Prompt EngineeringUpdated April 2026 • 2 min read

How to Write Great Prompts

A practical framework for writing prompts that actually get useful results from LLMs.

Author: Edward Chenard
Updated April 2026

The biggest bottleneck in AI isn't the model. It's the person using it. I've watched talented engineers fail with AI while non-technical people crush it.

The difference? Five skills nobody's talking about. They're not technical.

They're not about knowing Python or understanding transformer architectures. They're human skills. And honestly, that's what separates people who get real value from AI and people who just play with it.

Here are 5 skills I've learned that help people get the most out of AI: 1. Mental Planning: You need to be able to plan out and visualize what you want to build as an end product. Not in vague terms.

With the subtle details. If you can't see it clearly in your head, AI sure isn't going to see it for you. The more precise your mental model, the better the output.

Every time. 2. Creative Thinking: AI can execute.

It can execute fast. But it needs you to dream up what's actually worth building. Have the creativity to imagine something new and innovative.

AI is a tool. A powerful one. But tools don't have vision.

You do. 3. Critical Thinking: The ability to look at a problem and solution from multiple angles.

See the pros and cons from each perspective. Don't limit yourself to just one viewpoint, that's how things get missed. This is especially important with AI because it will confidently give you an answer.

Your job is to know when that answer is incomplete or flat out wrong. 4. Writing Clearly: This one surprises people.

Being able to write in clear, direct, and complete sentences matters more than most realize. AI doesn't do well with slang, double meanings, text shorthand, or innuendo. Be clear and direct.

This reduces hallucinations because you give AI clear directions so it doesn't have to guess what you're trying to say. Garbage in, garbage out. That hasn't changed.

5. Real-World Experience: Having deep experience allows you to bring that knowledge to your AI projects. AI is powerful but it needs you to steer that power correctly.

If you lack the knowledge that comes from actually doing the work, often the AI will fall flat in what it can deliver. You bring the wisdom. AI brings the horsepower.

Notice something? Not a single one of these is about prompt engineering templates or fancy frameworks. They're about thinking well, communicating well, and having done the work.

Information without transformation is just entertainment. Same goes for AI without the right skills behind it. What skill would you add to this list?

I help companies figure how to apply data and AI to help them grow, connect better with customers and increase revenue. DM me if you need help.