Prompt Engineering
The discipline of writing inputs to language models that reliably produce useful, structured outputs.
Prompt engineering is the practice of designing the text you send to a language model so the response is consistently good. It includes techniques like role assignment, few-shot examples, chain-of-thought, output structure constraints, and explicit guardrails.
Good prompts are precise about the task, the persona, the input format, and the desired output format. Bad prompts lead to vague or inconsistent answers, which is why almost every production AI feature has a 'prompt library' that real engineers iterate on.
In 2026 prompt engineering is less about tricks and more about engineering: prompts are versioned, evaluated against test sets, and refactored just like code. Tools like LangSmith, Helicone, and PromptLayer treat prompts as first-class artifacts.