What is Prompt Engineering?

Prompt engineering is the art of communicating with AI models, such as ChatGPT or Claude, to get the best possible results. It can be compared to the skill of asking good questions of a teacher – the better formulated the question, the better and more useful the answer.

In practice, prompt engineering involves creating text instructions (prompts) that guide an AI model in such a way as to get the desired result. It’s like giving directions to a person who wants to help us but needs to know exactly what we expect.

Why is Prompt Engineering Used?

1. Increasing Answer Quality and Precision Well-constructed prompts allow you to get more accurate and useful answers from AI models.

2. Saving Time and Increasing Productivity When an AI model immediately understands what we expect, we don’t have to repeatedly correct and refine our commands. One good prompt often replaces several attempts with less precise instructions.

3. Automating Repetitive Tasks Prompt engineering allows you to create “templates” for frequently performed tasks - from writing business emails, through data analysis, to generating reports. Once a good prompt is created, it can be used multiple times.

4. Personalizing Results to Specific Needs Thanks to thoughtful prompts, we can adapt the style, tone, level of detail, and answer format to a specific recipient or application. The same topic can be explained differently for an expert than for a layman.

5. Maximizing the Potential of AI Models AI models have enormous potential, but without proper guidance, they can generate answers that are too general or inaccurate. Prompt engineering allows you to fully utilize their potential.

6. Achieving Consistency in Results In a business or educational environment, it’s important to get consistent results. Well-designed prompts help maintain a consistent quality standard in generated content.

Advantages of Prompt Engineering

• Accessibility: Anyone can learn the basics of prompt engineering without specialized technical knowledge.
• Low cost: Compared to other techniques, it requires the fewest resources – you only need access to an AI model.
• Flexibility: You can quickly modify prompts and experiment with different approaches.
• Fast implementation: Does not require lengthy preparation processes or additional infrastructure.
• Process control: You directly guide what the model should do and how.

Disadvantages and Limitations

• Model’s knowledge: A model can only answer based on the knowledge it has from training – no prompt will extract information the model doesn’t know.
• Dependence on prompt quality: A poorly constructed command will give poor results.
• Limited context memory: Models have a limit on the length of text they can process (e.g., 100,000 words), which limits instruction complexity.
• Repeatability: It’s difficult to get identical answers each time using the same prompt.
• No long-term memory: The model doesn’t remember previous conversations outside the current session.

Costs and Requirements

• Memory: Uses only the model’s context memory (typically from thousands to 100,000 tokens, or approximately 75,000 words for the newest models).
• Infrastructure: Does not require additional system components beyond the AI model itself.
• Financial costs: Costs result only from using the AI model’s API – the longer the prompts and answers, the higher the cost.
• Time limitations: Performance depends on the complexity of the prompt and the load on the AI provider’s servers.

Practical Examples of Application

Example 1: Correcting Texts

Weak prompt: “Check my text for errors.”

Good prompt: “Analyze this text for grammatical, punctuation, and stylistic errors. Suggest corrections while preserving the original tone of the statement and explain why you propose these changes.”

Example 2: Writing a Business Email

Weak prompt: “Write an email to a customer.”

Good prompt: “Write a professional email to a customer who has not paid an invoice for 14 days. The email should be polite but firm, no longer than 10 sentences, containing a payment reminder and consequences of delay. Sign as John Smith, Accounting Department.”

Example 3: Learning a New Topic

Weak prompt: “Explain quantum supremacy to me.”

Good prompt: “Explain the concept of quantum supremacy to me as if you were explaining it to someone without scientific knowledge. Use everyday analogies and explain step by step why it’s important. Then ask me one question that will test my understanding of the topic.”

Summary

Prompt engineering is the simplest and most accessible technique for using AI models, which does not require programming knowledge. It is primarily used to maximize the potential of artificial intelligence, get precise and useful answers, and save time in everyday work.

Its effectiveness depends mainly on the ability to formulate clear and precise instructions. It’s an excellent first step in your AI journey, allowing anyone – regardless of technical knowledge – to effectively collaborate with artificial intelligence models in various areas of professional and personal life.