[noud]

I 100% do exactly the same. I gave up following what's new in Artificial Intelligence (Machine Learning?) years ago. 99% of it is distraction, and not worth my time to find that last 1% of useful information. Instead, I focus on improving my foundations: statistical inference, linear algebra, calculus, classical machine learning (e.g., regression, boosting, component analysis, ...), programming, domain knowledge, social skills, ... I only learn a new technique if I cannot solve it with my usual toolbox (which is not very often).

I'm way more productive, have to work less hard, and I'm not distracted. Sure, I don't do that fancy new thing, but at the end of the day (or earlier) I get the job done. And I'm judged on what I do, and how it brings money into the company, not how I do it.

Another benefit working mostly with a box of boring, old tools, is that it will likely still be relevant in the next 30 years. You never know how long that new popular thing will remain popular and useful. But I'm pretty sure we'll still fit datasets with linear/logistic regressions, optimize processes with linear programming, or do straightforward A/B testing for the next few decades (if not centuries or millennia).

[p1esk]

Or, far more likely, you get laid off in 2 years because GPT-6 will do everything you can do, but better, faster, and cheaper.