I indeed have a engineer-like approach, but engineering absolutely does not assume draw line from A to B and expect that's enough:

Real world, as you say, not so simple. Everything has to deal with certain degree of forecastable nonsense, e.g. a bridge has to cope not only with traffic and winds, but the possibility that someone will be drunk in charge of a ship and crash into it.

> AI is built on human knowledge so guess what it will keep doing.

Yes, and also brings its own additional mess on top of that. All machine learning takes a huge number of examples to get good, so an LLM isn't just "read all the online courses in how to run a business", but also likely has 50 business versions of the recent demonstration of common sense failure with "I live 100m from a car wash, should I walk or drive?"

> How do we build systems without assuming complete adherence, but tolerating imperfection and failures? Isn't there some discipline teaching us that?

Many such disciplines. Perhaps all except maths and computer science? Or even including maths and computer science, given stats is part of maths and even compsci has to deal with fault tolerance.