Error Logging
Updated 2026-08-17
INTRODUCTION
English translation pending.
CORE DEFINITION
A learning practice borrowed from software engineering, where systems write structured records of failures so that faults can be located and prevented. Applied to personal and organisational decision-making, it treats each error as a data point with a type, a context, a root cause and a remedy, rather than as a character defect to be regretted. The value comes from pattern detection across entries: a single mistake teaches little, but repeated entries reveal systematic weaknesses in how one gathers evidence or judges risk. It requires disciplined recording and scheduled review to work.
SCAFFOLDING EFFECT
Reduce cognitive load
- Post-mortem review: Record the decision, the outcome and the reasoning that connected them, then look for recurring patterns. - Bias auditing: Tag entries by error type to see whether one bias dominates your record. - Process repair: Convert a repeated error into a checklist item or a change to the decision rule.
Anchor fast decisions
Memory rewrites failures into narratives that protect self-image, so the causal chain is lost before it can be examined. Writing the error down while the context is still fresh preserves the details that later judgement depends on, and a fixed schema forces the vague feeling of having messed up into a specific, checkable claim. Once entries accumulate, the same cause appears across different situations, which converts an anecdote into evidence about a stable weakness that can be fixed at the level of process.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- analogypkm.comhttps://analogypkm.com/experience/mental-models/zh/066_错误记录.htmlverified
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