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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 Concierge MVP
Product Discovery
Concierge MVP
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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 an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution.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
MediumHighMediumLow
Timedifferent
2–4 h review as a planning range; preparation and evaluation additional1 Tag bis mehrere Wochen1-4 Wochen30-60 min
Participantsdifferent
Designers, developers as users, and facilitation4-103-10 Kunden1-5
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsProblem Statement, Prototype, Test LearningsConcierge Learnings, Service Blueprint, MVP RisksCompleted Experiment Canvas, Success Metric
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
InnovationPrototypeResearch
MVPValidationServiceDiscovery
ExperimentsValidationDiscoveryHypothesis
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