If you have built a multi-agent AI system over the past two years, you have almost certainly encountered what we call the Supervisor Tax . The pattern usually starts with clean intentions: you have 3–4 specialized subagents (a researcher, an executor, an evaluator, and a reporter) coordinated by a central "Supervisor" or "Router" LLM. The supervisor inspects intermediate outputs, decides who gets called next, evaluates task completion, and synthesizes the final response. In local testing ...