AI Code Reviews Work Best When a Second Model Checks the First One's Work

A development team discovered that AI models struggle to spot bugs in their own code because they retain the original reasoning used to write it, causing them to overlook contradictions. In one case, a security fix intended to block root-level shell access via Discord contained conflicting permission lines that the original author missed but a second AI model caught within seconds. A separate bug in a blog deployment script would have published all queued future posts simultaneously, a flaw only flagged during a cross-model review. Both bugs produced no runtime errors and would have reached production undetected without an independent review pass. The team concludes that the long-standing human practice of separating author and reviewer applies equally — and perhaps more critically — when AI is writing code at speed.