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Selected:Shape-First ModelingARID (Active Reviews for Intermediate Designs)Riskiest Assumption TestLearning Card
| Criterion |  Knowledge Modeling Shape-First Modeling |  Architecture ARID (Active Reviews for Intermediate Designs) |  Product Discovery Riskiest Assumption Test |  Product Discovery Learning Card |
|---|---|---|---|---|
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. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. |
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 | 25-40 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 | Learning Card with evidence and next action |
Tags1 shared | Knowledge graphValidationSemantic | ArchitectureEngineeringFeedbackValidationTasks | ExperimentsValidationDiscoveryAssumptions | ExperimentsValidationDiscoveryLearning |