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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 discernm

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 22d 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 22d 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 22d 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 22d 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 22d 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
        bogzz 22d ago
        I'm not discrediting them as being of no value, I am just discrediting the notion that devs who are unable to find work now should be beefing up their AI skills so that they can get a job in the future. "AI skills" as they are talked about are easier and quicker to pick up than working with a library, e.g. React. And if they are not difficult to learn, then they are not a differentiator nor should they be treated as such.
    - eudamoniac 21d ago
      I had a similar interview and I find it to be a stupid question. Of course I know AI can oneshot it, and of course I know you know it can. But I'm aware this is an interview so you're probably assessing something about my skills. Pasting the prompt doesn't assess anything so surely that isn't what you want me to do, so I don't do that. Instead I have to magically divine what level of involvement you're hoping to see on a scale from vibecode to handmade. The whole thing provides literally no information to the interviewer about real work processes, because the intelligent candidate will behave differently in this situation than they would at work.
  - JDups 22d ago
    Yeah I've seen a lot of applications and some interviews where what they are looking for the most, by far, is your "AI skills". Questions like: How are you currently using AI day to day?; Can you describe your current agentic setup?; things like that are the only questions asked in the application. And I don't understand why you would wave away needing to know anything about the codebase's underlying tech because "The AI can take care of all that, we don't need to look at code anymore" while also not believing that any competent developer could prompt AI to get a good setup within a week or two max.
- 8cvor6j844qw_d6 22d 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 22d 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 22d 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 22d 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 22d 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 22d 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.

vanuatu 22d 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 22d 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 22d 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 22d 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 22d 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
      - bogzz 22d ago
        I'm not discrediting them as being of no value, I am just discrediting the notion that devs who are unable to find work now should be beefing up their AI skills so that they can get a job in the future. "AI skills" as they are talked about are easier and quicker to pick up than working with a library, e.g. React. And if they are not difficult to learn, then they are not a differentiator nor should they be treated as such.
  - eudamoniac 21d ago
    I had a similar interview and I find it to be a stupid question. Of course I know AI can oneshot it, and of course I know you know it can. But I'm aware this is an interview so you're probably assessing something about my skills. Pasting the prompt doesn't assess anything so surely that isn't what you want me to do, so I don't do that. Instead I have to magically divine what level of involvement you're hoping to see on a scale from vibecode to handmade. The whole thing provides literally no information to the interviewer about real work processes, because the intelligent candidate will behave differently in this situation than they would at work.
- JDups 22d ago
  Yeah I've seen a lot of applications and some interviews where what they are looking for the most, by far, is your "AI skills". Questions like: How are you currently using AI day to day?; Can you describe your current agentic setup?; things like that are the only questions asked in the application. And I don't understand why you would wave away needing to know anything about the codebase's underlying tech because "The AI can take care of all that, we don't need to look at code anymore" while also not believing that any competent developer could prompt AI to get a good setup within a week or two max.
8cvor6j844qw_d6 22d 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 22d 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 22d 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 22d 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 22d 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 22d 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.