The adoption rate of AI tools has skyrocketed in the programming world, enabling coders to generate vast amounts of code with simple text prompts. Across the 470 pull requests the company analyzed, AI code produced an average 10.83 issues per request, while human-authored code produced just 6.45. In other words, AI code produced 1.7 times more issues than human code, once again highlighting major weaknesses plaguing generative AI tools. On the upside, CodeRabbit found that AI code was adept at keeping spelling errors at a minimum. “These findings reinforce what many engineering teams have sensed throughout 2025,” said CodeRabbit AI Director David Loker in a statement.