Why must humans carefully review an AI-generated PRD?
Understand why AI-written PRDs need human checks for invented assumptions, unclear scope, conflicting rules, missing journeys, and measurable acceptance criteria.
Why must humans carefully review an AI-generated PRD?
An AI-generated PRD can look complete even when it contains unverified assumptions. Clear formatting and confident wording do not establish that the document reflects user needs or approved decisions. Human review connects the draft to the evidence, constraints, and accountability behind the product.
Check the source of every important requirement
Compare the draft with the actual brief, discussions, and user research. Separate confirmed requirements from suggestions the assistant introduced.
In a wedding app, AI might assume that guests need accounts, organizers collect payments, or every collaborator can edit all events. Each assumption can significantly affect scope and user experience.
Ask why each feature exists and who needs it. Remove unsupported additions or label them for discussion rather than accepting them by default.
Look for contradictions and missing behavior
Trace complete journeys across the document. A role section might say guests can respond without signing in while the invitation section requires an account. Resolve these inconsistencies before implementation relies on either statement.
Review permissions, empty states, error handling, data ownership, and dependencies. Check whether acceptance criteria describe observable results rather than vague aspirations such as “seamless” or “intuitive.”
Different reviewers can contribute different perspectives, including product, design, engineering, and operational concerns.
Record decisions and unresolved questions
Update the PRD with the conclusions of the review. Keep unanswered questions visible and identify who can resolve them.
When a change affects several sections, check them together so the document remains consistent. Ask AI to help find related passages, but verify the edits yourself.
The review is complete when the team has a reliable baseline for the next stage, not merely when the document has received stylistic improvements.
The assistant may assume every guest needs an account or that all collaborators have identical permissions. These decisions should be checked because they shape both user journeys and implementation scope.
Include people responsible for product priorities and technical delivery, with design or operational input where relevant. Representative user feedback can also challenge assumptions that internal reviewers overlook.
Trace the statement to the brief, a documented decision, or user evidence. If no supporting source exists, label it as a proposal or open question until a responsible person decides.
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