Platyps
A collaborative workspace to take your code to production
What it does
Writing code stopped being the hard part. Platyps is the workspace around your coding agent: plan it properly, hand over full context, test against real logs, and deploy. One place for the project and everyone working on it.
Platyps is the end-to-end workspace for teams building with AI coding agents. Bring your own agent (Cursor, Claude Code, Codex, Gemini), plan and wireframe, test against real and simulated enterprise APIs, and deploy to production without becoming a DevOps engineer.
Writing code stopped being the hard part. Planning, environments, collaboration, testing, deploys, and agents losing context still are. Platyps puts all of it in one workspace. One source of truth. Talk it through once. Everything after checks itself. A sandbox that mirrors production with real logs and testing. Secrets, deploys, bugs, fixes, and everyone working on them. Three chapters, nine steps — from the first conversation to a running product. Brainstorm your idea out loud. It asks the questions you skipped and challenges your assumptions. Every decision from that conversation, written down as one document. This is your source of truth. See the screens, how they connect, and…from platyps.com
Does the same job
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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.
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