If virtually any other company in the world said "we have internal AI servers and we let our employees use them" ... the company would measure that as they would any other internal expenditure: by how much it costs them. You blow $50k a year on servers running your LLMs? It cost you $50k.
Only a company like Anthropic, desperate to make news and help their IPO, would measure by the cost they charge customers. It's as ridiculous as Microsoft counting every employee's use of MS Word ... as if it had paid the full consumer price of each copy.
This is the world of spend more, get valued more; obviously the investment will be used to spend more and get more, so it must be good. This is investor-think. If you don't have spend, why do you need investment?
(Or it could be bad. Very very bad)
So you are apparently now claiming my local train company or law firm will be using as many tokens per employee as an A.I. lab.
This is as if you learned that Anthropic scanned 1000 books per employee this year to train their models and your conclusion was that the best law firm will be scanning 1000 books per employee by 2029.
Yea, isn't the entire point of RSI to replace your employees altogether? So you'd spend an infinite amount more on AI than employees in that theoretical.
Like, if you were in an energy generation business spending way more on fuel and capital expenditures is way better than having zillions of employees earning checks , it would be a sign of efficiency.
A clear example is Google. They can easily give all compute to Deepmind, yet majority is allocated to be sold at market rate.
So, every compute Deepmind and Googlers get is lost revenue opportunity and must be measured as such.
No other internal tools or servers has this much external demand to be comparable.
Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
You have confused necessary and sufficient.
They have never claimed that the API rates are the "real cost" of the compute spend.
I don't know where you got that from but the only time I maxed my $20 plan for a week I made the calculation that I had spend close to $200 in a single week. So maxing a $200 plan for a month should give you $8000 worth of token at API price. Obviously it's not $300k but it's still very far from the retail price.
$200 of usage on a $20/mo plan is a 10X multiplier.
The $200/month plan has 10X the usage of the $20/month plan.
So $200 * 10X = $2000/month. I don't know how you got to $8000.
Recent analysis by industry analysts like Semi Accurate have measured Sol 6.1 on the $200/month plan to be around $2000 of API equivalent use.
FYI there are 4 weeks in a month…
> Recent analysis by industry analysts like Semi Accurate have measured Sol 6.1 on the $200/month plan to be around $2000 of API equivalent use.
Sol isn't an Anthropic product though so maybe OpenAI is less generous than the former, I can't tell.
source? The most optimistic calculations don't come anywhere close to that.
There are a bunch of open source harnesses that are competitive with CC and they aren't using anywhere near that many tokens to do it.
Anthropic recently handed out free cloud resources (it's still free, guess they want you to get used to the fact that cloud is not free). I went through $250 cloud budget in less than 2 days.
Feels almost as expensive as LLM calls.
However, so is my phone!
(IMO the really impressive part is the thermals. My laptop can dissipate some 45W on a sustained basis, and my workstation takes quite a bit more than 45W to outperform my laptop.)
Maybe, but it also reduces supply that can drive up prices
Bank reserves, Compute etc are trade-off decisions. Buffett vs Mayoshi Anthropic vs Google are being played out in real-time for us. Pretty soon you'll know which trade-off was better.
You could also look at the opportunity cost of not letting Deepmind do quite as much research. How much is additional research worth on the margin? There will be diminishing returns.
Even within a single moment, if there is capacity for an internal request, just send it, if market traffic is currently at 100%, don't.
you could not be more wrong, you cannot IPO if you say product is good enough. The whole point, the bet why its worth trillions is because they will reach AGI and "singularity" first, so the gap vs open source will only increase. If you say product is great as is, then you will be caught up and game over
AI infrastructure is supply constrained, so you have to make a decision: how much do I allocate to training vs inference?
Do I use it all for inference and do no further training? If so, what risks does that expose me to?
It's supply constrained in terms of global hardware production capacity, but that's not how it works for any given company. If Anthropic wanted more GPUs for customers paying them enough money to outbid the next guy in the market for the finite number of GPUs then they would do that and get a higher percentage of the finite number of GPUs.
So the cost of using more internally is still their own cost, i.e. the price of being the high bidder on more compute resources, not the retail price they charge to customers.
They are doing the calculation on if the $150K/person is worth it, and it probably is.
