提示工程教程：从杂乱想法到AI工作流

中文摘要 AI 辅助

本文将提示工程视为一门将非正式的人类意图转化为结构化AI工作规范的学科。它将这一实践发展为一连串可复用的设计步骤：定义工作内容，仅构建答案所依赖的上下文，选择角色或经过主持的角色小组作为注意力透镜，并陈述肯定性的质量目标，将禁止性条款保留给硬性边界。为保持提示简洁，它借鉴了奥卡姆剃刀和契诃夫之枪两条经典原则，使每条指令都物有所值。对于后果重大的任务，它通过钢人法和事前验尸法增加结构化批判，随后进行验证，并在涉及工具或多步骤操作时，加入带有明确边界和升级机制的智能体操作循环。本教程面向普通读者，并非基准测试研究；它提供了一条从随意提示到规范化AI工作流设计的实用且技术扎实的路径，并通过一个工作示例加以说明，该示例将一项任务从弱提示提升为强规范。该框架以原则和检查清单的形式呈现，在模型和工具变化时依然有用。最强的提示很少是最长的提示；它是那种使期望行为、所需来源和检查以及成功标准都明确无误的提示。

英文摘要

This paper treats prompt engineering as a discipline for turning informal human intent into structured AI work specifications. It develops the practice as a sequence of reusable design moves: define the work, construct only the context the answer depends on, choose a role, or a moderated panel of roles, as an attention lens, and state affirmative quality targets, reserving prohibitions for hard boundaries. To keep prompts lean, it adapts two classical principles, Occam's razor and Chekhov's gun, so that every instruction earns its place. For consequential tasks, it adds structured critique through steelmanning and premortems, followed by verification and, where tools or multi-step actions are involved, agentic operating loops with explicit boundaries and escalation. Aimed at a general readership, this tutorial is not a benchmarking study; it offers a practical, technically grounded path from casual prompting to disciplined AI workflow design, illustrated by a worked example that carries one task from a weak prompt to a strong specification. The framework is presented as principles and checklists that remain useful as models and tools change. The strongest prompt is rarely the longest prompt; it is the one that makes desired behaviour, required sources and checks, and success criteria unmistakable.

发表机构

• Cisco（思科）
• University of Edinburgh（爱丁堡大学）
• Islamic Azad University（伊斯兰阿扎德大学）
• SLAI
• CUHK-SZ（香港中文大学（深圳））

机构由 AI 辅助整理，请以论文原文为准。