LiveCrew AI
AI Executive Team
What it does
LiveCrew is a SaaS platform that lets solo operators and small teams run structured, multi-agent AI meetings as the CEO. You direct specialized AI agents through collaborative working sessions with defined roles, turn-taking, and persisted context, instead of fragmented one-off prompts. Unlike single-agent chat tools or autonomous agent swarms, LiveCrew keeps the human in the decision seat while compounding agent expertise across recurring meetings.
Four AI executives, a CTO, CMO, Head of Product and Head of Operations, who hold a domain, remember every meeting and push back. Every all-hands ends with a written recap and the documents to act on.
LiveCrew hands every founder four executives: a CTO, a CMO, a Head of Product and a Head of Operations. They hold a domain, remember every meeting, and tell you when you are wrong. Sessions end with a written recap and the documents to act on. 7 days free with a card up front, then $29 a month in beta. The price you join at is the price you keep. Onboarding rewrite is done. I want to ship it Friday and post the launch note the same day. Not Friday. The account migration is not reversible yet. If signups spike we cannot roll it back. Tuesday. Tuesday works. The launch note moves to Wednesday then, posting into a weekend buries it. And it ships behind a flag. I want activation on 10% of…from livecrew.tech
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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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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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