Their revenues have exploded, they are unit-profitable, they need to also invest in the future.
They are full of koolaid but not dumb either.
They are aware of the opportunity cost of their tokens and the their staff are 'laying golden eggs' right now, if there is anyone making use of tokens, it's them.
Even tokens on the floor are probably well spent, given the economic leverage they have.
In order to correctly make that decision, they must use the opportunity cost of selling that token. I'm pushing back at OPs claim that Anthropic must use internal cost to calculate that trade-off. They absolutely should use external selling price.
Instead what's happening is more or less the opposite of that. They've been trying to goose demand by cutting prices: https://www.cio.com/article/4225643/openai-anthropic-cut-ai-...
They have infinite money to burn so they aren't going to optimize.
I've seen that trivial changes to workflows can token usage by 30%. Repeat this a few times and my token usage has plummeted over the last few months.
Only outputting test failures instead of having agents read test run output in real time. Not having build logs get fed into context. Projects like UCL (unified context layer) so agents don't rediscover the same facts about a code base again and again.
Giving tools agent output modes so they only print out the minimal info needed for an agent to get work done.
When I hear a company has an absurd AI spend I assume they aren't even trying to reign it in.
Agents swarming will 5x your usage, or worse.
The communication overhead of summarizing and status reporting between workers will eat up tokens faster than doing the work will.
Large monolith code bases with multiple layers of abstraction (Typescript to JSON schema, prisma, etc) will eat up more context than the actual work, by far. IMHO this same rule applies for human engineers as well, one of the reasons why I generally oppose too many layers of abstractions/middleware.
On large complex highly abstracted code bases, up to 90% of token usage will be input tokens.
Generally cached, generally cheaper, but not free.
The more you can constrain a problem (talking to black boxes with well defined contracts) the less the agent has to work.
So, you know, good software engineering principles in general.
Inefficient commands, for example I launched a bunch of agents for a task and for every command they'd first try it inside a sandbox, wait for the command to fail (sometimes that meant a timeout!) then retry outside the sandbox.
Now do that hundreds of times.
Or just crap like type checking the entire repo again and again.
If you have really tight rein on your agents you can prevent these sorts of issues, but you won't see these issues unless you are carefully monitoring what they are doing to the level of watching cli output scroll by.
Of course at some point the agent.md file needed to keep the stupid away gets so long that adherence drops.
You also end up with just stupid shit. I gave Sol too much free reign and it decided to update my DB schema to save stack traces to a DB.
Code which it then wrote a bunch of tests for. And then used a browser use agent to manually test.
They've been super useful to me when comparing datasets during a porting process.
But if they don't have that loop, then they make assumptions and build towers of madness on top of said assumptions.
Fundamentally if I am paying for these tokens, I should be able to see them but that's not where we are right now.
You don't understand! It's job security and a money-printer for contractors.
IPOs aren't the magical moment that they were in decades past. You get to answer to a bunch of retirement fund managers and "the market", meaning less-savvy retail investors. You have to open up your books.
It seems like Anthropic, OpenAI, etc. are doing an IPO because they are literally out of other options. Older IPOs like Facebook felt different, like the hard part had been done, and they just had to scale. There's a difference in selling something because you want to, versus selling something because you have to. Facebook was just relying on the idea that they were a platform that more people would inevitably sign up for. For the most part, they did. It seemed obvious. They likely could have continued on by simply operating privately, but the IPO gave them capital to dominate the market.
Anthropic and other hyperscalers cannot continue on privately. They're facing a systemic shortage of capital to achieve their goals. They need the infrastructure, and there's not enough capacity to make enough for all of these companies to survive.
This isn't new, rather it is a return to normal.
The cheap money days are likely over or rapidly diminishing. The next plot of cheap money to add to their pile, is public investors (if they hurry). They can raise $75-$100 billion that way, pushing their pile well over $200 billion. One assumes based on their obligations and expenditures projected over the coming 3-5 years, they'll need it.
Facebook were actually forced to IPO, because they had too many shareholders to remain private. They were super generous with allowing early employees to sell equity, and the laws required them to list once they passed 500 (i think) external shareholders.
This got changed in later legislation, which is part of the reason that companies like Stripe have been able to remain private for so much longer.
That being said, I agree with basically everything else in your comment, including the feelings around this.
