Source: https://www.maximum-progress.com/p/grad-school-applications

The author uses coding as an example to state the below:

all empirical evidence so far points to AIs being highly complementary to human labor, rather than substitutes

and on the value of studying economics

Deep Research doesn't close the gap between the productivity of the most skilled academics and the least skilled ones, it widens it. If you have taste, determination, and enough knowledge to evaluate AI outputs, then you can run a one-man research lab.

And the point that hit home the most - anything else I have a comparative advantage on is also exposed:

AI career uncertainty applies pretty broadly to all the jobs I could be doing. [...] Anything where the inputs and outputs happen on a computer seems exposed, but that’s basically all I’m good at

Finally, the author admits that the future of how one does economic research may change (aka the variance of the research path) but the actual value of this research (and I take it anything else that is highly specialized) may also be rising (which is counter to our default assumptions):

I don’t think that business as usual is the right prediction for the future of economic research. Some big things will obviously change. The variance of this path has gone up, but the expected value hasn’t clearly fallen and may be rising.