Google's Finance Engineering team needed to modernize their legacy data layer with Spanner, a globally distributed and strongly consistent database. Migrating without downtime presented a significant challenge, as manually rewriting dual-write logic across numerous Data Access Objects (DAOs) was slow and error-prone. To overcome this, they developed an automated refactoring pipeline using Antigravity CLI in headless mode. This approach accelerated their migration velocity and ensured data parity in staging environments. The migration involved three phases: historical data backfill, dual-write/dual-read implementation, and automated API verification. At their scale, manual implementation of each DAO's unique requirements, like MutationConverters and rollback logic, was impractical, estimated to take months. They standardized their DAO refactoring pattern by decoupling Spanner schema translation into dedicated MutationConverter units. This created a deterministic contract for an AI coding agent to generate code reliably. Antigravity CLI's headless mode allowed for repeatable refactoring across many files without human prompts. Deterministic prompts, batch execution with automated verification, and overnight execution at scale significantly reduced migration effort. This resulted in a highly reliable data migration with sustained data fidelity and allowed engineers to focus on higher-value tasks. Key takeaways emphasize decoupling schema translation, moving from interactive chat to headless automation, and using build systems as guardrails for AI code generation.