"An Endless Stream of AI Slop": The Growing Burden of AI-Assisted Software Development
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866918414462746624 |
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| author | Baltes, Sebastian Cheong, Marc Treude, Christoph |
| author_facet | Baltes, Sebastian Cheong, Marc Treude, Christoph |
| contents | "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 conducted a qualitative analysis of 1,154 posts across 15 discussion threads from Reddit and Hacker News, 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, offering actionable insights for tool developers, team leads, and educators. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_27249 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | "An Endless Stream of AI Slop": The Growing Burden of AI-Assisted Software Development Baltes, Sebastian Cheong, Marc Treude, Christoph Software Engineering "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 conducted a qualitative analysis of 1,154 posts across 15 discussion threads from Reddit and Hacker News, 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, offering actionable insights for tool developers, team leads, and educators. |
| title | "An Endless Stream of AI Slop": The Growing Burden of AI-Assisted Software Development |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2603.27249 |