Every team does the same thing. Agent behaves weirdly in production - retries endlessly, drops tasks, returns confident nonsense. First reaction: swap the model, tweak the prompt.
It's never the model.
Multi-agent systems aren't an AI problem. They're a distributed systems problem with an AI layer on top. And most teams skip all the boring infra - state management, observability, failure handling, routing - and pay for it later.
We'll go through 8 agentic patterns (supervisor/worker, swarm, reflection, human-in-the-loop and more), and for each one: what the pattern does, where it breaks, and what infra you actually need before shipping it to production.
This talk has been presented at AI Coding Summit NYC, check out the latest edition of this Tech Conference.


















