>There's an important distinction here. Anthropic isn't actually spending more cash on AI than salaries. It's valuing its internal AI consumption at retail prices.
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.
> Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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.
I don't buy it. A company like Anthropic is not going to just walk away from revenue. If external demand were really that high, then they should take the money first. And not just for the revenue; customer demand being that high is also an indication that the product is already great as-is so they stand to improve their bottom line by easing off on the R&D spend.
They are making a deliberate trade-off decision
token use for their own
vs
token use for the rest of the world.
while Google is making the opposite bet
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.
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
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.
It’s supply constrained for now, the moment companies like Anthropic have to switch to profit-making-mode, demand will dip as the prices skyrocket imo.
>> the moment companies like Anthropic have to switch to profit-making-mode, demand will dip as the prices skyrocket imo.
Yep. I bought a $20 per month Claude subscription last week. As I was using it last night I saw some tags in the log with prices at $36.xx and slowly rising. After asking and searching I got convinced that those are equivalent prices for API access at full price and Im not getting billed. As soon as $20 per month goes to $30+ per week I will change my behavior to lower it, up to canceling if it won't come down enough.
Unfortunately I keep thinking of more uses for it. Fortunately I don't need to do any of them.
It's complete bologna. Basic GAAP accounting eliminates intra-company service consumption/sales. Looking at cloud compute, say, Amazon "bills" departments for AWS cloud compute consumption, but reporting internal cloud compute consumption as a thing they were doing assuming the rates charged to their least efficient customer would be beyond meaningless.
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.
> 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.
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.
It depends on your assumptions. When Google is in "space crunch" mode, there are opportunity costs. Otherwise, there aren't, because you could do both.
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.
> Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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)...
So every business should measure any client fungible resource that way? Should a bank put a revenue number to any capital held in excess of regulatory requirements, for example?
Excess capacity sitting idle is the cardinal sin in modern economy.
I was merely pushing back at the insinuation that internal costs should be used to measure internal resource use.
No. The costs should always be external market price because that's where you are making the correct trade-offs.
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.
There is a huge difference between Anthropic and Google dog-fooding: Anthropic does not own or build data centers, they rent (as far as all the reporting on this I've read). Anthropic employees dog-fooding with Claude tools isn't "internal", its most likely being run on external AI data center compute, which they have to pay for, there's just no margin on it. It might even be run out of Google's data centers.
They also offer $300,000 in compute spend (allegedly) for $200 a month to anyone who isn't employed by a large corporation so their pricing should be taken with a grain of salt.
> If you use 100% of the quota every week it's closer to $2000 at API rates.
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.
> 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.
$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.
I get a LOT of mileage out of my $20 plan. It's at least $500+ a week at API rates. I sometimes wonder if there's something wrong with their billing system.
On the $200* consumer plan, according to "npx ccusage", I'm using $11,000 per month at API rates. Possibly significantly more, because I was previously using the $100 plan so that only reflects about 1 week of the $200 plan.
It's not just the LLM costs, to keep your agents busy you need to move them of your workstation onto a server/cloud. I currently have about 16 claude code agents working on different bugs, uses so much resources that my macbook pro m5 max becomes slow to respond. Using cloud session would free up my macbook for other work.
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.
I'm impressed you have a workflow that can keep 16 separate agents fed without the whole thing collapsing into nonsense. Even running full agent teams I can't think of ways to do that without being intentionally inefficient
I let one agent categorize all bugs, then have it decide which clusters of bugs should be addressed together, and which ones can be addressed in parallel.
6 years ago i had a lenovo thinkpad p1, branded by lenovo as a portable workstation. Today i have macbook pro m5 max, much faster and more powerful than the lenovo, so why not call it a workstation?
Technically it is... According the original vision for workstation, a computer with >1MB RAM, >1 megapixel of screen resolution, >1 MIPS and costing under 1 Mega cents (10K dollars).
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?
If it were opportunity cost, that would imply that Anthropic can't sell as many tokens as people want to buy. But as far as I can tell, there aren't any "token shortages," at least at API prices. Or is there a maximum per-customer limit that I'm not aware of?
Plenty of companies use retail/wholesale pricing internally to make sure a business unit doesn’t appear profitable just because it’s being subsidized by the one providing the resources. Plenty also have to have arm’s length pricing for legal reasons.
Anthropic isn’t booking it as GAAP revenue, they’re just using the number for marketing.
That's not really true. Measuring the equivalent retail cost of the usage is the only way to put it in a relatable perspective.
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.
Most "enterprise" companies are paying full API costs. The subscription deals are only available to consumers. If you want enterprise levels of control over how your staff are using the models you need to pay up.
Not even close. "enterprise" companies are negotiating contracts. Call it pre-provisioned capacity, wholesale pricing, etc. Same is true for AWS, Azure, Salesforce, or literally any SaaS provider ever. There is a reason literally every single pricing page for any SaaS provider has an "Enterprise? call us" column.
