AI coding tools are accelerating software delivery, but enterprises are hitting a new bottleneck: verifying that AI-generated code is correct, secure, and compliant. The reporting highlights “vibe coding” workflows powered by tools such as Anthropic’s Claude Code and OpenAI’s Codex, where code can be produced faster than humans can type it. The emphasis is shifting from writing software to proving “code integrity.” The article points to real-world failures as evidence of the risk, including scrutiny after Anthropic Claude Code source code was reportedly leaked due to a packaging mistake—raising concerns about vulnerabilities created by rapid automation. As a response, the piece spotlights Qodo, an AI code review tool that has raised $70 million to tackle “AI slop” using a multi-model approach (one model generates, another critiques) and layered testing. The core argument is that AI alone is insufficient for production governance, making an explicit trust layer necessary before changes ship in large codebases. For universities and colleges, the story underscores a practical risk facing any institution deploying AI in software, labs, IT operations, and student development pipelines: governance and auditing processes must move at the same speed as AI adoption.