What you describe is certainly possible, but it's not what's happening. You can go on Blind, Fishbowl, any work related subreddit, etc. and hear the same story over and over and over - "My company replaced half my department with H1Bs or simply moved it to an offshore center in India, and then on the next earnings call announced that they had replaced all those jobs with AI". There's a reason why "AI = Actually Indians" is a meme everywhere on the internet, and it isn't racism, it's just people observing the reality around them.

I’m not describing what’s happening right now — I’m saying the data shown in the article is insufficient to ground what it claims. The testimony you mention better supports the argument, but also is insufficient to show that this shift to H1-B is not in addition to a reduction of overall projected headcount due to AI.

Multiple things can be true at once. Some jobs have been eliminated by AI. The H1B system is being abused by employers. Offshoring has replaced more American jobs than H1Bs. Corporations are lying to investors about the impact of AI on their headcount. All of the above are true.

Again, however, the data in the article does not show that. The article is attempting to argue this point with facts (hard data), while not presenting said hard data. It's especially egregious because of the naming of specific companies.

Why is it especially egregious to name companies?

It's a false accusation. The numbers have no meaning. Is that not obviously the point of contention?

It's one thing to say, this is aggregate in the industry (and still be misleading), or say group by MAG7, or AI companies, or some sector. It's another to name Amazon as the ringleader when the data don't show that.

The US is getting outcompeted by India, basically.

On short term price.

>The US is getting outcompeted by India, basically.

And it almost completely comes down to housing costs. If half of your $150k salary wasn't going directly into a landlord's pocket in the US, we would easily be able to compete.

If that explains most/all of it, why don't we see more tech companies moving into areas of the US with low housing prices?

I guess some of it is the "captive" effect for an individual - if you leave the expensive property market for somewhere cheaper with a lower salary, it becomes very hard to move back to the expensive place. But is that a strong enough effect?

Surely an efficient free market should theoretically make tech companies much more geographically distributed?

Many expanded to Texas, for example. Also Hollywood left LA. There aren’t any/many desirable locations left in the US that have low housing costs.

People perhaps don't like the word desirable here. What I meant is not just pretty streets, but many other factors, such as nearby industry, infrastructure, educated workforce (in the thing you need), reasonable weather/sunshine, etc.

Yeah, you can find something cheap, but often it is cheap for a reason. Especially when the whole country has a housing shortage. I'm sure Alaska is beautiful, for example.

Alaska is beautiful, but the polar opposite (no pun intended) of where someone should be looking for LCOL. Alaska is outrageously expensive for myriad reasons, and it is also not exempt from the nationwide housing crisis / greed crisis.

There are also cultural differences in these low cost USA areas that will make it hard to find educated techies there and/or get them to move there. Like it or not, the socially-liberal urban-California culture has become a sort of "Defacto Standard Culture" for tech, and a company is not going to be able to simply move all these people to rural Alabama because the cost of housing and living is cheaper there.

When work-from-home became more widespread, my spouse and I did the whole "Oooh, where could we live to maximize our income/expense ratio!" Zillow fantasy-exploration, and we concluded that even though many places in the country are significantly cheaper than where we are, we would be miserable in these places.

Reminds me of that story that made the rounds on HN a few years ago about that techie who moved to Bumblefuck Arkansas and bought an insanely cheap office for his tech enterprise, and regretted it for years due to the place otherwise being a total shithole.

What could we do to produce educated techies in these low cost areas?

It seems like a USA specific problem because from my understanding low cost areas in much poorer countries produce many highly skilled educated techies. What are they doing differently from the US?

Here's an idea, better education?

Replace the Bible with a science textbook.

There's plenty of science textbooks in our public schooling from what I've seen.

Not enough apparently, else you wouldn't see Texan schools debate about creationism vs evolution.

Those areas are producing educated techies. Those record them move to better areas.

Because low housing price areas are low priced for a reason.

US housing is pretty much mega fucked. The price is close to the maximum people are willing to pay. In many areas, it's well over that maximum.

There's also the small matter of healthcare and education costs.

Or you could say the ruling class is generously donating their software industry to India, much like they generously donated their manufacturing industry to China.

> There's a reason why "AI = Actually Indians" is a meme everywhere on the internet

As a good reminder of the weird information bubbles the modern Internet has become, this is literally the first time I have ever seen this.

It might seem like it's "everywhere on the Internet" but it's really just what your Twitter/discord/subreddit/TikTok cohort are talking about.

And keep in mind, I'm a fellow HN user and likely overlap with you far more than even the average Internet user.

> It requires an accounting perspective on the inflows and outflows of an ongoing process and not just a small slice of data.

Correct, but we don't have that information so we have to rely on a best guess. We're not dealing with code here where everything is known exactly.

> Yet, the main question for actually measuring the (firm and investor expected) impact of AI is whether that rate of headcount growth has changed without the stock price going down.

Stock price is not necessarily a proxy for headcount either. Some companies have much lower headcounts per stock price (for example, Nvidia).

