When should an AI-generated PRD be revised?

When should an AI-generated PRD be revised?

An AI-generated PRD should be revised whenever the team’s current understanding differs from what the document says. Revision is expected during product development. The important distinction is between deliberate, recorded changes and silent drift that leaves contributors working from incompatible assumptions.

Update incorrect or incomplete requirements

Review may reveal invented features, unclear role permissions, contradictory terminology, or missing failure states. Correct these before the affected sections guide implementation.

For a wedding app, the initial draft might describe a single RSVP per guest. If guests can attend different events independently, the requirement needs to change to event-specific responses.

A writing improvement also matters when clearer wording removes a meaningful ambiguity.

Respond to evidence and implementation discoveries

User feedback may show that the primary workflow is harder than expected or that a planned feature adds little value. Technical exploration may expose a dependency, cost, or limitation that changes the available choices.

Do not automatically rewrite requirements to match whatever the current code happens to do. First decide whether the product behavior should change or the implementation needs correction.

Document the evidence and the person responsible for the scope decision.

Assess and communicate the impact

When a requirement changes, inspect related user journeys, designs, database rules, API contracts, tests, and delivery plans. Update affected references together.

Record what changed and why, and keep unresolved questions visible. If AI helps revise the document, verify that it did not alter unrelated commitments or reintroduce rejected ideas.

Use the latest agreed version in future prompts and reviews. A maintained PRD remains a practical coordination tool because its readers can trust that it represents current decisions.