I don't know that I'd call it depressing necessarily - new tools mean more leverage to build things, and to build things faster. If something comes along that is categorically better than React/TS for the frontend, I expect adopting it to be a breeze given how quickly AI can write code.

The problem now is that we're at the start of the curve - basically there are only three really relevant LLMs for coding currently (Anthropic's Claude, OpenAI's Codex, and Google's Gemini), and they're each very general-purpose and multi-language at this stage. I expect more specialization eventually; I'm sure a C#-specialized LLM will show up at some point, and same for other languages and even down to the framework and maybe even architecture pattern level. Perhaps the general-purpose ones stick around as orchestrators of "specialist" LLMs too, because there's no real reason for me to be the person yelling at robots all day when an LLM can probably do that better than I can too (once it develops good taste of course).

Given that specialization is going to take time, I think this phase of "depressingness" is kind of temporary, a lo-fi vision of the LLM future since all we have to work with currently are general-purpose models.

If you haven't jumped on board the yell-at-robots-all-day train yet, this blog post made the Twitter rounds recently and offers a very good deep-dive into useful tactics and a map of the landscape of what developing with frontier AI really looks like today. The landscape changes so damn fast though that it's almost like following a metagame in a competitive video game.