Why We Added Rate Limits Between AI Agents

AI agents differ from traditional automation by shifting from rigid rules to goal-oriented adaptability. While standard infrastructure focuses on rate limits at API boundaries to protect databases and providers, a critical need emerges between AI agents themselves. Initial clean architectures, where specialized agents call other agents or retrieval services, can lead to unexpected bottlenecks. Implementing rate limits between agents is now essential to maintain stability as workflows evolve from simple tasks to complex, interconnected agent interactions.