that git...
infrastructure layer improvement does help the overall system because many of the improvements that make model repos work better make all repo infrastructure work better.
And so like I can kind of keep going like down the line where it's another thing where, you know, we're moving out of we're changing how we do.
like i'll just say like job queuing for lack of a better like explanation like changing the underlying technologies there i spent two years being a job queuing guy and so like it's kind of a little bit of like a little bit of piece by piece and it's mostly because as we were as it was built we built everything in a way that uh uh assumed i guess in some ways that the size of the pipe of work was going to remain the same.
There's just going to be more people coming through each of those pipes.
But instead now in places where a Git push was generally a certain size, for example, is now like no longer true.
Oh, yeah.
You know, or like on the average.
Same thing with PRs, you know, like PRs, like same thing.
And like we've talked about optimizing that and making changes where like and there were.
like technology choices that did not work there, you know, and it got slow and it didn't, it was not fast.
It did not do what the users wanted.
And so we've been like reeling that all out, you know, going, okay, that's just not right.
Let's stop putting, you know, good money after bad and do it the, do it the right way or the right way now.
So there's, it's a, it's a lot of things, not quite like when I've experienced scale at GitHub historically, it's almost always.
two options that we've used.
We go vertical scaling, particularly with databases, right?
And we go horizontal scaling.
Oh, we just have more people using this service?
Great, we're going to add more servers and we rack them in our data center or we use it in a cloud.
And now, like, we're sort of in a, like, diagonal where, like, vertical doesn't really work anymore.
Horizontal doesn't work either because, like, we're all, we all have some CPU or GPU constraints in the world now.
And now we have to go and, like, crack open services that have been running for 10 or 15 years and go, okay, the rules of this service have like legitimately changed and now we have to rewrite them none of this is an excuse this is like we're we have to do the work we have to make it better i mean actually as an infra guy i'm like this is like one of the most fascinating scaling challenges i've ever seen that's like that's that's the thing that that's the thing that it's hard for like when we weren't talking about it publicly and i was like i came out and i was like hey i just want to explain what's going on part of it comes from a very old github like ethos which is It's our uptime.
It's down.
I know you're a developer, so you're inclined to want to understand more what's going on.
But at the same time, us going, hey, this service didn't perform the way we expected, and now we have to go change it.
We're not trying to hide anything from you in that.
Well, that's our problem because you expect us to be up.
And I think that's like really baked into the core origins of GitHub.
And so now what we're trying to do as a team is do all that work and just talk about it more and just share you more technical details.
Write these blogs.
Write the posts.
Get the engineers who built it after they finished the work.
Just tell you, okay, this is what we did.
I think that's the contract that we want to bring back to the community and say, hey.
We're still very serious about what we're doing.
We haven't been telling you about each piece.
So let's do that.
And we're going to keep building this and scaling it in a way to support the – if it's not 14, then it's 30 or it's 50 or whatever the next exponential growth is going to be.
Yeah.
First of all, fantastic answer.
I mean, I think I apologize in advance if like any of that is like slightly incorrect, just simply because I'm not, you know, I'm like still in the weeds with this, but it's not my day to day.
But like, that's the thing is we're all looking at it to that level.
Yeah.
You know, you know, and like, obviously, if people want to help, they can join.
Yeah, absolutely.
So, like, I think that is.
Good.
I think people also just want to know, like, when are you through the thick of it, right?
Like, is there, have we identified all the issues?
Is this just never ending?
Like, is Git broken?
Like, do we have to change the Git protocol?
Like, how much is breaking, right?
Like, it's been a while.
Yeah.
And so I think people do want to know what's the path back to the reliability that everyone expects out of GitHub.
Yeah.
So, I mean, like, are...
Our availability in recent few weeks has been much better than the three weeks before that or the three weeks before that and so forth.
So a lot of these improvements are still very much paying off for us.
I think that we're still working on that database piece that I mentioned.
And that just is a little bit physics, like a little bit of time to get it fixed up.
Because we have to...
The answer I had in my head was call YouTube.
So YouTube ultimately...
They also use Vitesse.
They also use Vitesse.
But the...
Like whoever was the guy, the scaling guy at YouTube.
Yeah, yeah, yeah.
That I believe went to PlanetScale and was a part of PlanetScale too.
Oh, you mean Sugo?
I think so, yeah, yeah, yeah.
He's at Superbase now.
The whole Postgres drama.
Yeah, yeah, yeah.
Totally.
So, I mean, like some of it's that.
I think the other piece of it is our move to get additional compute will alleviate a fair amount of this, particularly on the action side because a lot of the underlying outages is actually related to – I'll tell you, actions is the root of all evil.
