Definition
Prompt engineering is the practice of designing the input to a large language model so the output is reliable, structured, and useful. Instead of asking a vague question, a prompt engineer specifies role, context, audience, format, tone, and constraints — turning ambiguous requests into precise instructions. The discipline emerged in 2022-2023 as users discovered that LLM output quality depends heavily on input structure. By 2026, prompt engineering is a baseline skill across marketing, design, software, and research roles.
Example
Bad: 'write me an email'. Good: 'Act as a senior B2B copywriter. Write a 90-word cold email to a Series A CTO pitching observability. Format: subject + 4 short paragraphs. Tone: confident, specific, no buzzwords.'
When to use
Whenever AI output quality matters — production systems, brand-voice content, multi-step reasoning, structured extraction.