This article explains prompt engineering as the skill of crafting clear instructions for large language models to ensure reliable and consistent outputs. It likens LLMs to brilliant but literal contractors who need explicit guidance. The piece breaks down prompt structure into key components: defining a role and rules, stating the task clearly, separating data with delimiters, specifying the desired output format with examples, and adding step-by-step reasoning only when necessary for complex judgments. AI
IMPACT Improves user ability to get consistent and accurate results from existing LLMs.
RANK_REASON Article explains a technique for using existing LLMs, not a new release or research.
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