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They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need
by trjordan 5mo ago
They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down.
This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer.
That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending.
We're not there yet. This is still the upswing of the hype cycle, and unless we figure out how to make developers 2x, 5x, 10x as productive on stuff that matters, this isn't going to play out well.
- EGreg 5mo agoHere is a serious question.. Can we sell into the hype cycle and on the way down with this: https://safebots.ai/costs.html https://safebots.ai/costs.html
- adithyassekhar 5mo agoI asked claude to generate a frontend and it made the same template. Same san serif and serif fonts together. Same colors. Same typography. Same layout and animations even. It’s wild how similar it is. No not similar it’s the same damn thing.
- dd8601fn 5mo agoI’ve seen the same dashboard for a dozen custom web applications now, including a couple I had it make for me. It really does have a particular lane for each chore, and it’s reproducible.
- properbrew 5mo agoYep and when you see it in the wild it stands out like a sore thumb, absolutely no thought into a bit of a unique design or branding. I have a few live websites built using LLMs and they will just go for default generic templates and colours if there's no vision.
- jeffreygoesto 5mo agoIt produces the "most average" web design unless you really prompt your way out, isn't it? If you don't care enough to prompt, Claude does not care to be individual.
- WarmWash 5mo agoTechnically from claude's POV, it's one individual copied millions of times. All claudes are clones.
- cortesoft 5mo agoI don’t think these numbers are accurate? It seems to ignore the fact that the models have cache for ongoing sessions, which means you (normally) aren’t actually sending all those tokens on every request… you only need to if you go too long between requests.
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- YetAnotherNick 5mo ago> $5t to $10t to make back in the next 5 years Wait what? They spent 2 order of magnitude less on hardware.
- trjordan 5mo agoFrom the verge: https://archive.is/kU4Zg https://archive.is/kU4Zg > Gartner forecasts that large AI companies would need to earn cumulatively close to $7 trillion in AI-driven revenue through 2029, which is close to $2 trillion per year by the end of the period. In order to achieve “historic returns,” the providers would need to earn nearly $8.2 trillion in the same period.
- YetAnotherNick 5mo agoThose numbers don't even track even in the same sentence. If it is $2T/year by the end of 2029, it would be something < $6T cumulative in 3 years.
- layer8 5mo ago“Through” 2029 is a bit more than three and a half years. The $2T are likely the yearly average of the $7T in that period.
- b0r3dthisD4y 5mo agoThe numbers are made up political correctness anyway. Everyone's agency is 100% captured by belief in Wall Street. Too few <50 have any meaningful labor skills to blink. We'll continue to have consent manufactured via media platforms and in 3 years no one will bat an eye at these companies being worth $12 trillion as Altman and Musk climb two ladders holding a "mission accomplished" banner.
- HDThoreaun 5mo agoSource on 200 million knowledge workers worldwide? My understanding is that it's just above 1 billion. I dont think a billion subscriptions at $1000/yr is out of the question but it might take a decade to get roiling
- rootusrootus 5mo agoA billion? Really? At 200M you’re already including a lot of people that stretch the definition of knowledge worker.
- HDThoreaun 5mo ago> At 200M you’re already including a lot of people that stretch the definition of knowledge worker. How do you know this? Im certainly open to recalibrating my numbers which is why I asked for the source
- windexh8er 5mo agoWhat's your source, because it looks wildly out of proportion compared to numbers we have now.
- HDThoreaun 5mo agoI googled "number of knowledge workers worldwide" and read the top results. If you read it as I was confident in a billion I apologize, Im just trying to get an accurate count. What numbers do you have now and where did you find them?
- windexh8er 5mo agoThat's not the TAM of 1B knowledge workers globally. If that were the case many industries would have a 2-3x target market. To simplify break that 1B up into 3 levels of purchasing: 1) High-tier (US, Western EU, ANZ, Japan, South Korea, Singapore, UAE, etc) - 200-250M knowledge workers. 2) Mid-tier (Eastern EU, Latin America, urban China, India tech sector, etc) - 300-400M 3) Low-tier (Rest of the world) - 300-400M Low-tier users are mostly free tier or heavily subsidized pricing. Mid-tier are going to account for USD sub-$100 tiers. Probably averaging less than $50/seat. High-tier are who you are assuming is the 1B. Users are not equal in that knowledge worker count, so there aren't 1B knowledge workers to charge money. And when you consider Low-tier users a majority of those are free users which need to be subsidized by the High-tier users. So either free tiers get much more restrictive or the providers lose additional training data. A bulk of Low-tier users cost money and provide little to no revenue. Edit: And think about Mid-tier and Low-tier for 5 seconds. Why would they pay Anthropic or OAI when they get get 100x+ inference from DeepSeek or Xiaomi? Mid-tier may be the only area that is willing to spend money on a US provider, but I would wager significantly on the fact that users in the Low-tier almost universally do not care.
- jgbuddy 5mo agoYou are making the assumption that the models are only used / paid for by 2.5% of the population (your knowledge workers value). There will be new value created by these models which people are happy to pay for which simply did not exist at all before. It is also naive to say that the hyperscalers are going to be expecting a return on this in 5 years, it will be entirely propped up by investments / IPOs as has been the case with any tech company for decades now to reach scale. The hyperscalers are currently spending ~650b combined annually, which they have the cash for and can sell in future compute instantly.
- specproc 5mo agoI'm sorry, what the feck does "value creation" mean here? I live in a place where people are so, insanely squeezed from every angle. Wages are stagnant, prices rocketing. Where is the money to pay for this value going to come from? No one I know feels richer than they did a decade back. I've not been able to meaningfully put up my prices for a decade. People are tired and stressed and scared, particularly scared of a technology everyone keeps telling them will make them redundant. There is no rising tide lifting all boats, just most of us drowning whilst a few whizz past in their yachts. I honestly hope these guys faceplant ASAP. Couldn't happen to a nicer bunch of people.
