Definition·
Prompt Engineering

Prompt Engineering

Prompt engineering is the discipline of designing, structuring, and refining the instructions given to an LLM to obtain reliable, accurate, and well-formatted answers.

Detailed explanation

Prompt engineering covers every technique used to get the most out of an LLM: setting a clear role, providing context and examples (few-shot), structuring the output (JSON, lists), splitting reasoning into steps (chain-of-thought), and constraining the format. A well-crafted prompt can dramatically improve quality without changing the model. It is the first lever to try before considering RAG or fine-tuning, and it remains essential in production to control cost, latency, and consistency.

Examples

Adding a few-shot example to enforce a specific JSON format
Asking the model to 'think step by step' to improve mathematical reasoning
Setting the role: 'You are a senior cybersecurity expert'

Frequently asked questions

Is prompt engineering still useful in 2026?

Yes. Even with stronger models, a well-designed prompt remains the cheapest and fastest way to improve quality, format, and reliability.

What is chain-of-thought?

A technique where you ask the model to explain its reasoning step by step before giving the final answer, which significantly improves results on complex tasks.

Related terms

Last updated: 7/15/2026

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