Collection Prompt
1,000+ Personalized AI Prompts that Adapt to Your Needs.
What it does
Unlock 1,000+ personalized AI prompts designed to adapt to your style, goals, and workflow. Each prompt includes roles, constraints, structures, and placeholders—so you can instantly customize it for any task. Optimized for ChatGPT, Claude, Gemini, Midjourney, Veo, Sora & more. Unlike generic prompt packs, Collection Prompt uses a personalized placeholder system. Change one keyword and the entire prompt adapts to your product, niche, tone, or client—instantly.
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Prompt Builder – Free Templates12d ago · promptbuilder.space · ▲21Hi HN, I built Prompt Builder (https://www.promptbuilder.space/) because I was frustrated managing complex AI prompts in plain text boxes. The core idea: instead of one giant textarea, you compose prompts from draggable, reorderable blocks. Each block can have its own XML/custom tags, visibility toggles (so you can A/B test sections), and duplicates. Key technical details: - Live compiled preview: the right pane shows the exact string being sent, updating as you drag/toggle blocks - Dynamic variables: define {{var_name}} once, use across blocks, change in one…
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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…
AI · 28d ago · cactuscompute.com
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