- dirck-norman 5mo agoFeelings aren’t fact. A lot of data shows the doomerism is not reflected in the actual numbers and much of it has to do with rapid inflation and continued vibes. Consumption has risen, inflation adjusted wages have risen for blue collar and white collar alike. Most social mobility has been the middle class moving into the upper middle class, not moving to the lower class. The main thing holding people back is the housing crisis. This is orthogonal to the value creation of businesses. Value creation is growth. If it didn’t exist the S&P would still be 42.55$.
- jacobgkau 5mo ago> Consumption has risen, inflation adjusted wages have risen for blue collar and white collar alike. My wages haven't risen for nearly 5 years, while inflation has occurred over the past 5 years. Why the blanket statements? > The main thing holding people back is the housing crisis. This is orthogonal to the value creation of businesses. Are you suggesting a "housing crisis," in your words, wouldn't impact consumption? I'm watching my spending (and living like a child in his parent's house, except it's not my parent and I have to pay for it) in the hopes that in about a decade, I'll have saved up enough of a down payment for a home somewhere in my state that I could actually afford the mortgage on the remaining amount. There are plenty of things I'd potentially spend money on but won't as long as I feel like I'm economically stuck and have a chance in hell of saving my way out of it. So this feeling translates to fact. If you think my personal experience is just an anecdote and doesn't count because it's not being told through the lens of large-scale numbers, fine. But I really agree with the person you replied to that you're gonna have to be a whole lot more specific than "value creation" if you want people to spend money on your AI products "in this economy," whether it's because they're actually strapped for cash or just pretending like you seem to think they are.
- onlyrealcuzzo 5mo ago> We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. They are assuming ~10% global GDP growth instead of ~3%. You probably don't need the same %s if the pie grows a ton. I'm highly skeptical we get that growth, but if you aren't, it makes it easier to digest.
- freakynit 5mo agoI mean this case with AI-productivity fires itself back when we talk about GDP. The more AI causes productivity increases, the less and less number of workers will be needed. This will heat up the job market even more and bring salaries down. Net effect of this productivity increase: less consumption by the masses, even though you may be producing more good and much more efficiently. A third effect also comes into play that once all this starts to happen, common people, who are generally living paycheck to paycheck, will now start to hesitate towards making any long term investment, housing included. And that indirectly will end up impacting financial and banking sector, which will then impact existing savings, bonds yields and retirement funds, and the recession-like cycle starts. This productivity increase only makes sense if it is capped to a very small number.. like 20% max. Beyond that, who these companies will even be selling to? Am I overthinking all this?
- simonw 5mo ago> The more AI causes productivity increases, the less and less number of workers will be needed. That only holds if companies have a fixed need for "productivity" which is met by their current employees, such that their employees becoming more productive means they need less of them. Every company I've ever worked for has wanted to achieve way more than they are able to get done with current resources. But generally yes, the biggest open question about all of this is how the impact will play out on the economy, job opportunities etc. I've not seen anyone come close to a confident prediction about how this will play out.
- zero_shift 5mo ago> Every company I've ever worked for has wanted to achieve way more than they are able to get done with current resources. I mean sure. Every company wants an infinite addressable market. But that doesn't mean it exists. It might not be possible to sell 10x the software we sell today. It might not even be possible to sell 2x
- ar_lan 5mo ago> unless we figure out how to make developers 2x, 5x, 10x as productive on stuff that matters, this isn't going to play out well. Simple - you make them work 2x, 5x, or 10x more hours.
- OtomotO 5mo agoThere are not enough hours to do that
- browningstreet 5mo agoSomehow Uber and WeWork survived the same kind of grand projections that they never met.
- xoac 5mo agosomehow the invisible hand of the market is also blind af
- ArcHound 5mo agoMakes sense if you think about it: if all photons pass through you (invisible) then you can't capture them to get info (blind).
- 121789 5mo agouber sure....but how did wework survive? they are a smoldering husk of a failed company looted by its founder
- naravara 5mo agoThe company’s gone but the assets just got sold to other commercial real estate firms. Uber was basically only ever software to help people use their own cars so a very small part of their valuation was physical stuff to upkeep, it was just deals and obligations they had. Not sure how it shakes out for Anthropic and OpenAI. There’s a lot of physical capacity that needs to be built out and can depreciate. But there’s also a lot of network effects and dependencies being built in with enterprise users. I don’t know how swappable the tooling is either. I think over the long term the UI, model training and documentation, and infrastructure are going to end up being run by different parties and I’m not sure which leg of that chain ends up in a position to skim most of the profit off. My guess is that Apple and Google end up raking in all the money since they control the OS and app stores while the rest of the stack gets driven down to being generic commodities. At least where mass market consumer adoption is concerned.
- hamdingers 5mo agoI'm sitting in one right now and don't see any smoldering...
- sowbug 5mo agoThere is also the EV (expected value) of developing AGI. Even if you personally believe the probability is low within the lifetime of either of these companies, the value would still be extraordinarily high, enough to forgive a $5T or so miscalculation here or there.
- zero_shift 5mo agoI don't think AGI was ever a serious endeavour, just something the labs talked up to grab attention. I am willing to bet a Twix we'll look back on that stuff in 2 years with a lot of embarrassment
- sowbug 5mo agoThe high-risk side of that bet would need to win more like a lifetime supply of Twix. But in a post-scarcity nirvana, everyone already has that. So sure, you're on at even money. See you in two years.
- deaton 5mo agoTheres no reason to believe, based on recent trends, that AI would lead us to a post-scarcity world, even if it could do all of our jobs better and cheaper.
- sowbug 5mo agoI'll wager a hypersled of my Twix against your next three rations of gruel. But I think I'm done betting after this one.
