Prompt Engineering – The Art of Instructing AI

Have you ever tried ChatGPT or another AI tool and wondered why the response wasn't quite what you were looking for? The reason often lies in how the request – the prompt – was formulated. This is the essence of prompt engineering: the skill of writing instructions that get AI to produce exactly what you need.

Prompt engineering isn't just technical jargon or a specialist field for programmers. It's a practical skill that benefits anyone using AI – whether for writing emails, summarizing reports, or developing new ideas.

Why Prompt Formulation Matters

AI does what you ask – not what you mean. This sounds obvious, but in practice, the difference is significant. A vague instruction produces a vague response. A precise instruction produces a precise response.

Think of it this way: if you ask a colleague to "do something with that report," you can't expect to get exactly what you want. The same applies to AI. The more clearly you describe your goal, context, and desired format, the better the result you'll get.

The Four Parts of a Good Prompt

An effective prompt typically consists of four parts that can be combined as needed:

1. Context: Background information and situation
2. Task: What you want the AI to do
3. Data: Material to be processed or source information
4. Format: How you want the response presented

Not all parts are needed in every situation, but the more you define, the more accurate the result you'll get.

Six Practical Techniques

1. Be Specific and Detailed

The most common mistake is a request that's too general. The more precisely you define what you want, the less the AI needs to guess.

2. Assign a Role

When you tell AI what perspective it should respond from, you activate different "thinking patterns." This is especially useful for producing expert content.

3. Use Examples

Examples are the most effective way to guide AI responses. By showing what kind of result you want, you reduce the need for guessing.

4. Request Step-by-Step Thinking

For complex tasks, ask the AI to think step by step. This often leads to more accurate and better-reasoned responses.

5. Define the Response Format

Clearly state what format you want the response in: list, table, paragraph, summary, or something else. This saves time on post-processing.

6. Iterate and Improve

Prompt engineering is rarely done in one go. The first response is often a good starting point from which you refine and improve your instructions.

Common Mistakes

• Too long or complex prompt: If you don't understand what you're asking, AI won't understand it any better
• Contradictory instructions: "Write briefly and comprehensively" leaves AI guessing which to prioritize
• Missing context: AI doesn't know if you're a student, executive, or expert unless you tell it
• One-prompt expectations: Complex tasks are worth breaking into parts

Practical Exercise: Learning by Doing

The best way to learn prompt engineering is to practice. Take a daily task – like writing an email – and try different ways to formulate the request. Compare results and consider what worked and why.

It's also good practice to save prompts that work. Over time, you'll build your own collection of ready-made templates for different situations, which significantly speeds up your work.

Conclusion

Prompt engineering is more of a communication skill than technical expertise. It's about clear communication: what you want, why, in what format, and from what perspective. These skills benefit not only when working with AI but also in communication between people.

AI is a tool, and like all tools, its usefulness depends on the user's skills. With a little practice, prompt engineering becomes a natural part of work – and AI becomes a truly useful partner.

Sources and Further Reading

• Prompt Engineering Guide – Techniques
• OpenAI: Prompt Engineering Guide
• Lakera: The Ultimate Guide to Prompt Engineering