The irreducible epistemic atoms underlying the curriculum. 2,888 atoms across 3 types and 2 molecules
Schedule schema reviews at cadences matched to environmental volatility: weekly/biweekly for high-change contexts, monthly/quarterly for stable contexts, plus triggered reviews when surprises occur.
Treat surprising outcomes as automatic triggers for schema review rather than waiting for scheduled validation cycles, as surprise signals that at least one schema in your stack has drifted from reality.
When validating schemas about personal capability or performance, include external observer ratings alongside self-assessment to detect systematic overconfidence blind spots that introspection cannot reveal.
Run a pre-mortem on each critical schema by specifying what the early warning signs would look like if that model is becoming obsolete, then check whether you have already seen some of those signs.
Before attempting to update a deeply-held schema, explicitly restate it as 'I hold the belief that [X]. This belief is a model I use. It is not who I am.' to create cognitive distance between identity and the belief.
After updating a belief, identify one downstream decision where the revised model produces a different recommendation than the old one to ensure the update becomes operational rather than merely verbal.
When updating a schema, map all downstream dependencies (habits, commitments, tools, relationships, routines) before implementation and migrate high-friction dependencies first.
Before finalizing any schema update, list five situations where the old schema produced accurate results and verify the new schema handles all five to ensure backwards compatibility.
Set a tolerance window of at least sixty seconds to sit with cognitive dissonance before attempting resolution, as premature resolution systematically favors existing schemas over new evidence.
Set prediction failure thresholds as numeric ratios (X failures out of Y recent predictions) for each schema before observing prediction outcomes to trigger review when the threshold is crossed.
Define environmental change triggers by listing key assumptions underlying each schema and specifying observable indicators that each assumption no longer holds.
Accumulate anomalies (observations that don't fit the schema) in a running list and trigger full schema review when the count reaches a pre-defined threshold, rather than treating each anomaly as requiring immediate action.
Create a dedicated anomaly log separate from regular notes where each entry records what you expected, what happened, and which schema generated the expectation.
Assign review cadences to schemas based on their pace layer—weekly to monthly for fashion/commerce layers in complex domains, quarterly for infrastructure layer, annually for governance layer, and only on anomaly for culture/nature layers with high dependency depth.
When a schema has many downstream dependencies, apply slower and more deliberate revision cadences than its pace layer alone suggests, because updating foundational schemas requires cascading updates to all dependent schemas.
In complex or chaotic Cynefin domains, increase schema review frequency beyond what the pace layer suggests because unpredictability generates more frequent anomalies requiring evaluation.
Schedule schema reviews on actual calendars at the assigned cadence rather than relying on subjective feelings of uncertainty to prompt reconsideration.
When attempting to shift a shared team schema, create low-cost experiments where the team uses the new schema on one real decision, rather than presenting the new framework in slides or documents.
Before attempting to change a shared team schema, map what the current schema supports—which decisions it enables, what coordination it simplifies, and what would break if it disappeared—to understand its load-bearing function.
Scale your timeline expectations for schema change with group size—weeks for pairs, quarters for 50-person orgs, years for industries—and measure progress in behavioral change rather than stated agreement.
When your schema can no longer formulate the questions you need to ask about a domain, treat this incommensurability as a signal that the framework itself has become a cage requiring replacement.
Write schema evolution log entries with four mandatory fields - date, schema affected in original language not current interpretation, specific triggering evidence or encounter, and the replacement belief - to defeat hindsight bias through fixed external records.
Maintain schema evolution logs with minimum viable entries of four fields - date, schema affected, what changed, and what prompted the change - reviewed weekly, to generate a dataset about cognitive patterns that introspection alone cannot produce.
Treat any schema that has gone six months without deliberate review the same as a software dependency unupdated for six months - not necessarily broken but requiring verification before continued reliance.