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：大型语言模型（LLM）的进步同样导致了其应用领域的广泛扩展。软件设计作为其中之一，在将LLM用作扩展固定用户故事的界面组件方面获得了巨大益处。然而，在软件设计中引入基于LLM的智能体常常带来意料之外的挑战，尤其是在开发工作量估算方面。通过以基于用户界面的用户故事为例，我们将其与传统方法进行了比较，并提出了一种改进自然语言问题规范的新方法。该方法通过综合考虑数据源、接口和算法，实现了对开发工作量的有效估算。