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AI Evidence Gap Notes
Implementation Note
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AI Evidence Gap Notes
Implementation Note
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Model Changes Should Reopen Previous Evidence
Why model, prompt, or tool changes can affect previous acceptance evidence—and what regression testing should verify.
Oct 29
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CodeYourCompliance
Corrected Evidence Must Not Erase the Original
Why evidence revision needs lineage, not a replacement JSON file
Oct 19
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CodeYourCompliance
Why AI Agent Testing Needs Repeated Runs
Why one passing test is not enough to establish consistent AI agent behaviour, reliable outcomes, and control enforcement across repeated runs.
Oct 12
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CodeYourCompliance
1
A Matching Hash Does Not Authenticate Evidence
Why evidence integrity and chain of custody are different problems
Oct 8
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CodeYourCompliance
What Evidence Proves Human Oversight Actually Works?
Why a human approval step is only useful as a control when the execution record shows that the system actually respected the decision.
Oct 3
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CodeYourCompliance
1
September 2026
A Timestamp Field Does Not Prove When Evidence Existed
Why evidence time needs provenance, not just UTC
Sep 25
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CodeYourCompliance
A Successful Demo Is Not an Acceptance Test
Why one successful run shows that a workflow can work, but does not establish the tested boundary needed for acceptance.
Sep 19
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CodeYourCompliance
An Empty Result Does Not Prove Absence
Why collection outcome has to survive the evidence pipeline
Sep 14
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CodeYourCompliance
1
Valid Evidence Is Not Sufficient Evidence
Why control evaluation needs an evidence requirement map
Sep 7
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CodeYourCompliance
August 2026
A Changed Control Result Does Not Mean the System Changed
Why policy evaluation provenance belongs in replayable evidence
Aug 31
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CodeYourCompliance
A Policy Is Not Evidence That an AI Agent Obeys It
Why documented AI controls still need execution evidence before they can be relied upon.
Aug 31
•
CodeYourCompliance
1
A Normalized Fact Is Not the Original Observation
Why transformation logic belongs in the evidence chain
Aug 25
•
CodeYourCompliance
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