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Criterion
Four paper stations connect system purpose, quality goals, risk cards and focused investigation with a target and gap profile.
Architecture
LASR (Lightweight Approach for Software Reviews)
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
LASR helps development teams identify where their software falls short of important quality goals and which improvements to consider. A small group with existing system knowledge can make an initial assessment and investigate open questions in more detail.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.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
MediumMediumLowLow
Timedifferent
3–4 h for initial assessment; preparation and deeper analysis additional1-5 Tage25-40 min30-60 min
Participantsdifferent
1 or a small team; particularly suitable for 3–4 peopleNutzertraffic1-51-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Lean Mission Statement describing the software’s purpose, Prioritized quality goals and evaluation criteria, Risks and estimated gaps against quality goals, More closely examined findings and open checksClick Data, Interest Signal, Learning DecisionLearning Card with evidence and next actionCompleted Experiment Canvas, Success Metric
Tagsno overlap
ArchitectureQualityRiskAssessmentLean
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryLearning
ExperimentsValidationDiscoveryHypothesis
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