What is happening to jobs? Separating AI hype from reality(siepr.stanford.edu) |
What is happening to jobs? Separating AI hype from reality(siepr.stanford.edu) |
General agents (OpenClaw, Anthropic Copilot, ChatGPT "Work") started working even later than that.
This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using from 2022-2025.
Studies that mainly focus on 2022 to end of 2025 might be missing out on a material uptick in capabilities.
2026? 5? 4? 3?
Heard this one way too many times.
Time will tell of course, and it’s early, but inflection points do exist with progress.
But it seems more correlated with hype-cycle-stage than anything else. Right now a lot of founders seem to be convincing a lot of VCs that they can make $LOTS by replacing/changing $BIG_INDUSTRY/$BIG_PRODUCT with an agent-first blah blah replacement, and then using that money to hire more people to manage/execute/coordinate the coding agents...
Last year, by comparison, there seemed to be a mood of "software will stay the same but will require less people" while right now there's a lot of hype around "we can build different types of software or build it in different ways" and those early-stage things are in growth-mode. That guarantees nothing about how many people they'd need in the future, or their success at all, ofc.
The news that I'm getting from contacts in non-startup-land is a bit different - still layoff threats. Still pressure to use AI tools more. Mixed confidence on whether or not longer-running "agent" modes are that much more effective-without-breaking-things in legacy code if not used with care.
Maybe the future will change that for very specific things, but I think people should be learning and preparing for that, which isn’t any different than what everyone has been told in every job market since the start of the Industrial Revolution.
I'm nervous that the studies which show that so far don't seem to be taking the 2026 improvements in coding and general agents into account.
1) I hesitate to believe that losses were disproportionately technical roles as opposed to administrative.
2) Over-hired by what metric? It's well known that hiring never fully recovered after the GFC; was the recruitment post-pandemic just bringing us to parity with where we had been 20 years earlier?
Not to say that I disagree with your following point. The AI overspending and the layoff cost-cutting are not in a direct causal relationship; both are rather symptoms of a common corporate pathology.
Everything impressive has happened in the last six months.
[0]: well...
All the reports of productivity since then are self-reported, or using questionable measures such as SLOC and PRs, so it’s reasonable to say that productivity improvements are still unknown.
Unfortunately, METR hasn’t been able to replicate the study because they couldn’t find enough willing participants.
"Move fast like a blur so people can't see that you have no clothes"
This has led to many of them instilling dollar limits or demanding proof of increased productivity (not just output) with the implication being if you don’t provide value with it it’s getting taken away.
So that is to say, if they aren’t happy with the price now, how will they feel when it goes up again compared to just keeping a certain headcount?
> So that is to say, if they aren’t happy with the price now, how will they feel when it goes up again compared to just keeping a certain headcount?
They should have done that from the beginning - demanding proof of increased productivity - if that was their goal. otherwise they were not using their brains well enough.
And you doubly don't want to work with them, first because they confused output with productivity at first. and second, because they're parroting the productivity metric.
You only need one guess for whose pockets the productivity benefits go into.
10 . 9 . 8 . 7 . 6 ...
What I found was pretty brutal. Companies asking for 4 years of agentic AI experience… pardon?
Then it hit me.
Oh they are all making shit up now and have no bar that anyone can hit because they are believing in the hype without understanding the fundamentals.
GREAT. Even as I climb the AI-Native ranks, I apparently am unqualified for any AI-Native job.
You just have to get past the recruiter/talent acquisition where everyone else is getting auto-rejected. You should be doing that anyway.
Not that I am trying to excuse it, but this is not a new thing, nor specific to AI.
Job listings that ask for X years of experience where X years is sometimes literally longer than the technology has even existed has been a staple complaint of developers over my entire career, and I'm old af.
So, leave college/uni with your "Desmond" (1) in comparative pornography in Feb 2026, buy a PC/Apple and by now you will be writing Windows Entra 2027 on your own.
Profit!
(1) Tutu - geddit!
This has been almost a meme on hacker news for some time. You can google it via hn dot algolia dot com by using the right keywords.
Of course, i exaggerated it a bit, just like a lot of startups and vcs pimp their stuff, just that they do it much more, and they do it for money, while my mine was for fun. ha ha ha.
Literally some minutes later, i scrolled down below my above comment.
And saw this one.
https://news.ycombinator.com/item?id=49053201
Which doesn't validate mine, but agrees with what I said.
Except that it was posted about one hour before mine.
go figure.
In my workplace, we're going to decline to renew some software subscriptions because a non-programmer vibe-coded their replacement in a week.
The impacts are here, they're just not evenly distributed yet.
Interesting to see the impact in the long term when battle tested software gets replaced with vibecoded variants by non-programmers. Does it increase data breaches or quality actually goes up?
But in reality, a lot of corporate software exists just because there are plenty of companies who are afraid of owning code. They don't want to maintain any in-house coding skills, and therefore are willing to buy literally any vaguely-relevant CRUD app that the manager heard about at the conference. I don't think replacing that class of software with vibe coded alternatives will be any worse, because the bar is starting on the floor.
There are entire software categories that consist entirely of code that is only one or two evolutionary steps away from some engineer's spreadsheet originally written in 1995. One fine example I work with has changed its backend database 3 times in the past 4 years. Their most recent decision to use mongodb came with the questionable decision to store json as a raw string literals complete with bizarre escaping inside a database literally designed to store json-shaped-objects.
I don't think Opus could store data that poorly, even if the end user prompting it didn't know what they were doing.
- benefits of AI murky to slightly positive
- hiring impact limited except for junior level
The problem is that these two statements each have massive implications, so instead of treating these findings as point in time snapshots they are the whole ballgame and should be explored in depth.
Most of HN recognized the "We're firing people because AI makes people efficient" as one of the stupidest sales pitches ever and the CEOs that fell for it are just poorly ran companies that outed themselves.
AI is just another cycle in technology that is genuinely useful. The companies that are going to jump the gap are those that are hiring to use this new skill. If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x. You invest, ruthlessly train, hire, and surge forward and leave your competition in the dust.
> If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x.
Very smart people aren't immune to being worn down over time
You seem to be suffering from ai psychosis. You're compromising on quality. If you're not, then you're a shit developer. But I suspect you just haven't really dived into the code on a domain you know, because the generated code usually looks okay from a cursory glance... And it works, more or less. So ymmv
One example: everything I do is properly tested and documented now, even the most trivial of changes. Previously I would have weighed those tradeoffs and sometimes decided not to bother with the tests because they weren't worth the time.
This just reads like another variation of “it’s the user not the tool,” which is just endless runway for always blaming people and never acknowledging the limitations of LLM’s.
I’d be curious to hear how the recipients of your work enabled by the “productivity multiplier” feel about the quality.
Of course don’t let me assume, maybe you have a higher quality disproof for the Jacobian conjecture you could share with the class.