The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
Define explicit trigger conditions and time bounds for waiting periods to distinguish strategic patience from avoidance behavior.
Calculate the value of delaying irreversible decisions by comparing the cost of waiting against the expected value of information that will arrive during the delay.
Conduct scheduled recurring audits of information sources to counteract subscription inertia and source degradation.
Execute source removal decisions immediately during audits rather than creating deferral lists, to prevent audit theater that produces no behavioral change.
When capturing information that confirms your existing beliefs, deliberately search for and record contradictory evidence before filing the note, creating structural resistance to confirmation bias in your knowledge system.
Before finalizing any important judgment, explicitly construct at least one alternative interpretive frame from a different stakeholder's perspective, forcing your perception outside its default construction.
Structure your AI prompts to request multiple competing interpretations rather than a single answer, using the tool's capacity for parallel hypothesis generation to compensate for your brain's default single-model construction.
Record predictions as quantified probabilities with explicit reasoning and resolution dates before outcomes are known, creating an external reference that defeats hindsight bias and enables calibration feedback.
Aggregate predictions by confidence level and compare stated probability to actual frequency across dozens of cases rather than evaluating single predictions, as systematic patterns reveal calibration while individual outcomes contain too much noise.
Anchor estimates to outside-view base rates before constructing inside-view narratives to correct systematic planning optimism.
Before committing to irreversible decisions made under strong emotion, implement a mandatory 12-24 hour delay to allow emotional state to shift and expose state-dependent distortions in your original assessment.
When anxious, apply corrective questions that anchor to base rates and external data rather than internal feelings, as anxiety systematically inflates threat probability and deflates perceived competence.
When angry, deliberately seek disconfirming evidence and independent risk assessments, as anger systematically inflates certainty, deflates risk perception, and increases risk-seeking behavior.
Track both your predictions and your emotional state at prediction time, then analyze correlation patterns to build a personal emotional distortion profile showing which emotions warp which judgments by how much.
When identifying overconfidence in retrospective prediction reviews, widen future confidence intervals by 2-3x in that domain until hit rates align with stated probabilities, using mechanical correction where intuitive adjustment fails.
When group consensus forms quickly, assign one person the role of constructing the strongest case against the consensus before finalizing decisions, as naive realism operates at group level and suppresses dissent systematically.
Schedule consequential decisions outside metabolic depletion windows and defer irreversible commitments when running a sleep deficit of more than one hour.
Maintain external cognitive systems with the same rigor as internal cognitive health, because a disorganized external system is functionally equivalent to degraded biological memory when that system constitutes part of your thinking.
Implement controlled breathing at approximately six breaths per minute before high-stakes decisions to reverse stress-induced prefrontal cortex impairment.
Before estimating event frequency or probability, explicitly ask whether you are reasoning about base rates or about the ease of mentally retrieving vivid examples.
Maintain decision logs that record the domain, your intuitive estimate, the actual base rate, and the vivid example that inflated the estimate to build a personal availability calibration map.
Consult full historical records before consequential judgments to prevent recent data points in your cognitive buffer from overwriting distributional evidence.
Define regime-change thresholds in advance for each domain you monitor to distinguish between variance within the existing distribution and genuine structural shifts requiring model updates.
When vivid individual narratives compete with statistical base rates for your judgment, deliberately translate the problem into natural frequencies (concrete population counts) to force base rate incorporation into your reasoning.