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.
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?
The more specific the prompts are, the more details one extracts from Ai.
AI is not bias because, even when asked, “Why is Einstein not the best scientist?” the response was to justify why Einstein should indeed be considered the ‘best’ scientist. In the aspect of reverse engineering for better content, the more detailed the prompt, the better the response/information received.
As a teacher, I will apply AI reverse Prompt engineering in designing Better Questions and Assignments, Enhancing Feedback and Rubrics, and Improving Lesson Plans.
The aspect of AI bias was notable because, even when asked, “Why is Einstein not the best scientist?” the response was to justify why Einstein should indeed be considered the ‘best’ scientist. In the aspect of reverse engineering for better content, the more detailed the prompt, the better the response/information received.
Reverse prompt makes us communicate better with an AI model and get very accurate and informative data. It also helps in extracting more data and also detect bias or misleading responses from AI, enhance digital marketing skills like content creation and optimization.
Reverse prompt make us communicate deeper,and extract the type of answers we want from the AI.
1. Patterns Noticed In AI’s Responses
✓ Structured Outputs – AI often organizes information into bullet points, numbered lists, or labeled sections (e.g., “Introduction,” “Benefits,” “Challenges”) even when not explicitly asked. This makes responses easy to scan and digest.
✓ Polished, Formal Tone – Unless guided otherwise, responses lean toward a professional, academic, or explanatory tone, making them suitable for reports, presentations, or knowledge-sharing.
✓ Context Awareness – When given prior context, the AI continues conversations logically and maintains tone consistency. It remembers key names, projects, or roles, which makes follow-ups more meaningful.
✓ Assumption-Filling – AI often fills in gaps or makes reasonable assumptions to complete a prompt if instructions are incomplete or ambiguous—especially when you provide a goal but not detailed steps.
✓ Over-Explaining (especially when hen under-specified) – Without clear direction, responses can be overly broad or lengthy, trying to cover all possible angles of a question.
2. Prompt Structures That Developed The Most Useful Results
✓ Clear Roles + Action Requests – e.g., “Act as a PPP Analyst and draft a one-paragraph summary of project risks for a stakeholder meeting.” This combo works well: role + task + context.
✓ Step-by-Step Prompts – Asking the AI to “walk me through this step-by-step” or “first do X, then ask me for Y” leads to better, layered responses.
✓ Examples Included – Including sample input or expected output (“e.g., like this…”) helps the AI match tone, structure, and depth more accurately.
✓ Constraints or Style Requests – e.g., “Limit to 100 words,” “Use plain English,” “Make it suitable for a PowerPoint slide.” These sharpen results and avoid overly generic output.
✓ Iterative Refinement – Starting with a basic prompt and then refining: “Good, now make it more concise,” or “Now adapt this for a technical audience.” This creates tailored results efficiently.
3. Application Of Reverse Prompt Engineering In My Work / Studies In PPPs
✓ Faster Document Drafting – By analyzing well-written AI outputs, I can reverse-engineer the type of prompt that produces them and replicate that structure for future reports, memos, or summaries.
✓ Template Creation – I can design prompt templates for routine tasks (e.g., risk matrices, stakeholder maps, executive briefs), saving time while maintaining quality.
✓ Improving Collaboration – Teaching colleagues or teammates how to craft better prompts (or reverse-engineer ones that worked) can make team output more consistent and efficient.
✓ Training & Knowledge Sharing – I can use reverse prompt engineering to help junior team members understand how to frame their questions to AI tools, which boosts their productivity and independence.
✓ Scenario Design – In PPP training or stakeholder sessions, I can reverse-engineer prompts to create AI simulations (e.g., contract negotiation, risk allocation) for interactive learning experiences.
OGBEKHIULU Cynthia Ikhiannosen
Cohort 1, Team 2
Reversed prompt engineering is an eye opening to the different ways Ai answers questions based on the prompt provided..
Sure! Here’s a thoughtful and well-structured response you can use or customize when clicking **”Click Here To Post Your Thoughts”** in your course:
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### 🌟 **My Thoughts on Reverse Prompt Engineering Exercises**
Participating in the reverse prompt engineering exercises was eye-opening. I realized how *critical* the structure, clarity, and intent of a prompt are in getting useful and relevant responses from AI systems like ChatGPT, Gemini, or Claude.
#### 💡 Key Takeaways:
* **Precision Matters:** A vague prompt gives vague answers. But as I refined my prompts—by narrowing the topic, setting a format, or giving a word limit—the responses became more insightful and tailored.
* **Reverse Engineering = Deeper Learning:** Asking the same question from different perspectives (like with Einstein or machine learning examples) helped uncover bias and also stretched the AI’s creative capabilities.
* **Practical Value:** These techniques are not just theoretical. I now see how they can directly improve my work—whether it’s writing better content, conducting more targeted research, or avoiding biased assumptions.
#### 🧠 What I Learned:
* The AI can be *coached* to behave more intelligently just by how we talk to it.
