Mechanize the Lesson

Mechanize the Lesson: what to do when your AI repeats a corrected mistake
An Ena Pragma method.

THE LAW (observed, dated, in our own logs)
Lessons shipped as procedures/mechanisms tend to hold on first use. Lessons
recorded as written rules tend to be violated at least once more before they
stick, if they stick. The failure is structural: a rule requires the system to
remember to consult it at exactly the moment the wrong reflex is firing.

THE CHECKLIST (run it the second time you correct the same thing)
1. NAME THE REFLEX, not the rule. What does the system actually DO in the wrong
   moment? ("greps once and declares the thing missing", "renders a third
   attempt instead of asking", "trusts its own summary of state")
2. FIND THE INTERCEPT POINT. The last moment before the damage where a check
   could sit IN THE PATH: before a claim ships, before a file writes, before a
   third attempt renders, before money or messages move.
3. CHOOSE THE WEAKEST SUFFICIENT MECHANISM, in this order:
   a. a required tool (must run before the claim is allowed: cheap, loud)
   b. a gate that refuses (a check that blocks the path until it passes)
   c. a pipeline step (built into the workflow, cannot be skipped)
   d. only if none fit: a hard trigger rule ("at 2 rejections, X fires")
4. MAKE IT REPORT, NOT REPAIR. The mechanism surfaces the problem; a person or
   the agent fixes it deliberately. Silent auto-repair hides drift.
5. BIRTH-TEST IT ON THE REAL CASE. Point it at the exact incident that motivated
   it. If it would not have caught that incident, it is decoration.
6. RETIRE THE MEMO. Fold the written rule into the mechanism's documentation and
   stop counting on it. One pointer remains: "the tool enforces this now."

SMELL TEST
If your fix to a repeated failure contains the words "always remember to", you
have written admonition number two, not a fix.