If tools or LLMs can help them with it then that's fine, but it should always be at least two humans involved, one making changes, one verifying, and if something like this happens, they're both culpable. Not that they should be blamed for it per se, but the process and their way of working should be reviewed.
Our brain is designed to fill in gaps, it's why memory is so blurry when it comes to reciting the facts of what we saw in a trial.
It's why you could swear you saw "x" in the production software you were about to push. But it really comes down to expectations - and those expectations help reduce cognitive load/increase cognitive efficiency (resource usage).
So after more and more people get used using AI, you will see these mistakes occur more frequently. B/c it's how our brains work.
No, AI code review doesn’t help. Claude can’t even give me correct line numbers 80% of the time, literally just makes them up, and more than half of it is false positive BS anyway.
Why not use both?