How to write a product requirements document (PRD) with AI

A product requirements document (PRD) describes what you are building, for whom, and how you will know it works. Done well, it is the single page everyone on the team can point to. Done badly, it is a long document nobody reads. AI can now draft most of a PRD in minutes, but only if you give it the right decisions.

What a useful PRD contains

• Problem and goal: what is broken today and what success looks like
• Users: the primary users and what they need to get done
• Scope: the features in this version, and what is explicitly out
• User flows: how each key task moves through the product
• Requirements: behaviour, edge cases, permissions and data
• Success metrics: the numbers you will watch after launch

What AI is good at

Given a clear idea and a few answers, AI is very good at the heavy lifting: structuring the document, listing edge cases you forgot, drafting acceptance criteria, suggesting metrics and spotting gaps between features and flows. It turns an hour of blank-page writing into a few minutes of reviewing.

What you still have to decide

AI cannot decide your strategy. Who the product is for, which problem matters most, what is out of scope and what “good” looks like are choices only you can make. A PRD generated without those decisions reads well and says nothing.

Keep the PRD connected

The biggest weakness of PRDs is that they drift. The document says one thing, the designs another, the tickets a third. Keep requirements next to the flows and tasks they describe, and update them together.

A PRD is only as useful as its connection to the work.

In TwoSprint

You don’t write a separate PRD in TwoSprint: Sprint 1 builds it as you go. The Idea Workspace, Feature Set, Journeys and Flow Builder together form a living product spec, and the Tasks step turns it into ordered work. Because Sprint 2 builds from the same plan, the spec and the product stay in sync.