Looks like Conda is still the best package/env manager for ML engineers.
At my last job, we lost days if not weeks to "solving environment" due to poetry and many folks not understanding that ceiling pinning is BAD when you use a tool like poetry to manage your deps.
/root/miniconda3/build/_placehold_placehold_placehold_placehold_placehold_pplacehold_placehold_placehold_placehold_placehold_p ...
Seriously, conda can be pretty annoying for packagers. I don't like the Jinja configuration stuff, I don't like the chaotic build output (see above), sometimes libraries are leaking in from the system, for some undocumented issues it takes ages to search for an answer.
One everything is set up, things tend to work, apart from the slow solver. I also do not like the way that conda embeds itself in the Windows installation.
It is a bit overhyped, like all things in the "scientific" ecosystem.
Here's a fun challenge: try to determine channel priority in your conda env, go ahead try.
Conda is the single worst packaging tool I have ever used.
It's not perfect but the best bet for complex and collaboration-heavy projects.