Breaking the Generalist Trap: Why Specialized AI Agents Outperform Multi-Purpose Designs

Designers often create generalist AI agents modeled on human expertise, but LLMs struggle maintaining attention across multiple responsibilities, leading to context exhaustion and accuracy loss. By applying the single responsibility principle and decomposing tasks into highly focused sub-agents—each handling one function like searching or writing—developers can achieve dramatically better reliability, mirroring successful patterns from distributed systems architecture.