14 published lessons with this tag.
What you learn but do not write down you will learn again and again. The act of writing about what you learned is not documentation — it is a second act of learning that encodes deeper than the first.
A failure you analyze in writing becomes data. A failure you only remember becomes shame.
The discomfort of a failing schema is data not damage.
When your prediction is wrong you have learned something about where your schema is off.
Your schema for how learning works determines how effectively you learn.
Areas where connections should exist but do not indicate knowledge gaps.
When an agent fails to fire or produces bad results you learn how to improve it.
Action observation evaluation and adjustment form the basic feedback cycle.
The faster you get feedback on an action the faster you can adjust.
Long delays between action and feedback make the loop harder to learn from.
Reviewing what happened after completing a task surfaces errors for future correction.
Focusing on who caused an error prevents understanding why it happened.
Errors teach you more about your systems than successes do.
The way you create, maintain, and retire agents mirrors how you learn, practice, and let go of knowledge. Recognizing this parallel turns agent management into a form of self-directed development.