The practice of crafting effective inputs to AI systems to elicit desired outputs. This involves designing clear instructions and context that guide the AI toward generating accurate, relevant, and useful responses.

Prompt engineering has emerged as a critical skill for working with powerful generative AI systems, particularly LLMs. Effective prompts can significantly improve model performance for specific tasks without requiring model retraining. Techniques include providing examples of desired outputs (few-shot learning), breaking complex tasks into steps, specifying desired formats, and controlling response style and tone. In enterprise contexts, standardised prompting templates often help ensure consistent AI performance.

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An enterprise developing standardised prompt templates for their sales teams to generate product descriptions, where the prompt includes specific instructions about tone, length, key features to highlight, and target audience considerations.