"AI slop", that is, low-quality AI-generated content, is increasingly affecting software development, from generated code and pull requests to documentation and bug reports. However, there is limited empirical research on how developers perceive and respond to this phenomenon. We qualitatively analyzed how developers discuss AI slop in 1,154 Reddit and Hacker News posts, developing a codebook of 15 codes organized into three thematic clusters: Review Friction (how AI slop burdens reviewers, erodes trust, and prompts countermeasures), Quality Degradation (damage to codebases, knowledge resources, and developer competence), and Forces and Consequences (systemic incentives, mandated adoption, craft erosion, and workforce disruption). Our findings frame AI slop as a tragedy of the commons, where individual productivity gains externalize costs onto reviewers, maintainers, and the broader community. We report the concerns developers raise and the mitigation strategies they propose, with implications for tool developers, team leads, and educators.

翻译：“AI垃圾”，即低质量的AI生成内容，正在日益影响软件开发领域，从生成的代码、拉取请求，到文档和错误报告。然而，关于开发者如何看待和应对这一现象的实证研究仍然有限。我们对1,154篇Reddit和Hacker News帖子中开发者讨论AI垃圾的内容进行了定性分析，提炼出一套包含15个编码的编码本，并将其组织为三个主题集群：审查摩擦（AI垃圾如何加重审查者负担、侵蚀信任并引发应对措施）、质量退化（对代码库、知识资源和开发者能力的损害），以及驱动因素与后果（系统性激励、强制采用、工艺侵蚀和劳动力干扰）。我们的研究将AI垃圾视为一种“公地悲剧”——个体生产力提升的成本被外部化，转嫁给了审查者、维护者以及更广泛的社区。我们报告了开发者提出的关切及其建议的缓解策略，这些结论对工具开发者、团队领导者和教育工作者具有启示意义。