The irreducible epistemic atoms underlying the curriculum. 2,888 atoms across 3 types and 2 molecules
When searching for disconfirming evidence, if your search could not have actually changed your mind, you performed a ritual not genuine disconfirmation—redesign the search until failure is possible.
Frame feedback requests as specific behavioral questions ('What do I consistently do that I probably don't realize?') rather than character evaluations to keep feedback at task level instead of identity level.
When new evidence arrives, classify it by diagnostic value before updating—ask whether you'd see this evidence regardless of belief truth versus only if belief were true/false.
After accumulating 15-20 judgments in the same domain, analyze whether errors cluster directionally (bias requiring correction factor) or scatter randomly (noise requiring aggregation).
Conduct a two-week bias journal recording significant judgments with confidence levels, then categorize errors by direction and type to build your personal bias profile.
For each identified bias in your profile, write a specific pre-correction question or procedure to execute before acting on judgments in that domain.
After identifying that you are systematically overconfident on timelines by X%, multiply your initial timeline estimates by (1 + X/100) before stating them publicly.
After four weeks of belief tracking, examine whether beliefs barely moved despite evidence (conservatism) or swung dramatically on single data points (base rate neglect) to identify domain-specific updating patterns.
Before interpreting any piece of information—a message, a metric, a statement, a data point—run a five-question context scan: What environment am I in? What role am I occupying? What just happened that might color my perception? What are the goals (mine and others')? What assumptions am I importing from a different context?
When switching between cognitive contexts, implement a three-step loading protocol: (1) close the current context by writing a one-sentence summary and noting open loops (30 seconds), (2) create a transition gap of deliberate non-engagement (60 seconds), (3) load the new context by reviewing relevant notes and orienting before producing (60 seconds).
Record decision context at the moment of commitment using five elements: (1) decision statement, (2) forces/constraints/emotions active at choice point, (3) expected consequences with timeline, (4) confidence level 1-10, (5) review trigger date—before hindsight bias can rewrite your reasoning.
When reviewing a past decision, read the original context record before evaluating the outcome, because evaluating outcome first allows hindsight bias to contaminate your assessment of whether the reasoning was sound.
When you experience confusion, friction, or judgment in a cross-cultural interaction, document three elements before reacting: (1) what you expected, (2) what actually happened, (3) what cultural assumption might explain the gap—treating the collision as diagnostic data about invisible defaults.
Set the threshold for decision context documentation at any choice where you deliberated between options for more than sixty seconds, because if you considered alternatives consciously, the reasoning is worth preserving against memory reconstruction.
During context loading for complex cognitive work (coding, writing, design), spend the first 60-90 seconds orienting through review of previous state before attempting to produce output, as the cognitive system requires initialization time before it can operate at full capacity in that domain.
Distinguish domain-specific facts (treatment protocols, software frameworks, market conditions) requiring aggressive temporal updating from structural principles (logic, mathematics, core psychological mechanisms) where age indicates Lindy-tested robustness, applying opposite update strategies to each type.
When importing best practices or frameworks from another era or scale, explicitly verify that the contextual conditions (organizational size, technological infrastructure, market maturity) that made the practice optimal still hold before adopting it.
For each high-stakes word in decisions or commitments (quality, ownership, alignment, done, strategy), require independent operational definitions from each stakeholder before proceeding, then compare and reconcile the definitions explicitly.
Before sending any consequential text-based message, reread it as a stranger with zero shared context would—no tone, no history, no knowledge of intent—and revise any content that could be misinterpreted in that cold reading.
When emotional content must be conveyed via text, state the emotion explicitly ("I'm frustrated about X") rather than relying on word choice or punctuation to convey tone, because textual cues for emotion fail approximately 45% of the time.
When encountering a frustrating recurring behavior in your organization, map the actual incentive structure (what gets rewarded, punished, and measured) before attributing the behavior to individual character, because most problematic behaviors are rational responses to system design.
When an AI system makes consequential decisions about people (hiring, performance evaluation, resource allocation), audit what organizational context and metrics trained the system before evaluating algorithm quality, because AI inherits and amplifies the biases of the measurement system.
Configure workspace lighting to match cognitive mode—bright, cool-temperature light (5,000-6,500K) for analytical work requiring convergent thinking; dim, warm light (2,700-3,000K) for creative work requiring divergent thinking.
Before committing to a private written position for any group decision, externalize your reasoning and conclusion before the group discussion begins, then compare it to your post-discussion position to detect social influence effects.