New Harvard's study (62M workers, 285k firms) shows firms adopting generative AI cut junior hiring sharply while continuing to grow senior roles — eroding the bottom rungs of career ladders and reshaping how careers start.
No, I was being sarcastic.
Currently part of the problem is the taboo using AI coding in undergrad CS programs. And I don't know the answer. But someone will find the right way to teach new/better ways of working with and without generative AI. It may just become second nature to everyone.
That's not true anymore in the smart phone / tablet era.
5-10 years ago my wife had a gig working with college kids and back then they were already unable to forward e-mails and didn't really understand the concept of "files" on a computer. They just sent screenshots and sometimes just lost (like, almost literally) some document they had been working on because they couldn't figure out how to open it back up. I can't imagine it has improved.
Some people dont want to hear that, but...
i just want devs who actually read my pr comments instead of feeding them straight into an llm and resubmitting the pr
But if they're not hired...?
Pretty sure it's a self-destructive move for a CS or software engineering student to pass foundational courses like discrete math, intro to programming, algorithm & data structure using LLM. You can't learn how to write if all you do is read. LLM will 1-shot the homework, and the student just passively reads the code.
On more difficult and open coursework, LLM seems to work pretty well at assisting students. For example, in the OS course I teach, I usually give students a semester-long project on writing from scratch x86 32-bit kernel with simple preemptive multitasking. LLM definitely makes difficult things much more approachable; students can ask LLM for "dumb basic questions" (what is pointer? interrupt? page fault?) without fear of judgement.
But due to the novelty & open-ended nature of the requirement ("toy" file system, no DMA, etc), playing a slot machine on LLM just won't cut it. Students need to actually understand what they're trying to achieve, and at that point they can just write the code themselves.
Kind of like that meme or how two AIs talking to each other spontaneously develop their own coding for communication. The human trappings become extra baggage.
From company interns. Internships won't go away, there will just be less of them. For example, some companies will turn down interns because they do not have the time to train them due to project load.
With AI, now employed developers can be picky on whether or not to take on interns.
It's pretty hard for a non-big tech company to pay big tech level salaries.
I personally turned down an Apple offer because they required 3 days in office and went this a much smaller fully remote team.
I think this is the gambit that we have already committed to.
Cheap labor. It doesn't take that much to train someone to be somewhat useful, in mmany cases. The main educators are universities and trade schools. Not companies.
And if they want more loyalty the can always provide more incentives for juniors to stay longer.
At least in my bubble it's astonishing how it's almost never worth it to stay at a company. You'd likely get overlooked for promotions and salary rises are almost insultingly low.
You get a lot in the interim!!! I started at Andersen Consulting (now Accenture.) The annual attrition was ~20%, but they still invested over a year of training into me.
But it worked:
- They needed grunt work in early years (me, working 75hr billable weeks). Not sure how much of this is viable now given LLMs
- They had great margins on the other four years. Not sure how much of this is viable now, as margins have shrunk in the past 25yrs as there is more way competition
- They used me to train the next cohort in years 4/5
- I appreciated the training and give them 60hr billable weeks on average for five years
It was a brutal and exhausing five years but i'm forever thankful to AndersenConsulting/Accenture for the experience.