From what I've heard those enterprise negotiated discounts for Anthropic tend to be in the 15-30% range, which isn't anywhere near the deal you could get from using the $100/ or $200/ or $500/month subscriptions.
Most of their revenue comes from customers pay API pricing.
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.
Big companies actually are paying published API rates, Anthropic and OpenAI models are desirable enough that there is very little wiggle room to negotiate. It's their way or the high way. Same with things like "safety" filters and (for Fable) mandatory data retention.
It might be difficult to value because datacenters have high fixed costs and upfront investment and low marginal costs. If I spend 1B building a datacenter and 10M/month to run it (assume this varies negligibly with usage) and on average 25% of it goes to internal use and 70% to customer inference and 5% idle, should I charge 25% of it to internal use even though the marginal cost is lower because internal workflows are predictable and can be scheduled during off peak hours?
With that being said I agree it's wrong to value it at the retail price (unless they are supply constrained) and this is probably for marketing purposes.
In the US, the IRS doesn't see it that way, at least when it comes to fringe benefits as a part of employee compensation. https://www.irs.gov/businesses/small-businesses-self-employe... says, "In general, the amount the employer must include is the amount by which the fair market value of the benefits is more than the sum of what the employee paid for it plus any amount that the law excludes."
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.
Not an apt comparison. You are conflating the opex of the company with taxable benefits.
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.
IRS rules should never be used as an example of how accounting "should" work. They're full of politics and the implications of the rules on tax avoidance.
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.
Suppose a company could transfer an asset to an employee and have its value set as the employer's cost.
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).
Microsoft basically does the same with internal Azure services? When I was there our budget/usage was based on and consumed at the consumer price for GPUs and other compute. What happened behind the scenes really I have no knowledge.
Not true. Azure has a very different internal pricing. You can often get a glimpse of it if you have a.. particularly enterprising TAM. What happens sometimes (Like now when compute/GPUs are in high demand) is finance department would calculate the opportunity cost on allocating those resources internally vs selling them externally. The calculation isn't even always straight forward. What is the opportunity cost of using compute for internal CI or company operations vs selling them externally? It's not a straightforward equation and you would have to adjust the scale often depending on how clogged your internal processes get.
The extremely discounted internal cost promote waste, so there is always a room for improving efficiency, but that too has a cost.
Actually I think it's very informational. For every other company, working on the cutting edge of technology, paying for intelligence at retail prices, means you are now paying more for AI than you are employees. That $ could have been spent on 2x the employees, however that's not as useful as 50% AI / 50% humans, and indicative of where we are headed.
>means you are now paying more for AI than you are employees.
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.
Anthropic is full of the smartest talent and a bellwether for how the rest of the service industry will work. Just as cutting edge companies of the past, like 2005-2020 Google's use of computers and software were indicative of the software every other service company was going to be using, lest they turn into an old fashioned uncompetitive dinosaur.
Yes service industry is quite broad, is white collar work more clear in general?
Yes, it is quite obviously apparent that law firms are and will be using lots of token-based intelligence. They won't be using the same tokens at the same time as an A.I. lab. However, the best law firms of 2029 will be using approximately the same tokens per employee as an A.I. lab of 2026, that much is clear.
> . However, the best law firms of 2029 will be using approximately the same tokens per employee as an A.I. lab of 2026, that much is clear.
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.
Do they actually book the revenue against themselves?
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?
It's kind of expected, no? If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level. And if I am not being metered, I'd probably do more stuff that I know are likely low yield since I am not worried about a quota. This would probably take my "API-equivalent" usage beyond the average salary in far less than a month.
I wonder how much dog shit has crept into their codebase by this point. Another company might dogfood their product but Anthropic is so heavily marketing oriented, I doubt this is driven by the desire to improve the product as much as it is by the desire to pad out usage numbers and create shareable stories. No matter the consequences. I bet $1 it sucks to be a good engineer in their software effort.
I'm personally really not impressed by their software quality, at least we know from their experience that infinite tokens at the best model available still doesn't replace good engineering.
It doesn't replace MBA-brained bad roadmapping. Good engineering is determined more by the processes you have in place for catching something that breaks bad. The system produces good code - singular 'good' developers are great but if they're not socializing what makes them good then it's just competency. Great engineers teach and mentor and advocate for capacity dedicated to testing and health-checks.
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.
I find Claude to be exceptionally well-designed software that almost never has notable issues.
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.
> If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level.
Mythos at the highest thinking level is not the only product from Anthropic though.
True. I was reacting to the article mentioning that April was when the usage exceeded salaries. Mythos was released in restricted preview through Glasswing in early April, and I presume was available internally for at least a few weeks before that, which helped tip the numbers.
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?
