How do you scale routine code migrations across thousands of files and multiple languages, without burning out your developers? Google just shared how they used LLMs to automate identifier migrations (32-bit → 64-bit) across their codebase. AI wrote nearly 75% of the code, and developers say it boosted productivity by 50% Compared to a similar manual effort that took two years, this approach cut the workload in half. Better yet, the process was repeatable, validated, and safe. Rather than chasing experimental use cases, Google focused on high-effort, low-complexity tasks that AI could handle well. This is a practical blueprint for engineering leaders looking to deploy AI for real outcomes. Break down the strategy and see how it applies to your team: https://lnkd.in/gNRSp5vK
