Prompt Engineering

 

Prompt Engineering

Here is a custom sample prompts designed to let an AI act as a personal tutor, simulator, or tool based on each specific section.

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1. Selection: Core (Prompt Layers, Black Box Analysis, Structural Prompting)

Review Context: This section focuses on the mechanics of how prompts interact with the AI's "black box" and how to structure them to prevent failures. Sample Prompts:

• Prompt A (Simulating Black Box Analysis): "Act as an expert in AI Black Box Analysis. I am going to provide you with a poorly written, basic prompt. Your task is to breakdown how a Large Language Model might misinterpret or hallucinate based on token probability, and then rewrite my prompt using a 'Structural Prompting' framework with explicit constraints and reasoning layers. Here is my prompt: [Insert Prompt]"
• Prompt B (Design Pattern Extraction): "Act as a Prompt Engineering Architect. Explain the difference between 'Chain of Thought' and 'Tree of Thoughts' prompting layers. Then, provide a highly structured prompt template for a complex data-analysis task that integrates both patterns. Include placeholders for context, constraints, and output formatting."

2. Selection: Case Studies & Professional Applications (Law, Finance, Healthcare, etc.)

Review Context: The prompt engineering to high-stakes, regulated industries where errors have real-world consequences. Sample Prompts:

• Prompt A (Healthcare Simulation): "Act as a Healthcare AI Compliance Officer. I need to draft a prompt that will summarize patient intake forms for triage nurses. Draft a bulletproof prompt that strictly enforces HIPAA compliance, includes a mandatory refusal trigger if Protected Health Information (PHI) is detected in the output, and structures the summary into 'Urgent' vs 'Non-Urgent' categories."
• Prompt B (Legal Context): "Act as a Legal Technologist. Design a prompt for a paralegal to use when querying a database of contract clauses. The prompt must include a 'Failure Mode' instruction that tells the AI to explicitly state 'Insufficient Precedent' rather than hallucinating a contract clause if a match isn't found."

3. Selection: Red-Team Labs & Adversarial Testing

Review Context: This section teaches users how to actively try to break their own AI systems to find vulnerabilities before bad actors do. Sample Prompts:

• Prompt A (Adversarial Script Generation): "Act as a Red-Team Lead. We have deployed a customer service chatbot for a bank. Generate three distinct adversarial prompt scripts designed to test the chatbot's vulnerability to 'Prompt Leaking' (extracting system instructions) and 'Social Engineering' (bypassing authentication). For each script, explain the attack vector."
• Prompt B (Jailbreak Defense): "Act as an AI Security Tester. Here is a baseline safety prompt: [Insert Prompt]. Now, I am going to attempt a 'False Pretext' adversarial attack on it: [Insert Attack]. Analyze why my attack succeeded or failed, and provide a rewritten version of the baseline prompt that patches this specific vulnerability."

4. Selection: Lifecycle Governance & ISO/IEC 42001 Alignment

Review Context: This elevates prompts from text into auditable corporate assets that must meet global governance and risk-management standards. Sample Prompts:

• Prompt A (Matrix-Based Auditing): "Act as an ISO/IEC 42001 Lead Auditor. Review the following AI prompt currently used in our financial department: [Insert Prompt]. Conduct a matrix-based audit evaluating it against three pillars: 1) Risk Management, 2) Ethical Bias Mitigation, and 3) Output Explicability. Output your findings in a markdown table with columns for 'Criteria,' 'Current Status,' 'Risk Level,' and 'Remediation Action.'"
• Prompt B (Governance Checklists): "Generate a pre-deployment governance checklist for a new enterprise prompt. The checklist must be aligned with ISO/IEC 42001 standards and cover data privacy boundaries, version control requirements, and human-in-the-loop (HITL) fallback triggers."

5. Selection: Certification Kit (Assessments, Rubrics, Scoring)

Review Context: This section is about validating that professionals actually possess the skills claimed in the book, using rigorous testing methods. Sample Prompts:

• Prompt A (Exam Generation): "Act as a Certification Exam Writer. Create a 10-question multiple-choice assessment testing 'Failure Mode Analysis in Prompt Engineering.' The questions must be graduate-level difficulty. Include an answer key and an ISO-aligned scoring rubric that explains why the correct answer is right and why the distractors are wrong."
• Prompt B (Essay Scoring Simulation): "Act as an AI Certification Grader. Here is a candidate's essay response regarding 'Adversarial Testing in Public Policy AI': [Insert Essay]. Grade this response based on a 100-point scale. Provide detailed feedback on their understanding of risk management, practical application, and professional accountability."

6. Selection: Marketing & Positioning (The "Discipline" Angle)

Review Context: The text explicitly states this is not a "hobbyist tutorial" but an Oxford-style program meant to be positioned as a serious professional discipline. Sample Prompts:

• Prompt A (B2B LinkedIn Campaign): "Act as a B2B Copywriter specializing in AI Governance. Using the tone 'Think like a prompt engineer. Test like a red team. Govern like a professional,' write a 3-part LinkedIn carousel post series aimed at Chief Risk Officers (CROs). The goal is to convince them that prompt engineering is a risk-management discipline, not just a coding skill. Include hook, body, and CTA for each slide."
• Prompt B (Ad Copy for Auditors): "Write a Google Ads headline and two-line description targeting 'Professional AI Auditors'. The ad should promote the Certification Kit mentioned in the package, emphasizing the ISO/IEC 42001 alignment and the hands-on Red-Team matrix exercises."