I'm not really sure I understand the excitement around this. It seems like the implication is that if retail price > employee salary, you are replacing employees with AI spend? Yet, anthropic's head count has nearly doubled since last year - so, in a company where nearly half of that head count is engineers, but claude is "writing 90% of the code," what is everyone doing then? You would think, if the hype feeling around this held true, that the output would be going up and costs remaining stable. Costs rising as you scale is not a new thing but that's not really what AI promises. It sounds to me like the retail AI spend per employee is very high. What is the appeal of that?
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.
> 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.
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.
> I would just expect with this AI narrative they'd be "doing more with less" as this thing improves every year.
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.
I mean, just what I did this morning with Claude would have taken me 2 weeks on my own. So 20x is pretty reasonable for certain types of engineering.
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.
Sorry, I know this is the story, but am I expected to believe that Anthropic would need 20,000+ engineers in their org without their use of AI? I do not believe that is close to true.
No, one thing that would happen is that many projects would never be undertaken - basically, there's latent demand for software that would simply go unmet, because of resource constraints.
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.
Yes, one can quite easily make quite fantastic numbers fall out of simply applying arithmetic and not dealing with messy propositions like grounding those numbers in any kind of real world outcome.
> In March, I wrote about a new trend: Tech companies are starting to treat AI tokens (the main way to measure usage) as a fourth component of employee compensation, alongside salary, bonuses, and stock awards.
Until employees can use those AI tokens for personal projects, it's not compensation. Rather, it's just a cost of doing business, like laptops, office space, or testing servers.
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".
Is that really true? At least at large companies, the components are not usually fungible in my experience. At startups or smaller companies I'm sure it's a lot more flexible.
Yea they used the wrong word and it felt like rage bait. AI tokens you use for your job given by your employer is not compensation. Hell money isn't even compensation in many cases, it all depends on the context. The author needs use AI to help them rework that sentence or open a dictionary
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.
It's certainly a cost of having an employee, along with salary and benefits. But employee costs also include things like laptops, electricity, internet, management, support staff, and possibly office space. Tokens are much more like the latter than the former.
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.
I can see where there might be a truth to it. My company offers a fairly generous monthly token budget. If I were evaluating an offer from another company, but they offered a lower monthly budget, it would definitely influence my decision, all else being equal. It's not compensation, but it does affect my day-to-day experience at work.
Everyone is saying it is expected, and I agree, but it’s also clear that employees of AI companies spending unlimited zero-cost tokens in their day-to-day work is resulting in products that aren’t usable by the vast majority of regular workers who don’t have this luxury. Dogfooding your product is good but you should also use it with the same constraints that you place on your users, otherwise what signals are you really getting?
They're dogfooding the way Xerox PARC was dogfooding in the 01970s.
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.
They aren’t usable? I’ve been using them a bunch and have been having good results. Dogfooding is always good, but I don’t think there’s some kind of major problem here.
Dumb question, what most engs at Anthropic work on? It doesn't seem like release some large new products all the time while they have quite a few of engs. What are the major branches of work besides LLM research? I guess there is a lot of infra stuff to support the scale of operation, just supporting API and TUI shouldn't be that demanding I guess.
I'd guess they have a lot of internally facing tooling for monitoring, one-shot eval to catch people prompting bad things, etc. That stuff can probably be yolo'd and it just annoys the internal teams using it.
I'm kinda curious about this too. But then I'm always amazed at the enormous workforces these tech companies have, and I'm sure they cut them as thin as they can. Like adobe has 30,000 employees & some blogger estimated that 1/3rd of their workers are actually working on their software. I use their software sometimes and I really haven't noticed many changes to it over the years, except recently with the ai stuff. Like from 2015-2020 I can't think of any major things they added to adobe illustrator. I guess making and maintaining software is hard.
I fully agree most big tech companies are pretty bloated. But FWIW a lot of my time at SaaS companies, especially in the B2B space, was spend working on features for larger customers that most others would never use or even see. Like, yeah, product X isn't that complex, but $BigCorp wants to use it in their private cloud, or needs it to be single tenant, or needs these audits done, or want their $Gov client to use it. Now you have a ton of work for zero visible changes.
- Cross-platform desktop apps
- Cross-platform mobile apps
- Claude Code TUI
- Product-specific verticals like Claude Design
- Corporate marketing website
- APIs
- Writing technical documentation for APIs
- Enterprise support
- And what must be a massive infra team to run training and inference at scale in a heterogeneous cloud environment
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.
Does anyone pay retail API pricing to Anthropic at scale? The last time I checked, I was burning > "$10K" per week with my $200/month subscription.
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.
There are many internal developers at $dayjob (where core products are not based on AI) that spend over a thousand dollars every day on average, which is likely higher than their salary.
I doubt they are bringing that much value to the company for whatever work is done with that much token.
that's crazy: in my experiments (and experience) i can get ~ 90% the quality of the most expensive settings on frontier models for far far less than 90% of the cost by changing settings down.
Are you kidding? Did you not see Anthropic's S1 filing? Never has so much value (in dollars) been created by a company in such a short time in the history of humanity. I'm not sure how your takeaway from that is "don't do this".
