How to build a startup with AI, step by step

There's a lot of vague advice about "building with AI." Most of it skips the actual sequence of decisions. Here's the version grounded in what the process actually looks like end to end, using tools that exist today.

Step 1: start from evidence, not a blank page

The hardest part of any startup isn't writing code — it's knowing whether the thing is worth building at all. Starting from a product that already had real users, and figuring out specifically why it stopped working, replaces a guess with a starting hypothesis you can actually reason about.

Step 2: let AI stress-test the idea before you commit

A good AI collaborator should push back — ask what's actually different this time, what audience is being underserved, what the honest weaknesses are. If the only thing that changes between the dead product and your new idea is the name, that's not a plan yet.

Step 3: get the boring parts done fast

Pricing strategy, a technical architecture, a database schema, launch copy — none of these need to take weeks when you have a clear, evidence-based starting point and an AI collaborator that can draft a first version of each in minutes. The job becomes reviewing and refining, not staring at a blank document.

Step 4: hand the plan to a coding agent, not a to-do list

The last mile — actually building it — is where AI coding agents like Claude Code, Cursor, or Lovable earn their keep. A structured, specific prompt (tech stack, schema, feature list already decided) turns "I should learn to code this" into "the scaffolding is already running." That's the difference between an idea staying an idea and becoming something real.