GPT needs training data. Once a problem is "figured out" and there is enough information about it to reach a treshold where it's learnable by the AI, it will stop being something done manually.
There is reason to believe that most commodity software (e-commerce, content management, media asset management, any CRUD-with-makeup, infrastructure automation, etc) will be commoditized even further to the point that no software developer would be needed to create a product that leverages these approaches, or any reasonble combination of them.
Sure, there will be a need to guide the AI to the best solution. A need to harness it properly. Some software development skills will be needed for that, and my guess is that this will become a temporary occupation in the near future, either explicitly or not.
Eventually, there will be problems that large models can't solve. Not even partially. Stuff that has no training data and there is no way to acquire inferred knowledge about it. We'll know what that is only when the commoditization of what we already know is almost complete. My guess is that it will be something trivial but rarely considered worthy exploring, writing about or pursuing, but valuable. Some kind of impossible miracle software that will be not that impossible in the future (complete protocol/data portability, wide compatible standards across thousands of different systems, etc).
Or we all will have to learn how to flip burgers in a boring dystopia. That's a reasonable scenario as well.