I’m not sure what this “stat” tells us other than Anthropic is dogfooding its own tech. Which is kinda expected.
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.
I mean, they probably could not have done most of it with open models. Again, a lot of this isn't going to standard software development, at least I would assume but instead to SOTA model development and RSI.
Note, this doesn't include options or stock benefits. That's a huge part of actual compensation for engineers at this level even if it's on a different balance sheet.
Regardless of one's opinions about future AI usage, I'm not sure this metric says anything at all.
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.
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.
> Anthropic's numbers show why. More than 90% of the code added to its software in September was written by Claude. Meanwhile, revenue has grown vastly faster than headcount.
ummm yes, they have to dogfood it... this is that lucky area of the venn diagram where you have to do it, measure it an act on it... because improves the bottom end and the product.
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
to spell it out: the implicit claim is "ai companies think ai is a scam, as evidenced by them using humans instead of ai", and I believe the huge internal ai use is evidence to the contrary
Anthropic 10x'd its employees over the past 3 years. Shouldn't it be cutting employees if that's the case? Especially because they probably have access to more powerful models which aren't released to the public yet, probably with fewer restrictions, and don't need to pay the markup for using their own service?
I will keep assuming any news coming from AI companies are a type of corporate propaganda, and that AI companies frequently use their millions of dollars of marketing money to create a narrative to maximize hype and make money.
Recursive self-improvement is just around the corner. Any day now they'll be laying off all their employees as their god-like AI makes investors trillions of dollars. /s
You shouldn't be getting downvoted, people should be concerned that a company that's about to hit the valuation that it's at is not exploding in junior hiring and expanding their workforce like prior companies
>There's an important distinction here. Anthropic isn't actually spending more cash on AI than salaries. It's valuing its internal AI consumption at retail prices.
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.
No. This is opportunity cost.
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
> Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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.
are there any other trivial changes you'd care to share that can reduce token usage?
I don't buy it. A company like Anthropic is not going to just walk away from revenue. If external demand were really that high, then they should take the money first. And not just for the revenue; customer demand being that high is also an indication that the product is already great as-is so they stand to improve their bottom line by easing off on the R&D spend.
They are making a deliberate trade-off decision token use for their own vs token use for the rest of the world. while Google is making the opposite bet
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.
> by easing off on the R&D spend
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
Anthropic has a ton of great things ahead of them.
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.
Revenue growth is slowing..
> If external demand were really that high, then they should take the money first
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?
> AI infrastructure is supply constrained
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.
No. Applying your own logic you got this wrong
It’s supply constrained for now, the moment companies like Anthropic have to switch to profit-making-mode, demand will dip as the prices skyrocket imo.
>> the moment companies like Anthropic have to switch to profit-making-mode, demand will dip as the prices skyrocket imo.
Yep. I bought a $20 per month Claude subscription last week. As I was using it last night I saw some tags in the log with prices at $36.xx and slowly rising. After asking and searching I got convinced that those are equivalent prices for API access at full price and Im not getting billed. As soon as $20 per month goes to $30+ per week I will change my behavior to lower it, up to canceling if it won't come down enough.
Unfortunately I keep thinking of more uses for it. Fortunately I don't need to do any of them.
Not if you’re desperately trying to stay ahead of AI frontier pack.
It's complete bologna. Basic GAAP accounting eliminates intra-company service consumption/sales. Looking at cloud compute, say, Amazon "bills" departments for AWS cloud compute consumption, but reporting internal cloud compute consumption as a thing they were doing assuming the rates charged to their least efficient customer would be beyond meaningless.
> No. This is opportunity cost.
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.
> 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.
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.
lol no. The poster above you was correct.
It depends on your assumptions. When Google is in "space crunch" mode, there are opportunity costs. Otherwise, there aren't, because you could do both.
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.
aka Cobblers children have no shoes. Anthropic profit less by selling it.
> Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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)...
So every business should measure any client fungible resource that way? Should a bank put a revenue number to any capital held in excess of regulatory requirements, for example?
Excess capacity sitting idle is the cardinal sin in modern economy. I was merely pushing back at the insinuation that internal costs should be used to measure internal resource use. No. The costs should always be external market price because that's where you are making the correct trade-offs.
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.
There is a huge difference between Anthropic and Google dog-fooding: Anthropic does not own or build data centers, they rent (as far as all the reporting on this I've read). Anthropic employees dog-fooding with Claude tools isn't "internal", its most likely being run on external AI data center compute, which they have to pay for, there's just no margin on it. It might even be run out of Google's data centers.
>> Anthropic does not own or build data centers, they rent
Thats a problem since they will always pay a pemium for compute. The data centers owners can compete on price if they choose to.
They also offer $300,000 in compute spend (allegedly) for $200 a month to anyone who isn't employed by a large corporation so their pricing should be taken with a grain of salt.
