Tag. Publish. Hope.

Teams carefully engineer application delivery with CI, canaries, staged rollouts, observability, and rollback. Libraries often get a very different delivery process: tag a version, publish it, and hope consumers are fine.

AI makes changing libraries, generating releases, and opening migration pull requests dramatically faster, but generation was never the hardest part. The hard part is knowing whether an API change is safe, who depends on it, which consumers actually call the affected symbols, and whether those consumers successfully adopted the new version. An autonomous agent without those signals is simply a faster way to cause an incident.

Drawing on lessons from Netflix’s large, decentralized JVM library ecosystem, this talk presents a paved road that library producers, consumers, and AI agents can share. It combines explicit API stability, compatibility validation, artifact- and symbol-level impact analysis, lifecycle and health signals, migration coordination, and representative consumer verification.

Aubrey and Roberto will explore why library criticality, lifecycle, and health are independent signals; why maintenance does not mean abandonment; why a created or merged pull request is not proof of a successful migration; and why making library knowledge machine-readable also improves the experience for every engineer and/or agent.

Attendees will leave with a five-part checklist for determining whether their library ecosystem is ready for AI-assisted development or whether AI will merely help them tag, publish, and hope faster.