I mean it has its – pros and that it's the core it's the core compute layer for either ci side projects no i don't know i mean like actions i pay a lot for compute right yeah i mean like actions is like definitely a a piece of the overall business but i would say that like we ultimately also give away so many like minutes you know as part of our entitlements as that but that's what i was saying everyone's using it We talk about it as CICD, but the reality is people use it for CICD and various processing and automation.
And so, I mean, like part of it is also that like compute piece that is also alleviating some of our availability.
This is my abuse of actions.
I've been scraping for every day.
Thank you for your service.
But this is also how I track actions on time.
Sure.
Anyway.
So I feel like some of it's going to be that.
I would say that each month, I expect in the next three months, you're going to see fewer and fewer moments where we have an availability problem, where things are going to go down.
And that's not just it stopped.
It's that we're still experiencing faster growth than ever before.
It's just that those underlying improvements that we've been hard at work on are finally paying off.
It's just that their improvements take – it's less about these incremental improvements where you make a small change and you get this big output.
material change that takes a bit of time and then you see a step change in our availability.
There's a thing we used to do at Amazon.
I don't know if it's like a thing, but like, you know, automated software verification or simulation of load testing and all that.
Like, I'm just like, at this point, you have a whole map of GitHub and like, well, you can assume whatever growth rates on whatever dimensions that you care about and just run it through a system, right?
Like, I feel like there's a way to, I don't know, have a systems model of GitHub and like see what breaks.
But obviously I'm...
I'm not that close to problems.
Yeah, but I mean, so yes, totally.
And I would say like that's been the journey and work that's been happening since like I would say November to now.
Because October, right, was the time where we even said like, oh, look at the growth.
And like and then you start to see the chart like really, really pick up.
And it's like, oh, we tested it at, you know, N amount of scale.
And now it's at like N cubed maybe, you know, like in some vectors.
And so now we have to go and build it, you know.
that way and make sure that it can handle all of that skill uh let's talk about it yeah so how many original creators of co-pilot are there oh jeez i count like 12 yeah i mean like i forget like all joking aside i forget the number of people that were on like the original like uh github co-pilot team uh But there was a bigger group.
Alex worked on it.
Luga worked on it.
There's a bunch of people.
And then their entire management line.
So enormously successful in its day.
I think the last number, I think Mario came to my conference and talked about the $100 million mark.
I think most recently $300.
I might be out of date as well there.
I don't think we shared the dollar amounts.
Just like what's the state of Copilot?
It's obviously as a concept brought into more of Microsoft.
But just add GitHub.
Yeah, yeah.
I mean, so I think, you know, one of the challenges that we had with Copilot, right, is that we came out the gate with code completion.
It was, you know, super great, powerful, et cetera.
And then what we initially worked on after that sort of like initial year, year and a half was going after fine tuning.
Because, you know, our customers, the industry on the whole was really talking about, okay, well, like, how do we get more, you know, more correctness or performance out of this?
And so we were working on a whole bunch of efforts to do fine tuning on larger and larger co-completions or like.
next edit suggestions with fine-tuning etc and let me clarify uh is this fine-tuning one model or per customer a fine-tuned model both but like but like fine-tuning one model for the overall like uh use and then fine-tuning per customer that wants this as like a service effectively and around that time is when uh you know the next generation of models came and that's around the same time that you know all these other, you know, AI coding tools came to be because the models really, really sped up.
And so everyone kind of like will ask like, well, what happened to GitHub Copilot?
Like there's all this time.
And I would say that we were on an era of going, okay, we want to improve everyone's results.
And so let's focus in on fine tuning because that'll give us these better results.
And then the models got better.
And so then ever since we've been really on this kind of journey to go, okay, of course we have like this great code completion.
done a ton of investment in the better underlying models that we have, you know, post-trained, better next set of suggestions of post-trained language-specific models, all this stuff that kind of like sits in the ether of GitHub Copilot is code completion, but also have now have like a single underlying SDK and harness for our coding agent, you know, Copilot ultimately.
the new CLI, the new desktop app, cloud agents that use the same SDK.
And so there was this moment of, you know, both really, really trying to figure out what our customers want, models Sherlocking us a little bit, then going and saying, okay, what does everyone ultimately need?
And what we think is that it's not solely about the code generation.
It's really about having the ability to use these coding agent-brained harnesses or runtimes across not just the coding experience where I'm going to send a bunch of tasks out or I'm going to use Fleet to break up a single task or autopilots and lure to goal, all this stuff.
But also, how do I do that for all of my security remediation?
