Prompt Engineering
The practice of crafting effective inputs to LLMs to get desired outputs. Combines clear instructions, context, examples, and format specifications.
Prompt engineering is the discipline of writing effective inputs to LLMs to produce useful outputs. Despite the technical-sounding name, it's mostly about clear communication: specifying what you want, providing relevant context, giving examples, and constraining the output format.
Effective prompts often include: a clear role ("You are an expert tax accountant"), specific task ("Review this contract for liability issues"), format constraints ("Respond in JSON with fields X, Y, Z"), examples (few-shot prompting), and reasoning instructions ("Think step by step before answering").
In 2026, prompt engineering is becoming less critical because models have improved at understanding intent. But the highest-quality outputs still come from well-crafted prompts — particularly for code generation, structured data extraction, and complex reasoning tasks.