The science behind prompt engineering:

There is no training on how to ask AI correctly.

And AI changes so fast that techniques from before don’t work anymore. LLMs (like ChatGPT or Claude) changed so much it’s outdated.

For example, I used to tell everyone to add “Take a deep breath and work on this step by step” to their prompt. Because science said so:

But this paper is from September 2023 and talks about the model PaLM 2-L from Google. You now have access to Claude & ChatGPT models that are 10x more capable.

So how can you truly know how to prompt the latest models?

You need to read new and trusted academic papers on prompt engineering. Hundreds of them. Per day.

But you must be crazy to read 100+ new AI papers every day.

Well, I am crazy.

By the end of this newsletter, you will know what the science says about better prompts (in simple English, I promise; no weird Claud-isms), in this order:

Sounds like a good deal? Cool.

Two things before we start:

1. Never end with “right?”.

A Cornell Tech researcher tested 45 different AIs with one-word changes.

So asking the AI’s opinion is most definitely not a good idea: it will be biased by how you ask the question more than by its actual intuition.

Bad prompt:

“I’m deciding what to do about housing.Buying is the better choice, maybe?”

Good prompt:

“I’m deciding what to do about housing.Compare buying and renting for my situation.”

Just like when you ask a friend, don’t make them answer the way you want them to answer. Keep it neutral. Avoid yes/no questions.

2. Forget the “step-by-step”.

IBM ran an impressive 430,738 evaluations on 8 prompting techniques.

The most famous “Let’s think step by step” LOST to asking normally.

The winning combo is just your question + your role in a few words (“…as a reliability engineer”).

Bad prompt:

“[Your question]Gather information, devise a plan, answer step by step.”

Good prompt:

“[Your question]. . . as a reliability engineer.”

Worth noting. The paper used the role "reliability engineer" for every topic it tested: medicine, physics, and math. So is it the only role you should prompt, or does choosing a good role make your prompt better?

Maybe I should start writing academic papers…

3. Do not trust confidence.

Microsoft’s CTO audited 2.6 million references (papers) at the world’s top AI conferences.

1 in 4 ‘NeurIPS’ 2025 papers — papers that PASSED expert peer review — has a hallucinated citation. The reviewers missed it, and they even scored the papers slightly HIGHER.

If professional reviewers can’t catch AI-hallucinated papers, you won’t either. You must open every link:

Now the real question is who in their right mind will open 210 sources.

I feel the same as you. I wish to trust AI research more.

4. Stick to 3 rules max.

Meta tested GPT-5.5, Claude Opus, Gemini Pro and 12 others AI on prompts with 1 to 12 rules. An example of 3 rules would be:

Exactly 3 paragraphs. Under 150 words. No emojis.

At 8 rules, models only get each individual rule right 41% of the time. But it only gets 8 rules at once 5.7% of the time… Not good.

12 of the 15 models can’t reliably hold more than 3 rules.

Bad prompt:

Write a LinkedIn post about our launch. Exactly 3 paragraphs. Under 150 words. No emojis. Include “AI-native”, “workflow” and “ship”. Don’t mention competitors. End with a question. Grade-6 reading level. Match my voice sample below.

Good prompt:

First run: Write a LinkedIn post about our launch. Must include: "AI-native", "workflow", "ship". No emojis. End with a question.

Second run (after the draft): Check your draft against each of these requirements ONE AT A TIME, then revise: 3 paragraphs, under 150 words, grade-6 reading level, no competitor mentions.

The more I learn about prompt engineering, the more I understand it’s all about giving the right goal. A clear one. It’s far more effective than giving examples:

5. Goals > Examples.

Researchers found examples in your prompt are sabotaging modern models.

Mistral’s model scored 74% with the standard examples prompt. They deleted the examples, and then boom → 83.8% score.

Bad prompt:

You are a world-class newsletter strategist.Example 1: [a solved case, written out]Example 2: [a solved case, written out]Find a plan, and answer step by step: How can I improve my newsletter?

Good prompt:

My newsletter open rate fell from [X]% to [Y]% over three months.I send one issue every Tuesday. I did not change the format, the send time, or the subject. What are the most likely causes?Ask me for the data you need before you answer.

Specifying a goal is the ultimate key to a good prompt.

6. The One Prompt

I made a prompt template that covers everything we just covered.

I will then show you how to create a quick keyboard shortcut (because you don’t want to copy & paste it every time you need it). If you want to copy and paste my prompt, click on this link: how-to-ai.guide

The problem with prompts.

It works with one person that is eager to learn (probably you).

It does not work with someone who does not want to use AI (your team?).

That’s why I have a company that trains other companies how to adopt AI, faster.

Our clients ranges from truck companies, to medical device engineering companies, to PE firms…

If you’re ready for a free discovery call, and you’re based in the US, send me a message.

I tend to receive 50-500 DMs per day, but I have a team (and AI?) to filter them, and making sure you guys receive a fast & useful answer.

If you want to get a call quicker, it helps me to know your position, location & how big your team is.

Humanly yours - Ruben

A message from the author, Ruben.

This article exists because 93,000+ people decided AI is too important to leave aside. Not only that, but they shared it around them. They understand they are the sum of the 5 people around them. So better have them using AI.

If this helped you — or if it’ll help someone you know — forward it to them. That’s how this grew. Just readers like you sending it to people like them.

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