I'll admit that I haven't looked it in a while, but as originally released, it was a textbook example on how to complicate a fundamentally simple and well-understood task (text templates, basically) with lots of useless abstractions that made it all sound more "enterprise". People would write complicated langchains, but then when you looked under the hood all it was doing is some string concatenation, and the result was actually less readable than a simple template with substitutions in it.

I am not sure what's the stereotype, but I tried using langchain and realised most of the functionality actually adds more code to use than simply writing my own direct API LLM calls.

Overall I felt like it solves a problem doesn't exist, and I've been happily sending direct API calls for years to LLMs without issues.

No dig at you, but I take the average langchain user as one who is either a) using it because their C-suite heard about at some AI conference and had it foisted upon them or b) does not care about software quality in general.

I've talked to many people who regret building on top of it but they're in too deep.

I think you may come to the same conclusions over time.