Coordination Layer for Coding Agents
We built an open sourced coordination layer for AI agents working on the same repository. Detects work duplication and design conflicts early
What it does
Agent swarms now ship whole features at once. Twing is the coordination layer, review standard, and organizational memory built for that scale.
AI agents don't write one function at a time anymore — they write whole features, in parallel, on the same codebase. Twing is building the layer underneath that: so agents stop stepping on each other, reviews stay meaningful at machine scale, and the reasoning behind your system stops evaporating the moment a session ends. A single engineer used to open one PR at a time. Now a handful of engineers each run several agents, each agent opens PRs that touch dozens of files, and all of it lands on the same codebase in the same afternoon. The old assumptions — one author per change, a human reads every diff, tribal knowledge lives in people's heads — don't hold anymore. We think three things need…from twing.dev
Does the same job
all alternatives →- CMCodingagents.md – The open directory for AI coding agentsFeb 2026 · codingagents.md · ▲5
- TATaskPeace – a task queue my AI coding agents pull work from over MCPJul 2026 · taskpeace.com · ▲7
- AOAgent Office – Slack for (OpenClaw Like) AI AgentsMar 2026 · github.com · ▲5
- GLGit-lanes – Parallel isolation for AI coding agents using Git worktreesMar 2026 · github.com · ▲5
- AFA framework that makes your AI coding agent learn from every sessionFeb 2026 · github.com · ▲8
- AAAgyn, an open-source Kubernetes runtime for AI agentsMay 2026 · github.com · ▲9
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the category →
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AI · 16d ago · simedw.com
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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, August 2026
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Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
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 · 16d ago · simedw.com