Of course some people still do, but hard lessons were learned and all experienced people I know are a lot more mindful and cautious what dependencies they add.
It seems to me that this space, and maybe data science more broadly, is currently in that situation. Maybe it's the lack of coding skills, maybe it's the transition from one-off research notebooks to production applications, or maybe it's just the norm to have big do it all libraries (like pandas, scikit etc), idk, but I expect the same lessons will be learned.
For Langchain I wonder how they will keep up with changes in all the things they have their abstractions on. I guess having a huge community helps, but that doesn't help you with compatibility. It would not surprise me if that will get really ugly.