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Criterion
Blameless Postmortem workspace showing the question, observations, and next decision.
DevOps
Blameless Postmortem
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration: scenarios and architectural decisions are connected to identified risks.
Architecture
ATAM (Architecture Tradeoff Analysis Method)
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
After an incident with damage or a near miss, the method creates a sober field for learning without assigning blame. It directs attention to the course of events, conditions, and effective countermeasures.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.ATAM helps teams weigh architecture decisions when quality goals compete. The team considers business goals, stakeholder expectations, and technical decisions together. The evaluation shows which risks need further investigation.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
MediumMediumHighLow
Timedifferent
30-90 min1-5 TageSeveral meetings plus preparation and analysis; total effort depends on scope25-40 min
Participantsdifferent
3-12NutzertrafficEvaluation team, architects, and relevant stakeholders1-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Postmortem Doc, Action Items, TimelineClick Data, Interest Signal, Learning DecisionPrioritized quality scenarios in a utility tree, Architecture risks with reasoning and assumptions, Sensitivity and trade-off points, Findings report with open investigationsLearning Card with evidence and next action
Tagsno overlap
Site Reliability EngineeringIncidentLearningReliability
ValidationExperimentsDemandDiscovery
ArchitectureQualityRiskTradeoffsStakeholders
ExperimentsValidationDiscoveryLearning
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