Public press paints picture of the firm laying off due to adoption of AI. Yet, I can assure you without doubt its not because of it but due to continued offshore.

I think we are at the brink of opening another large campus in India, not sure which city. Oh another thing is these full time position in NA were eliminated and replaced with employees from TCS.

My own boss is against it but its coming from higher ups. I have no idea what's driving them. We made billion in net revenues last year and we are actually part of the org that is in 'cash cow' category - upper management literally said this too in our town halls

https://www.futuriom.com/articles/news/why-we-dont-believe-m...

https://www.cnbc.com/2025/11/04/white-collar-layoffs-ai-cost...

And this isn't about AI (well, not primarily anyway). It's offshoring, offshoring, offshoring.

IMO, what's taking place now is absolutely transformative and the world economy is in the process of being reshaped. It's not just tech jobs that are being offshored - we're just one of the first/early movers. Many other professional/white-collar jobs (accounting, etc.) are also getting offshored at an accelerating rate. And it's happening all over the western world - it's happening in the US, it's happening in Australia, Canada, the UK, etc.

And unlike previous periods of mass offshoring, I don't think the jobs are ever coming back.

Opening in a private window solved the issue, however I'm pretty sure I don't regularly read anything on this site (maybe never was an overstatement?).

Over the last 20 years of tech, the giants have taken the smartest folks out there and put golden handcuffs on them. You could hire up all the smart folks and put them to work, or leave them out there and have them compete with you. With the launch of cloud providers and (expensive) dynamic scaling the problem only got worse. Think about hiring in the pandemic. Every one at home, with a stimulus check and nothing to do. Rather than a flurry of new software you got mass hiring.

But now we are in a capital intensive hardware cycle. Where in order to compete you need to have lots of $$$$ as well as software know how. It does not matter that there are smart people out there, without hefty backing they wont get very far.

I suspect that software is about to enter its "punk" era. We have software for small businesses that will help with accounting, HR, customer service, and cloud providers are starting to see some interesting competition. Much like the old punk poster showing you 3 chords and telling you to start a band it is entirely possible to find three friends and start a business that makes 1-10 mill a year with little effort and lower costs. The moment you stop thinking "unicorn" and start thinking "sustainable" the economics shift radically.

Obviously layoffs correlate with AI age, but it's most definitely not AI replacing jobs, not yet. Even in 2025 stories about a job fully taken by AI need to be scraped for, and it's almost always about non-SWE jobs. And in 2023, when the first layoffs already started, models sucked and none of the existing tools and agents even existed yet! But if you search for example for headcount growth in India/Mexico, the numbers can only be described as "booming".

I don't know what exactly is going on, but it's pretty obvious the companies are moving offshore or simply doing less work, and for some reason need to lie about why.

Not a single mention of jobs being moved to India including tens of billions of investments in new offices.

Backing links from a quick search earlier this week when an obviously Indian HNer tried to deny this was really happening:

Microsoft announces US $3bn investment over two years in India https://news.microsoft.com/en-in/microsoft-announces-us-3bn-... (Jan 2025)

Google announces $15B investment in AI hub in India https://apnews.com/article/google-artificial-intelligence-vi... (3 weeks ago)

[Indian] ex-Accenture CTO named Google Cloud’s Chief Product https://www.hindustantimes.com/trending/us/who-is-karthik-na... (last week) (a lot of people speculate they named an Indian Accenture guy to move as much as possible to India)

Big Tech giants defy US-India trade tensions, record strongest 12-month headcount growth in India in 3 years https://www.moneycontrol.com/technology/big-tech-giants-defy... (September)

https://www.reuters.com/world/india/openai-launch-first-indi...

https://www.anthropic.com/news/expanding-global-operations-t...

and so on. Something very crazy is going on.

NOTE: I am not American and this doesn't affect me directly.

1. How will tangible assets generate profit net of near term capex requirements and interest on debt?

2. Why wouldn't payroll shrink as a result of the increased AI capabilities emerging from the capex spend?

3. If AI lives up to the hype & given recent news that public backstops are being requested, why shouldn't the US quasi-nationalize cash strapped players and distribute equity to every American?

4. As NVDA and AAPL local models and local compute eat into utility and base automation business, how do edge players maintain profitability without pricing capabilities well beyond the affordability of SMBs and individuals?

> Those expenditures may be approaching $1 trillion for 2025, while AI revenue—which would be used to pay for the use of AI infrastructure to run the software—will not exceed $30 billion this year

While it's clear that the author is summing up the spending from the big players, it's not clear to me that their math is right for revenue. Yes, OpenAI, Anthropic, Thinking Machines, SSI, etc. have pretty limited direct revenue (including zero!).

