ChatGPT's code generation seems most useful for boilerplate code. I've seen it used to great effect for scaffolding projects that use stable and established frameworks. It'll easily handle generating as much stupid fluff as needed for you to start from—but it will barely get started on your domain-specific use cases, and won't be able to implement anything novel, as you said.

We still don't seem to have reached the point where it's "intelligent" enough to generate new information. Only repeat new permutations of existing information. Obviously, this is currently a fundamental property of LLMs (as someone who's implemented one), since they are trained to learn and repeat existing data (hell, even the model I've been playing with lately is benchmarked solely on "perplexity", how well it can repeat its training data).