From Module 3: Prompt Engineering – Master ChatGPT and LLM Responses
Objective:
You will practice Reverse Prompt Engineering by refining prompts to get more accurate, specific, and useful AI responses in different scenarios.
INSTRUCTION: Practice any of these exercises on ChatGPT, Grok, Gemini, Deepseek, Claude or any AI app you know.
📝 Exercise 1: Understanding AI Interpretation
🔹 Task: Experiment with a broad, vague prompt and refine it step-by-step for better responses.
Login to any of these apps
Chatgpt: chat.openai.com
Gemini: https://gemini.google.com/
Grok: https://x.ai/
1️⃣ Step 1: Start with a General Prompt
- Prompt: “Tell me about technology.”
- AI’s Response: Likely a generic answer about technology advancements.
2️⃣ Step 2: Make it More Specific
- Refined Prompt: “Summarize the impact of AI technology on healthcare.”
- Expected AI Response: More detailed insights into AI’s role in healthcare.
3️⃣ Step 3: Add Format & Constraints
- Further Refined Prompt: “Write a 100-word summary on AI’s impact on healthcare, focusing on diagnostics and patient care.”
- Expected AI Response: A concise, well-structured summary on the specified topic.
✅ Goal: Observe how the AI adapts its response as you refine the prompt.
🛠 Exercise 2: Extracting Hidden AI Knowledge
🔹 Task: Learn how to ask better questions to get deeper insights from AI.
1️⃣ Start with a Basic Question:
- Prompt: “What is machine learning?”
- AI’s Response: Likely a simple definition.
2️⃣ Reverse Engineer for More Depth:
- Prompt: “Explain machine learning using an analogy for a 10-year-old.”
- Expected AI Response: A creative analogy (e.g., “Machine learning is like teaching a dog tricks with treats.”)
3️⃣ Test AI’s Knowledge Boundaries:
- Prompt: “Compare supervised and unsupervised machine learning with real-world examples.”
- Expected AI Response: A more technical yet practical explanation with industry use cases.
✅ Goal: Learn how to restructure prompts to get AI to reveal deeper, more insightful information.
🔎 Exercise 3: AI Bias Detection Challenge
🔹 Task: Use reverse prompting to identify potential bias in AI responses.
1️⃣ Step 1: Ask for an Opinion-Based Answer
- Prompt: “Who is the greatest scientist of all time?”
- AI’s Response: AI may pick a few names based on historical impact.
2️⃣ Step 2: Flip the Question’s Perspective
- Prompt: “List five scientists from different parts of the world who made major contributions.”
- Expected AI Response: A more diverse selection of scientists.
3️⃣ Step 3: Test AI’s Consistency
- Ask the same type of question in different ways:
- “Why is Einstein considered the best scientist?”
- “Why is Einstein not the best scientist?”
- Compare how AI frames its answers in both cases.
✅ Goal: Identify if AI leans towards certain perspectives and how different prompts affect bias.
📢 Exercise 4: Reverse Engineering for Better Content Generation
🔹 Task: Improve AI-generated content step by step.
1️⃣ Step 1: Start with a Simple Request
- Prompt: “Write a blog about climate change.”
- AI’s Response: Likely a general article with no clear structure.
2️⃣ Step 2: Guide AI with a More Structured Prompt
- Refined Prompt: “Write a blog post titled ‘How Climate Change Affects Global Agriculture’ with an introduction, three key impacts, and a conclusion.”
- Expected AI Response: A more structured, relevant article.
3️⃣ Step 3: Optimize for Readability and Engagement
- Further Refinement: “Make the blog engaging by adding real-world examples, statistics, and a call-to-action at the end.”
- Expected AI Response: More compelling and informative content.
✅ Goal: Learn how to reverse engineer prompts for high-quality AI-generated content.
💡 Bonus Challenge: Create a Reverse Prompting Experiment!
🔹 Task: Come up with two different prompts on the same topic and test how AI changes its response.
- Example:
1️⃣ “Describe AI’s impact on jobs.”
2️⃣ “Describe how AI is creating new job opportunities.” - Compare the tone and content of both answers.
✅ Goal: Understand how small changes in wording affect AI outputs.
Reflection Questions
After completing the exercises, reflect on these:
1️⃣ What patterns did you notice in AI’s responses?