>$300,000 in compute spend (allegedly)
source? The most optimistic calculations don't come anywhere close to that.
https://x.com/SemiAnalysis_/status/2064815044085318040
Usage allowances have decreased since that analysis. Also the 20X plan became the 10X plan (cut in half).
It was never 20x, that was just 5 hour usage limits. There's a class action on this...
Are you talking about their $200 consumer plan? If you use 100% of the quota every week it's closer to $2000 at API rates.
They have never claimed that the API rates are the "real cost" of the compute spend.
> If you use 100% of the quota every week it's closer to $2000 at API rates.
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.
> 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.
$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.
> $200 of usage on a $20/mo plan is a 10X multiplier. […] So $200 * 10X = $2000/month. I don't know how you got to $8000.
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.
I get a LOT of mileage out of my $20 plan. It's at least $500+ a week at API rates. I sometimes wonder if there's something wrong with their billing system.
On the $200* consumer plan, according to "npx ccusage", I'm using $11,000 per month at API rates. Possibly significantly more, because I was previously using the $100 plan so that only reflects about 1 week of the $200 plan.
I was spending thousands of dollars a day in funny money (free promotional tokens from VCs) before switching to a paid subscription for convenience.
i don't understand why so many people on this site comment on issues they clearly do not know anything about
Obvious bullshit that's been disproven many times already.
The price is the price, everything else is bullshit.
> Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
You have confused necessary and sufficient.
> So, every compute Deepmind and Googlers get is lost revenue opportunity and must be measured as such
Maybe, but it also reduces supply that can drive up prices
> Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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.
It's not just the LLM costs, to keep your agents busy you need to move them of your workstation onto a server/cloud. I currently have about 16 claude code agents working on different bugs, uses so much resources that my macbook pro m5 max becomes slow to respond. Using cloud session would free up my macbook for other work.
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.
I'm impressed you have a workflow that can keep 16 separate agents fed without the whole thing collapsing into nonsense. Even running full agent teams I can't think of ways to do that without being intentionally inefficient
I let one agent categorize all bugs, then have it decide which clusters of bugs should be addressed together, and which ones can be addressed in parallel.
Then all the other agents get to write more bugs.
You call your laptop "workstation"?
6 years ago i had a lenovo thinkpad p1, branded by lenovo as a portable workstation. Today i have macbook pro m5 max, much faster and more powerful than the lenovo, so why not call it a workstation?
Technically it is... According the original vision for workstation, a computer with >1MB RAM, >1 megapixel of screen resolution, >1 MIPS and costing under 1 Mega cents (10K dollars).
However, so is my phone!
https://en.wikipedia.org/wiki/3M_computer
just get a mac mini headless
Wouldn't that depend on how much hardware you have to run them on, too?
Not really- since they have an internal view of low and high usage times of the day, they can optimize differently.
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.
> No. This is opportunity cost.
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?
By 'operate at Anthropic level', you mean terrible reliability and availability, and terrible efficiency right?
If it were opportunity cost, that would imply that Anthropic can't sell as many tokens as people want to buy. But as far as I can tell, there aren't any "token shortages," at least at API prices. Or is there a maximum per-customer limit that I'm not aware of?
Plenty of companies use retail/wholesale pricing internally to make sure a business unit doesn’t appear profitable just because it’s being subsidized by the one providing the resources. Plenty also have to have arm’s length pricing for legal reasons.
Anthropic isn’t booking it as GAAP revenue, they’re just using the number for marketing.
My understanding is most use a cost + figure and not retail. Do you know of any that use retail?
That's not really true. Measuring the equivalent retail cost of the usage is the only way to put it in a relatable perspective.
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.
What's is the 'retail cost'? Because nobody (except total idiots) is actually paying their published API pricing.
Most "enterprise" companies are paying full API costs. The subscription deals are only available to consumers. If you want enterprise levels of control over how your staff are using the models you need to pay up.
Not even close. "enterprise" companies are negotiating contracts. Call it pre-provisioned capacity, wholesale pricing, etc. Same is true for AWS, Azure, Salesforce, or literally any SaaS provider ever. There is a reason literally every single pricing page for any SaaS provider has an "Enterprise? call us" column.
The enterprise discounts are not as extreme as the personal subscriptions.
Unless you managed to talk them into that, in which case, share your secrets!
From what I've heard those enterprise negotiated discounts for Anthropic tend to be in the 15-30% range, which isn't anywhere near the deal you could get from using the $100/ or $200/ or $500/month subscriptions.
Most of their revenue comes from customers pay API pricing.
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.
Big companies actually are paying published API rates, Anthropic and OpenAI models are desirable enough that there is very little wiggle room to negotiate. It's their way or the high way. Same with things like "safety" filters and (for Fable) mandatory data retention.
