arXiv:2607.21079v2 Announce Type: replace Abstract: Generative artificial intelligence (GenAI) has introduced new forms of AI assistance into software development, but less is known about the repositories and issues of early adopters of GenAI tools. We study the repository and issue characteristics of early adopters who state interest in GenAI on their public profiles on GitHub by analyzing 531 early adopters, 100 of their repositories with AI-tool configuration files (ACFs), 100 matched control repositories without ACFs, and 370 issues from the two repository groups. Repositories with ACFs show modest distributional differences in selected README structural characteristics. They contain longer README files with more code blocks and include a license more often, while repositories without ACFs contain more external URLs. The category distributions of the two repository groups show weak evidence of a difference. Once GenAI relatedness is held fixed, we detect no difference in issue Type or Outcome between the two repository groups. Our data, collected from May to August 2025, record how early adopters developed software in Software Engineering 2.0, the stage in which developers use both AI assistants and autonomous AI agents. When these agents become the norm, later studies can compare their data with ours.
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