For the past year or so, I've been trying (off and on) to formalise part of my undergraduate complex analysis course in Lean. It has been instructional and rewarding, but also sometimes frustrating. I only recently was able to fully define polar form as a bijection from C* to (-pi,pi] x R, but that's because I insisted on defining the complex numbers, (power) series, exp and sin "from scratch", even though they're of course already in mathlib.
Many of my troubles probably come from the fact that I only have a BSc in maths and that I'm not very familiar with Lean/mathlib and don't have anyone guiding me (although I did ask some questions in the very helpful Zulip community). Many results in mathlib are stated in rather abstract ways and it can be hard to figure out how they relate to certain standard undergraduate theorems - or whether those are in mathlib at all. This certainly makes sense for the research maths community, but it was definitely a stumbling block for me (and probably would be one if Lean were used more in teaching - but this is something that could be sorted out given more time).
In terms of proof automation, I believe we're not there yet. There are too many things that are absolutely harder to prove than they should be (although I'm sure that there's also a lot of tricks that I'm just not aware of). My biggest gripe concerns casts, in "regular" mathematics, the real numbers are a subset of the complex numbers and so things that are true for all complex numbers are automatically true for all reals[0], but in Lean they're different types with an injective map / cast operation and there is a lot of back-and-forth conversion that has to be done and muddies the essence of the proof, especially when you have "stacks" of casts, e.g. a natural number cast to a real cast to a complex number etc.
Of course, this is somewhat specific to the subject, I imagine that in other areas, e.g. algebra, dealing with explicit maps is much more natural.
[0] This is technically only true for sentences without existential quantifiers.