Install
openclaw skills install @deciqai/map-is-not-the-territoryActivate when: a metric is improving but customers or employees are signaling problems; a strategy or process hasn't been reviewed in over a planning cycle; a team keeps disagreeing and can't resolve it with data; someone says 'the model shows...' or 'the data doesn't show any problems'; a plan is being followed because 'that's how we do it.' Do NOT activate when: the map is demonstrably current and freshly validated against the territory; the decision is so low-stakes that map imprecision doesn't matter.
openclaw skills install @deciqai/map-is-not-the-territoryAny representation — metric, model, strategy deck, org chart, or process manual — is a selective, simplified, aging abstraction. Maps omit (reflecting past priorities), distort (projecting dynamic reality onto static surfaces), and age (the territory moves; the map does not). The map is useful because it compresses complexity; dangerous because users forget it is a compression. Composes with goodharts-law (optimizing a metric makes it an even worse map), first-principles (rebuilding from territory when maps fail), and narrative-fallacy (every narrative is a map that ages).
Not when: the map is demonstrably current and well-calibrated; decision is low-stakes; territory is stable and map is freshly validated.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
[WAIT — do not advance until user responds]
[WAIT — do not advance until user responds]
[WAIT — do not advance until user responds]
S1 — Name the map: what is it (metric, model, plan, process)? who made it and when? what territory does it claim to represent?
S2 — Structural omissions: what does it omit by design? by measurement limits? by aging? what signals are outside this map?
S3 — Structural distortions: what relationships does it assume (linear, causal, static)? what assumptions must be true for it to be accurate?
S4 — Map age: when was it last calibrated? what has changed since? is it inside or outside its useful life?
S5 — Direct territory signal: what direct observations are available (interviews, field visits, primary data)? where is divergence from the map greatest?
S6 — Decide: use as-is / update / replace. what specific updates close the most important gap? what is the update trigger?
Map: <name> | Created by/when | Territory it represents
Omissions: by design | by measurement limits | by aging
Distortions: linearity assumptions | artificial boundaries | hidden assumptions
Age: last calibrated | territory change rate | inside/outside useful life
Territory signals: source | key divergences from map
Decision: fit Y/N/Partially | required updates | update trigger
→ Method in Action: McNamara and the Vietnam Kill-Ratio Map
| Domain | Map | Key omission | Territory signal missed |
|---|---|---|---|
| Startup growth | MAU | Churn drivers, value realization | Users activate but don't retain |
| Sales | Pipeline × close rate | Buying-committee dynamics | Close rate collapses late-stage |
| Team health | Satisfaction scores | Silent disengagement | Top performers leave without warning |
| Financial model | Revenue/cost projections | Cash flow dynamics | Model shows profit; cash crisis arrives |
| Org chart | Formal authority | Informal influence networks | Decisions route through uncharted nodes |
→ Primary sources: references/sources.md
[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.
| Fake move | Reality |
|---|---|
| [D] "Our metrics are all green — we're doing well." | Metrics are a map. Green metrics with deteriorating qualitative signals indicate map-territory decoupling. |
| [D] "The model shows this will work." | The model encodes assumptions that may be outdated. The territory does not read the model. |
| [D] "We followed the process exactly." | The process was a map of conditions that may no longer exist. Process compliance is not territory compliance. |
| [D] "The data doesn't show any problems." | The data measures a subset of territory designed for past priorities. Absence in data ≠ absence in territory. |
| [D] "We optimized the KPI — we improved the business." | Optimizing a metric is optimizing the map. Only direct territory observation shows whether underlying reality improved. |
| [D] "The expert said this is how the market works." | Expert models are maps from past encounters. Novel conditions may invalidate the map without invalidating the expert's confidence. |
| → Add [O] entries here after each real use — paste the actual failure pattern | What went wrong and why |
Stop rule: if territory observation and map are consistent across multiple independent signals, stop auditing. Over-applying risks paralytic model-skepticism where no map is trusted enough to navigate.
Part of deciqAI Knowledge Skills — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.