Multi-Agent Orchestration Solves Coordination. It Doesn't Solve Governance.

You've set up your multi-agent orchestration stack. A planner agent breaks down tasks. A researcher agent retrieves context. An executor agent takes action. They hand off to each other cleanly. The demo works. Then you ship to production and start asking different questions: What happens when the executor agent takes an action you didn't anticipate? Which agent is responsible when something goes wrong across a three-step handoff? How do you enforce a policy that applies to all agents in the system, not just one? Who — or what — is watching the whole thing? These aren't orchestration questions. They're governance questions. And your orchestration framework doesn't answer them. Multi-agent orchestration is the set of patterns and frameworks — LangGraph, CrewAI, AutoGen, KAOS, and others — that define how agents divide work, pass state, and communicate. It solves coordination: who does what, in what order, with what inputs. Multi-agent governance is the separate layer that defines what ag