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In my experience, you can't expect it to deliver great working code, but it can always point you in the right direction.
There were some situations in which I just had no idea on how to do something, and it pointed me to the right library. The code itself was flawed, but with this information, I could use the library documentation and get it to work.ChatGPT has been spot on for my DDLs. I was working on a personal project and was feeling really lazy about setting up a postgres schema. I said I wanted a postgres DDL and just described the application in detail and it responded with pretty much what I would have done (maybe better) with perfect relationships between tables and solid naming conventions with very little work for me to do on it. I love it for more boilerplate stuff or sorta like you said just getting me going. Super complicated code usually doesn't work perfectly but I always use it for my DDLs now and similar now.
The real problem is when people don't realize something is wrong and then get frustrated by the bugs. Though I guess that's a great learning opportunity on its own.
It can point you in a direction, for sure, but sometimes you find out much later that it's a dead-end.
Which is, of course, true for every source of information that can point you in a direction.
It’s the same with using LLM’s for writing. It won’t deliver a finished product, but it will give you ideas that can be used in the final product.