It might be difficult to value because datacenters have high fixed costs and upfront investment and low marginal costs. If I spend 1B building a datacenter and 10M/month to run it (assume this varies negligibly with usage) and on average 25% of it goes to internal use and 70% to customer inference and 5% idle, should I charge 25% of it to internal use even though the marginal cost is lower because internal workflows are predictable and can be scheduled during off peak hours? With that being said I agree it's wrong to value it at the retail price (unless they are supply constrained) and this is probably for marketing purposes.
In the US, the IRS doesn't see it that way, at least when it comes to fringe benefits as a part of employee compensation. https://www.irs.gov/businesses/small-businesses-self-employe... says, "In general, the amount the employer must include is the amount by which the fair market value of the benefits is more than the sum of what the employee paid for it plus any amount that the law excludes."
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.
Not an apt comparison. You are conflating the opex of the company with taxable benefits.
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.
IRS rules should never be used as an example of how accounting "should" work. They're full of politics and the implications of the rules on tax avoidance.
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.
Suppose a company could transfer an asset to an employee and have its value set as the employer's cost.
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 think it's usually cost +, but yeah, I don't know of another company offhand that sells the services at RETAIL.
I’ve worked at and with large orgs - it’s absolutely standard practice for BUs to bill other BUs at “retail” or at the very least a commercial rate.
Microsoft basically does the same with internal Azure services? When I was there our budget/usage was based on and consumed at the consumer price for GPUs and other compute. What happened behind the scenes really I have no knowledge.
Not true. Azure has a very different internal pricing. You can often get a glimpse of it if you have a.. particularly enterprising TAM. What happens sometimes (Like now when compute/GPUs are in high demand) is finance department would calculate the opportunity cost on allocating those resources internally vs selling them externally. The calculation isn't even always straight forward. What is the opportunity cost of using compute for internal CI or company operations vs selling them externally? It's not a straightforward equation and you would have to adjust the scale often depending on how clogged your internal processes get.
The extremely discounted internal cost promote waste, so there is always a room for improving efficiency, but that too has a cost.
In a lot of companies, you would get charges back on usage/license/cost and this can get even funnier in NGOs.
In a similar way, internal employees would have also a "standard daily rate" like an external employee.
> You blow $50k a year on servers running your LLMs? It cost you $50k.
Plus electricity
Seems entirely in line with Hollywood-style practices.
Actually I think it's very informational. For every other company, working on the cutting edge of technology, paying for intelligence at retail prices, means you are now paying more for AI than you are employees. That $ could have been spent on 2x the employees, however that's not as useful as 50% AI / 50% humans, and indicative of where we are headed.
>means you are now paying more for AI than you are employees.
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.
Anthropic's use of AI in no way translates or represents any other companies' use of AI, so your apparent extrapolation makes no sense.
Anthropic is full of the smartest talent and a bellwether for how the rest of the service industry will work. Just as cutting edge companies of the past, like 2005-2020 Google's use of computers and software were indicative of the software every other service company was going to be using, lest they turn into an old fashioned uncompetitive dinosaur.
Wikipedia tells me that "service industry" is a term that includes transportation companies and law firms.
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.
Yes service industry is quite broad, is white collar work more clear in general? Yes, it is quite obviously apparent that law firms are and will be using lots of token-based intelligence. They won't be using the same tokens at the same time as an A.I. lab. However, the best law firms of 2029 will be using approximately the same tokens per employee as an A.I. lab of 2026, that much is clear.
> . However, the best law firms of 2029 will be using approximately the same tokens per employee as an A.I. lab of 2026, that much is clear.
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.
You still pay input tokens for Jev. "Should I crash this train, YES/NO?"
Do they actually book the revenue against themselves?
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)
It's kind of expected, no? If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level. And if I am not being metered, I'd probably do more stuff that I know are likely low yield since I am not worried about a quota. This would probably take my "API-equivalent" usage beyond the average salary in far less than a month.
I wonder how much dog shit has crept into their codebase by this point. Another company might dogfood their product but Anthropic is so heavily marketing oriented, I doubt this is driven by the desire to improve the product as much as it is by the desire to pad out usage numbers and create shareable stories. No matter the consequences. I bet $1 it sucks to be a good engineer in their software effort.
>>If I was an Anthropic employee expected to dog-food the product…
>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… ?
I'm personally really not impressed by their software quality, at least we know from their experience that infinite tokens at the best model available still doesn't replace good engineering.
It doesn't replace MBA-brained bad roadmapping. Good engineering is determined more by the processes you have in place for catching something that breaks bad. The system produces good code - singular 'good' developers are great but if they're not socializing what makes them good then it's just competency. Great engineers teach and mentor and advocate for capacity dedicated to testing and health-checks.
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.
I find Claude to be exceptionally well-designed software that almost never has notable issues.
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.
My fist reaction to this post was "why so little?". I very much expected the number to be higher.
> If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level.
Mythos at the highest thinking level is not the only product from Anthropic though.
True. I was reacting to the article mentioning that April was when the usage exceeded salaries. Mythos was released in restricted preview through Glasswing in early April, and I presume was available internally for at least a few weeks before that, which helped tip the numbers.
