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Criterion
A paper-based illustration representing C4 Model with its core stages and visible working result.
Architecture
C4 Model
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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.
Complexitydifferent
LowHighMediumLow
Timedifferent
1-4 h1-4 Wochen1-2 Wochen1-5 Tage
Participantsdifferent
1-51-61-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Context Diagram, Container Diagram, Component DiagramExperiment results, Decision log, Learning summaryExperiment card, Result summary, Next betInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ArchitectureCommunicationVisualization
ExperimentsGrowthAnalyticsValidation
MarketingGrowthExperimentsLearning
ValidationExperimentsDemandGrowth
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