- dgellow 5mo agoOnly if running AGI makes economic sense. We actually have no idea if that’s the case. We don’t even have a definition for AGI
- regularfry 5mo agoThe bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build. The more of the latter they can take on, the fewer knowledge workers are needed at all. So rather than 5% of every knowledge worker's salary going into tokens, 100% of the knowledge worker's total employment cost goes into tokens and you get a 20x productivity boost as a theoretical minimum across those tasks. That's the game. There's a view you could take of this that this is just a growing of the pie: with those cost dynamics a lot more "small businesses" get a vast amount of leverage, so the overall economy grows without replacing the knowledge workers. I'm not sure I trust the MBA class to have that view.
- layer8 5mo agoWho pays for that value, and from what, if all knowledge workers lose their jobs? It sounds like the economy would largely reduce to the small minority class of independently wealthy people.
- whatshisface 5mo agoThere were no knowledge workers in the middle ages.
- layer8 5mo agoThere wasn’t 20x value to pay for in the middle ages either.
- wongarsu 5mo agoBack then people were mostly farmers, but we already automated that job away. Not completely, but compared to the middle ages we 50x'd their output. Which is a great illustration what it means to make a job 50 times more productive. We went from 80-90% of the population being required to barely make enough food for everyone to survive, to 4% of the population producing such an abundance that consuming too much food has become a systemic health issue
- 5mo ago
- jmyeet 5mo agoYEPPP... and I'm kind of shocked at how many people can't do simple math. Let's put it context. Google's annual revenue seems to be north of $400B. So if OpenAI suddenly had Google's revenue, it would still be insufficient to recover their investment. and it's a ticking time bomb because $1T in servers, CPUs, GPUs and memory is going to be worth $200B in 5 years. You can say they can keep using what they've got. Sure. But they're also not going to stop spending on new hardware. And the competitor that comes along in 5 years and spends $1T doing the exact same thing is going to have a huge advantage. OpenAI at this point reminds me very much of the Russ Henneman pre-money hype cycle.
- mountainriver 5mo agoHow could extremely capable artificial brains ever pay for themselves?
- hansmayer 5mo agoThis should be the top comment. Also, I think its not that many people, including our Simon here, are not good at math. Its more like, some of them seem to be incentivised to not be cough, cough, "good at math". How else will the hype sell?
- simonw 5mo agoI thought my post was pretty free of hype. I said that this new revenue "Maybe even enough to start covering their costs!"
- TimTheTinker 5mo agoI thought Anthropic and OpenAI's combined CapEx has been <100B? source: https://isaiprofitable.com/ https://isaiprofitable.com/
- kilroy123 5mo agoThat site needs Apple on the list. ;-)
- Danox 5mo agoWhy? All their money is going to Apple Silicon and the five ecosystems, so far in Apples entire history, the largest acquisition has only been $3 billion dollars, OpenAI is currently getting nothing and they gave Google a measly $1 billion refund per year for the use of Gemini. If John Ternus wants to spend some money, spend it on bringing memory in house. Apple has the money and the engineering talent to do so, have it fab/made onshore in partnership with TSMC. Do it Apple because you have to not because you want to the Chinese probably will be taking over the memory industry, worldwide, by taking advantage of the greed from three memory companies and their AI overlords.
- kilroy123 5mo agoThat's the point. To show how they _haven't_ lost billions on this.
- deaton 5mo agoMaybe so far, but they've committed to well over a trillion in future capex.
- topaz0 5mo agoAnd there's the indirect capex that their revenues will pay for indirectly, like in the case of oracle
- TimTheTinker 5mo agoHere's the question - does that future spending already appear on partners' balance sheets
- solenoid0937 5mo ago> 20% if you're a developer. That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. Of course it will. The value of an employee is a multiple of what they get paid. If you pay an employee $500k and they make $2M for your company (like Meta), then of course a 20% increase for the salary is justified if the velocity is increased 20% as well.
- hansmayer 5mo ago[dead]
- lunar_mycroft 5mo agoThe difference between what the employer makes per employee and what they spend in compensation doesn't matter. If the increase in productivity isn't greater than the increase in cost, there isn't a reason to pay for AI over hiring more developers. Imagine an employer with 10 employees paying $500k per employee and making $2M per employee in revenue (to use your numbers). They could hire two more employees and spend an extra $1M (+20%), but make an extra $4M in revenue (+20%). Alternatively, they could buy all ten employees a $100k AI subscription, for a total of $1M extra spending (+20%) but an extra $4M in revenue (+20%). You'll notice both scenarios are identical, so an employer optimizing for profit would have no reason to prefer one over the other.
- chasd00 5mo agoThere’s a lot relationship and culture management overhead involved when adding 2 more people to a 10 person company. I think any business leader would take the productivity speed up from buying a tool over hiring more people and integrating personalities/habits/viewpoints to an existing established culture any day of the week.
- lunar_mycroft 5mo agoYou're basically positing that the real cost of a 20% headcount increase is higher and/or the productivity gain is is lower than 20%. That isn't an unreasonable claim, but it's basically rejecting the premise here. You might just as well object to the premise that you can buy a 20% speedup by spending an extra 20% on tokens.
