Nit – I rebuilt Git in Zig to save AI agents 71% on tokens
In plain words
Nit is a Git implementation written in Zig designed to reduce token consumption for AI agents. It rebuilds core Git functionality with a focus on efficiency, potentially decreasing token usage by 71% compared to standard implementations. The tool targets developers and AI systems that work with version control and need to optimize computational costs. Its Zig-based architecture emphasizes performance and minimal resource overhead.
written from the facts on this page · September 2026
Does the same job
all alternatives →- GFGit for AI AgentsMay 2026 · github.com · ▲129
hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…
- GAGitAgent – An open standard that turns any Git repo into an AI agentMar 2026 · gitagent.sh · ▲147
We built GitAgent because we kept seeing the same problem: every agent framework defines agents differently, and switching frameworks means rewriting everything. GitAgent is a spec that defines an AI agent as files in a git repo. Three core files — agent.yaml (config), SOUL.md (personality/instructions), and SKILL.md (capabilities) — and you get a portable agent definition that exports to Claude Code, OpenAI Agents SDK, CrewAI, Google ADK, LangChain, and others. What you get for free by being git-native: 1. Version control for agent behavior (roll back a bad prompt like you'd revert a…
- WGWhole Git repo was made with ChatGPT2022 · github.com · ▲231
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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 · 27d ago · cactuscompute.com
Launched alongside, March 2026
the whole month →
Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com
