Concepts
The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types
Link contradicting ideas together in your graph — spatial…
Deliberately link contradicting ideas in your knowledge graph rather than keeping them in separate domains, because spatial proximity forces the cognitive confrontation that compartmentalization prevents.
Use the cascade test — 'If I resolved this, what else…
Apply the cascade test to contradictions by asking 'If I resolved this, what else would have to change?' to distinguish surface contradictions (low dependency count) from deep contradictions (high dependency count).
Scale contradiction holding periods by cascade depth — one…
Set holding periods for contradictions based on cascade depth: one week for low cascade, two to four weeks for medium cascade, one month or longer for high cascade.
During a holding period, capture incubation notes on each…
During a contradiction holding period, write brief notes whenever the contradiction surfaces capturing what triggered it and what you noticed, without attempting resolution.
When a holding period expires without clarity, extend…
When holding period ends, extend the hold rather than forcing resolution if you cannot yet articulate a missing variable or synthesis, because premature resolution defeats the purpose of incubation.
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.
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.
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.
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.
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.
Name the schema before building the agent — a reliably…
Before building any agent, explicitly name the schema it operates on by writing what the agent assumes about how the world works, because unexamined schemas produce systematically wrong outputs despite reliable execution.
Separate reasoning from credentials
When someone shares expertise or makes a recommendation, separate your evaluation of their reasoning from your evaluation of their credentials by asking 'Would I find this compelling if it came from a low-status source?'
Apply the defense test to AI conclusions
Before acting on AI-generated conclusions, apply the defense test: 'Could I defend this conclusion without the AI's output? Do I understand the reasoning well enough to identify where it might be wrong?'—if not, do the cognitive work before proceeding.
Three filters for AI contradictions
After encountering AI recommendations that contradict your careful analysis, apply three filters in sequence: Does this present unconsidered evidence? Does this identify verifiable reasoning errors? Does it merely state a different conclusion without showing work? Only the first two warrant revision.