[bubblyworld]

I don't buy it, I've used LLMs (well, mostly sonnet 4.5 and sometimes gpt5) in a variety of front-end frameworks (react, vue, htmx) and they do just fine. As usual, requires a lot of handholding and care to get good results, but I've found this is true for react codebases just as much as anything else.

[mexicocitinluez]

> I don't buy it, I've used LLMs (

You don't buy what, exactly?

> As usual, requires a lot of handholding and care to get good results, but I've found this is true for react codebases just as much as anything else.

I think you and others in this thread have either just skimmed the article or just read the headline. The point isn't that you can't use LLMs for other languages, its that the creators of these tools AREN'T using other languages for them. Yes, LLM's can write Angular. But if there's less data to train on, the results won't be as good. And because of this, it's creating a snowball effect.

[hu3]

Not your parent commenter but their point was clear to me.

To me, they don't buy the argument that the snowball effect is significant enough to overcome technical merits of different frontend frameworks.

And I'll add that: older libraries like React have at least one disavantage: there's a lot of outdated React code out there that AI is being trained on.

[bubblyworld]

I don't buy the premise - that LLMs being trained on more React code than other frameworks is going to cause the collapse of alternatives. The data presented in the article isn't very convincing to me - it's absolute numbers, it's not a zero-sum game, and besides LLM coding is the worst it's ever going to be. Hypothetically, even if the data was convincing (showing a massively increasing relative share of React usage since LLMs entered the scene), I don't think it's sensible to extrapolate from current trends about LLM coding anyway. This stuff is barely a few years old and we want to make confident predictions about it?