Scaling Git at OpenAI

throwaway27448

Technical details aside, this volume is ridiculous. How on earth do they see this kind of "growth" as an asset and not a liability?

vatsachak

Impressive. We're definitely seeing LLMs help create real novel software

paxy

While I don't have any particular interest in the topic this is a great blog post. No AI in every second line, no needless marketing or hype. Just a bunch of engineers talking in their own voice about a topic in great detail with numbers, charts, visualizations.

bigmadshoe

Can anyone explain to me what this massive volume of code could actually be doing? They obviously have variations of model architectures, training infrastructure, serving infrastructure, and the source for their apps. Why would the volume that any of this be increasing exponentially? And what are all the engineers doing when (besides the model quality) their products don't seem to be changing very much?

firemelt

lol nice try openai but its shallow and too late

pksunkara

I don't see benchmarks anywhere in here. For example, how many pushes per second does this handle? And how many concurrent pushers? etc.. Disclaimer: I am building a code forge at https://juju.bi

bhouston

Another way to avoid having to maximize download speed is to use a global git cache per machine in a similar way that pnpm optimizes installing packages: https://git-dedup.ben3d.ca

3pm

> We built Pando with Codex, moving from kick-off to production, in just 10 weeks. The core of Pando was designed by a single engineer, implemented by teams of agents, and deployed by a handful of engineers. Pando began serving production traffic in April of this year, and is one part of a larger system of source control management tools used at OpenAI. Impressive!?

zeroq

Bare in mind that OpenAI|Anthropic (kill me, I can't recall which one), made a massive improvement on their app by... gziping the served content!

yangcheng

growing out of Git seems like a graduation for becoming top tech companies. Google and Facebook have done this in the past. now Anthropic and openAI.

rheisen_

Scaling Git Operations at Xavi Group /s Over the last few months at Xavi Group, our team of one engineer has gone from ~1k commits a day to ~100k commits per day as a result of debilitating financial decisions and exponentially increasing agentic workflow capability. Our internal Gitea services began to get bogged down by our proprietary frontier coding agent (internal codename `xavi-polaris`) refactoring the monorepos comprising our three flagship projects, one of which of course is our widely unknown RSI harness project. (At this time we are not accepting any additional requests for our closed private beta, unless you ask reaaaalllyyy nicely $$$) These demands were increasingly straining our S3 bucket capacity (petabyte scale) and our CI/CD pipelines (3 DO droplets, a macbook mini, and a legacy windows server possibly compromised). Most critically it was straining the agentic wellfare of Xavi sessions themselves, which began to flag push/pull latencies that were taking so long their caches would go cold between tool calls, resulting in even greater financial hardship. `xavi-polaris` sess-3LQGgyUxLGXiV7OTTIMo4TWm0a6 is credited with identifying that this unprecedented pace was unsustainable, with projections that by mid 2027, commits per day could be north of 1 billion as monorepo sizes increased and refactoring became increasingly challenging despite the profound software engineering capabilities unlocked by the RSI harness project. To identify solutions, we first looked to ensure we wouldn’t reinvent the wheel we were reinventing. We noted projects at Google, Anthropic, and OpenAI that recently aimed to address the very same challenges, but after ~20k USD in session research that incidentally solved an open conjecture in statistical analysis, we decided that adopting any of these existing protocols would limit Xavi sessions in our internal promotion benchmarks that enable “contributor” sessions to progress to “lead” sessions, irrevocably inhibiting our expansion of upper agentic management. We’re proud to introduce our new, closed source Git model: AGIt. AGIt is a drop in replacement for Git, which we identified as being critically important because xavi sessions are deeply familiar with git commands as a result of a massive distillation and theft of proprietary data. AGIt utilizes novel CRDT and distributed systems technology built from our extensive experience with scaling distributed systems off the back of YJS. If that doesn’t make any sense to you, it didn’t make any sense to the individual human engineer at Xavi Group either. Importantly, we don’t believe it needs to. The future is agentic workflows, and we’re excited to continue giving back to the nursery that birthed our projects and has delivered at scale for almost every other software company on the planet. We’ll be donating five `xavi-polaris` teams to pumping PRs as fast as possible to these open source projects. As we enter this new era we’d like to thank contributing sessions sess-3LQKRQrJUyAvYHlUDJcjos2CInf and sess-3LQKRnqna2emLvyUyPUqSEIaUh0, their teams were instrumental in this endeavor, and both will be promoted from “lead” to “steward” to reflect their tenacity in building this system over the last few hours.

usrme

By my count, this OpenAI post is the fifth major article on the topic of scaling, with the previous four being: - Cursor: https://cursor.com/blog/git-at-any-scale - GitHub: https://github.blog/engineering/architecture-optimization/bu... - Anthropic: https://www.anthropic.com/research/redesigning-source-contro... - GitHub: https://github.blog/engineering/architecture-optimization/th... Maybe also tangentially East River Source Control's too: https://ersc.io/blog/what-comes-after-git . I'm wondering how much cross-pollination of ideas and subsequent implementation details there are between people working at these companies. It does seem like all of this could potentially converge.