How open are you to the possibility that it's the other way around? Because the study suggests that it's actually junior code monkeys that benefit from LLMs, and experienced software engineers don't instead get a decline of their productivity.
At least that's what the only available study so far shows.
That's corroborated with my experience mentoring juniors, the more they struggle with basic things like syntax or expressing their thoughts clearly in code, the more benefit they got from using LLM tools like Claude.
Once they go mid-level and above, the LLMs are a detriment to them. Do you currently get big benefit from LLMs? Maybe you are more early in your career?
Once you are very comfortable in a domain, it is detrimental to have to wrangle a junior dev with low IQ, way too much confidence but encyclopediac knowledge of everything instead of just doing it yourself.
The dichotomy of Junior vs. Senior is a bit misleading here, every junior is uncomfortable in the domain they are working in, but a Senior probably isn't comfortable in all domains. For example, many people with 10+ SE experience I know aren't very good with databases and data engineering, which is becoming an increasingly large part of the job. For someone who has worked 10+ years on Java Backends, now attempting to write Pythin data pipelines, Coding Agents might be a useful tool to gap that bridge.
The other thing is creation vs. critique. I often let my code, writing and planning be rewiewed by Claude or Gemini, because once I have created something, I know it very well, and I can very quickly go through 20 points of criticism/recommendations/tips and pick out the relevant ones. - And honestly, that has been super helpful. Using it that way around, Claude has caught a number of bugs, taught me some new tricks and made me aware of some interesting tech.
Ahmen! I attend this same church.
My favorite professor in engineering school always gave open book tests.
In the real world of work, everyone has full access to all the available data and information.
Very few jobs involve paying someone simply to look up data in a book or on the internet. What they will pay for is someone who can analyze, understand, reason and apply data and information in unique ways needed to solve problems.
Doing this is called "engineering". And this is what this professor taught.
Most of us are also old enough to have had a chance to develop taste in code and writing. Many of the young generation lack the experience to distinguish good writing from LLM drivel.