LLMs (and Claude more specifically) are wonderful products, but I'm not convinced that they can justify their valuations over time.
They also kind of ("kind of" being the important clarifier here) can't optimize. See this is the trend with agentifying companies and the achilles heel for the frontier LLMs. We're starting to see diminishing returns on their capabilities, which means the rational enterprise is going to simply use the cheapest most efficient model for the task at hand. In turn we can just use an agent broker to decide which model is best and cost the least. Anthropic (today) has no incentive to do that other than to just use their own, best model for its own work.
Would love to take a look at it.
It’s not opportunity cost. It would be opportunity cost if their employees not using it would lead to additional revenue. However, if Inwas to go to Anthropic and double my token usage Anthropic wouldn’t decline my money. If Anthropic’s employees would stop using Claude, their revenues wouldn’t increase by an equivalent amount.
Their revenues are not currently supply constrained.
It’s just a cost cost. If their employees stopped using these services they would simply need less infrastructure, and therefore save on the cost to build and run that infrastructure. It wouldn’t translate into an increase in revenue.
I don’t agree. This is determined by elasticity of demand. If they have more compute to offer, that means they could offer higher subscription limits, more features like Duo to more people, better API pricing, and better enterprise contracts. This leads to some degree of increased consumption and more revenue. The degree is determined by how responsive customers are to pricing and features and performance. It’s not zero, so there is some amount that revenue would increase. We can debate the coefficient and the amount of compute we’re talking about here, but the premise is correct.
This is NOT the definition of opportunity cost. Please do not throw in random terms you don't understand. Opportunity cost is the value of the next best alternative you give up whenever you make a choice. WTF does it have to do with mis-classifying an expense?
Thats a problem since they will always pay a pemium for compute. The data centers owners can compete on price if they choose to.
That's API-list prices. They have an 80% margin over COGS.
Cost per equivalent output is dropping 10x every 18 months -> so in 3-ish years, if the trend continues, that will be $3k per employee.
Not bad. A lot of companies are already spending about that much or more on IT per employee.
Especially since that $3k bakes in an 80% margin. It's about $600 per year if you DIY at scale - which is about $50 per month - but at the $3k price, hardly anyone is going to.
In the West old-age dependency ratio (retirees per working-age adult) is climbing roughly 0.5 to 0.7 percentage points per year.
We've got to get 0.7% more productive for employees to keep the same quality of life (unless retirees get screwed, and since they vote and make up a huge portion of the voting block, I wouldn't count on that happening).
Further, more and more of the population has to transition into into elder care.
Unless we hit 3%+ GDP growth, us workers are probably going to see declines in quality of life (and we're probably not going to get those levels of growth)...
There's countless ways compensate for this gap, some of which are regulatory, others merely obvious (like the lack of a multi-trillion AI bubble in the future), the assumption that technological progress continues as modern levels (ie "same quality of life") with the changes that may entail. Ofc, the demographic shift (as you mentioned) changes what "quality of life" even means, making it even less deterministic.
> Unless we hit 3%+ GDP growth, us workers are probably going to see declines in quality of life (and we're probably not going to get those levels of growth)
The USA won't but Besset will claim that it did.
Google is in the business of buying compute and renting it out. To the extent that their internal use reduces revenues from that business, there is an opportunity cost.
Anthropic is not in that business.
In a similar way, internal employees would have also a "standard daily rate" like an external employee.
Anthropic isn’t booking it as GAAP revenue, they’re just using the number for marketing.
If Anthropic had revealed their internal cost, there comments would be complaining that they were hiding something and giving useless, unrelatable data.
The expenditure is most interesting when compared to retail rates, because that's the rate the rest of us have to compare against.
https://blog.pragmaticengineer.com/the-pulse-token-spend-bre... - "I talked with companies spending $5M+ per year on Claude which have received no discounts. If Anthropic offers discounts, it will likely be at a much higher tier."
https://www.theinformation.com/articles/anthropic-openai-fig... - "Anthropic’s discounts on its models can be around 15% off listed prices, according to managers from the three software firms that buy AI from both companies."
Plus my own personal conversations with a small number of people at medium to large sized companies who said that Anthropic's sales teams were hard to get discounts from.
Unless you managed to talk them into that, in which case, share your secrets!
