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| Criterion |  Agile Example Mapping |  Product Strategy DIBB |  Product Discovery Experiment Canvas |  Agile Acceptance Criteria Workshop |
|---|---|---|---|---|
Purposedifferent | When a story carries business rules and exceptions, it brings clarity before implementation. It makes examples, open questions, and boundaries visible enough that the logic becomes jointly sound. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When a story needs clear checkpoints before implementation, it sharpens expectation and scope together. It sorts work by value, risk, and delivery ability. The result is captured as Acceptance Criteria and a Story Update. |
Complexitysame | Low | Low | Low | Low |
Timedifferent | 30-60 min | 1-2 h | 30-60 min | 20-40 min pro Story |
Participantsdifferent | 3-7 | 2-8 | 1-5 | 3-6 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Example Map, Acceptance Criteria, Open Questions | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric | Acceptance Criteria, Story Update |
Tagsno overlap | Behavior-Driven DevelopmentRequirementsExamplesRefinement | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis | AgileRequirementsRefinementBehavior-Driven Development |