AI-Generated DDL and the DBA Veto Problem: Why Timing Breaks Database Safety

As AI coding agents accelerate DDL generation, database administrators face a structural timing problem where executable SQL often arrives for review only hours before a production deployment. The core issue is that a Tech Lead's PR approval addresses intent, while a DBA's veto must assess runtime risk — locking behavior, missing defaults, and schema rollback — yet both reviews are collapsed into the same late-stage window. A past incident illustrates the stakes: an add-column migration with no default passed on small staging data but locked production tables for twenty minutes, halting downstream reconciliation. Common workarounds such as post-merge review, manual diffing, or banning agents from live database credentials each address only part of the problem without surfacing intent earlier in the pipeline. The article argues that faster DDL generation by agents has outpaced human review cadence, making the veto structurally late rather than a failure of individual diligence.