"An Endless Stream of AI Slop": The Growing Burden of AI-Assisted Software Development
For software developers and tool designers, this paper provides empirical evidence of the negative impacts of AI-assisted development, highlighting systemic issues that need addressing.
This study analyzes 1,154 online discussions to understand how developers perceive AI-generated low-quality content ('AI slop') in software development, finding that it burdens reviewers, degrades code quality, and creates a tragedy of the commons where individual gains externalize costs on the community.
"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.