I use GPT-4 and still have problems getting it to write simple code correctly sometimes. I find it immensely useful in many areas but writing actual detailed code doesn't seem to be a game changing use case for me (yet).
Tip: it’s often faster to keep iterating on the problem with the LLM than to stop after the first response. “As an expert TypeScript programmer, you should know that X isn’t correct. Please try again.”
Sweet, now it is stuck in a loop where it says sorry, here’s a correction then spits out the same code. Do you have an example chat where that worked for you?
An example that didn't work that I thought should was to implement a Base62 converter. I thought it would easily be able to do it as the problem is so well scoped (an probably even exists in its training set). However, it either had poor performance characteristics or wasn't correct.
This is how an experienced dev would like to work - break the problem down and hand off some of the more well scoped problems to AI.