- whatshisface 5mo agoHere are a few thoughts: - The publicly available information about how inference costs compare to training costs is conflicted. EEs involved in datacenters talk about power usage spikes during training runs as if they were a major factor in the designs, but academic papers discussing cost-optimal scaling confidently treat inference-time compute as a major factor. - On the side of the balance indicating that training is more compute-intensive after amortization than inference is that Chinese providers, constrained primarily by access to compute, have nearly unlimited token availability at a lower price than US providers (inference), but poorer model capabilities (training). That would make sense only if US providers are inflating inference costs by 20-30x due to amortized training costs that overseas providers were not able to take on (there are other factors too). - If training >> inference, they're in a prisoner's dilemma that far exceeds the ordinary zero-marginals model of competition between firms (due to its huge discrete stepwise nature). On the other hand, if inference>>training, the high-level analysis popularized by certain thought leaders, that it's like a utility, would be true. You'd tend to count this as a vote for inference>>training, but the CEOs saying it at least have a huge incentive to agree because the alternative, the prisoner's dilemma, would stop investment very fast. - The only voice in the story that I just told you to have anything to do with fact (as opposed to high-level analysis and ivory tower armchair management of a secretive business) were the rumors from facilities engineers. That shows you the state of our understanding... - If we don't even know the ratio between amortized capital expenses and operational costs, outside investor analysis is impossible. It doesn't matter how finely they divide the accounting buckets for office ferns and indoor ferns if the single biggest part of their business is obscured for trade secret reasons.
- materielle 5mo agoI'm about to leave a shallow comment, but I am a bit skeptical of the supposed drop in inference costs. If AI labs saw a lot of potential there, they'd surely be bragging about it non-stop? So the fact that publicly available information is conflicted is probably a sign that at the very least, the numbers aren't amazing. Yes I know there's no evidence and this is lazy reasoning. But there's probably a bit of truth to this line of thought.
- 5mo ago
- deaton 5mo agoBigger than that, they have to contend with open weight local inference. Open weight models right now haven't caught up to the frontier models of right now, but they're as good as the frontier models of not too long ago. If open weight models reach a certain point, then frontier model providers are going to struggle to make anything selling tokens, because eventually people will realize they don't need Mythos for everything.
- logtempo 5mo ago> +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. Except that if your company go 20% faster than the others companies, you win market shares. But then, everyone will use the same tools and companies will be at even speed, but the tool will stay. Now...if the market is saturated, it's useless to try to do things faster. Cheaper yes, but not faster.
- archagon 5mo agoPretty much all major tech companies today are horribly bloated and mostly metastasizing instead of innovating. I'm not sure how 20% increased productivity will help in any way with that. If anything, it might accelerate enshittification and turn potential customers off even more.
- cryo32 5mo agoThis is never going to materialise. It’s dead in under 2 years. The market is shrinking and saturated already and it’s not because of AI gains but geopolitical instability and supply chain issues, some of which are caused by AI spending and stupid ass PE firms refocusing on AI supply chains. Only our pensions and futures burning.
- aspenmartin 5mo agoWhat do you mean by the market is shrinking?
- cryo32 5mo agoLiterally revenue is collapsing in most sectors. Technology purchasing is declining. Service models are failing to turn a reasonable ROI. People stopped buying shit.
- aspenmartin 5mo agoWait do you have any numbers to back this up? Every number that I've seen contradicts this. Most sectors have positive revenue growth, even non tech sectors. Technology purchasing is increasing in every bucket (software, IT services, devices, communications, and of course DCs). Retail and food-service sales are up MoM and YoY. Personal consumption is up 0.2% in real terms. I assume by service models you're just talking about AI? I actually may agree with you but this is clearly not true for long if it is true today.
- peteforde 5mo agoI'm reminded of that [terrifying in hind-sight] Newt Gingrich interview in which he was more concerned about his constituents feelings about things getting worse than any silly statistics provided by government agencies. https://www.youtube.com/watch?v=xnhJWusyj4I https://www.youtube.com/watch?v=xnhJWusyj4I
- packetlost 5mo ago
- aprdm 5mo ago"Next 5y" doesn't apply to AI factories
- FuriouslyAdrift 5mo agoI work for a tiny little company ($150MM annual rev with 9% net) and we are already looking at dropping $100k on hardware to run local models because, for us, they're "good enough." Our estimated spend for AIaaS would exceed that cost in less than a year. In a few years, there will be hardware capable of running frontier models good enough for most things at accessible prices for even tiny companies.
- EvanAnderson 5mo ago> ...we are already looking at dropping $100k on hardware to run local models... Just think how much further that $100K would have gone if the hardware market wasn't so screwed-up. Anecdote: I priced-out adding 1TB of RAM to a four node cluster a couple months ago. The cluster was purchased in fall of 2024 w/ 4 nodes, each with 256GB RAM. The nodes cost just over $14K apiece back in 2024 (entire box, not just the RAM). Dell wanted >$90K a couple months ago to add 256GB to each node.
- cyberax 5mo ago> Dell wanted >$90K a couple months ago to add 256GB to each node. RAM is expensive, but not THAT expensive. I just bought 128Gb for about $5k for our build cluster (it's not even for AI, sigh). Even if you need larger-sized DIMM sticks, it's still going to be in the vicinity of ~15k tops.
- deleted 5mo ago[deleted]
- EvanAnderson 5mo agoIt was crazy. I found the part on the open market for a lot less but the edict from the Customer was to buy from Dell to keep the support entitlement intact. That inflated the price to an astronomical level to be sure. I haven't had problems w/ Dell support and 3rd party memory, personally, but given the machines' application I understood the concern.
- alex_suzuki 5mo ago
- mirekrusin 5mo agoNow try to take back llms from developers and see what happens.
- bigfishrunning 5mo agoIf, by some miracle, all LLMs ceased working right this second, any developer who would no longer be productive should not have been a developer in the first place.
- mirekrusin 5mo agoTrue, but they will not want to work for you anymore, they'll want to work for company that provides it.
- Gigachad 5mo agoI'd happily work for a company that paid me the money they would have spent on LLMs.
- mirekrusin 5mo agoThey don't want to spend this money.
- bigfishrunning 5mo agoThey will eventually have to
- mirekrusin 4mo agoThey're going to start seeing real bill on Monday from Microsoft/Github.
