Maybe because the models keep getting better and the tools are slowly getting good enough to replace people? Keep in mind we’re talking about oracle here, it’s not like we’re talking about humanity’s best and brightest.
The correlation between job cuts and ai growth is real. But it's related more to ai cost than ai performance. Especially in Oracle's highly leveraged case.
This conversation always gets lost in the weeds. You don't need a SOTA model to replace an entire engineer role from the time he gets into the office until he leaves.
If you have a team of 10 and make them all a little faster, you can do the same amount of work with 9. Run this out over the entire industry and it's hundreds of thousands of roles that are redundant.
Do you have any research, empirical data, or other hard evidence that shows that a model (especially a non-SOTA model) makes engineers even "a little faster"? I'm aware of anecdotes, but nothing more.
The cleanest positive study is Cui et al., because it used randomized rollout in real companies. Developers at Microsoft, Accenture, and a Fortune 100 electronics manufacturer were randomly given access to an AI coding assistant. Pooled across 4,867 developers, the authors estimate a 26.08% increase in completed tasks among users. They also report increases in commits and builds.
While that research was published in 2026, it analyzed the 2023 period. Very much NOT sota models!
When talking about bullshit jobs like, say, taking a bill received by paper and manually extracting data from it (company name, invoice number, bank account details) to enter into an accounting program, AI is already good enough according to the pareto principle.
Maybe. But the models weren't good enough 2+ years ago. And to cite just one example, in February 2024 Grammarly laid off over 20% of its employees, citing AI. So you'll have to forgive me if I am extremely skeptical of CEOs citing that as the reason today.
It's a very convenient excuse, especially given the apparent lack of public backlash to it, compared to, say, "the business isn't profitable and we need to save money."
A few years back I heard (via a friend who knows a CEO, so take it with appropriate pinch of salt given not a direct experience), that Gartner was asking the CEOs in its group meetings how many of them were laying off people due to AI, with the question presented in a very leading fashion that implied anyone not was behind the curve and failing their business or whatever.
Maybe because the models keep getting better and the tools are slowly getting good enough to replace people? Keep in mind we’re talking about oracle here, it’s not like we’re talking about humanity’s best and brightest.
> Maybe because the models keep getting better and the tools are slowly getting good enough to replace people?
I am not sure we are there yet.
In my experience even the SoTA models are faaaaar away from replacing humans, maybe making them a bit faster.
The correlation between job cuts and ai growth is real. But it's related more to ai cost than ai performance. Especially in Oracle's highly leveraged case.
This conversation always gets lost in the weeds. You don't need a SOTA model to replace an entire engineer role from the time he gets into the office until he leaves.
If you have a team of 10 and make them all a little faster, you can do the same amount of work with 9. Run this out over the entire industry and it's hundreds of thousands of roles that are redundant.
Do you have any research, empirical data, or other hard evidence that shows that a model (especially a non-SOTA model) makes engineers even "a little faster"? I'm aware of anecdotes, but nothing more.
The cleanest positive study is Cui et al., because it used randomized rollout in real companies. Developers at Microsoft, Accenture, and a Fortune 100 electronics manufacturer were randomly given access to an AI coding assistant. Pooled across 4,867 developers, the authors estimate a 26.08% increase in completed tasks among users. They also report increases in commits and builds.
While that research was published in 2026, it analyzed the 2023 period. Very much NOT sota models!
https://pubsonline.informs.org/doi/10.1287/mnsc.2025.00535
Thank you!
> I am not sure we are there yet.
When talking about bullshit jobs like, say, taking a bill received by paper and manually extracting data from it (company name, invoice number, bank account details) to enter into an accounting program, AI is already good enough according to the pareto principle.
[dead]
Maybe. But the models weren't good enough 2+ years ago. And to cite just one example, in February 2024 Grammarly laid off over 20% of its employees, citing AI. So you'll have to forgive me if I am extremely skeptical of CEOs citing that as the reason today.
It's a very convenient excuse, especially given the apparent lack of public backlash to it, compared to, say, "the business isn't profitable and we need to save money."
I doubt we are there yet, no.
But we are talking about a corporation that is one of the most sociopathic in modern business history.
Say what you want about their business practices, their products are top notch.
A few years back I heard (via a friend who knows a CEO, so take it with appropriate pinch of salt given not a direct experience), that Gartner was asking the CEOs in its group meetings how many of them were laying off people due to AI, with the question presented in a very leading fashion that implied anyone not was behind the curve and failing their business or whatever.
Yeah, the actual funny thing is they've been blaming AI since almost GPT-3 era.