What people are wary of is not solving the problem in the first pass. They are wary of technical debt and unmaintainable code. The cost of change can be enormous. Software engineering is mostly about solving current problems and laying the foundation to adapt for future ones at the same time. Your approach's only focus is current problems which is pretty much the same as people that copypaste from StackOverflow without understanding.

Technical debt and understanding is exactly why I still review the code.

But as I said, it's getting rare that I need to change anything the AI generates. That's partly because I decompose the problem into small, self-contained tasks that are largely orthogonal and easily tested -- mostly a functional programming style. There's very little that can go wrong because there is little ambiguity in the requirements, which is why a 3 line prompt can reliably turn into dozens of lines of working, tested code.

The main code I deal with manually is the glue that composes these units to solve the larger computer vision problem. Ironically, THAT is where the tech debt is, primarily because I'm experimenting with combinations of dozens of different techniques and tweaks to see what works best. If I knew what was going to work, I'd just prompt the AI to write it for me! ;-)