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Partly this is because the big companies are diverting vast amounts of money towards building data centers, instead of hiring new grads. I expect young people w

Partly this is because the big companies are diverting vast amounts of money towards building data centers, instead of hiring new grads. I expect young people who learn AI skills will be fine, once the data center spending binge is over.

dominotw 24d ago
they really dont need to divert. They are sitting on historical unfathomable amounts of money.
slipperybeluga 24d ago
[dead]
boshalfoshal 24d ago
What does "learning AI skills" even mean? You're typing into a prompt box. You are not applying any skill, the model is. At best, the skill you need is discernment about _what_ to type in this magical box. But if that gets cheaper and the output of your company doesn't necessarily scale horizontally that well. Why would I need as many people as before?
- vanuatu 24d ago
  - knowing what to prompt - directing the model and knowing when its going off the rails - verification - setting up the right loops, harness, graphs around the models economics still apply to hiring people. if all your competitors are using ai and there's market share to fight over and people still are a productivity positive vs. only ai, hiring will increase as we've seen recently with swes
  - bogzz 24d ago
    Again though, these recommendations are so vacuous. If you already are a capable developer, then you can pick all of that up within a week. "Learn AI skills" is such a low effort reflexive response that I'd expect it from a non-technical executive, not from an HN commenter.
    - vanuatu 24d ago
      You'd be surprised, I used to do a first round technical screen where we let the interviewee use any ai tool they want to build a simple api (and they can oneshot the problem if they just pasted it into any capable agent). I quite liked the problem, it was really a system design problem for senior+ but more algorithmic for junior/mid The more senior the candidate the less they took advantage of the tools. Most commonly they would manually copy/paste error or syntax errors and then run out of time. One candidate only copy pasted his questions into google and used the AI overview Junior candidates tended to be overly ai eager, a lot of them oneshotted the problem but were unable to explain any of the details That being said I think 80% of the skills should come easily to a capable dev that is willing to put in the effort to learn and get used to managing agents. Building agents that perform work themselves is a lot harder (and still pretty unsolved)
      - bogzz 24d ago
        But I don't believe what you've said disproves my point. To me, it boils down to attitude, not so much aptitude when it comes to "AI skills" in this context. You even admitted that some of the solutions could be one-shotted by copying and pasting the problem. As for building agents that perform work themselves, in my opinion it boils down to understanding the problem space, isolating the key business logic, and determining what the pertinent requirements are. Kinda sounds like looping back around to software engineering skills IMO.
        vanuatu 24d ago
        To be clear, I think young people need to learn traditional software engineering skills too (.. maybe having the wrong attitude towards it is even worse than the aptitude!) A junior with no foundational SWE skills will just become a meat wrapper. But thinking more about it I wouldn't discredit these "AI skills" so much. A lot of it is either using AI as a force multiplier or learning the specific skills around deploying it which I'd still categorize as 'AI skills' building agents is just a completely different ballgame, theres a lot of infra and harness engineering around handling the nondeterministic behaviors that are nonobvious unless you've shipped agents at scale
  - 8cvor6j844qw_d6 24d ago
    Could agree with some of the points. I noticed the newer batch of interns tends to have less mechanical coding skills but does well on understanding and planning on the design, DB design, etc.
  - boshalfoshal 24d ago
    The only thing here that _maybe_ has a durable long term moat is the first point. Even then, I don't see why stronger models can't also have discernment once more companies close the loop with their AI and their relevant company metrics. The other 3 you literally just get for free as models improve. The "state of the art" of "prompting" changes literally every week. It was loops, then graphs, now its harnesses (and self automating harnesses)? Why are these not just obviated by better models? These are barely skills, and are imo, just the tech equivalent of tabloids advertising 5 minute exercises or pills to get rid of stubborn belly fat. No amount of prompt engineering or graphs or loops could get your previous version of GPT to perform like Fable, and yet somehow Fable can do all of that and more without any random built in "ai engineering skills." The labor chart for SWEs will look like a slope up as productivity with AI increases, and then past a certain point where AI is like 99% good enough, employment will fall off a cliff. We are already seeing this with junior hiring, and who is to say that AI will magically only ever be as capable as a junior engineer?
    - vanuatu 24d ago
      i mean the meta point is having "AI skills" is understanding the jagged frontier and operating accordingly Given that we can keep making infinite abstractions with software if we actually saturate software demand with AI then I don't see why every other industry is cooked (robotics is downstream of software).
- y-curious 24d ago
  I imagine the meta will be “build a micro saas product that’s marginally successful” for younger folks. It’s trivial to make a product but you learn a lot seeing what the AI does wrong.
- schnevets 24d ago
  Upvoting this for asking the candid question that so many commenters dance around. I can't imagine a 22-year-old confidently walking into an interview (or getting introduced to a team) and assuring everyone that they have the "harness" or "guardrails" to confidently contribute at the level of a 10x engineer. If we apply the Gartner Hype Cycle to this disruptive technology, I do believe AI will hit a "slope of enlightenment" where an AI-assisted Analyst is properly understood in industries and can take productive roles. Conveniently, this will probably coincide with a lower interest rate where companies have funds for a talent acquisition spree/rapid growth. With that being said, today's graduates are stuck in an awful market with a lot of charlatans selling crappy online courses and bad ideas.
- AnimalMuppet 24d ago
  The models are currently not at a place where you can just "type into a prompt box", any more than you could just "type into the IDE". You have to know what and why to type. The models are not at a place where no skill is needed. It may be a different still, but it's still a skill, and it's still a software engineering skill.

