The advancement of Large Language Models (LLM) has also resulted in an equivalent proliferation in its applications. Software design, being one, has gained tremendous benefits in using LLMs as an interface component that extends fixed user stories. However, inclusion of LLM-based AI agents in software design often poses unexpected challenges, especially in the estimation of development efforts. Through the example of UI-based user stories, we provide a comparison against traditional methods and propose a new way to enhance specifications of natural language-based questions that allows for the estimation of development effort by taking into account data sources, interfaces and algorithms.

翻译：大语言模型（LLM）的进步也带来了其应用领域的相应扩展。软件设计作为其中之一，在将LLM用作扩展固定用户故事的接口组件方面获得了显著益处。然而，在软件设计中纳入基于LLM的AI智能体常常带来意料之外的挑战，尤其是在开发工作量的估算方面。通过基于用户界面的用户故事示例，我们与传统方法进行了对比，并提出了一种新方法，通过考虑数据源、接口和算法来增强基于自然语言的问题规范，从而实现对开发工作量的估算。