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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)
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
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.Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs.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 additionalMehrere Wochen1-4 Wochen30-60 min
Participantsdifferent
Designers, developers as users, and facilitation2-6 researchers plus sample3-10 Kunden1-5
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsDesired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesConcierge Learnings, Service Blueprint, MVP RisksCompleted Experiment Canvas, Success Metric
Tagsno overlap
ArchitectureEngineeringFeedbackValidationTasks
OutcomesInnovationResearchQuantitative
MVPValidationServiceDiscovery
ExperimentsValidationDiscoveryHypothesis
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