The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
Document the purpose each category serves by completing the sentence 'this category exists to [do what] for [whom]' to distinguish functional infrastructure from inherited furniture.
When someone proposes a different categorization and your first reaction is irritation that they are 'wrong,' treat this as a signal that you have mistaken a constructed category for an objective feature of reality.
When a binary classification hides multiple distinct failure modes or reasons within a single bucket, decompose it into separate dimensions that can be evaluated independently.
When forced to make a binary decision after spectrum-based deliberation, document the richer multi-dimensional signal alongside the binary outcome so future analysis can recover what the compression discarded.
For every pair of categories in a classification system, verify that no item can legitimately belong to both (mutual exclusivity test), and verify that no domain item falls outside all categories (collective exhaustiveness test).
Design multi-class classification systems with mutually exclusive categories when items can only be one type, and multi-label systems when items can legitimately belong to multiple categories simultaneously.
Write a one-sentence decision rule for each priority type that defines membership criteria operationally before applying the types to any backlog.
Ensure that highest-priority items constitute less than 20% of total backlog; if more items are marked critical, recalibrate threshold definitions to restore differentiation.
Include an explicit 'not now' or lowest-tier priority type to prevent deferred items from inflating middle categories and to create visible records of deliberate exclusion.
Attach specific response protocols (timing, resources, escalation) to each priority type rather than treating them as descriptive labels, making priority actionable.
For each agent-task pair in collaborative work, assign an explicit role type (Responsible, Accountable, Consulted, Informed) and verify that every task has exactly one Accountable party.
Before committing to a category assignment in high-stakes decisions, explicitly name what actions that category triggers and what you would do differently if the item belonged to an adjacent category.
When items consistently resist classification in your system (you hesitate, force-fit, or leave uncategorized), map what those resistant items have in common to diagnose missing categories that represent dimensions you care about but haven't encoded.
For each top-level category in your knowledge system, write one sentence explaining what value that category protects or promotes, then identify missing categories that would operationalize values you hold but aren't currently encoding.
Treat a validation log with no disconfirmations as a warning signal of selective documentation rather than validation success, because unbiased testing inevitably produces some surprises.
When a 'Miscellaneous' or 'Other' category grows faster than named categories, it signals that your classification dimensions are missing a meaningful distinction that reality contains.
Before attempting to learn a target skill, map its prerequisite chain backward by repeatedly asking 'what must I be able to do first?' until reaching skills you can perform reliably, then start at the lowest-rated prerequisite rather than the target.
For each candidate enabling relationship, articulate the specific mechanism through which one condition creates another; if you can only state correlation ('they go together') rather than mechanism, treat it as association not enabling.
Before attempting to resolve any contradiction between beliefs, construct the strongest possible version of each side that the most informed advocate would recognize and endorse.
When evaluating confidence in a belief, count only genuinely independent lines of evidence—sources that do not share origins, methods, or assumptions—rather than total source count, because correlated sources compound confidence on a single foundation.
Connect each abstract concept in your knowledge system to at least three concrete examples from different domains, because single examples invite surface-feature overgeneralization while multiple examples force attention to shared structural patterns.
Intervene in causal chains at the deepest link where you have both ability and authority to act, as fixes at deep links prevent the entire chain from firing while surface fixes only address symptoms.
After drawing a complete relationship map, write three to five sentences describing the structural story—focusing specifically on what was invisible before you drew the map rather than summarizing what you already knew.
When a relationship type is mathematically transitive (like 'is greater than' or 'is ancestor of'), you can safely infer the endpoint connection from a chain; when it is not transitive (like 'is friend of' or 'is close to'), you must verify endpoint relationships directly rather than inferring them.