LLMs can handle a lot of these issues already, without having the user think about such issues.

Problem is - while these will be resolved (in one way or another) - or left unresolved, as the user will only test the app on his device and that LLM "roll" will not have optimizations for the broad range of others - the user is still pretty much left clueless as to what has really happened.

Models theoretically inform you about what they did, why they did it (albeit, largely by using blanket terms and/or phrases unintelligible to the average 'vibe coder') but I feel like most people ignore that completely, and those who don't wouldn't need to use a LLM to code an entirety of an app regardless.

Still, for very simple projects I use at work just chucking something into Gemini and letting it work on it is oftentimes faster and more productive than doing it manually. Plus, if the user is interested in it, it can be used as a relatively good learning tool.