Sounds like this perspective is theoretical.
Been building for a long time, and more specifically overseeing building in detail, which transfers interestingly to overseeing LLMs.
Just like with coworkers, providing the right amount of context (not too much, or too little) for the request to succeed is critical.
I shared similar views, but I have seen first hand (using in production myself) that specs, well done in a way for LLMs, can do development with AI that works. If something doesn't work out, you don't fix the code, you adjust the spec. Highly recommend watching doers on Youtube who are sharing screens.
Discovering a problem is more difficult than expected allows you to take more shots at it, quicker by adjusting the spec, for example and running again. We are used to just plowing ahead to make the code right, instead of improving/clarifying the ask/spec.