A prompt pipeline that turns a vague idea into an MVP plan

What it does

This is a personal prompt library, not software — a set of Markdown templates that steer AI models through product development documents. You feed it your raw idea, and the PRD/Guided-PRD-Creation.md prompt produces a structured requirements doc; later prompts in the chain turn that into UX specs, an MVP concept, a development plan, and a test plan. There’s also a template for generating v0.dev visual prompts so you can get frontend scaffolding out the other end.

The interesting bit

The prompts are deliberately conversational rather than one-shot: the AI asks targeted questions, checks its understanding with you before moving on, and cross-references earlier documents (like the PRD) for consistency in later steps. It’s essentially a waterfall product process encoded as prompt engineering — the AI provides structure, you keep the decision-making authority.

Key highlights

• Sequential pipeline: PRD → UX specs → MVP concept → MVP plan → test plan → v0.dev visual prompt.
• Confirmation checkpoints baked into the prompts so the AI verifies direction before proceeding.
• An Ultra-Lean-MVP folder as a faster alternative to the detailed MVP planning track.
• Designed for large-context models (Gemini, GPT-4, Claude 3); the author suggests low temperature settings for final drafts.
• Honest disclaimer: prompts are starting points, and human review is required at every step.

Caveats

• It’s glue in the purest sense — Markdown files you copy and paste, with placeholders you must fill in manually.
• The repo description mentions an AI App Starter for Next.js/Supabase/Vercel and agent configurations, but the README itself only documents the prompt templates; those components aren’t explained here.
• The author is upfront that it’s primarily a personal collection, with contributions handled via DM rather than pull requests.

Verdict

Worth a browse if you want a ready-made conversational scaffold for product planning docs and like the idea of AI asking you questions instead of guessing. Skip it if you expected an actual toolkit — the code, such as it is, lives elsewhere.