Comment by stego-tech
2 months ago
I'm going to start calling these "Canary" moments.
Assuming we take everything at face value for these sorts of cuts, it creates the following scenario:
A company finds itself with surplus labor capacity due to the efficiencies in AI while also posting substantial profit or revenue growth. The company could downsize the workforce to capitalize on short-term efficiencies and increase margins, though this will come at the cost of long-term reputational harm due to posted profits/health as well as burning out staff who must do the same (or increasingly, more) work with less headcount, leading to attrition when the market shifts in their favor. Alternatively, it could leverage this surplus labor for a period of moonshot R&D or paying down technical/process debts while they have the capacity and the profit to pay for it, which harms short-term share price relative to their competitors slashing jobs, while improving the company's capabilities in the marketplace in the long-run, potentially through mastery of these AI tools or the creation of new product lines.
The fact so many orgs opt for immediate greed over long-term growth really is its own canary that leadership and governance both has failed the marshmallow test.
"A company finds itself with surplus labor capacity due to the efficiencies in AI"
That is one possible interpretation, though I don't think it's supported by any facts.
A competing explanation: companies are spending a ton of money on AI in search of efficiency, and then laying people off in order to offset these investments. That's certainly what's been happening at Microsoft, Oracle, Meta, etc.
You can't really compare them to Microsoft, Oracle, or Meta. Those companies aren't cutting costs because AI replaced their own employees. They're pouring money into AI infrastructure and models because they want to sell that capacity to others.
Their thinking is more: instead of funding another internal product team, they can redirect that payroll spend into more AI compute and models they hope to monetize.
I don't believe CloudFlare is doing that, though they might, they could be needing to spend in Edge AI compute and what not, building out that infra isn't free, so they might need to find places the cash will come from.
Hasn't Cloudflare been investing on AI infra for a couple of years now?
If you're not in leadership at Big Tech, you're only there for the stock price manipulations.
AI is a fraction of cost of an employee though right? I have an 1000$/mo AI budget which is a fraction of my salary, and most people don’t hit their limits.
Sounds like your company is burning 1000 dollars a month for something people are barely using. At some point those costs become unbearable and they admit that absurd AI budget was a mistake, or they admit no mistake and fire people. I know which they'll choose.
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Not everywhere, and this is the year where the price per token will go up closer to the supply cost.
Curious to know why are they not hitting their limits.
In the organization I work, things are crazy at the moment, we are drinking tokens as if we are in hot desert and 1k is barely enough for a week for some people
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I think as someone pointed out earlier, this is more likely about margin preservation as their gross margins are deteriorating really quickly.
Yeah, I wrote this before I dove into their balance sheets for another comment. Cloudflare’s cuts are more defensible than most, but the timing and explanation are shady given that they’ve had the same problems for years.
Turns out running a profitable business is really hard when all you've known was ZIRP.
Honestly think the business lessons from big tech over the last 20 years are hogwash, mostly due to them abusing their monopolies allowing them to subsidize failing BUs indefinitely.
37signals has a better approach to starting software companies, and many of their peers/near peers indicate that it's a better way to sustain lifestyle companies too.
Doesn't turn you into a billionaire tho, maybe that's a plus.
> A company finds itself with surplus labor capacity due to the efficiencies in AI
It's likely more:
A company finds itself with surplus labor capacity due to the over hiring during Covid, cutting down on risky ventures, protecting margins, and narrowing scope.
But I think there's also:
A company wants to see if AI is making them more efficient, decides to cut people as if it was and see what happens.
I also am not sure about the short term stock price, many recent mass layoffs the stock often moved down. The CloudFlare stock is tanking in after market for example.
There's STILL people propping the lie about over hiring? Just admit the economic system is not working for the workers already.
If using AI had a "substantial profit or revenue growth" wouldn't it make more sense to hire more people so they can use more AI and increase revenue?
If I can pay a person 100k and the result of hiring them is 1mil in my pocket, I am going to do that every day of the week.