But this comparison assumes no revenue growth for other top computing users. Some companies are certainly saving money on some tasks and increasing revenue, particularly in fields like customer support. See the confusing figure in section 5 of https://hai.stanford.edu/ai-index/2025-ai-index-report/econo... .

That chart is by number of respondents and not weighted by revenue. Like the MIT study, it would not be surprising that "just pipe this to an LLM" isn't enough for most fields or companies. But a few have likely made material improvements.

10% of respondents saying they've seen a >10% revenue gain could be substantial, if they're bigger firms with high leverage in computing.

Edit to add: the comparison also makes a classic "GDP vs market cap" style mistake. Capital expenditure has multiple years of useful life. Revenue is annual. You'd want to compare depreciation vs revenue.

The other factor is, will revenues really stay the same for companies once we have AGI / super intelligence? It seems value will not accrue to the companies that are in chill mode.

And investment and experiments by definition include the risk of failing. In almost everything lies a survivorship bias and no one talks about the 100+ car makers that went into goldrush mode 100+ years ago. This is life. Netflix vs Blockbuster - already forgotten?

Also the "fail rate" - so what part is failing and why? What's with the 5%? If we have a look at exponential functions this might be a really good deal, if the 5% can account for the losses. After all, benefits compound over time.

I witnessed first hand in FAANG some quota hires and I believe that now that no one gets paid for contrived and artificial business advantages, we are back to a more merits based evaluation of workers.

But AI should not be written off as fancy something with no impact. That's the wrong take. Whether it will be a springboard to new jobs that compensate for losses or replacements - I am not yet sure, but tent to be in the former group. ML engineers take care of ML - something new that takes care of something new.

We will see.

AMZN for example overhired in various functions because it expected demand that never materialised. Admitting that is bad for the share price, but writing some woo about "AI and agility" will convince at least some investors to keep the faith.

Likewise many tasks I used to do with Java, .NET, Node.js, have been replaced by low code/no code tools with agentic orchestration.

Thinking that AI isn't replacing jobs is wishful thinking.

Given all those articles with AI generated images I bet that some artists lost their jobs

If you've been outsourced, ask your representative to support the HIRE Act: - Creates a 25% tax on outsourcing payments - Creates a “Domestic Workforce Fund” for apprenticeships/workforce development. - Prohibits companies from deducting outsourcing payments.

Because in any country with poor worker protections, the outcome is layoffs regardless.

AI succeeds? Layoffs of unneeded roles.

AI fails? Layoffs to cut expenditure to make up for the written-off expenditure.

In the UK, if AI makes a well-established employee redundant, the employee is entitled to redundancy pay. And if the company fucks up and overspends on chasing a ridiculous Macguffin they can't just fire people without making them formally redundant.

The damage that is going to be done in the USA if the AI bubble bursts is going to be generational.

This year alone something like 400B was spent on investing in chips, datacenters, electricity buildouts. That's 400B that could have otherwise been invested in people.

While i don't doubt that people will find a few solid business cases for LLMs, i am on team-bubble. I don't think this investment will add 400B worth of value and I very much doubt that this 400B is any good for future growth or long-term aspirations of AGI. Investing 400B into people and (tech) manufacturing would be a solid long-term bet with benefits.

That being said, I think we as a society are quickly reaching the point where there just doesn't exist enough jobs to keep everyone gainfully employed. There may be new jobs opening up but not ones that people in the middle or ends of their careers can quickly pick up on. I don't think this is a bad thing necessarily, just that when combined with the shitty safety net that the US has, it's a recipe for disaster. If even folks who are working full-time still need assistance for groceries, then we've already failed, and that's not even AIs fault.

The spending-revenue gap is real. Hyperscalers are projected to spend $300-550B on AI infrastructure in 2025[1] while generative AI revenue won't exceed $30-40B [2]. Amazon's capex jumped from $48B in 2023 to $84B in 2024 to a projected $100B+ in 2025[3], that's capital intensity doubling from historical norms of 11-16% to over 22% [4].

But here's what the article misses: this isn't financial desperation. When Amazon's CEO announces 14,000 layoffs and explicitly states that AI will enable "fewer people doing some jobs"[5], he's revealing the strategic logic — show me the incentives and I'll show you the outcome. Companies aren't cutting jobs despite AI spending; they're cutting jobs because they know AI spending will pay off.

