The answer
Provide the target journey, learning goal, constraints, and candidate features. Ask for dependency analysis and tradeoffs, then review the suggestions using user evidence and realistic estimates.
How should features be prioritized for an MVP?
How can AI help compare competing MVP features?
More FAQs in How should features be prioritized for an MVP?
No. Easy work may contribute little to the core user outcome. Balance effort with user value, dependencies, and the need to resolve important uncertainties early.
Keep them in a clearly separated backlog with their rationale. Reassess them after learning from the first release rather than allowing them to enter implementation implicitly.
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