> That is, is it now proposed by management and accepted by investors that the firm will henceforth require less human labor in order to deliver on the present expected value of future free cash flow.

You are just talking without thinking now are you? It makes no sense. Human labor and free cash flow are probably correlated, but one isn't a proxy for the other. First you relate stock price to headcount and then you say "that is" and then you suddenly relate cash flow to headcount. Cash flow and stock price are correlated per industry, but it's also a very loose one.

> You cannot infer anything about this question from the data shown.

False. I only need to infer a tiny bit in order to falsify your extremely strong claim.

> For this, you would need to look at net hires year after year and prove that a growing percent thereof are H1-Bs.

Yes, this is something concrete that I can agree on. But how would you prove that given that we don't have access to that data?

Apologies if my presentation is inadequate, but I’m not suggesting that stock price is a proxy for headcount. I’m simply arguing that you have to look at the two together in the context of a particular firm — for exactly the reason you note, ie NVIDIA has a lower head count per share etc. It’s the ratio that matters and is the best proxy we have for inferring the cause of a shift in hiring. Lower growth of headcount and stock price going down suggests the cause of the former is reduced expectation of return, ie particular industry or general economic slowdown; lower growth of headcount and stock price remaining constant or rising would be more suggestive of (not causal proof of course) of an AI-related effect.

If we don’t have the data we shouldn’t argue that the data we do have says what it doesn’t. I actually agree with you and the author that trying to figure out what’s going on in labor markets right now is incredibly important — but for that very reason we have to be careful not to accept too easy conclusions. There’s a lot of information we do have about firm expenditure on labor within public filings — I’ll actually try to pull some figures this weekend, can let you know when I do if you’re interested. I think the interesting question on the AI side is whether it allows more firms to present a ratio like NVIDIA, ie reducing expenditure on labor that is considered a “cost center” in a particular industry.

>> lower growth of headcount and stock price remaining constant or rising would be more suggestive of (not causal proof of course) of an AI-related effect.

Since stock prices are basically future expectations, wouldnt it probably be because investors expect the company to be more efficient cashflow wise? (Earn more per employee)

Not necessarily because they already are more cashflow efficient?

> Yes, this is something concrete that I can agree on. But how would you prove that given that we don't have access to that data?

Without that data you can't really draw any conclusion can you? For all we know companies are hiring a higher percentage of American workers now. All we know from the data shown is that companies are hiring some new H1-B holders and retaining a lot of existing H1-B holders.

> given that we don't have access to that data?

Actually, we do have some of that data. You can just look at the H-1B employer datahub, filter by Google (or whichever other employer you want to scrutinize), and then look at the crosstab.

https://www.uscis.gov/tools/reports-and-studies/h-1b-employe...

Looking at Google specifically, I observe two things:

1. The number of new approvals has gone down drastically since 2019 (2019: 2706, 2020: 1680, 2021: 1445, 2022: 1573, 2023: 1263, 2024: 1065, 2025: 1250). (These numbers were derived by summing up all the rows for a given year, but it's close enough to just look at the biggest number that represents HQ.)

Compared to the overall change in total employees as reported in the earnings calls (which was accelerating up through 2022 but then stagnated around 2025), we don't actually see much anything noteworthy.

2. Most approvals are either renewals ("Continuation Approval"), external hires who are just transferring their existing H-1B visas ("Change of Employer Approval"), and internal transfers ("Amended Approval").

> Without that data you can't really draw any conclusion can you?

We're not dealing with software here. It's not black and white. We can try to make best guesses and then try to support it by evidence or reject it by evidence. A theory that is presented is that H1-B appear to replace US workers, but you are encouraged to provide another theory by using evidence.

> All we know from the data shown is that companies are hiring some new H1-B holders and retaining a lot of existing H1-B holders.

And why do you think that's not suitable evidence for the given theory? Another possible point of data that seems to point in the same direction could be the US Employment-Population Ratio, which, apart from some ups and downs, seems to have been steadily going down since 2000 [1]. More specifically, California's unemployment rate seems to go up since 2021 [2]. But these two data sources are way more broad than just big tech of course.

[1]: https://fred.stlouisfed.org/series/EMRATIO

[2]: https://labormarketinfo.edd.ca.gov/data/top-statistics.html

Of course it’s not black and white: it’s the very fact that there are so many possible explanations of the current changes that makes pretending data supports a given explanation more than another when it doesn’t so misleading. There’s no doubt that offshoring and H1-B hiring is an important trend — as it has been since the 1990s, NAFTA etc. We don’t need this article to tell us that. The difficult question is whether AI is actually introducing a new dynamic into the situation. The article suggests it isn’t. All I’m arguing is that, whether or not the conclusion is ultimately true, the data presented does not shed light on this important question.

Without knowing how many beneficiaries were approved in prior years we don't even know if there is a net increase in H1Bs. They have to be renewed every few years.