> employee expected to dog-food
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?
> I'd probably be using Mythos all the time at the highest thinking level.
Especially when I need to plan my next hike up Mount Shasta.
I'm not really sure I understand the excitement around this. It seems like the implication is that if retail price > employee salary, you are replacing employees with AI spend? Yet, anthropic's head count has nearly doubled since last year - so, in a company where nearly half of that head count is engineers, but claude is "writing 90% of the code," what is everyone doing then? You would think, if the hype feeling around this held true, that the output would be going up and costs remaining stable. Costs rising as you scale is not a new thing but that's not really what AI promises. It sounds to me like the retail AI spend per employee is very high. What is the appeal of that?
Imagine an employee is 1x productive without AI.
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.
> 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.
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.
> I would just expect with this AI narrative they'd be "doing more with less" as this thing improves every year.
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.
I mean, just what I did this morning with Claude would have taken me 2 weeks on my own. So 20x is pretty reasonable for certain types of engineering.
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.
Sorry, I know this is the story, but am I expected to believe that Anthropic would need 20,000+ engineers in their org without their use of AI? I do not believe that is close to true.
No, one thing that would happen is that many projects would never be undertaken - basically, there's latent demand for software that would simply go unmet, because of resource constraints.
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.
They are 20x productive on the old KPI.
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
Yes, one can quite easily make quite fantastic numbers fall out of simply applying arithmetic and not dealing with messy propositions like grounding those numbers in any kind of real world outcome.
Now spend 1.2x their salary on AI and they become 99999x productive. So why not just go further if we're making up numbers?
> In March, I wrote about a new trend: Tech companies are starting to treat AI tokens (the main way to measure usage) as a fourth component of employee compensation, alongside salary, bonuses, and stock awards.
There's a lot to unpack about this statement.
Until employees can use those AI tokens for personal projects, it's not compensation. Rather, it's just a cost of doing business, like laptops, office space, or testing servers.
> 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".
Is that really true? At least at large companies, the components are not usually fungible in my experience. At startups or smaller companies I'm sure it's a lot more flexible.
Yea they used the wrong word and it felt like rage bait. AI tokens you use for your job given by your employer is not compensation. Hell money isn't even compensation in many cases, it all depends on the context. The author needs use AI to help them rework that sentence or open a dictionary
I think the author used the wrong word.
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.
> I think the author used the wrong word.
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.
It's certainly a cost of having an employee, along with salary and benefits. But employee costs also include things like laptops, electricity, internet, management, support staff, and possibly office space. Tokens are much more like the latter than the former.
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.
I can see where there might be a truth to it. My company offers a fairly generous monthly token budget. If I were evaluating an offer from another company, but they offered a lower monthly budget, it would definitely influence my decision, all else being equal. It's not compensation, but it does affect my day-to-day experience at work.
Everyone is saying it is expected, and I agree, but it’s also clear that employees of AI companies spending unlimited zero-cost tokens in their day-to-day work is resulting in products that aren’t usable by the vast majority of regular workers who don’t have this luxury. Dogfooding your product is good but you should also use it with the same constraints that you place on your users, otherwise what signals are you really getting?
They're dogfooding the way Xerox PARC was dogfooding in the 01970s.
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.
They aren’t usable? I’ve been using them a bunch and have been having good results. Dogfooding is always good, but I don’t think there’s some kind of major problem here.
Dumb question, what most engs at Anthropic work on? It doesn't seem like release some large new products all the time while they have quite a few of engs. What are the major branches of work besides LLM research? I guess there is a lot of infra stuff to support the scale of operation, just supporting API and TUI shouldn't be that demanding I guess.
I'd guess they have a lot of internally facing tooling for monitoring, one-shot eval to catch people prompting bad things, etc. That stuff can probably be yolo'd and it just annoys the internal teams using it.
I'm kinda curious about this too. But then I'm always amazed at the enormous workforces these tech companies have, and I'm sure they cut them as thin as they can. Like adobe has 30,000 employees & some blogger estimated that 1/3rd of their workers are actually working on their software. I use their software sometimes and I really haven't noticed many changes to it over the years, except recently with the ai stuff. Like from 2015-2020 I can't think of any major things they added to adobe illustrator. I guess making and maintaining software is hard.
I fully agree most big tech companies are pretty bloated. But FWIW a lot of my time at SaaS companies, especially in the B2B space, was spend working on features for larger customers that most others would never use or even see. Like, yeah, product X isn't that complex, but $BigCorp wants to use it in their private cloud, or needs it to be single tenant, or needs these audits done, or want their $Gov client to use it. Now you have a ton of work for zero visible changes.
- Cross-platform desktop apps - Cross-platform mobile apps - Claude Code TUI - Product-specific verticals like Claude Design - Corporate marketing website - APIs - Writing technical documentation for APIs - Enterprise support - And what must be a massive infra team to run training and inference at scale in a heterogeneous cloud environment
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.
