The versioning problem hits harder for agents because they have stateful side effects. A web service rollback is clean - the database stays consistent. An agent rollback doesnt undo the emails it sent or the records it touched.
What worked for me:
Deployment contracts with effect boundaries - Document which external systems each agent touches, and version those boundaries. When you change behavior, you know the blast radius.
Shadow deployments for agents - New version runs in parallel, outputs go to logs not production. Old version still executes. You catch behavior drift before it matters.
Canary with semantic diffs - Not just does it work but did the outputs change meaningfully. Same answer, different phrasing can be fine. Different decision path for same input is worth investigating.
Effect replay for testing - Record the decisions, not just the outputs. Replaying decisions against new code surfaces breaking changes before deployment.
The you cant roll back behavior framing is exactly right. The question becomes: what guardrails prevent that behavior from touching production before youre confident?
klement Gunndu
Agentic AI Wizard