Well, on one hand they lack new data. Lot's of new code came out of an LLM, so it feeds back.

On the other hand, LLMs tend to go for an average by their nature (if you squint enough). What's more common in their training data, it's more common in the output, so getting them better without fundamental changes, requires one to improve the training data on average too which is hard.

What did improve a lot is the tooling around them. That's gotten way better.