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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)
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration for Fake Door Test
Product Discovery
Fake Door 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.For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.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.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
MediumHighLowMedium
Timedifferent
2–4 h review as a planning range; preparation and evaluation additional1 Tag bis mehrere Wochen1-5 Tage1-5 Tage
Participantsdifferent
Designers, developers as users, and facilitation4-10NutzertrafficNutzertraffic
Formatdifferent
Workshop + asyncWorkshopAsyncAsync
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsProblem Statement, Prototype, Test LearningsInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning Decision
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
InnovationPrototypeResearch
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
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