Principlev1
Extend trust incrementally based on accumulated evidence of
Extend trust incrementally based on accumulated evidence of reliability rather than as a fixed initial condition, tightening verification when errors surface and loosening it as performance stabilizes.
Why This Is a Principle
Derives from Domain-Specific Calibration Development (calibration from feedback loops), Learning occurs when outcomes differ from predictions, (learning from prediction error), and Self-efficacy beliefs are formed primarily through mastery (self-efficacy from mastery experiences). The principle prescribes treating trust as a dynamic variable updated by evidence, using verification feedback as the teaching signal. This operationalizes trust calibration.