Operating Theory · September 2026
Fidelity under acceptance testing
Judge a reflection by the work it improves. Add one fact, rerun the task, and keep the fact only if the accepted outcome gets better.
Under the pillar Eidolons: working digital reflections
The method
Fix a task, a reviewer, and an acceptance test. Run it against the current reflection. Add or remove one section. Run it again. Record whether the accepted outcome improved, stayed flat, or degraded.
This is the same discipline as Outcomes Acceptance Testing™ applied to context rather than to work. It is slow, and it is the only way we know to separate a reflection that helps from a reflection that is merely thorough.
The metric trap
A coverage percentage would be easy to produce and easy to game. Until a fidelity measure can be shown to predict better accepted outcomes, we report the outcome and leave the score alone.
Put this to work
Fidelity under acceptance testing challenge record
Test the claim behind Fidelity under acceptance testing against a real case and look for where it fails.
- For
- Operators redesigning a team, service, or AI workforce.
- What you keep
- A fidelity under acceptance testing challenge record you can review, revise, and send.
- What counts as sound
- Makes the claim testable
- Includes contrary evidence
- Preserves competing explanations
- States uncertainty
- Names what would change the conclusion
Do not infer that a task can move merely because it can be described.
Nothing entered here is stored or sent. Review the prompt before sharing confidential, personal, patient, or privileged information.
Review the prompt
You can leave any field blank. The prompt will mark it as not provided.
If the record survives your review, send the question, evidence, unknowns, and requested next step.