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Use AI full-stack generation tools to build a launchable MVP in a week

From PRD to a running product, this workflow uses AI to generate the front end, connect a database and login, and deploy — for indie developers who want to validate fast without hand-coding from scratch.

  1. 1. Break the PRD into a generatable page list

    Use Claude to break the PRD into concrete screens (login, main feature, settings) and each page's components, states, and data fields, organized into a clear prompt for an AI generator to read.

    Claude ChatGPT

  2. 2. Generate the front end and overall architecture

    Paste the page list into Bolt.new or Lovable to generate a working full-stack skeleton at once; for fine-grained single components, use v0 to produce high-quality React components and paste them back into the project.

    BN Bolt.new Lovable v0

  3. 3. Connect the database and user login

    Use Supabase to build tables, auth, and file storage, and connect the keys into the generated project so the MVP has real signup, login, and data persistence, not fake data.

    Supabase Cursor

  4. 4. Fine-tune and fix bugs in the editor

    Pull the whole codebase into Cursor and use AI dialogue to change layouts, wire up APIs, and fix errors; for stuck logic, have it explain step by step before changing, keeping your grip on the code.

    Cursor Claude

  5. 5. Deploy live in one click

    Connect the project to Vercel to deploy, set environment variables and a custom domain, and get a live URL; each push auto-updates, making it easy to iterate while gathering feedback.

    V Vercel

FAQ

Can I follow this with zero coding ability?

You can build a prototype, but at least being able to read basic HTML and JavaScript is recommended. Bolt.new and Lovable generate runnable products, but connecting a database, fixing bugs, and setting environment variables still need basic concepts, or getting stuck is frustrating. Using Cursor as a tutor to learn while building is a good approach.

Can AI-generated code go straight into production?

For the MVP validation stage, yes, but before scaling up, add security checks (permissions, input validation, key protection) and performance cleanup. AI-generated code often has hidden vulnerabilities, so a security review with Cursor or Claude before launch is essential.

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