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The Army of Juniors: The AI Code Security Crisis

Recent Statistics & Reports

60-70% of AI-generated code lacks deployment environment awareness, generating code that runs locally but fails in production.

40-50% of AI-generated code inflates coverage metrics with meaningless tests rather than validating logic.

80-90% of AI-generated code rigidly follows conventional rules, missing opportunities for more innovative, improved solutions.

80-90% of AI-generated code creates hyper-specific, single-use solutions instead of generalizable, reusable components.

80-90% of AI-generated code generates functional code for immediate prompts but never refactors or architecturally improves existing code.

70-80% of AI-generated code violates code reuse principles, causing identical bugs to recur throughout codebases, requiring redundant fixes.

40-50% of AI-generated code reimplements from scratch instead of using established libraries, SDKs, or proven solutions.

20-30% of AI-generated code over-engineers for improbable edge cases, causing performance degradation and resource waste.

90-100% of AI-generated code contains excessive inline commenting, which dramatically increases computational burden and makes code harder to check.

40-50% of AI-generated code defaults to tightly-coupled monolithic architectures, reversing decade-long progress toward microservices.

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