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Explore the knowledge graph

Optimization requires Trade-off. Activate to inspect this relation.Optimization applies to Efficiency. Activate to inspect this relation.Machine learning depends on Optimization. Activate to inspect this relation.Inequality applies to Optimization. Activate to inspect this relation.NP-complete applies to Optimization. Activate to inspect this relation.Gradient descent applies to Optimization. Activate to inspect this relation.Linear programming is a Optimization. Activate to inspect this relation.Process optimisation is a Optimization. Activate to inspect this relation.Parkinson's Law applies to Optimization. Activate to inspect this relation.Eisenhower Matrix applies to Optimization. Activate to inspect this relation.North Star Metric applies to Optimization. Activate to inspect this relation.Goodhart's Law applies to Optimization. Activate to inspect this relation.Goodhart's Law applies to North Star Metric. Activate to inspect this relation.Optimization applies to Mathematical model. Activate to inspect this relation.North Star MetricGoodhart's LawOptimizationTrade-offMachine learningEfficiencyGradient descentMathematical modelInequalityNP-completeLinear programmingProcess optimisationParkinson's LawEisenhower Matrix
Relationship types
Legend
  • Focused concept
  • Connected concept
  • Arrow points from cause / source to effect / target
  • A line with no arrow is a two-way relationship
  • Node colour marks the concept’s primary discipline
14 concepts14 relationships26 disciplines3 relation families

North Star Metric

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At a glance

A single key metric that best captures the core value a product delivers to its users.

Disciplines
Decision Theory
Role in the graph
Cross-disciplinary bridge reaches Business, Economics, Engineering, Mathematical Modelling, Optimization, Systems Engineering
Relationships
2 · 1 relation families

Insights from this view

Structural observations about the concepts shown here — descriptions of this graph, not claims about the world.

  • This view connects 26 disciplines: Algebra, Algorithms, Artificial Intelligence, Biology, Business, Computer Science, Data Science, Decision Theory, Design, Economics, Engineering, Environmental Engineering, Ethics, Industrial Engineering, Machine Learning, Mathematical Modelling, Mathematics, Operations Research, Optimization, Physics, Political Science, Public Policy, Statistics, Sustainability Science, Systems Engineering, Systems Science.
  • Efficiency is a bridge concept — viewed here through Economics, Engineering, Environmental Engineering, Physics, Sustainability Science.
  • The connections here span 3 relation families.
  • Trade offs explains 3 concepts in this view (Biology, Business, Design, Economics, Engineering, Environmental Engineering, Ethics, Mathematical Modelling, Optimization, Physics, Political Science, Public Policy, Sustainability Science, Systems Engineering).

Relationships as a list

The focused concept’s relationships. Pick another concept in the graph above to update this list.

Explore through a different lens

A lens is a deterministic projection of the graph. Pick a discipline, thinking pattern or journey to reframe the whole view.

By discipline

By thinking pattern

By journey

Concept collections

Concept collections are curated lenses onto the fabric — themed sets of ideas that recur across disciplines. They are not journeys; they are a way to read the graph.

About this view

What this is

Start from one concept and expand outward. The view never shows everything at once — click a node to refocus, filter by relationship type, or switch to an accessible list.

One fabric

3750 concepts and 5051 typed relations form one connected component — no isolated silo.

How to read it

Focus a concept, or apply a lens (discipline, mental model, journey) to see only the threads that matter.