Prompt Engineering & AI Instructions - The Thinking Lens

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Prompt Engineering & AI Instructions

A collection of 9 posts

Instruction Governance: The Missing Layer of Enterprise AI (Part 4 of 4)

AI Governance & Risk Management

Instruction Governance: The Missing Layer of Enterprise AI (Part 4 of 4)

[Views are my own] Part 4 – Implementation and The Business Case In this series, we’ve covered the "Triad" (Part 1), the "Golden Set" (Part 2), and the "Federated Framework" (Part 3). Now, we answer the hardest question: How do we implement this without

Instruction Governance: The Missing Layer of Enterprise AI (Part 2 of 4)

AI Governance & Risk Management

Instruction Governance: The Missing Layer of Enterprise AI (Part 2 of 4)

[Views are my own] Part 2 – Why We Must Evaluate Our Instructions Before We Evaluate AI In Part 1 of this series, we diagnosed the core problem with AI evals: we often evaluate the model's answers before validating our own instructions. We also introduced Step 1: The Governance

Instruction Governance: The Missing Layer of Enterprise AI (Part 1 of 4)

AI Governance & Risk Management

Instruction Governance: The Missing Layer of Enterprise AI (Part 1 of 4)

[Views are my own] PART 1 - Stop Blaming the Model – Start Evaluating Your Instructions The Debate: Engineering Rigor vs. Enterprise Reality This article was born from a recent discussion with peers, fellow VPs and Product leaders, on how to best approach AI evaluation. The prevailing view was that we

From “Don’t Do” to “Do Well”: Designing Instructions That Make AI Useful

Prompt Engineering & AI Instructions

From “Don’t Do” to “Do Well”: Designing Instructions That Make AI Useful

Instruction design turns a chaotic GPT into a reliable tool. Replace a 'don't do' list with a clear operating model: retrieve verbatim from the knowledge base, format consistently, handle exceptions, and test like software. Positive, explicit rules cut variance and improve UX.

Your Copy is Correct. It’s Also Forgettable.

Prompt Engineering & AI Instructions

Your Copy is Correct. It’s Also Forgettable.

Generative AI boosts efficiency but flattens voice. When tools push language toward the average, brands and leaders lose distinctiveness. Use AI for polish, not personality. Document tone, keep signature quirks, and build private style models to protect authenticity at scale. Keep your edge.

The “One Prompt” Fallacy: Why Voice, Not Prompts, Wins

Prompt Engineering & AI Instructions

The “One Prompt” Fallacy: Why Voice, Not Prompts, Wins

Stop chasing magic prompts. The fix is not a template. Define your problem, then train AI on your own writing to build a voice profile. Feed real samples, extract patterns, and revise in your style. Protect your data. Do not copy tone. Engineer sharper thinking, not generic outputs. Your voice wins.

LLMs, Longform, and Low-Code: What Worked (and Broke) in Real-World Tests

Prompt Engineering & AI Instructions

LLMs, Longform, and Low-Code: What Worked (and Broke) in Real-World Tests

LLMs aid with tight, scoped tasks: cut redundancy, multipass feedback, summary maps, brainstorming. But they struggle with long inputs, continuity and consistent voice. Useful for scaffolding and agents, not autopilot. Keep humans on structure, logic and style. Use models to spot patterns.

"Ahahaha! Busted! You used an em dash—must be ChatGPT!"

Prompt Engineering & AI Instructions

"Ahahaha! Busted! You used an em dash—must be ChatGPT!"

Ahahaha! Busted. You used an em dash, must be ChatGPT. I learned about hyphen, en dash, and em dash only recently. I asked ChatGPT, checked Treccani and Merriam Webster. I use AI a lot, but the voice is mine. Tools help me write clearer. The thoughts and the words are still mine. Fully human. True.

The Hidden Skill That Unlocks Generative AI

Prompt Engineering & AI Instructions

The Hidden Skill That Unlocks Generative AI

Generative AI’s power is tied to our ability to communicate with clarity; its output reflects the input. I saw this with my 8-year-old daughter: her vague prompt for a unicorn yielded generic results, but a detailed one created what she imagined. AI is a mirror.