Concepts
The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types
Audit your last seven days of behavior against stated…
Audit the last seven days of actual behavior (calendar, screen time, spending, energy allocation) against each stated value to calculate revealed preferences, scoring alignment from 1-10.
When behavior contradicts values, investigate the reward…
When discovering that behavior contradicts stated values, investigate the actual reward structure driving behavior rather than increasing willpower or restating values more emphatically.
Ask what competing value your misaligned behavior reveals…
For each identified values-behavior gap, ask what competing value the behavior actually reveals and what would need to change in environment, habits, or defaults for alignment.
True resolution satisfies both sides fully — if either…
Test whether a resolved contradiction is genuine innovation rather than compromise by verifying that both original requirements are fully satisfied, not partially abandoned.
Design early warning indicators for polarity drift…
Design early warning indicators for polarity drift by identifying the characteristic downsides of each pole, then monitor for those downsides to trigger course-correction before crisis.
Check subgroup relationships before aggregating…
Before aggregating data across subgroups, check whether the relationship holds within each subgroup independently, as aggregate patterns can reverse at the disaggregated level (Simpson's paradox).
Timestamp beliefs with validity windows — convert apparent…
Label each belief in your knowledge system with validity windows specifying the time period during which the belief held, converting apparent contradictions across time into explicit version transitions.
Apply the problem-vs-polarity test — if new information…
Before attempting to resolve any persistent organizational tension, apply the problem-vs-polarity test: can new information or analysis make one side permanently win? If no, design oscillation management rather than searching for resolution.
When credentialed experts contradict each other, treat…
When two credentialed experts contradict each other on the same question, treat their disagreement as a map of genuine uncertainty in the evidence base rather than as a problem requiring you to pick a winner.
Ask 'why do these experts disagree' not 'who is right'…
When experts disagree, ask 'why do they disagree' rather than 'who is right' to identify structural sources like different methodologies, populations, or outcome measures.
Resolve contradictions at the principle level once…
Address contradictions at the strategic principle level rather than re-adjudicating them at each tactical decision point to prevent decision multiplication.
Your steel man isn't ready until advocates say 'Yes…
When steel-manning an opposing position, verify adequacy by checking whether advocates of that position would say 'Yes, that is exactly what I mean' before proceeding to critique.
Your operating principles must explain your actual…
When articulating your core operating principles, require that each principle explain your actual observed behavior patterns rather than aspirational values, because a unified theory must match behavioral data not wishes.
Audit each schema's implicit assumptions, then…
For each schema, list assumptions it makes—things it takes for granted without defining—then compare assumption lists across schemas to find shared dependency gaps where both schemas assume the same foundational concept but neither defines it.
When a cross-domain analogy breaks down, investigate…
When a cross-domain mapping breaks down or fails, investigate the mismatch systematically rather than forcing the analogy—mapping failures reveal domain-specific structural features that successful mappings cannot expose.
Apply the scramble test to schema connections…
When two schemas appear to share a concept or principle, test whether the connection is genuine by attempting to scramble the specifics—if the 'connection' would work equally well between any two randomly selected schemas, you've found semantic coincidence rather than structural isomorphism.
After an insight "clicks," test if you can now…
After experiencing what feels like an insight or integration moment, verify whether it represents genuine integration by testing whether you can now do something you could not do before—if the click produced no new capability, inference, or prediction, you experienced fluency or familiarity rather than structural integration.
If integration requires reshaping one schema to fit…
When an attempted integration between two schemas forces you to reshape one schema to fit the other rather than discovering a higher-order structure that accommodates both unchanged, you are executing Procrustean integration—abandon the attempt and either maintain the schemas separately or search for a genuinely encompassing framework.
When frameworks 'click together,' immediately write what…
After experiencing a moment when previously separate frameworks 'click together', write down specifically what you can now do, see, or infer that was unavailable before the integration—this functional test distinguishes genuine structural integration from mere exposure effects disguised as insight.
Diagnose failing behavioral agents by component — trigger…
When a designed agent fails to fire consistently after two weeks, diagnose whether the trigger is not salient enough, the condition is too restrictive, or the action requires too much effort, because each failure type requires different corrections.
Only automate decisions that are frequent, stable…
Design agents only for decisions that score high on frequency (recurring often), stability (same answer each time), and low individual stakes, because these three properties determine whether automation saves resources without introducing unacceptable risk.
Measure behavioral agent progress by displacement rate…
Track agent displacement by measuring the percentage of times your designed agent fires instead of the default, not by whether you execute perfectly every time, because replacement is gradual and competes against thousands of prior reinforcements.
Never automate decisions with genuine per-instance novelty…
Do not automate decisions where the outcome is genuinely different each instance even if the category recurs (interpersonal conflicts, creative problems, novel diagnoses), because automating decisions with genuine novelty produces rigidity disguised as efficiency.
Write all three components of default agents — even…
When reverse-engineering a default agent, write down all three components (trigger, condition, action) even if the condition is 'always' or appears absent, because making the implicit condition explicit reveals where the default fires indiscriminately.