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Selected:Shape-First ModelingARID (Active Reviews for Intermediate Designs)Riskiest Assumption TestExperiment Canvas
| Criterion |  Knowledge Modeling Shape-First Modeling |  Architecture ARID (Active Reviews for Intermediate Designs) |  Product Discovery Riskiest Assumption Test |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | 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 | Medium | Medium | Medium | Low |
Timedifferent | Halber Tag pro Domain Slice | 2–4 h review as a planning range; preparation and evaluation additional | 1-2 Wochen pro Iteration | 30-60 min |
Participantsdifferent | 1-4 | Designers, developers as users, and facilitation | 2-6 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisions | Prioritized Assumption List, Test Plan, Results Report | Completed Experiment Canvas, Success Metric |
Tags1 shared | Knowledge graphValidationSemantic | ArchitectureEngineeringFeedbackValidationTasks | ExperimentsValidationDiscoveryAssumptions | ExperimentsValidationDiscoveryHypothesis |