Coachix
Build reliable AI agents with reviewable reasoning
What it does
Coachix helps builders turn AI-agent reasoning into a reviewable system: philosophy, knowledge capture, MCP tool use, skills, and model notes are organized so teams can inspect decisions, compare approaches, and improve agents with confidence.
Building AI agent workflows that are useful, not demos. A step-by-step guide to MCP tools, skills, knowledge bases, and private/self-hosted setup.
Build an AI assistant that is truly yours: keep your knowledge private, guide its work with the ideas you trust, and let it evolve through every task so it grows alongside you. Coachix lets you shape a personal AI assistant around your knowledge, privacy boundaries, trusted ideas, and evolving ways of working. It is not just a chat box; it is a workspace where the assistant can become more yours over time. Choose what role it plays, which tools it may use, what skills it can run, and what tone or workflow feels natural to you. The assistant becomes specific to your tasks instead of starting every day from a generic chatbot. Save notes, documents, decisions, and source material as private…from coachix.dev
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MorphMind: A Steerable AI PlatformMar 2026 · ▲102Build a team of AI specialists that deliver quality work
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Life & fun · 10d ago · louisabraham.github.io
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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