* Small tweaks in prompts can change tone, depth, and direction of answers significantly.
* Reverse prompting is a powerful tool for both *content creators* and *critical thinkers*.
#### 🚀 How I’ll Apply This:
I plan to use reverse prompt engineering in my daily tasks—especially when generating reports, brainstorming, or learning new concepts. It makes AI a much smarter assistant when guided effectively.
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Let me know if you’d like a version tailored specifically to your area of study or professional focus!
?
* What tools did they use and in what
sequence?
Q1.The patterns I noticed in AI responses are
as follows,
1 Coherence and Fluency: AI responses
generally maintain a logical flow and are
grammatically correct, often sounding quite
natural.
2 Neutral Tone: AI responses tend to be
objective and avoid expressing personal
opinions or strong emotions.
3 Consistency
4 Structure and Formatting: AI often employ
patterns like bullet points, numbered lists,
and paragraphs to organize information
clearly.
Q2.Which prompt structures led to the most
useful results? ANSWER
1. Clear and Specific Instructions:
* Action Verbs: Start with a clear action verb (e.g., “Write,” “Summarize,” “Generate,” “Explain,” “Analyze,” “Compare”).
2. Precision: Avoid vague language. Instead of “Tell me about marketing,” try “Explain digital marketing trends.
3. Unambiguity: Ensure there’s no room for misinterpretation.
4. Context and Background Information:
* Provide Relevant Details 5. Constraints/Limitations: Specify any boundaries, such as word count, timeframes.
Q3. How could you apply Reverse Prompt Engineering in your work or studies? ANSWER
Here’s how I can apply Reverse Prompt Engineering as a construction worker.
1. Troubleshooting and Problem Solving:
* Scenario: You encounter a completed
section of work (e.g., a wall, a foundation, a
pipe fitting) that isn’t up to standard, is
leaking, or has a structural issue.
* RPE Application: Instead of just fixing it, ask: “What ‘prompt’ (instructions, materials, conditions, sequence of steps) would have led to this specific fault?”
* Was the blueprint misinterpreted (a faulty “prompt”)?
* Was the wrong material used (a “prompt” for a different material)?
* Were steps skipped or done out of order (an incomplete or rearranged “prompt”)?
* Were environmental conditions (rain, cold, heat) not adequately accounted for in the original plan (“prompt”)?
* Benefit: Helps you diagnose the root cause of problems, not just the symptom, leading to more permanent solutions and preventing recurrence.
2. Optimizing Efficiency and Best Practices:
* Scenario: You observe a crew or a colleague
completing a complex task (e.g., pouring
concrete, installing roofing, framing a wall)
exceptionally well, efficiently, and with high
quality.
* RPE Application: “What was their ‘prompt’?”
This means trying to deduce:
* What specific preparatory steps did they
take?
* What tools did they use and in what
sequence?
* How did they communicate or coordinate?
* Did they have a specific checklist or mental model they followed?
* What pre-existing conditions (well-organized materials, clear markings) contributed?
* Benefit: Allows you to identify and replicate successful workflows and personal techniques, improving your own productivity and quality.
3. Learning from Past Projects (Post-Mortem Analysis):
* Scenario: A project is completed, or a phase
wraps up.
* RPE Application: Look at the finished
structure and documentation. “What were
the ‘prompts’ that led to the successes and
challenges?”
* For successful elements: What were the
clear instructions, well-defined scopes,
proper resource allocation, or effective
communication methods (“prompts”) that
made them work?
* For challenged elements: Where were the
ambiguities, missing information, unrealistic
deadlines, or poor material specs (“faulty
prompts”) that caused issues?
* Benefit: Provides critical insights for future
project planning, estimating, and risk
management.
4. Improving Safety Protocols:
* Scenario: An accident or near-miss occurs
on site.
* RPE Application: Analyze the incident:
“What ‘prompt’ (or lack thereof) led to this
unsafe situation?”
* Was the safety briefing incomplete
(“prompt” didn’t cover the hazard)?
* Was the PPE not mandated or available
(“prompt” for safety gear was missing)?
* Was the work area poorly lit or cluttered
(“environmental prompt” was unsafe)?
* Was a procedure misunderstood or ignored
(“prompt” for safe execution was unclear)?
* Benefit: Helps to refine safety training,
update safety protocols, and implement
preventative measures to ensure a safer
work environments.
5. Mastering Construction Techniques:
* Scenario: You watch a demonstration or a
video showing a skilled craftsman
performing a complex technique (e.g.,
intricate tiling, advanced formwork).
* RPE Application: “What ‘prompt’ did they give
themselves (or receive) that enabled them
to perform this so perfectly?”
* What were the initial measurements or
setup?
* What specific tools were selected and why?
* What subtle body movements or pressure
applications were used?
* What sequence of steps did they follow precisely?
* Benefit: Helps you break down expert techniques into reproducible steps, accelerating your learning and skill development.