Sub-Agents in LLM Systems : Architecture, Execution Model, and Design Patterns
As LLM-powered systems have grown more capable, they have also grown more complex. By 2025, most production-grade AI systems no longer rely on a single monolithic agent. Instead, they are composed of multiple specialized sub-agents, each responsible for a narrow slice of reasoning, execution, or validation. Sub-agents enable scalability, reliability, and controllability. They allow systems to decompose complex goals into manageable units, reduce context pollution, and introduce clear execution boundaries. This document provides a deep technical explanation of how sub-agents work, how they are orchestrated, and the dominant architectural patterns used in real-world systems, with links to primary research and tooling. ...