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Prompt engineering is the practice of designing well-structured inputs that guide AI systems to produce accurate, relevant, and creative results. By carefully choosing wording, context, and constraints, users can improve efficiency and get more consistent outputs.

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Prompt engineering is the practice of designing well-structured inputs that guide AI systems to produce accurate, relevant, and creative results. By carefully choosing wording, context, and constraints, users can improve efficiency and get more consistent outputs.

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Prompt Engineering: A Quick Guide

Prompt engineering is the skill of designing clear and effective prompts to guide AI systems (like

ChatGPT) in producing accurate, useful, or creative responses. It’s about asking the right question

in the right way.

■ Key Principles of Prompt Engineering

1 Clarity – Be specific and avoid vague wording.

2 Context – Provide background or details to guide the AI.

3 Format – Tell the AI how you want the answer (list, story, explanation, etc.).

4 Iteration – Refine your prompt step by step to improve results.

■ Examples

Vague Prompt: Explain computers.

Better Prompt: Explain how computers process data in simple language, with a real-life analogy.

Vague Prompt: Write about climate change.

Better Prompt: Write a 3-paragraph essay about the causes of climate change, its effects on

Africa, and one possible solution, in simple English.

Prompt engineering is like learning to have a smart conversation with AI. The better you guide it,

the better the results.

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■ Key Principles of Prompt Engineering

1 Clarity – Be specific and avoid vague wording.

2 Context – Provide background or details to guide the AI.

3 Format – Tell the AI how you want the answer (list, story, explanation, etc.).

4 Iteration – Refine your prompt step by step to improve results.