To be clear, the article treats the spending-revenue gap as evidence of irrationality. But infrastructure buildouts always precede revenue: railroads looked insane before they transformed commerce, electricity grids consumed massive capital before delivering returns, the internet required enormous infrastructure investment before creating trillion-dollar companies.

What's different now is companies are pulling the future forward. If we take this article at face value which I can appreciate is a BIG “if” then AI is already automating 25% of tasks and delivering 10-55% productivity gains[6] so they're not waiting for AI to replace jobs organically. They're cutting headcount now to fund the infrastructure that will make those cuts permanent.

More broadly, this is rational capital reallocation in a winner-take-all race. Companies that don't build AI infrastructure won't gradually decline, they'll lose competitive positioning entirely. That's why Meta is using off-balance-sheet financing for a $27B data center[7], why Oracle is borrowing $25B annually despite already carrying 450% debt-to-equity [8]. They're all-in because the alternative is obsolescence.

The real story isn't "spending causes cuts" it's that AI infrastructure commoditizes human expertise, the complement to compute infrastructure. Companies are trading labor costs for compute infrastructure because they've correctly identified compute as the new moat. The job cuts aren't the price of spending on AI; they're the business model shift that AI enables.

The article is right that we're not seeing mass AI job replacement yet. But the job cuts are happening in anticipation of replacement, not as an unfortunate side effect of spending. That's not desperation just business strategy.

-- 1.(Morgan Stanley: https://www.datacenterdynamics.com/en/news/morgan-stanley-hy...) 2. (Grand View Research: https://www.grandviewresearch.com/industry-analysis/generati...) 3. (CNBC: https://www.cnbc.com/2025/02/06/amazon-expects-to-spend-100-...) 4. (Cerno Capital: https://cernocapital.com/accounting-for-ai-financial-account...) 5. (CNBC: https://www.cnbc.com/2025/10/28/amazon-layoffs-corporate-wor...) 6. (PwC: https://www.pwc.com/gx/en/issues/artificial-intelligence/ai-...) 7. (Fortune: https://fortune.com/2025/10/31/metas-27-billion-bet-turns-ai...) 8. (The Register: https://www.theregister.com/2025/09/29/oracle_ai_debt/)

I literally just said that on Reddit:

"They [big companies] were already laying off lots of people and hoarding around 100 billion in cash. This has nothing to do with AI. The elites have been at that for some time for who knows what reason. If anything, they didn't start spending money until the AI boom.

You could say AI is destroying jobs for a different reason. The leaders of the companies believe in gold rushes more than a steady stream of investments into forming and growing actual businesses. They didn't or don't believe America is worth investing in. They're simply about extraction."

I wonder if that's true; I'm not in the US myself so I can't exactly just go have a drink in a place with lots of devs to try to find out.

The reasons are somewhat obvious:

* World economy in general and the US in particular is a rollercoaster, with the current administration being apparently dead set on flip flopping on every decision it makes, and always making extreme decisions. That's not a good time to invest. Hiring juniors is investing.

* AI not necessarily replacing the jobs, but that's not actually relevant: AI has already torpedoed the general notion that 'if you have investor money you gotta spend just hire a bunch of folks; # of employees is the primary yardstick to check company size / success', whether AI works or not. If the boss tells a VP to 'use more AI to get a handle on hiring practices', then they're going to stop hiring juniors because it looks like you're outright refusing a direct order if you hire a bunch. Even if AI 'employees' are useless, you are strongly incentivized not to hire juniors in such an environment. Juniors both lost the job opportunities stemming from companies just hiring folks because they have enough cash to do it and no good idea on where to spend it, and the downside of looking like you aren't on the AI hypetrain, if you hire juniors.

* There's evidently been a rather massive push in particular during the previous administration to get folks from dead end jobs into IT, so there's now an overwhelming amount of junior devs, and many of them didn't naturally get drawn to the profession; they were told it's an easy way to get a steady job.

* Even though there's some downturn/uncertainty, seniors/mediors aren't being fired because companies still remember how expensive and difficult it was to (re)hire dev teams post COVID. But that just makes the market for juniors even worse and makes it harder to hold out hope. When everybody is getting fired, then once the economy is in better shape you stand a good chance. But that's not happening; those mediors and seniors are continuing to get job experience whilst the juniors aren't.

Those 4 combined: Sure, yeah, I can imagine your average junior dev's odds to get hired are at this point well into the single digits. But is that actually true?

Are the numbers really that bad?

Google has been claiming that their cost per AI search query has dropped by over an order of magnitude.[1] They're presumably reaping the gains of not cranking up a really smart model on dumb questions.

[1] https://arstechnica.com/ai/2025/08/google-says-it-dropped-th...