Safer dependency updates with coding agents

AI coding agents can make dependency updates more effective by handling compatibility work beyond automated pull requests, including API migrations, configuration changes, generated files, and targeted regression tests. Updates should be narrowly scoped to a dependency family and target version, supported by maintainer release notes, and verified through clear evidence such as expected lockfile changes, removal of deprecated APIs, focused tests, and successful type, lint, test, and build checks. The approach emphasizes reviewability and supply-chain security by separating mechanical and behavioral changes, scrutinizing new transitive packages, registries, checksums, and lifecycle scripts, and using isolated environments with failure-aware CI automation. Existing package alerts and bots should remain the intake mechanism, while agents are triggered only for migrations or deeper validation, operate with least-privilege service accounts, and cannot merge their own changes, leaving final approval to branch protections and human reviewers.

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