Kerno report: New code complexity rises 50% after AI adoption
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Kerno has released the first edition of its "Impact of AI on Code Quality" report, analyzing 201,576 commits and more than 16 million lines of code across 46 open-source projects from October 2024 to October 2026, finding that after AI adoption, decision points per 100 new lines of code rose from 5.2 to 8.1, an increase of about 50%. Kerno says the 46 projects were hand-picked based on their size and popularity, not a random sample; most are core products of commercial open source, and 35 of them are written primarily in TypeScript, so the results describe this type of codebase. The report emphasizes that the data is observational, and "after adoption" means after the adoption date, which is not the same as "because of AI." All data and analysis scripts from the report have been made public on GitHub.
AI overview based on source reports · Updated 18 hr ago
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- Hacker News AIWe measured the impact of AI on 46 OSS repos (200k commits, 16M lines)
Kerno's first-edition report analyzes 201,576 commits across 46 open-source projects from October 2024 to October 2026 and finds new code carries 8.1 decision points per 100 lines after AI adoption, up from 5.2, with complexity growth shifting from −0.4% to +3.1% a month. Each engineer ships 71% more production code per week, while AI-marked commits are revisited 43% more often than other commits and are 17% more likely to add a hard-to-test function. Claude signs 69% of AI-marked commits, which are 54% bigger than unmarked commits, and on the current trend complexity per 100 new lines would rise another 42% by late 2028.
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