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Criterion
Paper illustration of a Polarity Map with two poles and four quadrants
Systems Thinking
Polarity Mapping
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration of two considered options leading to a decision record with a marked status and visible consequences.
Architecture
Architecture Decision Record
Causal Loop Diagram workspace showing the question, observations, and next decision.
Systems Thinking
Causal Loop Diagram
Purposedifferent
Polarity Mapping makes tensions between two opposing poles tangible, such as standardization and adaptation or control and autonomy. The method guards against making apparent either-or decisions prematurely.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.An ADR permanently records an architecture decision with context, trade-offs, and consequence. It creates continuity for later changes because the decision path stays traceable.A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations.
Complexitydifferent
MediumMediumLowMedium
Timedifferent
1-2 h2–4 h review as a planning range; preparation and evaluation additional15-45 min1-3 h
Participantsdifferent
3-12Designers, developers as users, and facilitation1-32-8
Formatdifferent
WorkshopWorkshop + asyncAsyncWorkshop
Outputdifferent
Polarity Map, Warning Signs, Balance ActionsPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsADR File, Decision Log, RationaleCausal Loop Diagram, Feedback Notes, Leverage Points
Tagsno overlap
Systems thinkingTradeoffsLeadership
ArchitectureEngineeringFeedbackValidationTasks
ArchitectureRationaleDocumentationGovernance
FeedbackSystems thinkingCausalityDynamics
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