Understanding the Agent Loop: How Tool-Using LLM Systems Actually Work

Short summary

Agent systems require an orchestration harness around the LLM that manages the loop: assemble input, call the model, validate and execute tool requests, append results, and iterate until final output. The harness, not the model alone, owns prompt assembly, state management, tool execution, and termination. Architectural choices in the harness—not just the model—determine agent behavior and reasoning quality.

• •Agent loops require explicit orchestration outside the model to manage tool execution and state continuity
• •The harness owns prompt assembly, validation, error handling, and loop termination—these architectural decisions drive different agent behavior
• •Client-side vs. hosted vs. MCP tool orchestration each have distinct tradeoffs between operational control and simplicity

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