I know that the common refrain is “think of yourself as a manager now” but I’ve actually taken the opposite approach and have been telling anyone I train the same.

Diving deeper into technical understanding makes more sense to me at this point both as a way to make yourself more useful in the age of AI and also to use AI more effectively.

I regularly tell the kids to grab a text book on a subject that interests them and I do the same.

I’m willing to bet deep understanding is going to become a commodity soon.

It is easier than ever to learn difficult concepts. It is also easier than ever to produce things that used to require understanding of those concepts without them. Discipline and drive to use these powerful new tools patiently and with purpose is what is required.

I wonder if it'd be more effective to teach how to critically use AI than to try to forward people to textbooks.

For myself, I have found that I am better able to learn new topics than ever before because being able to have a conversation with a moderately competent but sometimes catastrophically wrong AI about any new subject is actually the perfect mix of helpful and unhelpful for learning.

I use a loop along these lines:

* Ask a question * Get an answer * Be skeptical of the answer * Investigate/reason about the answer * Critique the answer * Rinse and repeat

This kind of loop is far more useful to me than any textbook ever has been, because a textbook just drips information into my head. It's more likely to be accurate, but not guaranteed, and it doesn't encourage me to actually engage with the material in the way that a wrong AI answer does.

> the common refrain is “think of yourself as a manager now”

One of the many reasons I'm determined to remain a luddite wrt AI. I hate the idea of being a manager and have refused promotions to avoid it in the past. I don't want to manage automatons any more than I want to manage people. I want to do stuff, not manage.

I too give juniors the advice to crack open $textbook. It’s just painful to see the complex things they’ve created with horrible performance and no cohesive data model because they don’t have the requisite academic foundation to hand code the same thing given unlimited time

a commodity is something of low value unless in a large aggregate.

Managers, good technical ones anyway, also dive deeper into technical understanding. They don't do it to write more code, they do it to figure out what the developer is saying to ensure the developers aren't blowing smoke.

Deep knowledge is going to be the opposite of a commodity.

> deep understanding is going to become a commodity soon

How does the text generated by LLM make “our” understanding deeper compared to text written in the books?

I couldn’t agree more. It seems AI is very good at middle of the distribution tasks where it has access to a lot of training data - enough to be highly reliable at that task.

Which means as a human your only added value is on the edge of the distribution. Which means you need to be learning and doing more complex, deep topics.

Are you really diving into technicals just by asking "sooo what did you do?" to your AI? Without document crawling, debugging and pulling your hair out, how much of it is really a deep dive? I feel like all that effort that goes into generating a mental image from bits and pieces is gone. I'm just grudgingly happy I went through all that before humanity retired.

The system does not reward deep understanding. It's too slow.

An analogy that I think helps describe how I feel about it all:

AI is like having cheat codes in a video game. You don't have to try hard and develop a deep understanding of how the game works. You aren't challenged anymore and it doesn't feel like you earned winning the game.

It doesn't matter because nobody cares. Businesses truly do not care. You are a cog, a means to an end. It's only about "winning". Now it's no longer fun to play the game.