Production-Minded Multi-Agent Orchestration in Java

The demo works. Your two-agent research-writer pipeline produces a decent article. Your hierarchical team generates a plausible report. Someone on the team says "let's ship it." And then reality sets in. How many tokens did that run consume? What happens when the LLM returns garbage JSON? Can we rate-limit calls so we don't blow our API budget on day one? What if a task takes 90 seconds and produces hallucinated nonsense -- does a human get to review it before it hits the customer? These aren't edge cases. They're the difference between a demo and a deployment. This post covers what production multi-agent orchestration actually requires, and how AgentEnsemble handles each concern. Observability: Know What Your Agents Are Doing Event Callbacks Every significant event in an ensemble run fires a callback. You register listeners on the builder: Ensemble . builder () . agents ( researcher , writer ) . tasks ( researchTask , writeTask ) . chatLanguageModel ( model ) . listener ( event -> { s