── ── Cognitive bias
Cynefin
Cynefin (pronounced "kuh-NEV-in"; Welsh for "habitat") is a sense-making framework by Dave Snowden (IBM, 1999). Its claim: the right decision approach depends on which of five domains the situation falls into — Clear (obvious cause-effect, use SOP), Complicated (knowable with expertise, use analysis), Complex (emergent, probe first), Chaotic (absent cause-effect, act first), Confused (unknown domain, decompose first). The most common…
Run Cynefin on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
Step 1 — Describe: Decision/situation: · Current approach: · What worked/not: · Stakeholders:
When to use it
- 'our best practices keep failing', 'experts disagree on the right answer', 'the old playbook isn't working', 'we're in crisis and don't know what to do first', 'best practice doesn't apply here', 'we need a different approach'
When not to use it
situation is unambiguously routine (execution only); a specialized tool (OODA, expected value) already fits.
Worked example
The Apollo 13 Mission Response (1970)
Apollo 13 is a compressed, four-day demonstration of every Cynefin domain — and of why survival depended on re-diagnosing the domain at each phase instead of running one method throughout.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skillsUseful? Star the repo — stars help other builders find it.
Related mental models
Two parallel modes: System 1 — fast, automatic, effortless (pattern recognition, gut feel).
The Dunning-Kruger effect is the systematic self-assessment asymmetry demonstrated by Kruger & Dunning (1999): bottom-quartile performers overestimate rank by ~50 percentile points; top-quartile performers underestimate by…
People demand roughly 2× more to give up something they own than they would pay to acquire the identical thing — purely because they own it.
The framing effect: logically equivalent descriptions of the same decision produce different choices depending on whether outcomes are cast as gains or losses.