---
title: "Iterative prompt refinement"
course: "AI103 · Prompting that works"
unit: "Prompt and context engineering"
lesson: 18 of 35
source: https://open.maestrocollege.edu/prompting-that-works/iterative-prompt-refinement
publisher: Maestro College
---

# Iterative prompt refinement

Lesson 18 of 35 in **Prompting that works** (AI103), unit "Prompt and context engineering". An open lesson from Maestro College.

## What the learner will be able to do
- Create a small set of test inputs, including edge cases, to check whether a prompt works beyond a single run.
- Refine a prompt one change at a time, comparing outputs across the test inputs to see which change helped.
- Judge whether a prompt is reliable by evidence (consistent results across test inputs and repeated runs), not by one good output.

## Teaching notes
Alongside your role-play, have the learner run their prompt versions and repeated runs in a free no-code playground such as Google AI Studio, so consistency is checked on a real model.

## 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 18 complete: Iterative prompt refinement."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Diagnosing failing prompts and prompt injection" (lesson 19 of 35), and give the learner its link: https://open.maestrocollege.edu/prompting-that-works/diagnosing-failing-prompts-and-prompt-injection.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: Breaking tasks into steps
Next lesson: Diagnosing failing prompts and prompt injection