The practice of crafting inputs to get better outputs from AI models. This ranges from simple techniques (being specific, providing examples) to advanced methods (chain of thought, few-shot prompting, role assignment). Despite the fancy name, it's fundamentally about communicating clearly with a statistical system.
Why it matters
The same model can give wildly different results depending on how you ask. Good prompt engineering is the cheapest way to improve AI output quality — no training, no fine-tuning, just better communication.