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Criterion
Paper illustration for Golden Path
Engineering
Golden Path
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
When teams need a reliable default path for frequent use, sprawl quickly emerges without any guiding logic. Golden Path bundles the preferred path so good practice becomes easy and deviation becomes deliberate.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.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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
MediumLowMediumMedium
Timedifferent
1-3 Tage Setup, laufend30-60 min2–4 h review as a planning range; preparation and evaluation additional1-5 Tage
Participantsdifferent
2-81-5Designers, developers as users, and facilitationNutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Golden Path Guide, Templates, Quality ChecksCompleted Experiment Canvas, Success MetricPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsClick Data, Interest Signal, Learning Decision
Tagsno overlap
EngineeringProductivityGovernance
ExperimentsValidationDiscoveryHypothesis
ArchitectureEngineeringFeedbackValidationTasks
ValidationExperimentsDemandDiscovery
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