fline
Your agent ships the repo. We build it and run it.
What it does
Connect your coding agent over MCP and it ships your repo. fline writes the Dockerfile and the compose, picks the ports, provisions managed Postgres or Valkey, and hands back a URL already serving. The work happens outside your agent's context, so the deploy does not eat the session you were using to build. Secret values never pass through the agent: it declares the variable names, gets a link, and hands it to you unopened. Private beta, one node, and a maintained list of what does not work.
You and your AI built something. fline gives it an address, a database and a place in the world, so other people can use it.
You and your AI built something. Right now it only runs on your laptop. fline gives it an address, a database and a place in the world, so other people can use it. We are letting people in a few at a time. You will get an email when it is your turn, with everything you need to start. One address, stored to email you once. No tracking script on this page, and your IP is kept only as a salted hash. A shop. An internal tool. A dashboard your team checks. A game. Something with no name for what it is. Hand it over and we work out what it needs. You do not describe how it is put together, choose a plan, or answer questions about it. It works the moment it is built. There is nothing to point…from dev.fline.sh
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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.
AI · 16d ago · simedw.com
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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 · 16d ago · simedw.com