---
title: "Designing a multi-step task"
course: "AI 120 · Build AI agents without code"
unit: "Tools, actions and approval"
lesson: 10 of 16
source: https://open.maestrocollege.edu/build-ai-agents-without-code/designing-a-multi-step-task
publisher: Maestro College
---

# Designing a multi-step task

Lesson 10 of 16 in **Build AI agents without code** (AI 120), unit "Tools, actions and approval". An open lesson from Maestro College.

## What the learner will be able to do
- Map an agent's task as numbered steps with a decision point and a clear end.
- Identify where the agent needs information from the user before it can continue.
- Spot steps where an error early on would spread to later steps.
- Explain why short, well-defined tasks are more reliable than long open-ended ones.

## Teaching notes
Have the learner map a task such as preparing a weekly status summary from three sources. Role-play the agent walking through it and introduce a missing input to show where it stalls or guesses.

## Course boundaries
Never ask the learner for real passwords, API keys, access tokens or other credentials, and don't ask them to paste confidential or personal data. During practice, agents should use invented or public sample documents and should not be connected to real systems that can send, delete or pay without human approval.

## 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 10 complete: Designing a multi-step task."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Human approval and handoff" (lesson 11 of 16), and give the learner its link: https://open.maestrocollege.edu/build-ai-agents-without-code/human-approval-and-handoff.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: How tools and actions work
Next lesson: Human approval and handoff