I would think the best option is to always be suspicious of hype, unless you understand why something is being hyped? I'd also argue its worth understanding where your stack falls down, so you know when you need to look for alternative stacks.
The other bit is it's worth understanding how your stack interacts with related stacks (to use your examples, does uv and pydantic using rust vs. being pure python cause issues), but your OS is also changing, are your tools still going to work?
First, you don't have to follow hype, but listening to it is how you know where your ecosystem is heading.
Second, there is way more to an ecosystem that hype. Api, compat, deprecation, new features...
If you never created an web api and have to do it now, you still have to make a choice, hype or not. This choice will have very different consequences if you know only about flask and drf, if you heard of fastapi, or if you get told about django-ninja.
It's the same for every single task.
And even without new things, just learning the old ones is work. In python you can encounter -o ir PYTHONBREAKPOINT, be put on a project with one of 10 packaging systems, have to deal with pth files, etc.
And it's the same for all langages. It's a lot of work.
Sure, languages have depth, and there is at some level some need to keep up with the Joneses (though to mix metaphors, different ecosystems have their red queens running at very different paces, and is it wise to be in or try to join the fastest paced race?), but I feel there is a distinction between following the latest hype blindly (and using the latest tool because of hype), and evaluating tools based on some criteria (and choosing the latest tool because it actually solves the problem on hand best). The latter is a skill that can be gained and taught in one ecosystem, and applied in another (and the former causes issues far too often).
I think this skill is very similar to what highly productive academics have, they evaluate and examine ideas, techniques and concepts from a wide variety of fields, and combine them to build new ones.
The other bit is it's worth understanding how your stack interacts with related stacks (to use your examples, does uv and pydantic using rust vs. being pure python cause issues), but your OS is also changing, are your tools still going to work?