dominotw 24d ago

they really dont need to divert. They are sitting on historical unfathomable amounts of money.

slipperybeluga 24d ago

[dead]

boshalfoshal 24d ago

What does "learning AI skills" even mean? You're typing into a prompt box. You are not applying any skill, the model is. At best, the skill you need is discernment about _what_ to type in this magical box. But if that gets cheaper and the output of your company doesn't necessarily scale horizontally that well. Why would I need as many people as before?

vanuatu 24d ago
- knowing what to prompt - directing the model and knowing when its going off the rails - verification - setting up the right loops, harness, graphs around the models economics still apply to hiring people. if all your competitors are using ai and there's market share to fight over and people still are a productivity positive vs. only ai, hiring will increase as we've seen recently with swes
- bogzz 24d ago
  Again though, these recommendations are so vacuous. If you already are a capable developer, then you can pick all of that up within a week. "Learn AI skills" is such a low effort reflexive response that I'd expect it from a non-technical executive, not from an HN commenter.
  - vanuatu 24d ago
    You'd be surprised, I used to do a first round technical screen where we let the interviewee use any ai tool they want to build a simple api (and they can oneshot the problem if they just pasted it into any capable agent). I quite liked the problem, it was really a system design problem for senior+ but more algorithmic for junior/mid The more senior the candidate the less they took advantage of the tools. Most commonly they would manually copy/paste error or syntax errors and then run out of time. One candidate only copy pasted his questions into google and used the AI overview Junior candidates tended to be overly ai eager, a lot of them oneshotted the problem but were unable to explain any of the details That being said I think 80% of the skills should come easily to a capable dev that is willing to put in the effort to learn and get used to managing agents. Building agents that perform work themselves is a lot harder (and still pretty unsolved)
    - bogzz 24d ago
      But I don't believe what you've said disproves my point. To me, it boils down to attitude, not so much aptitude when it comes to "AI skills" in this context. You even admitted that some of the solutions could be one-shotted by copying and pasting the problem. As for building agents that perform work themselves, in my opinion it boils down to understanding the problem space, isolating the key business logic, and determining what the pertinent requirements are. Kinda sounds like looping back around to software engineering skills IMO.
      - vanuatu 24d ago
        To be clear, I think young people need to learn traditional software engineering skills too (.. maybe having the wrong attitude towards it is even worse than the aptitude!) A junior with no foundational SWE skills will just become a meat wrapper. But thinking more about it I wouldn't discredit these "AI skills" so much. A lot of it is either using AI as a force multiplier or learning the specific skills around deploying it which I'd still categorize as 'AI skills' building agents is just a completely different ballgame, theres a lot of infra and harness engineering around handling the nondeterministic behaviors that are nonobvious unless you've shipped agents at scale
- 8cvor6j844qw_d6 24d ago
  Could agree with some of the points. I noticed the newer batch of interns tends to have less mechanical coding skills but does well on understanding and planning on the design, DB design, etc.
- boshalfoshal 24d ago
  The only thing here that _maybe_ has a durable long term moat is the first point. Even then, I don't see why stronger models can't also have discernment once more companies close the loop with their AI and their relevant company metrics. The other 3 you literally just get for free as models improve. The "state of the art" of "prompting" changes literally every week. It was loops, then graphs, now its harnesses (and self automating harnesses)? Why are these not just obviated by better models? These are barely skills, and are imo, just the tech equivalent of tabloids advertising 5 minute exercises or pills to get rid of stubborn belly fat. No amount of prompt engineering or graphs or loops could get your previous version of GPT to perform like Fable, and yet somehow Fable can do all of that and more without any random built in "ai engineering skills." The labor chart for SWEs will look like a slope up as productivity with AI increases, and then past a certain point where AI is like 99% good enough, employment will fall off a cliff. We are already seeing this with junior hiring, and who is to say that AI will magically only ever be as capable as a junior engineer?
  - vanuatu 24d ago
    i mean the meta point is having "AI skills" is understanding the jagged frontier and operating accordingly Given that we can keep making infinite abstractions with software if we actually saturate software demand with AI then I don't see why every other industry is cooked (robotics is downstream of software).
y-curious 24d ago
I imagine the meta will be “build a micro saas product that’s marginally successful” for younger folks. It’s trivial to make a product but you learn a lot seeing what the AI does wrong.
schnevets 24d ago
Upvoting this for asking the candid question that so many commenters dance around. I can't imagine a 22-year-old confidently walking into an interview (or getting introduced to a team) and assuring everyone that they have the "harness" or "guardrails" to confidently contribute at the level of a 10x engineer. If we apply the Gartner Hype Cycle to this disruptive technology, I do believe AI will hit a "slope of enlightenment" where an AI-assisted Analyst is properly understood in industries and can take productive roles. Conveniently, this will probably coincide with a lower interest rate where companies have funds for a talent acquisition spree/rapid growth. With that being said, today's graduates are stuck in an awful market with a lot of charlatans selling crappy online courses and bad ideas.
AnimalMuppet 24d ago
The models are currently not at a place where you can just "type into a prompt box", any more than you could just "type into the IDE". You have to know what and why to type. The models are not at a place where no skill is needed. It may be a different still, but it's still a skill, and it's still a software engineering skill.