Yep. No-code/low-code tooling never really took off beyond some small use cases for a pretty simple reason that will also apply to non-engineers using GPTs:
There is always a tension between having a simple-to-use tool and getting a custom result. The simpler the tool is to use, the less likely you'll be to get a custom result. Tools that are great at generating custom results are rarely simple to use.
GPT models demonstrate this very well. If you attempt to prompt it without any knowledge of a field you can get something back... but it won't be unique. To get a workable result to a more complicated problem you need to know how to prompt it, how to review what it spits out, how to modify your prompt in response to correct it, how to stitch the eventually working piece with other pieces. And so on.
If it were that easy for AI to step in and replace developers, then we'd have seen the same thing with "codeless" frameworks.
Maybe one day in the distant future it will be a different story. But I'd wager you'd be dead before that happens.