Does anyone pay retail API pricing to Anthropic at scale? The last time I checked, I was burning > "$10K" per week with my $200/month subscription.
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.
If 90%+ of the code is written by AI, why do they need so many engineers?
There are many internal developers at $dayjob (where core products are not based on AI) that spend over a thousand dollars every day on average, which is likely higher than their salary.
I doubt they are bringing that much value to the company for whatever work is done with that much token.
that's crazy: in my experiments (and experience) i can get ~ 90% the quality of the most expensive settings on frontier models for far far less than 90% of the cost by changing settings down.
So...given how much they are loosing and the looming bankruptcy risk, the lesson is: don't do this?
Are you kidding? Did you not see Anthropic's S1 filing? Never has so much value (in dollars) been created by a company in such a short time in the history of humanity. I'm not sure how your takeaway from that is "don't do this".
I’m not sure what this “stat” tells us other than Anthropic is dogfooding its own tech. Which is kinda expected.
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.
I mean, they probably could not have done most of it with open models. Again, a lot of this isn't going to standard software development, at least I would assume but instead to SOTA model development and RSI.
Are a majority of Anthropic developers working on SOTA models and RSI? I would have guessed not.
Note, this doesn't include options or stock benefits. That's a huge part of actual compensation for engineers at this level even if it's on a different balance sheet.
this is meaningless trivia as paying retail prices to yourself is nonsense.
Do the same math on AWS cloud use at AWS and you'll probably see proportionate massive costs.
This is the nature of managed anything. AI efficiency will improve but essentially this is what automation does.
all of that to hit two nines of uptime
Oh is it finally up to 89.9%?
"ohhh, la-di-dah, this guy's got tens in front of his two nines instead of just 9.9" - github, probably.
Is it because it's "unlimited" ? An analog would be lifestyle inflation.
The title is as stupid as Dario.
> excluding stock awards
So it exceeds employee pay if you discount the vast majority of employee pay.
This is like how soldiers use tools worth orders of magnitude more expensive than their own pay.
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.
What does this translate to in terms of number of 24/7 coding agents per engineering staff member?
Now imagine if they hired from other geographies.
I'm sure in several US-based companies, non-US workers AI spending is already beyond their own cash comp.
Regardless of one's opinions about future AI usage, I'm not sure this metric says anything at all.
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.
This is not a good measure. You have to measure productivity. If the AI is better, it DESERVES to be paid more.
- @robobun, plz rewrite in Rust.
- @fable, plz s0lv3 Riemann. You are doing great.
- @claude. rewrite yourself for the 10000th time. Use as many tokens as you like.
They giving stock options to the AI now?
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.
Don’t get high on your own supply
They should use Deepseek - much cheaper.
Could it be because spending it internally means they can’t receive retail prices for the tokens?
For every new hire, you have to ask yourself: "Will this employee be better than another $300k in tokens?"
> Anthropic's numbers show why. More than 90% of the code added to its software in September was written by Claude. Meanwhile, revenue has grown vastly faster than headcount.
Correlation does not equal causation?
ummm yes, they have to dogfood it... this is that lucky area of the venn diagram where you have to do it, measure it an act on it... because improves the bottom end and the product.
everyone who said "why aren't AI companies replacing their employees with AI?" should be rethinking their position
To what?
All this news says is Company A uses internally the resource they sell externally at ($X) value. It's not saying how much it cost the company to generate said consumed resource
to spell it out: the implicit claim is "ai companies think ai is a scam, as evidenced by them using humans instead of ai", and I believe the huge internal ai use is evidence to the contrary
AI, the technology, can be useful... And... AI the investment case can be a scam.
These are not mutually exclusive points, and I find it a common issue to get both sides to understand.
Anthropic/OpenAI should start doing mass layoffs if they want to convince other companies that this is really the human-labor killer.
they're using ai instead of employing more people, how is that not exactly the same minus a completely morale-destroying marketing stunt
both of those companies combined are smaller than the number of people microsoft is trying to buy out right now
Anthropic 10x'd its employees over the past 3 years. Shouldn't it be cutting employees if that's the case? Especially because they probably have access to more powerful models which aren't released to the public yet, probably with fewer restrictions, and don't need to pay the markup for using their own service?
10x in three years for a "trillion dollar" startup is nothing
I will keep assuming any news coming from AI companies are a type of corporate propaganda, and that AI companies frequently use their millions of dollars of marketing money to create a narrative to maximize hype and make money.
> I will keep assuming any news coming from AI companies are a type of corporate propaganda
That's just reverse naivity.
Reverse naivity? Never seen that term before, is that synonymous with healthy skepticism?
Recursive self-improvement is just around the corner. Any day now they'll be laying off all their employees as their god-like AI makes investors trillions of dollars. /s
You shouldn't be getting downvoted, people should be concerned that a company that's about to hit the valuation that it's at is not exploding in junior hiring and expanding their workforce like prior companies