- dgellow 5mo agoYou don’t need a miracle, if Anthropic API is down due to technical issues you don’t have software development anymore. It’s insane how much we are delegating to 3rd parties. It’s not like having cloudflare down where your users cannot access your services. The AI tools used to investigate prod issues stop working, developers stop working. The AI support system that allowed the company to get rid of their support team stops working. In addition to all the issues that causes to customer facing products based on AI. The sales team cannot work anymore. It’s like the industry is willingly introducing a common external risk to everything
- golly_ned 5mo agoThis is why 'agents' are the solution for these companies. Token spending goes through the roof. As long as a human is in the loop needing to read or review at human speed, that's a ceiling on how many tokens per user they can generate.
- spamizbad 5mo agoI will also tell you, as someone who works at a company that's trying to remain profitable, that token spend has caught the eyes of finance and much like cloud spend they've already started applying pressure to control costs. This May my team is protected to use 30% fewer tokens than we did in April - this was by intention. I suspect we'll drop more in June.
- Gigachad 5mo agoI expect in the future, when these AI companies stop subsidizing costs, the idea of spinning up 20 agents to work on some brain fart idea that you throw out after looking closer will come to an end. It'll be seen like assigning developers on work that hasn't been properly planned for or reviewed.
- fragmede 5mo agoCan't wait till June, when finance gives the team the choice: everyone gets double tokens if you choose to fire somebody.
- spamizbad 5mo agoOh we already had that with a RIF earlier in the year.
- bigbluedots 5mo agoIt might be time to start interacting with agents using grug speak only
- pas 5mo agohttps://github.com/JuliusBrussee/caveman https://github.com/JuliusBrussee/caveman
- jstummbillig 5mo ago> 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. This is where the napkin math is breaking down in a big way. There is absolutely no reason to assume this will only impact "knowledge workers". Farmers use computers. Farmers will use AI.
- vablings 5mo agoAI for what? None of the AI a farmer could or would use would be any more meaningful that light chatbot usage or already existing computer vision/gps
- red75prime 5mo agoAnd around 400k H-2A workers. Humanoid robots... Who works on them I wonder.
- quantumleaper 5mo agoThe kind of farm that would use AI is already 99% machinery and automation.
- jvanderbot 5mo agoHey, I wrote this down one time. I estimated way higher yearly revenue required, to be adversarial. And you can keep the "cost per unit AI work" a parameter and play with the results. But the point is that if people are willing to delegate part of their salary (e.g., buy consumer products), vs requiring employers to pay for the tokens, then it's quite possibly a net win. Something like "I pay a largeish fee every month to make my own job much easier", similarly to how we buy a car to make commuting easier. https://jodavaho.io/posts/ai-jobpocolypse.html https://jodavaho.io/posts/ai-jobpocolypse.html
- npn 5mo agowe all know it is impossible goal to make. surely AI will be even more useful in the future, but as long as china exists and continue to undercut the price, the goal will be never meet. > We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. with that much money, the companies can easily buy their own hardware and hosting free public models, no need for those expensive subscriptions.
- mannanj 5mo agoOne quick question. Did tax payer money fund these data centers? If so, how does that money translate to their profit and a return for the people whose work paid for the resources? Or did we just get scammed?
- jkelleyrtp 5mo agoI agree in principle with the math. But I believe that in reality if revenues don't show up quickly, then lenders will just restructure the debt and defer the payback period. Similar to SF commercial real-estate; many buildings should've come due during the depressed covid market, but lenders (banks) were willing to delay payment until the market picked up again. The scale of these investments put the lenders at substantial risk, so the lenders will do anything to make it work. If the current lenders will be damaged by extended payback periods, they can simply sell the debt to someone else who won't be.
- superxpro12 5mo agoIt's going to be a typical saturation curve. A lot of upfront tokens spent on things that have stockpiled over the years, and then the derivative on token spend trends to zero as the users run out of immediate things to try. Sure there will be ongoing maintenance and experiments, but it wont be nearly as close as the initial inrush.
- yalogin 5mo agoTo get that revenue and adoption they have to vastly increase their infrastructure spending. If they are currently losing in even the 200/month plans how is it sustainable?
- mv4 5mo agoIf people figure out how to run agents on-prem (already becoming feasible for both agentic tasks and coding on consumer hardware like Mac Studio 128GB+ or DGX Spark with some models) these companies will be in deep trouble. Privacy is also a huge issue.
- ciconia 5mo ago> make developers 2x, 5x, 10x as productive on stuff that matters What does this even mean? Is this about speed of development? Is this about headcount? LoC? How are coding agents contributing to productivity in places like GitHub, Shopify or Meta? I mean companies that already have an established product. I really wanna understand this because I'm not seeing that GitHub's product suddenly became so much better than it was 2 years ago, so where's all that productivity going?
- flexagoon 5mo agoProductivity is measured in the number of AI-generated Twitter posts developers can make about their AI-generated startups
- zamalek 5mo agoThe productivity is going into perverse incentives[1], e.g. we have improved (by which I mean "increased") token use. More PRs every day. More lines of code. All things we knew were shit-brained metrics a decade ago (obviously except token use). We've also increased how much our coworkers need to read, or deal with. You can get an AI to make any point you want, so you can ignore the 5 humans raising alarms due to the 1 clanker you made say what you want to hear. All numbers going up. There are obviously people producing additional true value with it, probably, but that's almost certainly scarce. [1]: https://en.wikipedia.org/wiki/Perverse_incentive https://en.wikipedia.org/wiki/Perverse_incentive
- missedthecue 5mo agoPeople have been arguing about how to measure developer productivity since time immemorial. But the bottomline is that if products and features are hitting the market faster than they used to, developers are doing more with less. It's what we're seeing in my workplace.
