── ── Mental model
Tipping Point
A tipping point is the threshold at which gradually accumulating change produces a sudden, self-reinforcing reorganization of a system. Below the threshold the system absorbs incremental change; above it, dynamics compound rapidly toward a qualitatively different state — often irreversibly. Formalized by Schelling (1969, segregation models), generalized by Granovetter (1978, threshold distributions), popularized by Gladwell (2000).
How it works
Step 1 — System: phenomenon · hypothesized tipping point (network effect / critical mass / behavior threshold) · self-reinforcement mechanism · direction (up / down).
Step 2 — Threshold: critical-mass user count for network products (often 100-1000 active in a segment); fraction of adopters for social diffusion (~10-25% empirically); social-proof threshold for behavior change. Document empirical basis.
Step 3 — Current state: adopters / incidence · distance from threshold · trajectory · rate of approach.
When to use it
- user asks 'how close are we to critical mass', 'why did growth suddenly explode (or collapse)', 'will this trend keep spreading', 'is there a network effect threshold here', 'what if we concentrated effort on early adopters'
When not to use it
the phenomenon is genuinely linear with no network effects or social-proof dynamics; the question is purely 'do we have product-market fit' before any diffusion has started.
Worked example
Schelling Segregation + Hush Puppies + Modern Platform Tipping
The intellectual lineage extends from physical phase transitions (water → ice; magnetic domain alignment; ferromagnetism) through Schelling's 1969 social application to Granovetter's 1978 generalization to Gladwell's 2000 popularization.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skills