How do I do that for every GitHub issue that comes in?
Just stick a coding agent on it just to say if it's possible.
How do I go through my repository and see all of my documentation and extract out, like, okay, this doesn't actually match?
Like, that amount of sort of AI coding agent automation I think is a big part of what we see when we're looking at, okay.
We're still kind of going through a similar but very different flow.
It's just all happening at the same time.
You know, like there's not really the same, like I'm going to create an issue to track my idea of building this.
You're probably just going to go like, do it.
You're going to say, hey, just build this, right?
And there are still tons of open issues and projects, et cetera, that are using issues like Peter and OpenClaw, you know, to be able to sick all of his agent on that.
That kind of infrastructure layer and a really, really great coding experience that allows you to handle the sort of multiplexing aspect.
is what we've built or still building with GitHub Copilot.
And so for folks that haven't really used GitHub Copilot since the thing that got them excited about this, which I get, I really encourage you to look at, especially the GitHub Copilot app.
That's my new daily driver.
Obviously, if you prefer the CLI, also the CLI, be able to use...
all the models, the bring your own key side of it.
We're still improving our own models and using those too.
It's just a very, very different experience.
But I think that broader sense of software development and how coding agents can help throughout, not just writing the code or even verifying it or deploying it, is where we have this unique angle.
The other side is the context piece.
Oh, God.
I mean, like we're still – it's like one of those things where I think the final thing that will let me ultimately feel complete at GitHub is like when we have this ability for – GitHub to act like Kyle wants it to act or Sean or whatever.
And we all codify that in rules and memory and everything else.
That's an open research problem, right?
A hundred percent.
A hundred percent.
But like if we can even just do it where my team, without me having to codify everything and as our methods shift on purpose, you know, to be able to have that full experience and all the understanding of what's happening in my dependencies or open source.
that feels like a big place for us to be able to continue to provide something really unique and valuable with GitHub Copilot.
Yeah.
Is there a form factor that we haven't explored?
You know, I think like, you know, we did code completion.
Yeah.
Then we did kind of broadly call it agentic IDE, which cursor famously popularized.
And then now it's not all about the sort of.
agent orchestration, background agent, whatever.
And then there's the security review.
I feel like everyone has just thrown agents at everything.
The entire SDLC has been covered with agents.
Are we at the end of history here, basically?
Is it just refinements from here on out?
I mean, I think that we're all still in such this hypermyopic era of AI, where the reality is that for various boring security and governance reasons, at least for most people's work.
Why is my coding agent, even if it's all background agents, background running, not like losing all the context that's available to it across everything that I'm doing outside of coding?
Yeah.
You know, like I think the most interesting thing to me in AI is actual ambient AI, not insert.
you know, assistant name thing, or like I've tried just about every pin in tool and whatever, and they don't work the way that I'm looking for them to work because they're just trying to capture and then they are trying to codify and then recall.
And I think the thing that I'm looking for is back to the very beginning.
I'm looking to be building out the next version of web hooks or like implementing a new feature and it, for it to know.
every spec doc, every email, the conversations that I've had online, everything about how this could be implemented and be able to like use that as part of its decision making.
And none of these tools are ultimately doing this.
So I think that it's as if like software development where it was a single lane task was like, it only needs a developer.
Once I write the perfect code, we'll be done here.
But that's just never been true.
It's all the context of the other team members, what the business is doing, what's popular right now.
And I think that's this huge opportunity for us to go much broader than really, really excellent coding agents.
And that is honestly why I think OpenClaw has been so interesting is that, sure, it's connecting to all the data sources that Kyle the Human cares about.
And now my question is like, okay, how can I take all that and use that every day as a software dev connected together, not just have a new way to kick off a coding agent?
And that's where we're at.
We're saying, okay, I'm going to go use this CLI under the hood or this SDK.
But that's not what I'm talking about.
I'm talking about I'm having a conversation with you.
It downloads the podcast and it realizes, oh, sounds like Kyle needs this app or this thing or this.
That level of – exactly.
That level of connectivity I think is where we still have a ton of ways to go in software because then when we have that red thread we want to pull, that idea, it can not only use the perfect way to write that code but instead all of the sort of taste and judgment calls and expertise that I've earned or that we've earned as a group and use it as part of the actual implementation.
Yeah.
You know, the extreme of it is AI runs your life, right?
And I think there's a scary inversion of control in the way that I'm literally doing it in the way that developers mean it in terms of frameworks, like, you know, the Hollywood principle, like, don't call me, I'll call you.
Like, at some point, there is an inversion of control where, like, you stop telling the AI what to do, AI tells you what to do.