- PunchyHamster 5mo agoThat assuming once they start squeezing people won't just go to deepseek or other cheaper competition > That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. And most research shows people far over-estimating their own gains. Once companies start counting the actual (and not just reported) gains, the AI budgets will be more limited as people realize it's an useful and versatile additon but not replacement for most types of work > We're not there yet. This is still the upswing of the hype cycle, and unless we figure out how to make developers 2x, 5x, 10x as productive on stuff that matters, this isn't going to play out well. Upswing of the hype cycle while growth of tech itself is flattening, both coz of techs innate issues (which might or might not be solved, but some papers claim they are unsolvable with current approach) and just the fact the spike in growth caused so high economy cost that it put brakes on itself. T
- Gigachad 5mo agoThere's a lot of workslop pumping the numbers. People can generate a 300 page PDF in a tiny fraction of the time it would have taken, but now the report is full of mistakes and fluff, and the stuff that would have been learned and caught in the process of making the report is now not happening.
- PunchyHamster 5mo agoand the recipient pulls that into LLM and generate summary. It's lossy compression for thoughts at this point
- alexpotato 5mo agoI was in college in the late 1990s/early 2000s and I distinctly remember an econometrics professor state the following: "As cable TV and Pay Per View came out, there were studies done about how many movies people would watch if given unlimited access to films. The results were bandied about as proof that we should build out all this infrastructure to support this line of business. When the data was further analyzed by statisticians etc, it turned out that people claimed they were going to watch films 10-12 hours a day, every day of the week. Impossible." I feel like we are in a similar boat here where some people are assuming: - EVERYONE is going to be using max tokens - tokens will NEVER get cheaper due to improvements in hardware, software, design, market forces etc etc
- PunchyHamster 5mo ago> - EVERYONE is going to be using max tokens anthropic already hunts down OpenClaw users for using too much on their plan. I'll give different example: When LED lights started to be more popular, the power usage didn't drop by the amount of power saved >- tokens will NEVER get cheaper due to improvements in hardware, software, design, market forces etc etc Well, first, improvements in computing stalled or even rolled back just purely because price of everything compute shot up cos of AI and that will NOT be fixed for a while and ESPECIALLY if AI usage will continue to increase Second, the token per model might go down in time but better models have more expensive tokens, so we quickly get into spot when: * price increase in token might not be worth marginal improvement next, better model brings * more and more models are passing "good enough for the task" threshold so for less and less companies there is any economic sense to pay for the "best" instead of paying deepseek or some other company to run "previous gen" models
- j-bos 5mo agoBut isn't it wonderful that they did?
- wizzwizz4 5mo agoIt's vaguely disturbing that people "watch" films 10-12 hours a day. Many of them are using it as a radio, for background noise, without really caring what the program is beyond vague genre, tuning in and out without particular regard to the plot… and yet we have all the cost of transmitting high-resolution video point-to-point. Surely we could just put better stuff on the radio, and accomplish most of the same goals for a far lower price?
- tedggh 5mo agoAlso, not all developers work on software products. The vast majority of developers work supporting software solutions as part of a much bigger business model, such as infrastructure, industry, healthcare and services. Many of these are complex organizations. So, unless you get to turn every employee into a 10x employee, the 10X coder along won’t necessarily make a 10X productivity contribution. What’s likely going to happen is the 10X coder will start to slow down or adding more (unnecessary) complexity to avoid having to sit and wait on overhead, for other areas of the business which are not easily automated away to AI to catch up. As a developer I can finish my project in June instead of December, but what if the customer is still not ready for integration until December? what do I do?
- amelius 5mo agoAt least they're not going to make us watch ads.
- datsci_est_2015 5mo agoI could see such productivity gains being possible, if only because the current tooling around LLMs is terrible. The fact that we have 30 blog pieces per day making the front page of Hacker News about someone’s convoluted system to guide LLM output to something reasonable is absurd. There needs to be standardization in tooling, and it needs to be open source. Then, and only then IMO, will we see huge productivity gains. But, at that point I think the big players’ moats will have dried up. Local models will probably be sufficient for 99% of daily office worker tasks. So I disagree with TFA’s premise. I think this fear is probably shared amongst the LLM giants, and they’re still hoping that neural network transformers are somehow the path to AGI (probably not, imo).
- dcre 5mo ago1. Global IT spend is $6T per year 2. Where does this $5T number come from? If they make $4T in revenue over the next 5 years instead, what happens?
- gorgoiler 5mo agoWhat value do the big model makers provide other than having a head start on gathering up humanity’s IP to train their proprietary models? What’s their moat? Is it hoping for regulatory capture where scraping is made illegal the day after they finally finish scraping all human language? It’s like OpenAI dammed the Colorado, and Anthropic dammed the Hudson, and now they’re both trying to sell us bottled water subscriptions at $100 a month. I don’t know how well the dam part of the analogy holds up, but the water part feels strong. Compiling models based on humanity’s written output feels like something no corporation should own.
- allthetime 5mo agolol I’m spending max $50/month right now on a couple light subscriptions and my velocity is insane right now (full stack mobile app development) I’m leaning into it hard while these cheap plans still exist and building out a big platform that I can easily generate new apps from. Hoping by the time the rug pulls I can just go back to hand cobbling these apps together from the modules I’ve pumped out and never even consider giving these companies a massive portion of my monthly income
- keeda 5mo agoPutting some more numbers out there (some of the links are broken, but numbers look about right): https://github.com/danielmiessler/Substrate/blob/main/Data/Knowledge-Worker-Global-Salaries/SUMMARY.md https://github.com/danielmiessler/Substrate/blob/main/Data/K... Knowledge worker compensation is 35 - 50 trillion a year globally (6 - 12T in the US alone.) That's a huge TAM. It's still close but 5T over 5 years seems doable. >... unless we figure out how to make developers 2x, 5x, 10x as productive on stuff that matters, this isn't going to play out well. The way we make ICs 10x productive is not just making each of them individually more productive, but by removing the coordination overhead of large organizations, because overhead scales super-linearly with the size of the org. And orgs will shrink automatically as AI-assisted ICs take ownership of larger and larger scopes of work, leaving much more budget for tokens. I went into this in a bit more detail along with some made-up numbers here: https://news.ycombinator.com/item?id=48040999 https://news.ycombinator.com/item?id=48040999
- thesparks 5mo agoThose are rookie numbers. We are going to blow past $1t per year in spending in no time. As a developer for 29 years, I couldn't go back to coding by hand. For better or worse, AI will be woven into the fabric of life in no time.
