A challenge with this kind of study is that coding agents (Claude Code, OpenAI Codex) only started working really well in late November, which for most people meant early January due to the December break.
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.
However, companies have been using AI as an excuse for layoffs since well before January 2026, which corroborates the study's conclusion. (Source: https://layoffs.fyi/ai-layoffs/) There is certainly an uptick starting 2026, but that could be explained either by AI actually causing more layoffs, or by AI becoming an even better excuse for layoffs.
It seems to be true this time though; I have observed it myself and heard it from several experienced developers I personally know and respect. It feels like some threshold was crossed with Opus 4.5 and Gpt 5.3, where the models are now able to reliably solve certain classes of problems that were previously unreliable.
Time will tell of course, and it’s early, but inflection points do exist with progress.
"unless you're content with producing low quality work." - With the right guiding hand, it is a productivity multiplier without compromising quality. As a fully autonomous developer, it is a disaster.
Anecdotally, I (along with the rest of my team) got laid off from a big tech company at the end of January. The stated reason was "AI", although I think as we all know the real reason was "we overhired in 2022". I managed to get a job by April without putting in a lot of work, though (mostly just listened to recruiters until something hit my fancy). My work experience is good, but I don't know if it's so good that I would be immune to market effects. The company that hired me is still hiring other software developers, and I was told that it took them a long time to find someone with my qualifications. (We use Claude, although so far I haven't seen a lot of AI psychosis like I have in other places.. that was also a big filter in my job search). Long story short, I think narrative of job loss is way overblown. It's more doom trolling from anthropic and openAI and their mouth pieces as far as I can tell.
Anecdotally I'm seeing a lot more recruiter activity/interest now than this time last year.
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.
This. Also I'm finding out that, after being blown away by agent mode lately, non-agent mode still kind of sucks across frontier models. Using GPT and Gemini in non-agent mode is asking for inaccurate information confidently presented as the truth. Turning on agent mode fixed a lot of that for me.
For whatever anecdotal evidence it's worth - that has been my experience as well. For the first time last December I noticed the harnesses performing like actual workers.
Everything impressive has happened in the last six months.
This isn’t the first study showing this though. It’s pretty simple, programmers and IT were severely overhired during the pandemic, there are massive job losses now, and it’s easy to blame AI when in reality there are a lot of economic factors and AI isn’t increasing productivity as much as anyone would think.
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.
>programmers and IT were severely overhired during the pandemic
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.
I personally hope that AI continues not to result in a noticeable negative impact on employment and that pandemic over-hiring turns out to be the major factor for all of the layoffs.
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.
Any research on the impact of AI would have been lagging indicators. It's not the researchers' fault[0], but the nature of a field moving at neck breaking speed. Remember there was a paper saying programmers were 20% slower with AI?
And this is why the labs cannot just "stop training and become profitable". I can't imagine they would like it if studies like this will actually become credible.
"Move fast like a blur so people can't see that you have no clothes"
Recently poked around the job market to see what I qualify for in this day and age. Working as a solo builder in my org I would say that I have done enough in the last 18 months to consider myself “with it”.
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.
> Companies asking for 4 years of agentic AI experience… pardon?
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.
A 10x engineer only needs about five months of experience.
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.
Organizational inertia is a real thing. There are still fortune 500 companies with internal bans on AI. A lot of the answer to "how much impact has AI had" comes down to "how much have we even attempted?"
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.
> 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?
I think Sturgeon's law would tell us that everything will stay about the same.
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.
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.
I don't feel like reading an article that will probably be out of date in 6 months, but from what I've seen, if agents keep improving at this rate, 80% of SWEs are going to be looking for new careers in 5 years.
Probably both. We were already hitting limits in terms of finding software that could generate returns; without public funding or enormous regulation the possibility of finding new jobs with a degree is lower than it's been in a while.
Seems like all companies think that their products are good enough and can’t offer more, as they always want to remove people instead of offering better and bigger products.
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.
Everything impressive has happened in the last six months.
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.
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.
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.
[0]: well...
"Move fast like a blur so people can't see that you have no clothes"
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!
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.
Yeah, sure you are. Report back when it happens.
- 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.