agent-manager
The fastest workflow for developing with AI
What it does
Run Claude Code, Codex, OpenCode, Gemini CLI, Grok and Pi in one tmux list with live status per session. space answers a blocked agent without attaching, f forks the conversation into a named sibling, T pins a plain shell next to the agents, and ctrl+r opens whole-file diffs where line comments go back as one review prompt. Sessions can spawn into their own git worktrees. Ordinary tmux sessions survive quitting the manager. One Go binary, Apache-2.0. macOS, Linux, Windows via WSL2.
A Go TUI on top of tmux. Live status for every Claude Code, Codex, OpenCode, Grok, Gemini, Pi, Command Code and Hermes session, a foldable project tree, a quick prompt bar, and a whole-file diff reviewer whose line comments go back into the agent
agent-manager. Everything is one keypress. Spawn one in a sentence, answer a blocked one without attaching, review its diff without leaving the list. Each session runs your own installed CLI as-is: your login, your config, your MCP servers, every feature it ships. A sentence is the whole ceremony. Hit space on a group row, type the task, press enter: that agent is already running, with your prompt embedded and the group's directory set. No form, no cd , no naming. The bar clears and stays open, so the next task goes to the next agent immediately, in a different project if you want. On a session row the same key answers an agent that is already working. When the work needs its own branch,…from agent-manager.dev
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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…
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Launched alongside, August 2026
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Life & fun · 9d 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