As AI coding assistants continue to gain traction, so does the growing body of data and research highlighting concerns about complacency with AI-generated code. GitClear's latest shows that in 2024, duplicate code and code churn have increased even more than predicted, while refactoring activity in commit histories has declined. Also reflecting AI complacency, on knowledge workers found that AI-driven confidence often comes at the expense of critical thinking ¡ª a pattern we¡¯ve observed as complacency sets in with prolonged use of coding assistants. The rise of supervised software engineering agents further amplifies the risks, because when AI generates larger and larger change sets, developers face greater challenges in reviewing results. The emergence of "" ¡ª where developers let AI generate code with minimal review ¡ª illustrates the growing trust of AI-generated outputs. While this approach can be appropriate for things like prototypes or other types of throw-away code, we strongly caution against using it for production code.
AI coding assistants like GitHub Copilot and Tabnine have become very popular. According to , "72% of all respondents are favorable or very favorable of AI tools for development". While we also see their benefits, we're wary about the medium- to long-term impact this will have on code quality and caution developers about complacency with AI-generated code. It¡¯s all too tempting to be less vigilant when reviewing AI suggestions after a few positive experiences with an assistant. Studies like show a trend of faster growing codebases, which we suspect coincide with larger pull requests. And has us wondering whether the mentioned 15% increase of the pull request merge rate is actually a good thing or whether people are merging larger pull requests faster because they trust the AI results too much. We're still using the basic "getting started" advice we gave over a year ago, which is to beware of automation bias, sunk cost fallacy, anchoring bias and review fatigue. We also recommend that programmers develop a good .
