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.

翻译：在敏捷软件开发中，维持高质量用户故事至关重要但颇具挑战性。本研究探索运用大型语言模型自动提升奥地利邮政集团IT敏捷团队的用户故事质量。我们构建了自主式大语言模型代理系统参考模型，并在该企业完成部署。来自六个敏捷团队的11名参与者评估了研究中用户故事质量以及这些代理对质量改进的实效。研究结果表明，大语言模型在改善用户故事质量方面具有潜力，为人工智能在敏捷开发中的作用研究提供了贡献，并以实际案例展示了人工智能在产业环境中的变革性影响。