Legit, Open source Git-based Version control for AI agents
Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https://github.com/Legit-Control/monorepo and the website here https://legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI…
What it does
In the maker’s words, at launch
Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https://github.com/Legit-Control/monorepo and the website here https://legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI tools either run without real guardrails or store their state in proprietary databases that are hard to inspect, audit, or migrate. Once agents start collaborating on shared data, you are often just crossing your fingers and hoping nothing goes wrong. We noticed something interesting. Developers do not have this problem when collaborating on code, and agent like workflows took off there first. The reason is relatively simple. Git already solves coordination, history, review, and rollback. That insight led us to build Legit. We bring Git style versioning and collaboration to AI applications and to most file formats. Every change an agent makes is tracked. Every action is inspectable, reviewable, and reversible. No hidden state. No black box history. Legit works as a lightweight SDK that AI apps can embed anywhere the filesystem works. It handles versioning, Sync, rollback, and access control for agens. Everything lives in a repository that you can host yourself or on any Git hosting provider you already trust. We believe the right way to scale AI collaboration is not to hide what agents do, but to let developers and users see, review, and control every change. Legit is our attempt to bring the discipline, visibility, and safety of modern developer workflows to write enabled AI applications. Give it a spin: https://github.com/Legit-Control/monorepo and let us know your feedback, criticism, and thoughts.
Does the same job
all alternatives →More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com


Launched alongside, January 2026
the whole month →- IN
Hey HN! I wanted to share something I built over the last few weeks: isometric.nyc is a massive isometric pixel art map of NYC, built with nano banana and coding agents. I didn't write a single line of code. Of course no-code doesn't mean no-engineering. This project took a lot more manual labor than I'd hoped! I wrote a deep dive on the workflow and some thoughts about the future of AI coding and creativity: http://cannoneyed.com/projects/isometric-nyc
AI · Jan 2026 · cannoneyed.com




Automatic AI-powered code reviews the moment you open a PR
Dev tools · Jan 2026 · kilo.ai