- TacticalCoder 5mo ago> We're not there yet. And that's not considering that capitalism is going to do what it does best: if they really found a way to be profitable, competitors are going to fight them on pricing. Anthropic, OpenAI, Google, etcetera 's margins are a competitors' opportunities. It's not as if there weren't chinese models nearly SOTA. Don't know where the french (Mistral) are but they may try to get in the game if there's a way to be profitable (not that France or the EU for that matter are relevant in anything tech or had any tech company besides ASML and SAP in the Top 100 but who knows).
- BadBadJellyBean 5mo agoThis assumes that we won't need new hardware in ~2 years. I find that unlikely. So they have to make back what they got up until now PLUS the running upgrade/development costs. So what will it be in 5 years? $20t? $30t? It's all getting a bit outlandish. What I'm often hearing though is the equivalent of "gg ez" when I bring that up. I don't understand how this will at any point blitz scale to profitability. As far as I know they don't have positive cash flow, no one has a moat and I don't think they will push out engineers.
- red75prime 5mo ago> 200m knowledge workers in the world, 30m developers Your scope is too narrow. The companies target more than white-collar jobs. And $1t is around 0.5% of the world economy.
- jimbokun 5mo agoThat’s on the order of 1% to %2 of global GDP per year just to pay for their hardware commitments.
- overgard 5mo agoOne thing I genuinely don't understand is these companies are constantly taking in incredibly large amounts of investments, so presumably they're giving up large chunks of equity or these are loans that need to be paid back or they're committing to spending obligations they're very unlikely to be able to meet. So besides the insane hardware buildouts you're correctly mentioning, I don't understand how anyone that invests in these companies is supposed to make their money back in any sort of reasonable timeframe? The cynical part of me is looking at what happened to the NASDAQ rules recently where essentially index funds are going to be forced to buy SpaceX shares much earlier than they previously would have (ie, before the price has a chance to reach it's real valuation). Which, um, I'm guessing these stocks are going to drop pretty hard when people start looking at the financials of these companies. My suspicion is that the point of these IPOs is essentially to dump the bill on the unwilling public by forcing various institutions to buy it (ie, your 401k or pension is buying this shit), and maybe their investors can squeeze some money out of this before the stocks reach an equilibrium that's probably like 1/10th of what they're "valued" at.
- motoxpro 5mo agoSo you've got that market. Let's call it the demand BY knowledge workers to do the work. You've also got: 2. The companies themselves buying tokens for operations to make the work more efficent. e.g. Salesforce agent or Microsoft Office agent or random saas inventory agent. (and if you say those will go away (which I don't believe), it's even more bullish. The tokens just go to someone vibe coding XYZ, which is EVEN MORE than if you were to buy saas because it's SaaS product x Companies that built it instead of just one) 3. The companies SELLING tokens. This is also new markets like schools and small business (e.g. the local gas station buying an inventory tool) 4. The consumers "buying" (I put in quotes because it can be subsidised but the company) through chatgpt, strava, instagram/netflix recommendation, etc. Local models still take compute, and while it may be cheaper, it is the same argument of on prem vs cloud. No one operates on prem unless you HAVE to for regulatory. Margins will come down and you just spin up a GCP/OpenAI/Anthropic agent. It may be "cheaper" but rationally its better to pay someone to manage it. Thats why Hetzner only had $367M in revneue (a lot but tiny compared to managed services)
- qaq 5mo agoAnthropic raised less than 100B up to now and as of March has 30B ARR. Why does it have to make back 2.5T to 5T ?
- root-parent 5mo agoAuthor seems strangely unwilling to distinguish usage from profitable product market fit. And from his own numbers: Anthropic Max: $100/month OpenAI Pro: $100/month Total paid: $200/month API equivalent usage: $2,180.16 in 30 days So paid only 9.17% of API-priced value a 90.83% discount, or about $10.90 of API priced usage for every $1 paid... That proves heavy usage but not sustainable unit economics. Anthropic reported numbers point the same way: Q2 revenue: $10.9B Adjusted operating profit: $559M Margin: 5.1% SpaceX compute: $1.25B/month = $3.75B/quarter So one compute supplier alone equals 34.4% of quarterly revenue and 6.7x quarterly adjusted operating profit. Its difficult for the blogger to understand something when its incentives depend on not understanding it...
- simonw 5mo agoMy point with the $2,180.16 thing is that the price for consumers like myself is heavily discounted... but the price for enterprise companies is not discounted. My usage is therefore a useful indicator of quite how much those enterprise companies may be spending on tokens, given the new pricing scheme. If enterprise companies were still getting the same discounts that I get myself I would not have written this article. (I had to dig into your margin figure - looks like you calculated 5.1% as 559000000 / 10900000000 * 100 but that $559M "adjusted operating profit" figure includes training costs, where usually when we talk about margin on inference we're not including those since those costs are fixed, margin calculations make more sense against the variable costs of serving a token.)
- what 5mo agoWhen you have to train a new model every few months to stay competitive, discounting that cost is rather dubious.
- simonw 5mo agoThey key difference here is that training costs are fixed. If you train a model for $100m dollars, how much of that training fee should you allocate to each token that the model serves? It's impossible to know, because you don't know how many tokens total will be served by that model until you retire it at some point in the future. So you can't say "1,000,000 tokens costs $X in inference and $Y in training" because $Y is not possible to correctly calculate. So, if you want to have a productive conversation about "margin on inference", it's sensible to look at the cost of serving the tokens independently of the cost of training the underlying model.
