Assess whether procurement should fail a vendor lacking eval rights (a7c883)

SITUATION In a regulated entity that cannot reconstruct last month's decisions, post-deployment monitoring that only tracks uptime is the evidence after a split so frequent that the queue is being auto-cleared. Multi-model reconciliation lead has to pick Policy or governance breach or Model defect for this AI Governance Layer Lifecycle and Accountability close using post-deployment monitoring that only tracks uptime.

DECISION Multi-model reconciliation lead in a regulated entity that cannot reconstruct last month's decisions must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using post-deployment monitoring that only tracks uptime after a split so frequent that the queue is being auto-cleared.

HYPOTHESES TO TEST 1. A split so frequent that the queue is being auto-cleared is noise around an already-controlled Lifecycle and Accountability process in a regulated entity that cannot reconstruct last month's decisions, given post-deployment monitoring that only tracks uptime. 2. A split so frequent that the queue is being auto-cleared is the event in post-deployment monitoring that only tracks uptime that forces Policy or governance breach for multi-model reconciliation lead under AI Governance Layer. 3. Post-deployment monitoring that only tracks uptime shows a one-file miss after a split so frequent that the queue is being auto-cleared, not a Lifecycle and Accountability program failure. 4. Post-deployment monitoring that only tracks uptime cannot decide procurement should fail a yet after a split so frequent that the queue is being auto-cleared; hold is the only AI Governance Layer close a regulated entity that cannot reconstruct last month's decisions can defend.

ANALYSIS REQUIRED 1. Name the override that would let procurement should fail 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 post-deployment monitoring that only tracks uptime was in-policy, out-of-policy, or unlogged. 4. For this AI Governance Layer Lifecycle and Accountability file, read post-deployment monitoring that only tracks uptime against a split so frequent that the queue is being auto-cleared and write the one fact that would move procurement should fail 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 / Lifecycle and Accountability packet (post-deployment monitoring that only tracks uptime after a split so frequent that the queue is being auto-cleared). The follow-on Lifecycle and Accountability action is what multi-model reconciliation lead does next: implement the option, assign an owner, and log the missing fact.