BuildPromptKit
AI prompts that ship real UI — every one has a live demo
What it does
Most prompt collections hand you text and a screenshot. BuildPromptKit hands you the running result: every prompt has a live demo rendered from the exact React component that prompt produces — click Demo and you see real output, not a mockup. 80+ live demos across Sites, Apps, Sections, Backgrounds and Components. Tested with Cursor, Claude Code, Lovable, Bolt, v0 and Replit. Free tier, or $29 once for everything plus future drops. No subscription.
Copy-paste ready AI prompts for stunning websites & apps. Built for Cursor, Claude Code, Lovable, Bolt, v0 and more.
Battle-tested AI prompts for landing pages, mobile apps, sections and components. Copy, paste into your AI builder, done. Scroll-tied cinematic section: a 500vh track scrubs an aerial clip frame by frame through a WebCodecs frame bank, with three sequential copy blocks. Full-bleed planet loop on a 1353x1163 unit grid: two edge-cropped cut-outs flank the button and swap which world is featured. Liquid-glass weather dashboard on a 1357x871 unit grid: frosted panels over a storm photo and a chart that draws itself, then fills. Single-screen AI app-builder landing: full-bleed dawn video, glass composer card and a pixel-specified absolute toolbar. Scroll-driven 3D product page — the model…from buildpromptkit.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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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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