The solution, at least for GPT-4, is to ask it to first draft a software spec for whatever you want it to implement and then write the code based on the spec. There are a bunch of examples here:

https://github.com/mckaywrigley/prompts

If you can't get GPT4 to do coding questions you're prompting it wrong or not loading your context correctly. It struggles a bit with presentational stuff like getting correct HTML/CSS from prompts or trying to generate/update large functions/classes, but it is stellar at producing short functions, creating scaffolding (tests/stories) and boilerplate and it can do some refactors that are outside the capabilities of analytical tools, such as converting from inline styles to tailwind, for example.

so, mundane trivial things and/like web programming? I got it eventually to answer what I needed but it always liked to skip part of the code, inserting // TODO: important stuff in the middle, hence 'laziness' attribute. Maybe it is just lazy, who knows. I know I am since I'm prompting it for stuff.

I wouldn't say mundane/trivial as much as well trodden. I get good code for basic shaders, various compsci algorithms, common straightforward sql queries, etc. If you're asking for it to edit 500 line functions and handle memory management in a language that isn't in the top20 of the TIOBE index you're going to have a bad time.

The todo comments can be prompted against, just tell it to always include complete runnable code as its output will executed in a sandbox without prior verification.

Fyi, I've never encountered what you're describing, whether with GPT 3.5 or 4.

It may be that you're expecting it to do too much at once. Try giving smaller requests.