Prompt Engineering is the practice of shaping the instructions, examples, constraints, and output format given to a language model to steer its behavior toward reliable, useful results.
Techniques range from clear role and task framing to few-shot examples, step-by-step reasoning, and strict output schemas. It works because model behavior is highly sensitive to phrasing and structure, so small changes can move accuracy and consistency noticeably.
For builders it is the fastest and cheapest tuning lever, but a narrow one: it sits inside the larger problem of Context Engineering, and prompts over-fitted to one model or task tend to break on another. Durable prompts specify intent and format rather than relying on brittle phrasing tricks.
FAQ
What is Prompt Engineering?
Prompt Engineering is the practice of shaping instructions, examples, constraints, and output formats for LLM behavior. GROUNDING tracks prompt patterns as part of broader context engineering and agent design.