LLMs提升团队协作效率，但也带来新挑战。
Impact of LLMs on Team Collaboration in Software Development
- 用代码生成助手和智能项目管理工具优化协作流程。
- 自动化重复任务使效率提升，沟通更清晰。
- 适合关注开发协作与AI融合的工程师和管理者。
大型语言模型（LLMs）正日益融入软件开发流程，有望重塑团队工作模式与生产力。本文基于2025年最新进展，重构并更新了以往研究，结合新文献与案例分析，探讨了在软件开发生命周期（SDLC）中协作障碍问题，并研究了LLMs如何提升团队效率、沟通与决策能力。通过文献综述、行业实例、团队问卷及两个案例研究，评估了代码生成助手、AI驱动的项目管理代理等工具对协作式软件工程的影响。结果表明，LLMs能显著提高效率（通过自动化重复任务与文档生成）、改善沟通清晰度，并促进跨职能协作，但同时也带来模型局限性与隐私安全等新挑战。文章讨论了这些优劣势，提出未来研究方向，包括领域定制模型、开发工具深度集成，以及建立可信与安全策略。
原文摘要 · Abstract (English)
Large Language Models (LLMs) are increasingly being integrated into software development processes, with the potential to transform team workflows and productivity. This paper investigates how LLMs affect team collaboration throughout the Software Development Life Cycle (SDLC). We reframe and update a prior study with recent developments as of 2025, incorporating new literature and case studies. We outline the problem of collaboration hurdles in SDLC and explore how LLMs can enhance productivity, communication, and decision-making in a team context. Through literature review, industry examples, a team survey, and two case studies, we assess the impact of LLM-assisted tools (such as code generation assistants and AI-powered project management agents) on collaborative software engineering practices. Our findings indicate that LLMs can significantly improve efficiency (by automating repetitive tasks and documentation), enhance communication clarity, and aid cross-functional collaboration, while also introducing new challenges like model limitations and privacy concerns. We discuss these benefits and challenges, present research questions guiding the investigation, evaluate threats to validity, and suggest future research directions including domain-specific model customization, improved integration into development tools, and robust strategies for ensuring trust and security.
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