The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
Design capture systems to minimize time-to-externalization rather than optimizing for downstream organization, because working memory decay begins within seconds and compounds with each additional step.
Build capture habits by anchoring them to existing routines with actions requiring under 30 seconds, because behaviors above this threshold require substantially more motivation and form habits slower.
Limit capture tools to 2-3 in a deliberate stack (fast capture layer + voice layer + processing layer) because more options increase decision time logarithmically while multiple inboxes fragment attention.
Route all captured material through a single inbox that is processed to zero on a regular cadence, because multiple unprocessed inboxes consume working memory slots for tracking their existence independent of their contents.
Process inbox items in two distinct passes—first clarifying what each requires, then organizing where each goes—because simultaneous decisions create high element interactivity that degrades both clarification and placement quality.
Complete actions requiring less than two minutes immediately during processing rather than deferring them, because the transaction cost of tracking (writing, reviewing, re-engaging) exceeds execution cost below this threshold.
Apply the two-minute completion rule only during dedicated processing sessions, not during execution time, because interrupting deep work for quick tasks imposes context-switching costs that dwarf the task duration.
Schedule asynchronous communication processing at fixed intervals rather than continuously to protect sustained attention required for cognitively demanding work.
Record the situational context that makes captured information meaningful (why it matters, what triggered it, how it connects) at the moment of capture, before context-dependent memory decays.
Use photographic capture for spatial, visual, or topological information where sequential text representation would lose critical structural relationships.
Match capture modality (text, voice, photograph) to the structural properties of the information and the physical constraints of the capture moment rather than defaulting to a single method.
Schedule periodic reviews at intervals that match the natural decay rate of the information type being reviewed — weekly for action commitments, monthly for strategic projects, quarterly for life direction.
End each review session by explicitly noting what to examine first in the next review, eliminating activation energy at the next session's start.
Separate capture speed from storage permanence by maintaining distinct hot and cold systems with explicit migration policies between them.
Avoid making classification decisions during capture — defer categorization to processing sessions to maintain capture speed and prevent premature filtering.
Treat the absence of captures in specific domains as diagnostic data revealing psychological avoidance patterns rather than random memory failure.
Choose capture tools based on what you will actually use in your most common insight-generating contexts, not on which tool benchmarks best in controlled comparisons.
Capture conversational insights within 30 minutes of the exchange using brief fragments written during the conversation, then expand those fragments while the context remains accessible.
Write compressed interpretations during conversations rather than verbatim transcripts, as the compression process itself creates stronger memory encoding than passive recording.
Write about emotional experiences with increasing use of causal and insight words (because, realize, understand) rather than staying purely in feeling-description to maximize psychological and physical health benefits.
Resist interpreting emotions during initial capture; record raw affective state and defer causal explanation to review when multiple entries enable pattern recognition.
Capture every instance of surprise (prediction-expectation mismatch) immediately, regardless of magnitude, because small surprises reveal systematic model blind spots that large surprises obscure.
When delegating to AI systems, maintain human capability to evaluate output quality independent of the AI, as AI assistance creates illusions of understanding that operate without the performer's awareness.
Identify tasks where you are a single point of failure (bus factor of one) and systematically transfer ownership to create resilient systems that function without your presence.