How do you keep an AI-generated PRD accurate during development?
Review assumptions, reconcile implementation changes, and maintain a clear source of truth for AI-assisted work.
How do you keep an AI-generated PRD accurate during development?
An AI-generated PRD is a draft that needs review. It can sound complete while inventing features, missing constraints, or mixing incompatible assumptions.
Review for evidence and consistency
Check every claimed user need, external capability, and quantitative target. Mark unverified assumptions rather than presenting them as facts. Trace a sample workflow through the feature descriptions, state model, and acceptance criteria to find contradictions. Remove repeated sections that use different names for the same concept.
Update decisions deliberately
When implementation reveals a constraint, decide whether to change the design or the requirement. Record the reason and revise affected sections together. Keep one clearly identified current document for coding assistants and archive obsolete alternatives. Before a new milestone, compare the PRD with demonstrated behavior and unresolved issues. This prevents an assistant from implementing an old requirement simply because it appears in a longer or more recent prompt.
No. Verify its assumptions, scope, consistency, and testability before using it to guide implementation.
Investigate the reason, make an explicit decision, and update the implementation or requirement accordingly.
Competing versions create contradictory context for developers and AI assistants.
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