Multi-Agent Systems Need a Control Plane, Not Just Better Orchestration

This story was originally published on HackerNoon at: https://hackernoon.com/multi-agent-systems-need-a-control-plane-not-just-better-orchestration. Multi-agent AI systems need control planes to separate agent recommendations from execution authority, policy enforcement, and auditability. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-governance, #multi-agent-ai, #ai-agent-control-plane, #enterprise-ai-governance, #agentic-ai-policy-enforcement, #ai-agent-in-production, #secure-multi-agent-systems, #ai-workflow-authorization, and more. This story was written by: @swapneswarsundarray. Learn more about this writer by checking @swapneswarsundarray's about page, and for more stories, please visit hackernoon.com. Multi-agent systems do not fail like normal software; they can coordinate into bad decisions without crashing. Orchestration only routes agents and tools, while a control plane decides whether an action is allowed before it executes. For enterprise AI, agents should propose actions, but policy, state checks, and deterministic controls must approve them.