The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
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.
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.
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.
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.
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.
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 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 sentence describing what happened stripped of emotion, then identify the single incorrect assumption the error revealed before the memory reconstructs itself.
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.
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.
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 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.
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.
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.
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.
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.
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.
When cognitive load increases or stress appears, rely on pre-defined explicit sequences rather than intuitive ordering, because implicit sequences degrade under pressure while externalized protocols remain stable.
At each handoff point between sequential agents, specify the exact information contract (what specific output the next agent needs from the current agent) to make dependencies explicit and auditable.
Run independent agents (those with no input dependencies on each other) in parallel to compress total execution time, and serialize only those agents where one genuinely requires the other's output.
Identify the critical path (longest chain of dependent tasks) as the minimum project duration, recognizing that no amount of parallelization or additional resources can compress completion time below this constraint.
Distinguish artificial serialization (treating independent tasks as dependent) from premature parallelization (launching tasks before their dependencies resolve) by mapping actual information flow rather than assumed ordering.
Before any contested time block arrives, define the allocation rule (priority ordering, rotation schedule, or time-slice) that resolves contention in advance rather than negotiating access when the block arrives.
Before attempting to resolve paralysis between competing priorities, check whether all four Coffman conditions hold (mutual exclusion, hold-and-wait, no preemption, circular wait)—if so, violate any single condition to make deadlock structurally impossible.