Honestly, sometimes I wonder if this is perhaps an under-considered area for Generative AI applications given how much drudgery is involved yet precision tends to matter.
There's nothing sustainable as an industry about something like software dependency management and versioning being so critical for things "just working" while people are sticking their heads in the sand saying "not my problem" as a rule. I'm so tired of solving the same problems that were already solved in the past because of developers wanting to work on "more interesting things" and doing the bare minimum to get stuff compiling and running again regardless of the package format. In fact, Docker may have made this situation even worse with so many Dockerfiles that will basically be unable to work. This is part of why I'm interested in the Nix ecosystem because there's so much work being done to make software installations repeatable and easier to manage. Unfortunately, it's squarely aimed at developers and is way, way too complex for most sysadmins to put the time into understanding, especially when they're so overwhelmed like everyone else with so many tasks.
As to docker. Yes I also think it made stuff worse in the majority of cases. What people forget to grasp is that Linux be it a vm or a container is just a the kernel and that we have dependencies for some programs and libraries to the kernel. Reason why we have distros in the first place. So not all containers might run the same on each host because it docker runs on the same kernel as the host machine or the VM which installed (macOS) Issues are rare but can happen. Also the number of base images. „Let’s use alpine because that means I build a small container image“ … No it means you build on top of an alpine release with all the installed system libs etc. And that may or may not work with your software. And stuff like that.