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| Criterion |  Knowledge Modeling PARA Method |  Product Discovery Smoke Test |  Knowledge Modeling Domain Storytelling |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | The PARA Method organizes knowledge into Projects, Areas, Resources, and Archives. It creates order when digital notes, files, and tasks no longer cleanly fit current work. | 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. | Domain Storytelling translates domain knowledge into a shared narrative of actors, objects, and workflows. It is especially useful when language, rules, and process understanding must be tightly connected. | 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 | Low | Low | Low |
Timedifferent | 1-3 h Setup, laufend | 1-5 Tage | 1-2 h | 30-60 min |
Participantsdifferent | 1 | Nutzertraffic | 2-8 | 1-5 |
Formatdifferent | Async | Async | Workshop | Workshop + async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Interest Metrics, Conversion Signal, Learning Note | Domain Story, Glossary Notes, Process Narrative | Completed Experiment Canvas, Success Metric |
Tagsno overlap | KnowledgeProductivityOrganization | ValidationExperimentsDemandGrowth | KnowledgeDomain-Driven DesignProcess | ExperimentsValidationDiscoveryHypothesis |