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Criterion
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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 of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Purposedifferent
The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.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.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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.
Complexitydifferent
LowMediumMediumMedium
Timedifferent
25-40 min1-5 Tage3–4 h for initial assessment; preparation and deeper analysis additional45-75 min
Participantsdifferent
1-5Nutzertraffic1 or a small team; particularly suitable for 3–4 people2-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Learning Card with evidence and next actionClick Data, Interest Signal, Learning DecisionLean 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 checksTest Matrix, Test Plan
Tagsno overlap
ExperimentsValidationDiscoveryLearning
ValidationExperimentsDemandDiscovery
ArchitectureQualityRiskAssessmentLean
ExperimentsValidationDiscoveryOptions
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