And, like, that's a little bit scary, but also, like, maybe better.
I mean, like, you know, Nat, I think Nat Friedman shared this in a, like a Stripe event, you know, like talking about his open claw was like, he connected open claw to his cameras and it was like watching him.
It redirected his Uber.
There's a degree of this where I was like, I actually would love open claw to tell me to like drink water.
I don't know that I want it to be changing where my car goes, but I do think that's kind of what I'm talking about, which is.
It needs to have so much more information at its disposal for it to be helpful to me.
And I still don't think we're like anywhere near talking about AGI.
I'm just talking about every time I have to tell you something I care about that I've ever kind of said or I've said a dozen times.
It should be able to know that, codify that, or gain access to it.
The dreaming ideas are an attempt to do some version of this, but I think there's a much more proactive angle that will help software devs if we can test that out a bit more.
Yeah.
Well, the other thing about OpenClaw that reminded me is Microsoft has a CVP dedicated to OpenClaw.
Yeah.
Why?
Because you don't think they should?
I don't know.
I mean, I think CBP is a high title.
Yeah, yeah.
Why is this so important?
Microsoft doesn't even own OpenClaw.
Yeah.
Yeah, I mean, so we're talking a lot more about this at Microsoft Build this year, too.
I think the main thing is that...
What OpenClaw has done is it has made this connection for people to have access to the resources that you have access to and be able to do things for you in a way that previously people were trying to codify into their own agents.
And so when you think about it, like in the work context, wouldn't it be great to have a claw-like object that I could actually run on my work device that had access to my work assets?
made, worked well on windows, like what that would look like.
And so I think that open claw has become the personification of like a valuable agent that understands me because it has access to all of my information and it can use a computer.
Uh, and so thus it can, you know, do a lot more than, uh, just a task oriented process or like a, you know, a chat tool, et cetera.
Uh, and that's like a bunch of, you know, the, the goal of build, right?
Like we're, At Build this year, trying to take a very different approach of, you know, it's unapologetically, you know, aimed at developers.
We're trying to show the, like, bigger investment to not just say, hey, like you said, why do you have a CVP of OpenClaw?
Well, because, like, one of the problems that we have, right, is that our agents, if you install them not on a Mac Mini or not on a hosted device, you install them on a personal device or a work device, we need better sandboxing at the OS level.
I need to be able to use that claw and not, like, get fired.
And so Microsoft is like, okay, great.
Let's, like, do that too.
And then it's, okay, well, where should I be able to talk to this agent?
Should each of us just have a claw available to us at work?
Probably.
And so there you go.
Continuing to contribute a ton to the open source project too.
Microsoft, I think, as I've gotten more and more information, there's so much investment into the open source projects themselves that for whatever reason just...
I think there's like this, they don't want to come off, like those teams don't want to come off as like taking any credit or getting any recognition.
But so many of these core contributors of teams are full-time just pushing into open source projects.
And like, I think that kind of shows the difference between like, well, why are we looking so hard at something like Claw?
Why are we looking at sandboxing on Windows?
Why are we looking at cloud versions of sandboxing?
Why are we looking?
Because ultimately, like.
We need more platform components.
We don't need everyone to be building the same exact top-line product.
And so if we're building for builders, that requires us to give you all these components and tell you what they are and how they work and why you should be interested versus only delivering that single vertical over and over and over again.
Yeah.
I think maybe one way of framing it.
is that Microsoft is the original operating systems company, and here's the new operating system for AI.
Yeah.
I mean, like, you know, I think that we are also in an era where we are, like, we need to help build that bridge.
You know?
Like, all joking aside, like, operating systems need to look different than they looked five years ago because it's not just you using them anymore.
Yeah.
You know, and that's changed the whole idea.
It's not, okay, my claw is going to create a user account.
It doesn't work like that, you know?
And so just like all of us, we all have to look much, much more deeply in the stack all the way down to like the silicon layer in Azure to be like, okay, well.
What do we need now?
Because the workloads are different.
It's not just, okay, we need more inference.
It's, okay, well, what type of inference do we need?
What type of compute do we need to run these agents or run these agentic flows?
It's a really interesting kind of like multi-layer problem versus kind of...
I would say, you know, software in the last, you know, five or six years, we're all going to our events and we're kind of saying a version of the same thing.
SaaS product has new SaaS thing.
It's the best SaaS thing ever.
It was boring for a while.
You know, and so now it's like, oh my goodness, like we're at physics.
You know, we're at physics problems.
And that's exciting.
Yeah.
I mean, we're now trying to make like room temperature superconductors still.
