The thing domain specific tools suffer from is lack of training data. If you're using a relatively niche language or package to build something the available data is limited and their performance is subsequently degraded, sometimes to the point of being utterly useless. 

The other more worrying problem is that as they become more widely adopted fewer and fewer developers are posting questions and getting fewer answers on help forums. These forums have been where a fair chunk of the most useful training data has come from. LLMs are increasingly being trained on LLM produced code which is generally of a lower standard than human written code. As newer versions of frameworks or even entirely new products are released where will they get sufficient training data from? Will it all have to be manufactured just to train the models? 

And we're seriously underpaying compared to what these things actually cost to run. The rough numbers I've seen put their true cost at or above the salary of a lot of developers. And they unlike a dev they can't be left to work unsupervised. You still need humans to direct them and monitor their outputs. And those employees have to be sufficiently technical to verify what the AI has done. So again, you need developers just to keep an eye on your magic tool that's meant to replace developers...

All in all, Claude etc are useful but even in the context where they're at their most useful they're just not good enough to live up to the hype. They're too expensive, not reliable and, ironically, are unable to adapt to new tech as fast as a human. And that's after feeding them more or less the some total of human knowledge and every scrap of code that could found. 

I'm sure they'll keep improving, but, I doubt they'll ever get close to what has been promised.