The only reason to fire them would be that I think the money will still end up in my pocket without them.
It depends if your market has room to grow. If it’s saturated it’s just about COGS.
If the market had been saturated then there wouldn't have been any (hypothetical) revenue growth which is what the comment above was arguing.
Personally I don't think there was any revenue growth to begin with. They are spending a lot on AI and haven't seen any ROI but for reasons they prefer to fire people and keep investing on AI.
That shouldn't apply to tech where there's generally always more market to capture and competitors looking to offer a better product and take your market share.
Excess labor would only translate to increased revenue and new products if these companies had a product vision to begin with. But they don't, so people get sacked.
You are on the right path, but I think you are off by a bit. Every company has more work they want to do than budget allows. However some of those things won't pay off fast enough. That is they have product vision but are smart enough to realize that those extra things they won't be able to do are not things customers are willing to pay extra for today.
I'd say the most accurate casting would be:
Companies have ideas.
Companies have finite budget to pursue these ideas, and never enough to fully pursue all of them simultaneously.
It's management's job to prioritize the order in which they're pursued, subject to available budget.
In the last 5 years, leadership at the Mag 7 has been bad at this core responsibility.
* Alphabet: failed to productize its AI research
* Amazon: completely ignoring the erosion of customer trust in its core logistics business driver (warehouse retail)
* Apple: Vision Pro and lack of product vision (outside of their microprocessor group)
* Meta: VR. Enough said
* Microsoft: Windows. Enough said
* Nvidia: Granted, probably the one standout, but they did get the golden ticket to own a shovel factory during a gold rush
* Tesla: Everything
Objective check: Mag 7 ex Nvidia only outperformed the S&P 500 by +17% over the last 5 years, in contrast to prior periods (and much of that thanks to Alphabet boosting the average)
cloudflare vibecoded a wordpress clone (emdash), they have no idea where to allocate engineers to make new products.
The work is mysterious and important.
> The fact so many orgs opt for immediate greed over long-term growth really is its own canary that leadership and governance both has failed the marshmallow test.
Why do you think it's greed? The company's stock is down and they just missed expectations on their last earnings report (unheard of in big tech in the last 2 years).
It seems more like a traditional layoff scenario
This was kind of my read as well. We are increasing our AI usage but not in a way that meaningfully affects our ability to deliver on our product roadmap, so the solution is to cut opex on people so we can devote more to compute. The last bit is obviously speculation but it doesn’t feel like a far leap.
My charitable company strategy take: this is companies skating to where they think the puck will be
Given the rapid progress in LLM capability in recent history, it's reasonable to expect that continues... at least to some degree.
Consequently, companies are going to need to continue to cut, and delaying those cuts will only leave them in a worse position.
Devil's advocate counterpoint: it's currently unclear where AI does and doesn't provide efficiency gains in a business, so some companies are making headcount reductions without knowing where they should target them
This is simply a symptom that the company doesn't have good Quality Control processes in place.
AI-produced code is good but it's not so good that it can replace hand-crafted (or heavily supervised) code written by the type of engineer who works at Cloudflare.
What's really happening is that a few employees realized they can game the system by turning on a firehose of AI slop and pushing 10x the LOC than any other engineer (with or without AI), because there's no one to tell them to stop, and in fact with a management that actively encourages this.
> What's really happening is that a few employees realized they can game the system by turning on a firehose of AI slop and pushing 10x the LOC than any other engineer (with or without AI)
Did they figure out how to game the system? Or was the system set up exactly with incitaments to produce exactly this outcome?
They figured out how. Mind you the system was setup with incentives to produce this outcome - but before AI it wasn't really realistic to produce all those lines of code even though you could and so nobody was gaming it so badly it broke. (it was always broke, but the breakage was acceptable before)
The new system is immature and hence open to exploitation. This is eventually going to destroy some companies.
That's the thing. There is no surplus labour capacity, neither they have any ideas for moonshot projects that could pay off left