Concepts
The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types
After 10+ post-action reviews, analyze in aggregate…
After accumulating 10+ post-action reviews, analyze them in aggregate to identify structural causes appearing across multiple unrelated tasks—these recurring patterns indicate systemic tendencies requiring architectural fixes not isolated corrections.
Add verification checkpoints at every coupling point where…
Insert independent verification checkpoints at every coupling point where one process automatically consumes another's output without review to interrupt error cascade chains before they amplify.
Design three operating modes for every important process
For every important recurring process, design three explicit operating modes—full, reduced, and minimal—where each preserves progressively less fidelity but never loses continuity.
Define triggers for mode transitions in both directions…
Define transition triggers for each operating mode that specify when to shift from full to reduced, reduced to minimal, and—critically—from degraded back to full operation.
Test degraded modes during calm periods — if they don't…
Test degraded operating modes during periods of abundant resources to verify they preserve core function, because modes that fail under calm conditions will certainly fail under stress.
Occasionally run processes in degraded mode…
Practice running processes in degraded mode occasionally even when not required to rehearse partial failure, making the transition familiar rather than frightening when real constraints force it.
Document five recovery components for every important…
For every important process, document five components of recovery: failure mode specification, detection trigger, ordered recovery steps, recovery time target, and verification check.
Set RTO and RPO before failure, not during crisis — define…
Set Recovery Time Objectives (RTO) that define maximum acceptable downtime and Recovery Point Objectives (RPO) that define maximum acceptable data loss before a failure occurs, not during crisis.
Log every mistake for 30 days with date, event…
Maintain an error log for 30 days that records date, what happened, and conditions present for every mistake, without analysis or interpretation, to create raw data for pattern detection.
Automate pattern-based error detection before manual…
Deploy automated grammar checkers, linters, or mechanical validation tools before manual review to catch pattern-based errors, reserving human attention for contextual judgment that tools cannot provide.
Never rely on human vigilance for low-frequency monitoring…
When sustained attention must monitor for low-frequency errors over extended periods (>30 minutes), delegate detection to automated systems rather than relying on human vigilance, because attentional resources degrade predictably regardless of motivation.
Detect errors at the earliest catchable point — correction…
Place error detection checkpoints at the earliest point in a process where the error can first be caught, because correction cost increases exponentially with propagation distance downstream.
Multiply direct correction time by 3x for true cost…
Track the full cost of recurring corrections by multiplying direct time by three to account for context-switching, opportunity cost, and verification overhead, revealing the true resource drain that justifies prevention investment.
When correction exceeds 20% of weekly capacity, shift…
When error correction consumes more than 20% of weekly capacity in a domain, shift resources from faster correction to upstream prevention mechanisms that reduce error generation rate.
Within 24 hours of an error, write one mechanistic…
Within 24 hours of an error, write one mechanistic sentence describing what happened stripped of emotion, then identify the single incorrect assumption the error revealed before the memory reconstructs itself.
Every active goal needs an error budget — define…
For each active goal, define an explicit error budget specifying how many misses, delays, or quality drops per period are acceptable before triggering system review, converting brittle expectations into resilient ones.
Three-tier error budgets
Define error budget thresholds in three tiers—green (within budget, no action), yellow (approaching limits, investigate), red (exceeded, halt and redesign)—with pre-committed responses for each zone.
Decompose error handling into four independent subsystems
Separate error detection, diagnosis, correction, and learning into independent subsystems so each can be improved independently and partial failure doesn't disable the entire error-handling architecture.
After one cycle, review the corrector itself — did…
After deploying a self-correcting mechanism for one cycle period, add a meta-correction review asking whether the correction actually prevented the target error, adjusting the corrector itself if it failed.
Find the leading indicator that appears days before…
For recurring errors, identify the leading indicator that appears days or weeks before full manifestation, not hours, because late signals provide insufficient time for corrective action to prevent the error.
Define non-overlapping agent scopes — scope collisions…
Design cognitive agents with non-overlapping scopes by defining exactly which situations, resources, or decisions each agent claims authority over, treating scope collisions as architecture problems requiring boundary redefinition rather than willpower failures.
Assign exactly one agent as accountable for each decision…
When designing RACI-style accountability for cognitive agents, assign exactly one agent as 'accountable' (final decision authority) for each contested decision or resource, allowing other agents to be consulted or informed but not to hold veto power.
Agent priority orderings must be context-specific — which…
Build priority orderings that are context-specific rather than global, defining which agent takes precedence during specific time blocks, capacity states, or situational contexts rather than attempting universal rankings.
Map agent dependencies and arrange in topological order…
Define cognitive sequences by mapping dependencies between agents (which outputs serve as inputs to which other agents), then arrange agents in topological order so no agent executes before its required inputs are available.