CodePulse — Know who owns your code
Know who owns every file in your codebase, weekly
What it does
Weekly reports showing code ownership, bus factor risks, and orphaned files in your GitHub repos. Built for engineering managers. Unlike generic code analytics dashboards, CodePulse also flags AI-generated files with no human review, not just code an ex-employee wrote. Delivered as a simple weekly email, not another dashboard to forget about.
Weekly reports showing code ownership, bus factor risks, and orphaned files in your GitHub repos. Built for engineering managers.
Every Monday, CodePulse tells you exactly where your codebase would hurt if someone left tomorrow, so you can fix it before it becomes an incident, not after. That developer left three months ago. Their code runs in production every day. Nobody on the team knows what breaks if you refactor it — so nobody does. Your payment logic just shipped reviewed only by the dev who joined last month. You found out after the deploy — because no one knew who actually owned that module. Your newest engineer asks a simple question. Three Slack threads, two DMs, and one unanswered @here later — still no clear answer about who owns what. Lands in your inbox. Covers every repo. Takes 90 seconds tofrom codepulse.beauregardsolutions.com
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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 · 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 · 17d ago · simedw.com