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Criterion
Paper illustration of Pretotyping with its method-specific working model.
Product Discovery
Pretotyping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.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.
Complexitydifferent
LowHighMediumLow
Timedifferent
Stunden bis wenige Tage1-4 Wochen2–4 h review as a planning range; preparation and evaluation additional30-60 min
Participantsdifferent
1-41-6Designers, developers as users, and facilitation1-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment results, Decision log, Learning summaryPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsCompleted Experiment Canvas, Success Metric
Tags1 shared
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
ArchitectureEngineeringFeedbackValidationTasks
ExperimentsValidationDiscoveryHypothesis
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