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AI for code migrations

Published : Nov 05, 2025
NOT ON THE CURRENT EDITION
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
Nov 2025
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Code migrations take many forms — from language rewrites to dependency or framework upgrades — and are rarely trivial, often requiring months of manual effort. One of our teams, when upgrading their .NET framework version, experimented with using AI to shorten the process. In the past, we blipped OpenRewrite, a deterministic, rule-based refactoring tool. Using AI alone for such upgrades has often proven costly and prone to meandering conversations. Instead, the team combined traditional upgrade pipelines with agentic coding assistants to manage complex transitions. Rather than delegating a full upgrade, they broke the process into smaller, verifiable steps: analyzing compilation errors, generating migration diffs and validating tests iteratively. This hybrid approach positions AI coding agents as pragmatic collaborators in software maintenance. Industry examples, such as Google’s large-scale int32-to-int64 migration, reflect a similar trend. While our results are mixed in measurable time savings, the potential to reduce developer toil is clear and worth continued exploration.

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