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Criterion
Four paper collections for projects, responsibilities, resources and archives.
Knowledge Modeling
PARA Method
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
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.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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
MediumMediumMediumLow
Timedifferent
1-3 h Setup, laufend30-90 min1-2 Wochen pro Iteration30-60 min
Participantsdifferent
11-62-61-5
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
PARA Structure, Project Notes, Knowledge ArchiveDecision Tree, Option Map, Assumption ListPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
KnowledgeProductivityOrganization
DecisionTreeOptions
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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