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)

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.

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.

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

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.

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.