Key takeaways

• The agent loop is tiny: call the model, run any tool it asks for, append the result, repeat until the model returns plain text.
• Anthropic's version is "gather context, take action, verify results." It is the same loop.
• Each model call ends one of two ways: a tool request (keep looping) or an assistant message (stop).
• For a software agent, the real output is the changes on your machine, not the final text. The text is just the "I'm done" signal.
• A turn can contain dozens of inference-and-tool laps, and each turn re-sends the whole growing history, which sets up the cost problem in Chapter 4.

Original sources for this chapter: Anthropic's How Claude Code works and OpenAI's Unrolling the Codex agent loop by Michael Bolin.

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