Unlike traditional tools that just flag known issues, LLMs can actually reason through how code works and spot deeper problems.
In fact, Claude Opus 4.6 has uncovered previously hidden bugs in legacy code and high-severity issues in real-world projects.
But studies show that while AI writes code much faster than humans, it also introduces up to 1.7 times more bugs, including serious ones.
As companies rush to use more AI in coding, in a 2025 head-to-head study, LLMs like GPT-4.1, Mistral Large, and DeepSeek V3 were as good as industry-standard static analyzers at finding bugs across multiple open-source projects.
So while LLMs are powerful for finding hidden issues, relying on them too much could make software less reliable, especially for older systems that can't easily be fixed.
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