Yep.
Yep.
That's that's that's never going away.
No, I think that that's a really good overview of like everything.
I think have I have we left anything unsaid that you wanted to really get out there that we should cover?
Yeah, I mean, you know, I I'm really excited by like for folks, you know, checking out checking out the announcements that we have a build like go, you know, you can go look at them online and take a look.
I think that.
I'm hoping that it's driving a degree of curiosity and interest because there's such this big shift that we're making at Microsoft for developers where if you're a daily driver of a Mac device or a Linux device, and you're like, okay, I don't use Windows.
I mean, there's improvements.
that are being made that I think are going to surprise folks to just be like, oh, that's like, they really want to do that.
Like not, and I'm talking for developers.
I'm not talking for, I play video games on the weekends on my Windows computer.
I'm talking like my daily driver.
All the way from that to, okay, well, what is it like to build an agent or build an app and deploy it and run it at work in particular?
I think that is a big piece of it where I talk all the time with the team.
How I build on the weekend should be how I build at work.
But if you're working in a Fortune 100 or Fortune 500, you're probably not vibe coding an app and then shipping it to some service.
You got to go through security and compliance.
How can we move just as fast?
at work uh and that's i think something that uh we have a bunch of different offerings for to give you that same sort of agility and power but in the work context and then i will tell you like i've mentioned it a couple times and uh it's very freaking cool uh like if you are in the m365 land in any way check out work iq check out foundry iq these little like uh oversimplifying that context engines are wild good.
And like we've given them to our developers at GitHub, we've given them to employees at GitHub as we've used these tools to be able to just ask questions around everything that you have in your work context.
And with Foundry IQ, be able to just do the same exact thing across all your existing stores, like not move to new tools, just connect them in.
It's surprisingly powerful.
And your boss is still not going to get fired and IT is not going to turn it off because it's leaking all this private information.
That is the trick that I think is sometimes getting lost.
And we're talking about all these great new platforms because I can use them.
I'm like, oh, this is super powerful.
Oh, and I can't use it.
And it's not because I'm at work at GitHub.
It's because I'm not allowed because they can't do all the things that large, complicated companies need.
And so whether it be, like I said.
just the kind of interesting daily driver curiosity all the way through to, oh my gosh, like I can go use this at work tomorrow potentially, uh, and have that context layer, have that intelligence.
Uh, it's a huge, it's a huge shift.
Um, uh, and so, you know, check it out.
I'd love to hear, I'm like, I'm not shy on social.
I'd love to hear feedback, like what's working, what's not.
Um, uh, but hopefully surprise folks a little bit.
What I'm hearing, I mean, so first of all, I think that's a great pitch.
What I'm hearing actually is that you should put the WorkIQ people next to the co-pilot people.
Because like the exact context problem that you named, they solved enough for you to do your job, which is nuts.
So like the thing that we are like...
That's literally what has been happening the last several months.
I already forecast you.
It's like, look, totally.
Cause like you're totally right.
The code, the code and the code asset problem is a little bit unique, but otherwise that's it.
Yeah.
We're all working with each other.
Now it's all just context.
Exactly.
Yeah.
Amazing.
Uh, great.
Uh, I, I'm going to be there.
I'm going to be doing a couple of sessions there.
I'm going to be interviewing Satya.
I know when I, um, uh, first started to pod though, I had like Jeff Dean on Jeff.
It's like hall of favor of like, I want to meet someday.
satya is on there so like what should i ask satya i mean i think i think that the best question to ask is what he thinks is true in like two or three years from now you know like it seems like such a throwaway question but ultimately uh the way that the way that he is looking at this ai problem in uh inference problem token problem and what we're at how we're actually going to be working uh I think you can see some of the recent shifts that have been happening inside of Microsoft to kind of drive us to a place where it's not four, five, six, seven, eight different things.
It's not a lack of context everywhere.
But like, why is this, you know, sort of approach in two years going to pay off?
Because that I think.
Wow, that's a bold.
Okay, I'll ask it.
I'll say I prompted by you.
Absolutely.
It's a bold question because, you know, I think there's a lot of.
doubts, to be honest, like, externally.
And so, like, yes, I want a straight answer from him on that I think would reassure a lot of people.
And honestly, like, give me a lot of food for writing.
So, thank you so much for spending your time.
Thank you for doing what you do.
I think, like, you know, as a CEO, you don't need to be the external face.
But, like, because you are authoritative, because you have so much background with GitHub and it's so authentic, like, we on the outside feel it.
So, thank you for that.
Of course.
Appreciate it.
Thank you so much, Sean.