AI Product Builder takes a product brief and generates requirements, user flows and a functional interface in a live, testable environment, skipping the static documentation phase entirely and moving straight to something a team can validate and ship from.

Scoping usually produces a document nobody can test. By the time it has been signed off, every assumption inside it has been agreed by people who have never seen it working. The point of the tool is to close that gap rather than describe it more thoroughly.

It runs as six numbered steps: industry, product type, goals, features, proposal, export. Most of the thinking sits in the features step, which splits into three tiers rather than one flat list: core features like authentication and a dashboard, advanced features like workflow automation, and AI capabilities like predictive analytics. Some carry a recommended flag based on the product type chosen earlier. A flat list makes everything look equally necessary, which is how scopes become impossible to cut. Separating core from advanced from AI is the difference between a scope somebody can negotiate and one they have to accept whole.

The decision I'd defend is at the export step, which splits in two. A proposal preview goes out as PDF, DOCX or Notion, carrying a project summary, the feature set and the tech stack, for whoever approves the spend. Designs and specifications go out separately as Figma, JSON or PDF, for whoever builds it. A single export serving both readers would have been quicker to build and wrong for each of them.

Working end to end, from industry selection through to both exports. It has only ever been tested against my own use, not a client brief.