Assess whether deprecation will strand a downstream process (bcc698)

SITUATION Multi-model reconciliation lead is responsible for deprecation will strand a in an enterprise that just bought an AI 'control plane' vendor, using output-scoring rubric that never fails a high-risk output as the only working extract. A split so frequent that the queue is being auto-cleared is what reset the timeline for this AI Governance Layer Audit and Vendor Terms file.

DECISION Multi-model reconciliation lead in an enterprise that just bought an AI 'control plane' vendor 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 split so frequent that the queue is being auto-cleared.

HYPOTHESES TO TEST 1. Authorize Policy or governance breach now; output-scoring rubric that never fails a high-risk output already has the discriminator after a split so frequent that the queue is being auto-cleared. 2. Keep Model defect in force until output-scoring rubric that never fails a high-risk output is completed after a split so frequent that the queue is being auto-cleared for multi-model reconciliation lead. 3. Treat output-scoring rubric that never fails a high-risk output as Dual failure because both readings appear after a split so frequent that the queue is being auto-cleared. 4. Refuse a AI Governance Layer close: multi-model reconciliation lead does not have the decision deprecation will strand a turns on in output-scoring rubric that never fails a high-risk output.

ANALYSIS REQUIRED 1. Name the override that would let deprecation will strand a proceed without a silent bypass. 2. Test whether a split so frequent that the queue is being auto-cleared changed routing, logging, or human-in-the-loop on the live agent path. 3. Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged. 4. For this AI Governance Layer Audit and Vendor Terms file, read output-scoring rubric that never fails a high-risk output against a split so frequent that the queue is being auto-cleared and write the one fact that would move deprecation will strand a for multi-model reconciliation lead.

RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance Layer / Audit and Vendor Terms packet (output-scoring rubric that never fails a high-risk output after a split so frequent that the queue is being auto-cleared). Lead with the AI Governance Layer option output-scoring rubric that never fails a high-risk output can support after a split so frequent that the queue is being auto-cleared, then the two facts that force it, then the Monday action for multi-model reconciliation lead in an enterprise that just bought an AI 'control plane' vendor.