When I see people worry about LLMs atrophying their mental abilities I assume they haven't thought very hard about ways to lean into using them to expand their mental capabilities.
It has definitely accelerated my learning: through the process of writing rigorous plans, I have learned so much about network programming... the intricacies of HTTP2, how to design a fast MITM proxy, performance pitfalls in SSL...
These are things I studiously avoided learning for a decade, now demystified, mostly through Claude patiently rendering many figures and diagrams.
And with Fable, I was able to ship a working Envoy Rust extension in a one-shot.
On the other hand, my grasp on the details is tenuous. Every so often the agent can't progress and I am stuck for ideas, hitting different prompts like they were slot machines. I forget how to solve problems by myself.
I can feel myself becoming supine and dependent on something I know is going to become more expensive, a dependency AI vendors will seek to exploit. It has happened quickly. I do not really consent; it is forced on me by my employer.
Obviously there are higher-level design issues that I might not notice while engaging with the code at the byte-by-byte level, but I won't have the embarrassing problem I had a couple of weeks ago where duck.ai wrote me a CPU in Verilog, and after I tested it, I tried to write something in Verilog myself and couldn't even figure out how to write a syntactically correct XOR-gate module. (Verilator's parse errors are not designed as a Verilog tutorial, it turns out.)
I always say that since one of the best ways of learning is by doing and given that with LLMs we can do so much so quickly, we are in a golden age of learning for those who really want to learn.