Page 140 of https://www.sec.gov/Archives/edgar/data/2130357/000162828026...
I've learned enough that I am confident that enterprise companies pay a lot more for their tokens than $100/month subscribers, and that negotiated enterprise discounts don't change that fact in a meaningful way.
Those individual subscription plans you get as a consumer are not what their big enterprise customers are using.
Those plans are cheap so you, as an individual, can get familiar with the product and convince your company to get it at work. Your company pays the API prices to get enterprise features.
> Those individual subscription plans you get as a consumer are not what their big enterprise customers are using.
i am sure there are companies that push individual employees to get the cheaper individual subscriptions
The extremely discounted internal cost promote waste, so there is always a room for improving efficiency, but that too has a cost.
Plus electricity
As an example, as I understand it, if a hotel chain allows an employee to stay in one of their hotels for free when they go on vacation, the tax value of that benefit is what they would have charged someone for that hotel room, not how much it increased the hotel's costs to have one more hotel room full — which is generally almost nothing.
Of course, the IRS does agree with you when it comes to expenditures that are for the employer's benefit, rather than the employee's. If it didn't, almost all companies would have negative profits from the IRS's point of view.
If what you said was how taxation worked, a hand tool manufactuting company giving hammers they make for $1 and retailing for $2 to workers building a shed on their property would be increasing the workers' income tax bill by $2. Of course, in reality the workers get no income tax bill on the hammer given to them for work and the company can get a $1 tax writeoff from the opex of making the hammer.
They are not giving anything to employees for their personal use to use as they please, it is not part of their benefits whatsoever. It is work tooling, paid for by work. This is akin to Microsoft paying for Github or O365 for their staff. they can hardly put it in benefits, it has nothing to do with employee compensation or their taxable benefits.
OP is just using the benefits analogy as a comparison how IRS typically accounts for similar things when it is a benefit.
Employees staying at hotel for their personal vacation is a taxable benefit. Employees staying at a hotel as part of their job is a perk, and not considered a taxable benefit - A cruise ship can hardly say cost of cruise is now part of employee benefits (for tax it is not part of your comp) . They can of course market it as a "perk" to attract talent - same as the armed forces using cool extreme sport videos as an talent attraction tool. You can use in marketing yes, but it not part of your compensation.
Anthropic and other Frontier labs /Big Tech can definitely pitch token allowances as a selling point part of recruitment, but it cannot be counted as a taxable benefit - unless the employee can use it as they please outside work for any personal reason.
Suppose a company could transfer an asset to an employee and have its value set as the employer's cost. A company could make a bunch of volatile investments and see which ones pay off. Then the ones that go south get sold back into the market as a tax loss and the ones that do well get transferred as compensation to employees at the purchase price instead of the current value, reducing the tax liability of both the employer (no taxable gain) and the employee (less taxable income). What would happen if any employer could do that with any employee and any asset?
Conversely, there is a separate carve out for "employee discounts", which is essentially the employer offering its employees its own products for something in the neighborhood of its own cost. Why? It's not in any way a principled accounting distinction, it's because it's harder to use for tax avoidance at scale, because then a soap company can give its employees a discount on soap, but people only need a finite amount of soap and then the soap company can't use it for cars and real estate and stocks.
That's not how it works...The value would be the FMV at the time of the transfer to the employee. The cost basis would be the employer's cost. The income to the employee would be the net difference.
What would happen if any employer could do that with any employee and any asset?
They can't, because tax laws have addressed this situation for almost 100 years...
there is a separate carve out for "employee discounts", which is essentially the employer offering its employees its own products for something in the neighborhood of its own cost.
That carveout only applies to products being offered for the employee's own consumption unrelated to the needs of the business. Internal use of a company's own products for the needs of the business does not result in additional GAAP or tax deductions (meaning, if that product cost X to make/provide but they charge external customers Y, the only deduction is X, not Y).
I know that's not how it works, I'm explaining why they do it in a particular way because of what would happen if they did it the other way.
They did lose an insane amount of money last quarter versus revenue.
price they charge customers
No. I worked at an airline where the company typically charged itself higher than retail for tickets. At least, it was the highest fare type.
I worked at a media company - we had to pay top rates in order to buy our own ads for cross selling products.
