Building an AI agent is one challenge, but knowing it's ready for production is a completely different one.
Traditional software can often be verified with unit tests and integration tests, but AI agents introduce additional complexity. They rely on reasoning, external tools, changing context, and non-deterministic model outputs, which makes testing much less straightforward.
I'm curious how other teams approach this before deploying AI agents to real users.
