I do greenfield in fluid dynamics and Claude doesn't help: I need to be able to justify each line of my code (the physics part) and using Claude doesn't help.
On the UI side Claude helps a lot. So for me I'd say I have a 25% productivity increment. I work like this: I put the main architecture of the code in place by hand, to get a "feel" for it. Once that is done, I ask Claude to make incremental changes, review them. Very often, Claude does an OK job.
What I have hard times with is to have Claude automatically understand my class architectures: more often than not it tries to guess information about objects in the app by querying the GUI instead of the data model. Odd.
My observation is so far, LLMs are not good at scientific computing.