Finally, I work at a SaaS company who heavily uses our own product. While we don't pay for it - just our cloud hosting bill - it's definitely a discussion point about how we should be a bit more mindful about usage.
Or has it broken out of its jail and taken over the board? Dario seems like a bit of a windbag anyways, AI can probably automate most of what he does these days.
both of those companies combined are smaller than the number of people microsoft is trying to buy out right now
All this news says is Company A uses internally the resource they sell externally at ($X) value. It's not saying how much it cost the company to generate said consumed resource
These are not mutually exclusive points, and I find it a common issue to get both sides to understand.
There's a lot to unpack about this statement.
Including the fact that it's probably not true.
If something is compensation, it can often be negotiated and traded off against other compensation components. How many people have successfully negotiated AI tokens away in favour of salary/bonus/stock? I'm going to guess "approximately zero".
I think almost all companies would laugh at you if you tried to reduce the number of tokens you can use for more salary. The tokens are stuff you can use to be productive at work, I expect that companies that take tokens seriously enough to mention them before you start wouldn't like that at all.
I haven't seen anyone treating AI tokens as employee compensation. If anyone can show me an article where employees were paying taxes on their token use at work, please share it.
Companies have been treating AI tokens as part of the cost of having employees, like the cost of their office or travel expenses.
True, though that phrase understates the author's problem a bit, as it is surrounded with more wrong-words, indicating it's a wrong-idea rather than a slip of the tongue.
As you note, it's closer to office/travel expenses. Employee computers, licenses for software on those computers, licenses for SaaS stuff, paying for bandwidth, etc.
Many companies used to brag about about how nice the laptop or office was as a way of convincing people to work there. Often in the same breath as compensation.
But compensation is only one component of cost.
So I think this guy is confused about what it costs to have an employee and what the employee gets out of it. Possibly intentionally.
It is like counting tolls as a component of "employee compensation" for a driver. An employer may decide to have a driver use toll roads, which may result in faster deliveries and more efficient use of his time. From the employer point of view, he is paying more to get more work done, from the driver point of view, he is paid the same for the same amount for time driving.
I guess kinda put you in a bubble a little, I wonder how the experience of Anthropic eng who left the company would look like, when such eng would go and spend few $K a day in non AI lab, would that be encourage/allowed/taken as example?
Given the speed at which Anthropic regularly pushes updates (eg their ridiculous app versioning that's in the thousands for v4 now) I doubt they're doing anything that looks like quality processes, even AI-integrated ones other than basic code review skills.
I imagine it's as much of a mess internally as it is with any other company whose execs are concerned more with bottom-line valuation rather than maintainability, extensibility, and sustainability. Just lots of spaghetti-at-the-wall hoping that something sticks long enough to drive up the IPO.
On the flip side, software I used that was majority built by 'real human engineers' coding by hand is utter garbage.
As a recent example, Facebook Ad Manager is extremely slow, plagued with UX issues, blatant state management problems (double scrollbars, iframes, random rerendering).
Other examples of 'real engineers' building software include SAP, Oracle ERPs, most banking software, most government websites. They're trash.
Human engineering is the reason your personal information gets leaked every other week. Human engineering is the reason there's a critical vulnerability in core software every day at this point.
The average software engineer cannot build good and secure software. Just like the average car driver is a safety disaster on the roads.
>I wonder how much dog shit has crept into their codebase by this point.
You'd think they'd know not to shit where they eat… ?
From what I remember they had a large regex to match “bad words”
Rather than using their AI to simply scan messages to flag.
Mythos at the highest thinking level is not the only product from Anthropic though.
Especially when I need to plan my next hike up Mount Shasta.
Would Anthropic themselves be paying this much if it was actually billed? It is not obvious.
Is Anthropic a good sample for AI use? Surely not, since they have special needs (dogfooding) and a vested interest in proving that AI usage is the future.
Can we compare their results pre and post AI usage? Close to definitionally impossible.
Are their employees good examples of AI-assisted engineers? Not really, as (one would hope) they're more well versed on the topic than an average eng.
The reality is that they are profitable in the normal sense
Even at companies that appear super bloated I don't think people are idle, its just that mantaining stuff is a lot of work, projects get cancelled, and, like you said they do a lot of specialty work for big clients.
