---
title: "From tool call to agent loop"
course: "AI103 · Prompting that works"
unit: "Building and choosing LLM systems"
lesson: 30 of 35
source: https://open.maestrocollege.edu/prompting-that-works/from-tool-call-to-agent-loop
publisher: Maestro College
---

# From tool call to agent loop

Lesson 30 of 35 in **Prompting that works** (AI103), unit "Building and choosing LLM systems". An open lesson from Maestro College.

## What the learner will be able to do
- Understand that an agent is an LLM called repeatedly inside a loop that code controls: the model picks the next tool call, code runs it and adds the result to the context, and the loop repeats until the model gives a final answer or a limit is reached; the growing message list is the agent's state.
- Extend a single tool-calling script into a loop that handles several tool calls in sequence, with a maximum step count as a safety stop.
- Add a human-approval check that pauses before a tool with real side effects runs, and identify what could go wrong without it.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 30 complete: From tool call to agent loop."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Inside an agent harness" (lesson 31 of 35), and give the learner its link: https://open.maestrocollege.edu/prompting-that-works/inside-an-agent-harness.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: Choosing a GenAI system architecture
Next lesson: Inside an agent harness