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Criterion
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
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 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.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
MediumHighMediumLow
Timedifferent
2–4 h review as a planning range; preparation and evaluation additional1-4 Wochen1-2 Wochen1-5 Tage
Participantsdifferent
Designers, developers as users, and facilitation1-61-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsExperiment results, Decision log, Learning summaryExperiment card, Result summary, Next betInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
ExperimentsGrowthAnalyticsValidation
MarketingGrowthExperimentsLearning
ValidationExperimentsDemandGrowth
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