That is a surprisingly common fallacy actually; I think you will find this book quite helpful to overcome it: https://www.penguinrandomhouse.com/books/44330/mindset-by-ca...

It's also important to learn how to "teach yourself".

Understanding transformers will be really hard if you don't understand basic fully connected feedforward networks (multilayer perceptrons). And learning those is a bit challenging if you don't understand a single unit perceptron.

Transformers have the additional challenge of having a bit weird terminology. Keys, queries and values kinda make sense from a traditional information retrieval literature but they're more a metaphor in the attention system. "Attention" and other mentalistic/antrophomorphic terminology can also easily mislead intuitions.

Getting a good "learning path" is usually a teacher's main task, but you can learn to figure those by yourself by trying to find some part of the thing you can get a grasp of.

Most complicated seeming things (especially in tech) aren't really that complicated "to get". You just have to know a lot of stuff that the thing builds on.

Unfortunately you must look closely at the details to deeply understand how something works. Even when I already have a decent mental heuristic about how an algorithm works, I get a much richer understanding by calculating the output of an algorithm by hand.

At least for me, I don't really understand something until I can see all of the moving parts and figure out how they work together. Until then, I just see a black box that does surprising things when poked.