What should an AI feature-planning document contain?
Capture user goals, scope, dependencies, acceptance checks, and open questions in a document that guides implementation.
What should an AI feature-planning document contain?
A feature-planning document should help a developer choose the next task and understand why it matters. It works best when decisions are explicit and unresolved assumptions remain visible.
Record decisions that guide the build
Include the target user, problem, intended outcome, essential journey, and release boundary. For each feature, describe the behavior, priority, dependencies, and acceptance checks. Separate requirements from example implementation ideas so a convenient suggestion does not accidentally become a permanent constraint.
Keep the plan useful as evidence changes
Add a short assumptions list with an owner or next validation step for each unknown. Note service access, media quality, and expected processing time when they affect feasibility. Record meaningful scope changes and their reasons. Before handing the document to an AI assistant, remove obsolete instructions and identify the current milestone. Finish a review by choosing one feature and verifying that someone unfamiliar with the discussion could implement and evaluate it from the document alone.
No. Name them and describe the evidence or decision needed to resolve each one.
Detailed enough to explain the behavior, dependencies, and completion checks without prescribing unnecessary implementation choices.
When evidence changes a requirement, dependency, priority, or release boundary.
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