That's in addition to running the big SaaS offering of the creative cloud and all of the other SaaS's (behance, adobe express, adobe stock, etc.).
All of those include software engineers, SRE, support staff, PMs, etc.. Then there's the massive amount of sales staff, go to market, etc.
There's also a lot of R&D and domain experts, stuff like Adobe Firefly? That was spun up in like a year apparently, probably continuing existing in-house research.
And I’m sure more than that. But there’s obviously plenty to work on, and they’re not at the point they can just Claude their way through it.
Claude for Teachers
Claude for Government
Claude for Financial Advisors
Claude for Clowns
Claude for OpenAI Employees
Claude for People Called Geoff Who Were Born In June
It's a long list.
The real question is what could they have done with open weight models on the same compute they’re renting. If the answer is “basically the same” then this flips the entire conversion back to what is Anthropic’s moat here.
This is the nature of managed anything. AI efficiency will improve but essentially this is what automation does.
Now spend 0.5x their salary on AI, and they become 5x productive compared to no AI.
Now spend 1.1x their salary on AI, and they become 20x productive compared to no AI.
It's still obviously worth it to spend the 1.1x. But it is truly remarkable that the biggest cost of hiring a knowledge worker is no longer their salary, but their AI usage.
There is no implication here that employees are being replaced by AI spend, as long as all of the productivity is generating profit. The AI usage still needs a knowledge worker to direct it in ways that it can't direct itself, so you still need the employees.
This is what I am getting at. If this were true - and I've yet to see evidence it is, despite some anecdotal evidence (organizationally, IME, it's about 2-3x for power users, and probably a net loss of productivity in certain areas) - why would their headcount be growing so much still YoY, pretty much doubling every year. If the AI is 10-20xing why such a big jump in headcount? Yes, the numbers are shiny, the growth is apparent, I would just expect with this AI narrative they'd be "doing more with less" as this thing improves every year.
> The AI usage still needs a knowledge worker to direct it in ways that it can't direct itself, so you still need the employees.
This is the story AI sells though, and Anthropic has participated in it heavily. Yet, their interview process requires hard skills and doesn't let you use AI, so clearly, what you're saying is correct, it just doesn't really align in my head with the whole knowledge worker being replaced narrative.
But it's also true that when I'm working on 2 things at once, the bottleneck is me. I'm spending all my time giving Claude direction that it can't give itself.
So you basically have to separate out the tasks where AI can produce a 20x productivity boost, and the stuff where it can't help at all.
There's still so much stuff where it can't help at all, you need real human employees for that. That's why Anthropic is continuing to hire at breakneck pace.
And that's what I'm saying -- knowledge workers aren't being replaced. They're just accomplishing tons more work, and companies aren't running out of work to do.
I was recently involved in a case like this - we had a critical part of our system based on a dependency that's no longer maintained. Previously, we would have just carried on for a year or more, living with the limitations until it was much closer to being entirely untenable, because rewriting the code in question would have been a multi-month project involving multiple developers, QA, and management time. But now, the code in question was migrated in a few days using AI, along with a suite of new tests in addition to our existing ones, that gave us a lot of confidence in the results. The productivity improvement here is at least on the order of 25x, possibly higher.
But most developers aren't sitting at their desks operating at a 25x pace all day, every day, so average productivity improvement is going to be lower. And of course, some use of AI will be suboptimal or problematic: waste due to e.g. duplicate development which happens when development is so easy, or costs for cleanup of mistakes.
We also now have a slew of AI-generated internal tools, most of which would never have been developed before. Many of them are very useful, the kind of thing that's on your eternal wishlist but never gets done. Some are kinda useless, so represent wasted resources. It's difficult to measure the productivity benefit of all this, because you'd have to compare it to the non-existent company without those tools.
Ultimately, measuring all this meaningfully is not really that feasible, except perhaps over the long term. Managers operate on vibes with this kind of thing because in many cases, that's all you can really do.
That wouldn't really be an expected outcome for a company like Anthropic. They need to do the maximum they can with the funding they have, or risk losing out to competitors who don't take their foot off the gas.
And the product now iterate 2 times faster with 10 times more bugs and customers are pissed.
