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My kids are high school age. It's hard to convey the deep existential dread their generation has about the future.

* They are growing up in a climate that is worse than any prior generation had and getting worse.

* In the US, they are growing up in a time with less upward mobility and more economic inequality than the previous several generations had.

* Trust in social institutions and government is crumbling before their eyes.

* Blue collar jobs are already gone and white collar jobs have no certainty because of AI. Almost all of the money has already been sucked out of artistic professions and what little is left is quickly evaporating because of AI.

Imagine you're 17 like my daughter and trying to decide what to major in in college. You want to pick something that you think is likely to give you some kind of decent career and sense of stability. What do you pick?

Because, I'll tell you, she asks me and I have no fucking idea what to say.

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I feel for you deeply. I’m equally fearful of this for my children, but one small blessing of my kids being very young is at least the ambiguity will probably be over by the time they have to decide. I don’t expect there to be good choices, but at least it will be clear?
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How about professions that require licensing to practice (civil engineering, accounting, insurance, actuarial science, law, medicine, pharmacy, nursing), or work in the government sector (defense, military, municipal/state/federal agencies)?
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> Blue collar jobs are already gone

This isn't true at all. There's never been a better time to be in the trades.

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Nursing perhaps? It seems like caring for other people would be useful even in an otherwise runaway AI world.
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Yeah, I think about this a lot.

Those days of grinding on some grad school maths homework until insight.

Figuring out how to configure and recompile the Linux kernel to get a sound card driver working, hitting roadblocks, eventually succeeding.

Without AI on a gnarly problem: grind grind grind, try different thing, some things work, some things don't, step back, try another approach, hit a wall, try again.

This effort is a feature, not a bug, it's how you experientially acquire skills and understanding. e.g. Linux kernel: learnt about Makefiles, learnt about GCC flags, improved shell skills, etc.

With AI on a gnarly problem: It does this all for you! So no experiential learning.

I would NOT have had the mental strength in college / grad school to resist. Which would have robbed me of all the skill acquisition that now lets me use AI more effectively. The scaffolding of hard skill acquisition means you have more context to be able to ask AI the right questions, and what you learn from the AI can be bound more easily to your existing knowledge.

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What strikes me is that AI can also be the best teacher in the world: your Makefile is not working, you ask the LLM what's wrong, you learn something new about the syntax, you ask for more details, you learn more, you ask about other Makefile syntax gotchas, etc. This is the most efficient deliberate practice possible: you can learn in minutes what would take hours of Googling, tinkering and scouring docs. You have a dedicated teacher you can ask your silliest questions to and have the insight you need "click" way faster.

The problem is: (almost) nobody does that. You'll just ask Claude Code to fix the build, go grab a coffee and come back with everything working.

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There are two sides to each coin though. For an employer, that grind is just additional cost that could be reduced by "AI".

It's like the difference between hand-made furniture and IKEA.

Until OpenAI etc need to turn a profit.

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I'm a professor at uni, and this is what is happening -- many students are never really learning. Then they crash into exams at the end of term when they don't have their AI, and they bomb, I'm seeing failure rates like never before.

Now, part of me thinks 'is not letting students having AI like not letting them have a calculator'. On the other hand, if I just let the AI do the exam, well I don't really need the student at all do I?

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That is part of why I am not... too worried as an engineer?

Like years of manually studying, fixing and reviewing code is experience that only pre ~2020 devs will have.

The intuitive/tacit knowledge that lets you look at code and "feel" that something is off with it cannot really be gained when using Claude Code, it takes just 1000s of hours of tinkering.

It will suck if the job shifts to reviewing and owning whatever an LLM spits out, but I don't really know how effective new juniors are going to be.

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> but I don't really know how effective new juniors are going to be.

True. Pretty soon, pre-AI devs may be the COBOL/Fortran engineers of this era: niche and hard to replace.

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This is the part that worries me most. It's not really about individual discipline - it's that anyone who chooses to struggle through problems the hard way is now at a measurable disadvantage against peers who don't. The incentive structure actively punishes the behavior that produces deeper understanding.
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