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Technique

Prompt Engineering

The practice of designing and refining prompts to get better AI responses.

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Definition

Prompt engineering is the skill of crafting, testing, and refining prompts to get the best possible responses from AI models. It's part writing, part experimentation, and part understanding how AI models interpret instructions.

Good prompt engineers know how to structure instructions clearly, provide the right amount of context, use techniques like few-shot examples and chain-of-thought reasoning, and iterate on their prompts based on the outputs they receive. As AI becomes more central to business workflows, prompt engineering is becoming a core professional skill — not just for developers, but for marketers, support teams, writers, and anyone who works with AI tools regularly.

Examples

1

Adding "Think step by step" to a math problem prompt to improve accuracy — a chain-of-thought technique

2

Including 3 example customer support responses before asking the AI to write one — a few-shot prompting technique

Related Terms

PromptFew-Shot PromptingChain-of-Thought PromptingSystem Prompt

Frequently Asked Questions

Is prompt engineering a real job?
Yes. Many companies hire prompt engineers to design AI workflows, build agent systems, and optimize how their teams use AI tools. Salaries range from $80K to $200K+ depending on experience and industry.
Do I need to know how to code to do prompt engineering?
No. While coding knowledge helps for advanced use cases, most prompt engineering is about writing clear instructions and understanding how AI models respond to different inputs.

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