I wouldn't agree that LLMs are a higher level of abstraction, but I've found they do help me think at a higher level of abstraction, by temporarily outsourcing cognitive load.

With changes like substantial refactors or ambitious feature additions, it's easy to exceed the infamous "seven things I can remember at once":

  * the idea for the big change itself
  * my reason for making the change
  * the relevant components and how they currently work
  * the new way they'll fit together after the change
  * the messy intermediate state when I'm half finished but still need a working system to get feedback
  * edge cases I'm ignoring for now but will have to tackle eventually
  * actual code changes
  * how I'm going to test this

  * wiring a new parameter through several layers
  * writing a test harness for an untested component
  * experimentally adding multibyte character support on a branch

The main benefit is to defer the concern until I have a mostly working system. Then I come back and review its output, since I'm still responsible for what it delivers, and I want better than "mostly working".