TileDD
AI-Friendly Planning: Design with Drag, Build with Prompts
What it does
TileDD is a next-gen planning tool optimized for AI agents. Design screen structures on a 24x14 grid and manage zone-specific prompts that AI understands perfectly. We transform your intent into "structural instructions" via Markdown, eliminating hallucinations and boosting developer productivity. Unlike tools focused only on visuals, TileDD ensures AI sees exactly what to build. Don't waste time explaining structures—show them with TileDD.
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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, March 2026
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Switch from ChatGPT to Claude with import memory feature
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