Now, I'm not saying I learned anything from the article (I gave up when it was talking about "uv pip" which I have never ever used and have no real idea why anyone would ever use, but that's okay). I don't think the article is a good fit for the HN python audience, and that's also okay. But I don't doubt many people can find value in it. "uv pip" exists even though I have never used it so clearly someone must be using it. I haven't used pip in years so it's not a reference point I am starting from. People do use pip and that's okay. Those people didn't suffer through figuring out poetry etc.
I do suspect that people who do system install of packages want uv workspaces. I think I want to migrate to that for my less engineered one-off jupyter calculations stuff since so far the things I've managed to get working for that sort of project have been either monorepos (which have their own issues) or millions of venvs (which constantly sync and take up space). But again I've tried to read and figure out that uv workspaces workflow and I give up after an hour or so of not figuring it out. So that's just to say I have learned to only go to astral's docs as references and even then they are incomplete (I had to guess a bit how to add a git repo via ssh as a dependency)
So your points are all valid -- but I'm trying to address pain points people have repeatedly raised, and that I myself experienced, and flatten the learning curve for as many people as possible.
System-wide package installs are a weird quirk of my own work, since I'm doing very little product development and lots of one-off classes. I'm not at all recommending that "normal" developers do this, and I make sure to say that in all of the courses I teach.