AI-generated code (or any AI output) can look clean, professional, and finished while hiding a flaw nobody caught, because the polish itself discourages scrutiny. Security researchers coined the phrase to explain why AI-assisted coding can raise commit velocity three to four times while vulnerability pass rates stay flat or worsen: reviewers extend less skepticism to output that already reads as done. Veracode's 2026 report found roughly 44% of AI code-generation tasks introduced a real exploitable vulnerability, an average security pass rate of only 56% across tested models, and one tracked environment saw monthly security findings climb from about 1,000 to over 10,000 in six months even as shipping speed increased.
The pattern generalizes past code: any AI output whose surface fluency outpaces its actual correctness invites the same failure, which is why Calling BS on AI Output (Critical-Thinking Check) has to get more deliberate, not less, as outputs get more polished. It also undercuts safeguards like mandatory human sign-off before merge or launch, since a review bottleneck only catches errors if humans are still motivated to look closely at something that already looks right — a tension noted alongside predictions (e.g. from Cognition) that such approval gates may not survive as a durable requirement.