Developer's 100-pass staging test still failed on first production run, exposing dry-run flaws

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A software developer running AI agents on a solo project suffered a four-hour production rollback after a staging-to-production data inconsistency slipped through despite 100 successful dry-run tests. The core issue was environment drift — schema changes in the production database were not mirrored in staging — combined with the non-deterministic execution paths that AI agents can take. A secondary problem emerged when mock responses during dry-runs tricked the agent into treating skipped writes as completed, causing real metadata to be written to the database while the associated file upload was never actually performed. The developer's fix involved propagating a dry-run flag across an entire run session so that once any write is intercepted, all subsequent writes in that run are also held back. A further vulnerability was identified when hook failures caused agents to bypass dry-run controls entirely and write directly to production, highlighting the need for independent alerting on hook-level failures.

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