🎯 Learning Objectives
- Write technical explanation prompts calibrated to audience expertise
- Extract insight from data using structured interpretation prompts
- Design validation and compliance review prompts
- Apply systems thinking frameworks through prompting
- Stress-test assumptions systematically
1. Technical Explanation Prompts
Explain [Concept] at three levels:
Level 1 — Executive: Analogy-based. What it does, why it matters. 50 words.
Level 2 — Manager: How it works, key components, what can go wrong. 100 words.
Level 3 — Specialist: Precise mechanisms, edge cases, technical trade-offs. 200 words.
This three-level approach means you always have the right version for the right audience — without running three separate prompts.
2. Data Interpretation & Insight Extraction
Analyse the following data: [data]
Answer these questions:
1. What is the single most important insight?
2. What trend is most likely to continue? Why?
3. What is the most surprising or counterintuitive finding?
4. What data is missing that would significantly change the interpretation?
5. What action does this data most strongly support?
Do not describe the data — interpret it. Each answer: 2–3 sentences max.
⚠️ Common Mistake
Asking "What does this data show?" produces description. Asking "What does this data mean for [specific decision]?" produces interpretation. Always connect data to a decision.
3. Validation, Compliance & Regulatory Prompts
You are a regulatory compliance specialist.
Review the following document for compliance gaps: [document]
For each gap:
- Gap description (1 sentence)
- Relevant regulatory reference area (flag for verification — do not cite exact numbers)
- Risk level: Critical / Major / Minor
- Suggested remediation (1–2 sentences)
Flag uncertain areas with [EXPERT REVIEW REQUIRED].
4. Assumption Stress-Testing
You are a critical strategy advisor.
Analyse the following plan: [plan]
Step 1: Identify the 5 key assumptions this plan depends on.
Step 2: For each assumption:
- How confident are we this holds? (1–5)
- What evidence supports it?
- What would need to be true for this assumption to fail?
Step 3: Which single assumption, if wrong, would most damage the plan?
✏️ Module 08 Exercise
Take a recent technical document, dataset, or plan. Run the assumption stress-testing prompt. Identify assumptions your team had never made explicit. Then run the data interpretation prompt, focusing on what the data means for an upcoming decision.
🔑 Key Takeaways
- Three-level technical explanations eliminate the depth-calibration problem
- Data interpretation prompts should ask 'what does this mean for X decision?' not 'what does this show?'
- Compliance prompts must include explicit uncertainty flagging and human review requirements
- Assumption stress-testing is one of the highest-value strategic uses of AI
- Always separate description from interpretation in analytical prompts
- Systems thinking prompts map cause-and-effect chains — valuable for risk and failure analysis