Claudit – Claude Code Conversations as Git Notes, Automatically
Uses agent and Git Hooks to automatically create Git Notes on commit, containing the agent conversation that led to that commit. Works if either you or the agent commit. It's basically the same thing as entire.io just announced that they got $60m investment for. Except I got Claude Code to write it last week, in my spare time, without really paying attention. I certainly didn't read or write any of the code, except for one rubbish joke in the README. I've got a Claude Code instance working on Gemini CLI support and OpenCode support currently.
Does the same job
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- ICI cut my Claude API bill by 66% with Git-based context2025 · shadowgit.com · ▲5
Hey HN, I built ShadowGit a while back to automatically commit code every minute to a hidden git repo (.shadowgit.git). Original goal was to easily rollback when AI tools break things. But I discovered something interesting: this minute-by-minute history is perfect context for AI assistants. So I built an MCP server that lets Claude/Cursor query this history using native git commands. The results surprised me: Before: Claude would read my entire codebase repeatedly, burning 15,000+ tokens to debug issues. After: Claude runs `git log --grep="drag"` finds when drag-and-drop worked,…


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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.
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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

