An LLM loop defines the core of an AI agent. LangChain details how these systems differ from linear workflows by using iterative reasoning to achieve goals. This distinction helps developers choose between rigid automation and autonomous agents. Practitioners can now better structure production-ready systems by balancing reliability with agentic flexibility.