In agile software development, maintaining high-quality user stories is
crucial, but also challenging. This study explores the use of large language
models to automatically improve the user story quality in Austrian Post Group
IT agile teams. We developed a reference model for an Autonomous LLM-based
Agent System and implemented it at the company. The quality of user stories in
the study and the effectiveness of these agents for user story quality
improvement was assessed by 11 participants across six agile teams. Our
findings demonstrate the potential of LLMs in improving user story quality,
contributing to the research on AI role in agile development, and providing a
practical example of the transformative impact of AI in an industry setting.

该研究探讨了在奥地利邮政集团信息技术敏捷团队中利用大型语言模型自动改善用户故事质量的方法，并基于自主的 LLM-Agent 系统开发了参考模型，并将其应用于公司。通过对六个敏捷团队的 11 名参与者进行用户故事质量评估，我们的研究结果证明了 LLMs 在提高用户故事质量方面的潜力，为敏捷开发中人工智能角色的研究做出了贡献，并提供了人工智能在行业环境中具有转变性影响的实际示例。