The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
After each decision agent activation, update the agent's criteria based on whether they produced a good outcome, treating the agent as a living heuristic that improves with each use rather than a permanent law.
In post-decision review, explicitly add the meta-question 'Did I use the right framework for this decision?' and note framework-decision mismatches (comprehensive analysis on trivial reversible choices, satisficing on irreversible high-stakes decisions) to build your personal routing table.
Add a 60-second structured observation step immediately after recurring activities, recording one sentence about output and one about potential changes, to convert open-loop repetition into closed-loop learning.
For any recurring activity, explicitly define three elements—the specific output being measured, the standard for comparison, and the adjustment rule triggered by deviation—to create a complete minimal feedback loop.
When a feedback loop identifies a discrepancy between current and target state, translate the evaluation into a specific behavioral adjustment for the next cycle rather than stopping at awareness, because learning occurs during adjustment not observation.
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.
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.