Multi-agent systems demo beautifully and bankrupt teams in production. This talk walks through orchestration patterns that survive enterprise cost and reliability constraints: supervisor-worker decomposition, when to use LangGraph vs. CrewAI vs. AutoGen, hierarchical vs. flat coordination, agent memory boundaries, and the eval discipline that prevents agents from looping.
Concrete trade-offs, failure stories, and a decision framework for picking the right orchestration shape for the problem.
Takeaways: A decision framework for orchestration topology. A cost-aware design checklist for multi-agent systems. Observability patterns that catch loops and drift early.

Preferred length: 45 min (also 30 min).
Audience: AI engineers, engineering managers.
Level: Intermediate to advanced.
First public delivery: 2026.