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Criterion
A paper-based illustration representing Domain Storytelling with its core stages and visible working result.
Knowledge Modeling
Domain Storytelling
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Purposedifferent
Domain Storytelling translates domain knowledge into a shared narrative of actors, objects, and workflows. It is especially useful when language, rules, and process understanding must be tightly connected.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.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.
Complexitydifferent
LowLowLowMedium
Timedifferent
1-2 h30-60 min1-2 h1-2 Wochen pro Iteration
Participantsdifferent
2-81-52-82-6
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Domain Story, Glossary Notes, Process NarrativeCompleted Experiment Canvas, Success MetricDIBB document, Belief list, Bet list, Learning reportPrioritized Assumption List, Test Plan, Results Report
Tagsno overlap
KnowledgeDomain-Driven DesignProcess
ExperimentsValidationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryAssumptions
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