Warren
A faster, more native Superset experience for AI coding
What it does
Warren is a fast, native workflow for AI coding. Keep Project, Workspace, Session, Runtime, and Agent in one model. - Host-owned Sessions that survive client quits and reconnects - A single Project → Workspace → Session resource model - Raw Terminal and structured Agent views - Native macOS terminal UI with libghostty; libghostty-vt runtime; xterm.js on Web - macOS, Web/PWA, mobile Web, and CLI clients - Open source under Apache-2.0 Learn more:
Warren is a local-first workspace for durable AI workflows. Run agent-driven work on a Mac or VPS and resume sessions from desktop, web, or CLI.
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Launched alongside, August 2026
the whole month →- TL
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