28 ChatGPT prompt tips: how to get the results you need from the AI

ChatGPT is known to almost everyone — but few truly know how to use it well. The publication Wired published 28 concrete techniques that elevate working with neural networks to an entirely different level.

Assign a Role — and Get an Expert

One of the most effective techniques is role-based instruction. Instead of "explain quantum physics to me," write: "you are a physics professor explaining quantum mechanics to a first-year student without formulas." The model immediately changes its style, depth, and vocabulary. The same approach works when writing code ("you are an experienced Python developer specializing in security"), analyzing data, addressing legal questions, or creating content. The more specific the character — the more specialized an answer you'll receive.

Examples, Format, and Constraints

Most users ignore the ability to directly show ChatGPT what the desired result should look like. Yet this is precisely what drastically reduces the number of iterations. Basic formatting techniques:

• Add 2–3 examples of the desired format directly in your prompt — the model will pick up the style
• Specify the output structure: "output as a table," "bulleted list," "three paragraphs"
• Limit the volume: "no more than 200 words," "explain in one sentence"
• Define the audience: "explain to a ten-year-old" or "for technical directors"
• Forbid extras: "without introductory phrases," "without recommendation to consult a specialist"

The few-shot prompting method — where you show several "question → desired answer" examples — is especially effective for classification, text styling, and generating content from templates.

Chains of Reasoning and Iteration

The phrase "let's think step by step" is one of the most powerful in the prompt engineering arsenal. It forces the model to "reason aloud" and significantly reduces the probability of hallucinations on complex logical and mathematical tasks.

"Smart users don't just enter a prompt — they iterate: ask clarifying questions, request reformulations, add context as they go," — notes

Wired.

Another powerful technique is to ask ChatGPT to first ask you clarifying questions before giving an answer. This is especially valuable when the user themselves doesn't fully understand what they need.

Additional techniques that work:

• "Play the role of a critic and find weak points in this argument" — for testing ideas
• "Suggest three different approaches" — instead of a single option
• "What else should I consider?" — as a final question in complex tasks
• Breaking a large task into several sequential short prompts

Context Is Everything

The neural network knows nothing about you, your project, or constraints — unless you tell it yourself. Adding context at the beginning of a request ("I'm a B2B SaaS marketer, my audience is technical directors in manufacturing") dramatically changes the quality of responses. The more specific the situation — the more important this step.

"Write an email" and "write a short email to a customer who yesterday declined to renew their subscription, citing budget concerns" — for the model, these are tasks of completely different levels.

What This Means

Prompt engineering is neither magic nor programming. It's a skill of structured communication that can be mastered with a few hours of practice. ChatGPT remains a generator of template answers only as long as the user hasn't learned to provide precise context, role, format, and constraints. After that, it's an entirely different tool.