Large language models (LLMs) require well-crafted prompts for effective use. Prompt engineering, the process of designing prompts, is challenging, particularly for non-experts who are less familiar with AI technologies. While researchers have proposed techniques and tools to assist LLM users in prompt design, these works primarily target AI application developers rather than non-experts. To address this research gap, we propose social prompt engineering, a novel paradigm that leverages social computing techniques to facilitate collaborative prompt design. To investigate social prompt engineering, we introduce Wordflow, an open-source and social text editor that enables everyday users to easily create, run, share, and discover LLM prompts. Additionally, by leveraging modern web technologies, Wordflow allows users to run LLMs locally and privately in their browsers. Two usage scenarios highlight how social prompt engineering and our tool can enhance laypeople's interaction with LLMs. Wordflow is publicly accessible at https://poloclub.github.io/wordflow.

翻译：大型语言模型（LLMs）需要精心设计的提示才能有效使用。提示工程，即设计提示的过程，对于不熟悉AI技术的非专业人士而言尤其具有挑战性。尽管研究人员已提出辅助LLM用户设计提示的技术与工具，但这些工作主要面向AI应用开发者而非非专业用户。为填补这一研究空白，我们提出社交提示工程这一新型范式，通过利用社交计算技术促进协作式提示设计。为探究社交提示工程，我们推出Wordflow——一款开源社交文本编辑器，使日常用户能够轻松创建、运行、分享和发现LLM提示。此外，借助现代Web技术，Wordflow允许用户在浏览器中本地且私密地运行LLM。两个使用场景展示了社交提示工程及我们的工具如何增强非专业用户与LLM的交互。Wordflow可通过https://poloclub.github.io/wordflow公开访问。