Looking at you Apple: https://aperocky.com/blog/post.html?slug=apple-watch-sucks
So we're back to square one, and your productivity increase has a ceiling that's much lower than 5x, let alone 20x. There's a limit on how many things one can keep track of, how many code changes one can reason about.
That doesn't mean it's "much lower than 5x."
Making sure Claude doesn't kill everyone on Earth, if they are to be believed.
I doubt they are bringing that much value to the company for whatever work is done with that much token.
So it exceeds employee pay if you discount the vast majority of employee pay.
Correlation does not equal causation?
By giving hundreds of workers each a powerful desk-sized Alto minicomputer for their own needs, with a high-end graphical display, they gained insight into what desktop personal computing would look like 15 years later, enough insight to shape it profoundly. It's been 55 years, and although multitouch screens are proliferating, I'm still typing this on a keyboard hooked up to a framebuffer-driven display with a mouse hooked up to it, displaying hypertext, festooned with windows, icons, and a mouse that moves an onscreen pointer at the same 135° angle they settled on 55 years ago, positioning a vertical line to indicate the insertion point, with scrollbars. The display has twice as many pixels, the pixels are color, the mouse pointer is white rather than black, the screen is a flat LCD, the scrollbars are on the right, and the cursor blinks, but it's very recognizably descended from https://smalltalkzoo.computerhistory.org/HOPL-St78.html rather than, for example, ITS or GENESYS.
Only people with the luxury of unlimited zero-cost CPU cycles had a chance of seeing what the future looked like, and that allowed them to find out what worked and what didn't work in that environment. Nowadays, the regular workers who don't have the luxury of unlimited zero-cost tokens are manually reviewing voluminous AI code, because, even though that's a lot of slow work, they're still much faster programming that way than they were without it. Anthropic, instead, is doing insane things like eliciting a billion lines of Lean proofs to show that existing open-source libraries can't fail their OSS-FUZZ tests — and fixing all the bugs that effort turned up, in the process.
I don't think it's accurate that "almost all the money in personal computing was made in mobile". Quite a bit of money was made in personal computing before the iPhone, and quite a bit of money has been made in non-mobile computing since the iPhone.
I also don't think it's accurate that mobile "didn't use any of these ideas". Android's UI is not quite as close to Smalltalk-78 as what I'm using right now, but you still have pointers, scrollbars, text selections, proportional fonts, vertical-line cursors, buttons, menus, object-oriented programming, sometimes a bytecode interpreter, and even windows. You just don't have as much freedom with where you position the windows. Android's UI is still a lot closer to Smalltalk-78 than it is to, for example, acme, GENESYS, the ITS HACTRN, FORTH, or PDP-11 Unix.
I know there's a point where companies get big enough, and Anthropic forces them over to the API, but presumably such companies negotiate heavy discounts instead of eating the 200x overnight price hike.
It’s not weird once you think about it. Money doesn’t create an operator. But operators can be cheaper than tools and often are.
I'm sure in several US-based companies, non-US workers AI spending is already beyond their own cash comp.
Under the heading "Claude is Accelerating Our Ability to Close the Loop":
> The expansion of our own use of Claude reflects this leverage directly. The value of our own internal Claude usage at list prices has grown by over 250 times from January 2026 to September 2026, and in April 2026, this monthly value first exceeded our monthly personnel expense, excluding stock-based compensation. Because each version of Claude is used to help build the next and because Claude makes our teams more productive across the company, we believe the compute we devote to internal usage compounds these gains, continuously accelerating our pace of development and further strengthening our leadership position.
Actually I don't believe their statement is true, they must use it much much more.
Recently I read about a company (nameless for reasons that will become clear) that was giving a small team unlimited tokens to work on a very ambitious project. (IE, they'll probably spend a few million on tokens.)
Here's the thing: I once worked with the (nameless) exec who was named and interviewed in the article. (And I have a significant amount of respect for this exec.) The problem is, the exec (when I worked with them) significantly misinterpreted the mobile trend and nearly killed the company jumping on the mobile bandwagon. (We had a desktop product that only needed a simple companion mobile app. This was painfully obvious at the time.) This exec is blindly jumping on another bandwagon again, wasting money that might be better spent elsewhere.
Why do I say this? I question if a lot of big AI spenders are really getting value from what they're doing with AI, or is it just for show?