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AI Slop Is Changing How Engineers Review Code

IEEE Spectrum – AI logo

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AI Slop Is Changing How Engineers Review Code

AI coding tools can now generate thousands of lines of code in minutes, helping companies build features, run tests, and fix issues faster. But the flood of AI-generated code still has to be reviewed. Large language models can produce code that looks clean on the surface but conceals sloppy mistakes such as faulty assumptions, security vulnerabilities, or subtle errors that emerge only after deployment. Fixing those problems could erase the productivity gains AI promises.

Companies are responding to the onslaught of AI code slop by rethinking how they review code. New strategies are emerging. Among other approaches, engineers are scrutinizing plans before AI begins coding, deploying specialized AI agents to catch routine flaws, sending risky changes to human reviewers, or requiring developers to defend the code their agents produce.

The shift comes as the surge in AI-generated code puts new pressure on engineering teams. In a survey of more than 1,100 developers by Sonar, an AI code-verification startup, respondents estimated that AI contributed 42 percent of the code they added to shared codebases. Yet while developers found AI useful for explaining and prototyping code, 96 percent did not fully trust its output to work correctly.

Investors see an opportunity in closing that gap. In August, for example, AI code-review startup CodeRabbit raised US $143 million at a $1.5 billion valuation, while claiming it performs more than 2 million reviews a week for 17,000 customers, including Nvidia, Indeed, and BMW Group.

The new era of code review will determine whether AI can ever provide code that is both faster and more reliable.


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