Most developers think about rate limits at API boundaries. Protect the database. Protect external services. Protect model providers. Protect public endpoints. That is standard infrastructure design. What surprised us was where we eventually needed rate limits the most. Between AI agents. Not between users and agents. Between agents themselves. Everything Looked Fine Initially Our workflows started simply. One agent handled a task. If it needed additional information, it called another specialized agent. That second agent might call a retrieval service. Or a third agent. Or an external integration. The architecture looked clean. Responsibilities were separated. Each agent had a focused purpose. The system worked well during testing. Then we put it into production. Agents Create More Work Than Humans Humans are naturally slow. Agents are not. An agent can make decisions and trigger follow-up actions almost instantly. That sounds great until multiple agents start interacting continuously.…