Assess whether agents must have a human gate for external actions (600ff6)

Situation

Agents must have a human gate sits with multi-model reconciliation lead because a batch job still calling a retired endpoint hit a publisher needing provenance on generated copy. Evidence is output-scoring rubric that never fails a high-risk output; write the AI Governance Layer Control Plane and Scoring option that extract can carry.

Decision

Multi-model reconciliation lead in a publisher needing provenance on generated copy must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using output-scoring rubric that never fails a high-risk output after a batch job still calling a retired endpoint.

Hypotheses to test

• Multi-model reconciliation lead can defend Policy or governance breach from output-scoring rubric that never fails a high-risk output after a batch job still calling a retired endpoint in a AI Governance Layer challenge.
• Multi-model reconciliation lead cannot defend Policy or governance breach from output-scoring rubric that never fails a high-risk output; Model defect is what the extract actually supports after a batch job still calling a retired endpoint.
• A batch job still calling a retired endpoint never reached the population in output-scoring rubric that never fails a high-risk output — reopen intake, do not close agents must have a human gate.
• Two facts in output-scoring rubric that never fails a high-risk output after a batch job still calling a retired endpoint conflict for multi-model reconciliation lead; hold this Control Plane and Scoring file.

Analysis required

• Test whether a batch job still calling a retired endpoint changed routing, logging, or human-in-the-loop on the live agent path.
• Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged.
• Confirm the inventory line still matches the running configuration in a publisher needing provenance on generated copy.
• For this AI Governance Layer Control Plane and Scoring file, read output-scoring rubric that never fails a high-risk output against a batch job still calling a retired endpoint and write the one fact that would move agents must have a human gate for multi-model reconciliation lead.

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