Even if I were the stupidest and least curious engineer around (and I was far from it), that's basically irrelevant to what you're scolding me for here…
As part of a team with both software development and operational responsibilities, like most teams at AWS, I had to deal not only with the consequences of my own imperfect knowledge, but also with the imperfect knowledge of my coworkers past and present.
The underlying reason is more that by being in us east coast you have about equal latency for customers in us west coast and Europe. That's a very large population covered from a single site.
If you're building a single datacenter site this is where you start building first.
There was an recent article on X with an interesting take - it could be that companies are doing layoffs not because AI is making them more productive but because it hasn't. Their costs have gone up paying for expensive AI but haven't seen any revenue benefits to offset it.
This genuinely wouldn't surprise me, and I need to go back to looking at balance sheets to see if I can sus out the validity of that narrative. As AI subsidization ends prematurely and costs skyrocket, we should expect to see those costs reflected in the operation statements of major customers.
Since I had Coinbase up for review already, I decided to peek there first for any sort of correlation. In 2023, their "Technology and Development" line item shows $1.32bn going out, and by 2025 it'd ballooned to $1.67bn. This is despite headcount actually contracting by almost a thousand people between those two statements, which would normally mean a smaller technology spend since a lot of corporate software is seat-based nowadays. This suggests that yeah, actually AI spend is creating a heavier drag on the balance sheets and it's being offset with layoffs since the "job replacement" narrative is strong. That said, I'd need to check dozens' more balance sheets to draw any sort of industry-wide conclusion.
And to factor in other infrastructure costs that's become more expensive too, such as hosting or hardware.
So unless you can isolate AI spending from others that's not going to be convincing.
...hence why I qualified the statement like I did. I'm well aware one example from one company in a budgetary line item that's inclusive of labor and licensing and hardware and purchases and AI is not going to be remotely conclusive on its face.
Yet even taking into account all of that data, a $300m jump in three years must include some significant and growing amount of AI spend; everything else would've contracted (licensing, hardware) stagnated (cloud consumption), or been a singular event (CAPEX purchases) relative to the company's health and headcount.
Rings true because now teams end up building a lot of things that may or may not have alignment to customer/business needs.
The slow part has always been figuring out exactly what the customer/business actually needs, not the coding. Now teams are throwing money at tokens without solving the "who's buying this?" part appropriately and end up just building excess.
Now that you can just throw tokens at it, it seems like actually thinking about what is useful and productive is no longer a practical skill (it still is, just no one in leadership nor product wants to practice discipline any more).
I don't know what to say about it except that it legitimately feels like some folks have just shut off their inquisitiveness and willingness to investigate and think before acting.
Now it's act, waste tokens and time, only to learn that the result of the action was obviously bad from the start because of some real-world human nature that we now no longer stop to try to understand first before applying a technical solution.
Personally, I think AI is just a convenient scapegoat for these mass layoffs. Also, these kinds of announcements contribute to sustaining the AI hype which all tech investors benefit from. And investors looove hearing about mass layoffs, stock goes up every time without fail.
investors are not some nefarious monolith cheering for companies to make decisions based on how it benefits The Vibes. they're analysts assessing business decisions.
It went down on poor earnings call. Layoffs were probably an attempt to soften the blow. Hard to tell what was the effect, because the two happened simultaneously
This is the simplest and almost certainly correct answer.
I’ve seen this at a number of public companies, and is a reason I hate working for them. These decisions are always unbelievably short sighted and ruin companies in the long term.
This is no that far fetched...
I don't think it's that common that a customer sits on the fence and says "If only company X had Y on their feature list I'll be a paying customer". So the speed at which the company now runs through its roadmap does not equate to new customers joining.
They are laying people off because the cost of financing have gone up. The risk free rate is now almost 5%. For equity financing you'd need to show revenue growth models that allows repayment at that rate plus equity risk premium (which is quite large for new growth companies).
So the CFO makes a model that allows for this and for sufficient ROI they need less people to be more productive. This mechanically forces them to lay people off.
Of course laying people off might actually not improve productivity, but they need this to have chance.
They're laying off the people who can't produce a minimum of 2x with AI, and keeping the maximalists with no life outside of work barely keeping up with the 100k LOC a week they're shipping to prod.
Suits have an idea of what the New Model Coder should be, and it's not people who don't burn through 100,000,000 tokens a week.
The promise of AI gains with fewer people is what's triggering this - before, you needed ~1 coder to do ~1 unit of work. Suits now think you only need 1 coder to do X units of work because LLMs.
I wouldn't argue that it doesn't give any benefits. However, it's not worth the current cost unless you already own RTX PRO 6000 to run any reasonable LLM. I'm using Claude Free and I'm happy with what I get, especially for the cost of $0.
I'm eagerly waiting for the prices to come down so I can upgrade my PC to AM5 and run Gemma 4.
Its quite possible that LLMs become housed units like the next PC. Initially it starts off as being a large thing in data centers (like computers did) until they got smaller and smaller. Except I expect the time it takes to get smaller and smaller to compress much more - given that we live in a world with far more resources and risk-taking.
Cutting salaries to pay the AI costs for the remaining engineers. Going to be rough as this trickles through the entire economy over the next 10 years.
I know this is cold comfort, but in times like this, it can be a good idea to start your own company. Cloudflare itself was founded in the wake of the GFC (post-2008), when tech was dead as a doornail. The best time to start something is when awesome people to work with are unemployed.
You're not going to fit a data center in a Starship either, unless you are talking a Tiny Corp Exabox "data center in a shipping container" sized one. Even something that small (1MW) would still need 4x the solar capacity of the ISS, and therefore likely some assembly required. Then you've got latency from satellite to satellite ...
In any case, it appears that Musk can't even generate enough AI demand to utilize his own ground based data center. Maybe he can add "data centers in space" to part of his Mars colonization plan. Maybe have Tesla Bots driving around in Cybertrucks too ?
You realize natural gas is one of the more environmentally friendly methods of generating power. Lots of work went into moving to natural gas generation to improve the environmental impact for electricity generation.
While the burning of methane is cleaner, the extraction of methane is a massive source of uncontrolled pollution emissions which is made worse by the fact that methane is 20x worse for greenhouse effect than CO2. Clean methane is another green washing myth to encourage people to keep consuming at much as possible
as other have mentioned tons of portable generators are no where near as safe as power plants and these are built right next to people's homes with no oversight or regulation.
Most municipalities ban nat gas in new construction because it’s so unhealthy and unsafe compared to an induction or resistive electric range. No, it doesn’t boil water faster than electric either.
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