17 published lessons with this tag.
Your brain does not fail randomly. It fails in a specific, measurable, predictable direction: too much confidence. Across decades of research, in every population tested, the dominant calibration error is overconfidence — believing you know more than you do, that your estimates are more precise than they are, and that your performance exceeds what it actually achieves.
Assigning types to objects restricts what operations make sense on them.
No process works perfectly every time — error correction must be built in from the start.
You cannot fix what you cannot detect — invest in error detection mechanisms.
Execution errors knowledge errors and judgment errors require different correction approaches.
Design systems that surface errors early when they are easiest and cheapest to correct.
Accept that some error rate is normal and define how much error is tolerable.
When the same error happens repeatedly fix the root cause not just the symptom.
Asking why five times in succession usually reaches the root cause of a problem.
A checklist is an error prevention agent that catches predictable mistakes.
Reviewing key conditions before starting a task catches errors before they propagate.
Small uncorrected errors can trigger chains of increasingly large errors.
Recurring errors point to structural problems not personal failures.
Use tools and systems to catch errors that manual vigilance misses.
Every correction takes time and energy — reduce the error rate rather than just correcting faster.
Errors teach you more about your systems than successes do.
Expecting perfection creates fragility — expecting and handling errors creates resilience.