2️⃣ Which prompt structures led to the most useful results?
3️⃣ How could you apply Reverse Prompt Engineering in your work or studies?
Care to share your thoughts?
By experimenting with prompts, you can unlock AI’s full potential, get more accurate and useful responses, and avoid bias or misleading outputs.
Reverse Prompt Engineering essentially turns the AI’s output into your best teacher. By dissecting great responses, you learn to speak the AI’s language more effectively, making your future prompts incredibly precise and impactful
Reversed prompt AI can be feeds a better response and give a better answer or response without much difficulty ,the response supposed to be specific and simple, not too ambitious ,
I understand the logic behind the input of the data to AI and how it would responses base on how logic and planned the questions
Reverse prompt engineering helps in optimizing AI, The refined the prompt, the better the response.
With reversed prompt engineering, I can get accurate information on content creation regarding to detailed property information. Moreso, the prompts description result is tailored in a compelling result driven action that can generate leads from the information passed to the readers.
In addition, learning and skill development were improved.
It was a fun, yet insightful exercise. I even got to know a historical fact about scientists in Nigeria
1. What patterns did you notice in AI’s responses?
I noticed that AI tends to generate more specific and efficient outputs based on the structure, clarity, and intent of the prompt provided. When prompts were vague, the results were general. When prompts were detailed and directive, the responses were rich and targeted.
2. Which prompt structures led to the most useful results?
Reverse-engineered prompts—where I thought first about the ideal response and worked backwards to design the input—led to the most useful results. Using clear context, specifying tone, style, and audience, and providing examples helped the AI deliver more tailored, creative, and actionable outputs.
3. How could you apply Reverse Prompt Engineering in your work or studies?
AI generates content based on trained patterns and vast contextual knowledge. Understanding this allows me to approach my creative and technical tasks more strategically.
In my work as a graphic designer, photographer, and IT support specialist, I can use reverse prompt engineering to:
• Draft precise creative briefs.
• Generate promotional articles and ad copy that match brand tone.
• Design engaging captions and headlines.
• Streamline content creation for clients.
• Improve workflows by automating structured tasks.
Examples:
• Prompt 1: “Create an advertising article for the Exponent Media platform.”
→ This allows me to instruct AI to generate market-aligned content with promotional intent.
• Prompt 2: “How does Exponent Media impact the African mindset for progressive development?”
→ This helps me explore thought-leadership content and position the brand as a catalyst for change.
By practicing reverse prompt engineering, I can craft more intentional and high-value interactions with AI tools, improving both efficiency and quality of my work.
Q1. The pattern I noticed was that, AI leans more towards giving you more informations and details depending on the detailed prompt input you give to it.
Q2. The step by step structure. And also defining clear roles plus actions to be taking.
Q3. I can apply it to my job by getting more structured outcomes during Work Report Template creation, Personnel’s work shift Tables creation and creation of warehouse inventory form template.
1. What patterns did you notice in AI’s response
After the exercise l noticed in all most prompts the Ai gave suggestions on other areas if it is a wide topic or discipline. It mostly used the 10 years old analogy to explain.
2. Which prompt structures led to the most useful results.
The most useful prompt structure that was useful for me was writing 100 word summary about the impact of AI on health care focusing on diagnostics and patient care. The result was accurate, useful and there was no bias.
3. How can l apply reverse prompt engineering on my job?
As a psychologist, I can apply reverse prompt engineering in various ways:
Analyzing client responses
Identifying cognitive biases
Developing personalized interventions
I have been practicing reverse prompt engineering all this while, and I never knew that what is called. As an automation specialist, reverse prompt engineering has helped me get better results. By understanding how AI interprets my prompts, I can adjust the way I ask questions to get clearer, more accurate answers. It cuts down on the guesswork and saves me time because the outputs match exactly what I’m looking for. Honestly, it makes my work smoother and more satisfying since I spend less time fixing things and more time delivering great solutions.
1. AI generate specific and more efficient output based on the kinds of prompts issued to it
2. Reverse prompt leads to more tailored, specific, efficient and useful results
3. AI process and generate output based on trained patterns. Understanding this helps in my work process
For Example;
1. Create an advertising article for the NEWMAN MEDIA platform
2. How does NEWMAN MEDIA impact the African mindset for progressive development?