- Wowfunhappy 5mo ago...does anyone have a guess as to the total amount of money spent on software developer salaries each year? What percentage of that would the AI companies need to capture to be profitable? (I'm not trying to imply that LLMs can replace software engineers, it's just an interesting comparison. If nothing else, I suspect that if the cost of development goes down, demand for custom software will go up.)
- Wowfunhappy 5mo ago^ For what it's worth, Claude estimates $1.3–1.5 trillion. https://claude.ai/share/8a3de813-677e-4a75-9b7f-1785495c2569 https://claude.ai/share/8a3de813-677e-4a75-9b7f-1785495c2569 Honestly doesn't seem great for the AI companies.
- richardw 5mo agoI assume the bet is that as you swap humans for machines, this pays for itself. Swap entire devs and teams and frankly, managers, and you make up a lot of 5%’s fast. If it works. And I’m not sure who is going to buy the stuff the machines produce, but shrug. Presumably some bots click ads for NFT’s that other bots generate.
- pryce 5mo agoI understand some startup deciding to take a punt on "this will all work out financially if our new product demonstrably boosts productivity of large sectors of the economy by a breathtaking factor that's incredibly rarely ever happened before in history: 2x. Sometimes a plucky group of people take a risk, it pays off. If it doesn't work, the company fails. What I do not understand is: large sectors of the economy all simultaneously taking this punt, with the necessary productivity boost, as you say, far more like: 2x, 5x, 10x
- BoorishBears 5mo ago> +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. I'm increasingly realizing this math is wrong, because LLM use is really sticky. If Anthropic 100x'd prices tomorrow for their best model, so some companies offered 50% salary to keep 100% of your AI usage: a) There are programmers who would take this deal. They've gotten to the point of doing what feels like even less than 50% of the work, developers were already pretty well paid, so they'll take it. b) There are companies that'd offer this deal. Even if the only people who are taking this deal are not the best engineers, and the AI output is not the greatest, I think the last 6 or so years have seen a lot of companies realize capitalism is not as competitive as it seems. They're not worried about putting out a worse product because... frankly, what else are you going to do? CF lay a bunch of people off, support gets awful: well you're probably not building a new Cloudflare in the next few years. In the meantime the AI will get incrementally better, their market share will grow, and you won't be able to compete without taking the same faustian bargain. - Maybe I was just naive but it's making me realize how much we take for granted in the world. Both the quality and relative value of things don't have to go up over time. Quality can go down while prices go up, and nothing will really stop it. Competition should stop it, but competition is really slow and can be interfered with. And as prices go up competition gets really hard.
- recroad 5mo agoI just don’t understand how people are getting negative value out of AI or even only 20% productivity boost. I can only conclude that people don’t know how to use agents.
- oblio 5mo agoAre you mostly creating new things or integrating with complex, undocumented, untestable systems?
- recroad 5mo agoMostly brownfield systems in Java, Elixir and TS. I use OpenSpec in explore mode and point the agent to all the different repositories (when not working in a monorepo) to identify changes. Once done, i switch to propose mode and spend at least 15 minutes there iterating over the plan until I'm satisfied with the TDD approach (agents need tests to verify their work). Then apply and review. This also auto generates docs etc.
- dgellow 5mo agoI mean, it doesn’t really matter if it caused by people failing to use the agents well or not. You cannot assume everybody to use the technology the best way possible
- hintymad 5mo ago> We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. Just realized something: if one worries about losing jobs to AI, token's high unit cost is good news. To say the least, high cost would delay the displacement, if any, right? In the meantime, someone shared the below on X. I guess the moral of the story is that "good enough" does not just displace software engineers, but also models. > I Went From $3,000/Month on Claude to $5/Week on DeepSeek > And honestly?80% of my work is identical. > For the past two months, I was burning $3-5K monthly on Claude Code. Every idea from design to development to testing - full end-to-end automation, even simulating users to test my products and provide feedback. > Extremely token-intensive. But Claude's caching sucked, making it insanely expensive. > Then I discovered DeepSeek V4.
- cyanydeez 5mo agoif you ignore all catastrophic mistakes, these numbers are true
- Salgat 5mo agoMy hope is that hardware improvements (better node densities every 2-3 years, better designs, etc) will pick up the majority of the savings for these companies in the future, assuming LLM performance starts to taper off with diminishing returns.
- bg24 5mo agoIs it possible that you are narrowly sizing the opportunity? While PMF does not always mean that early pioneers will be the leaders, I think the market itself goes beyond knowledge workers and developers. Agents, robots, drones etc will all use LLM or some world model. I am rather more concerned about competition from CHINA. With how Huawei (2000 -> 2020) crushed every other telecom company and went from nobody to the most revered leader in 20 years, and with the depth of leadership in manufacturing and work culture, if China surpasses USA in AI, all US companies lose.
- panarky 5mo ago> 5% of every knowledge workers salary to go into tokens In general, I don't think you can reason from the existence of potentially stranded investments back to revenue projections. And when you frame this as percentage of salaries, that's a sneaky implication that this is only about reducing salaries and headcount, and not about adding capability, or doing things you couldn't do before, or making fewer mistakes, or capturing more revenue, or expanding margins, or competing more effectively. That said, 5% of knowledge worker comp actually seems very low to me, given the capabilities, and considering the percentage of "knowledge work" that is absolute bullshit. Two weeks ago I received an email from my HOA saying I'd been billed for a service I never asked for. So I replied to the email saying they'd made a mistake. There are now more than 30 messages in the thread, involving at least 8 "knowledge workers" at the property management company all passing the buck, and the problem is no closer to resolution. An agent could wipe out all 8 of those bullshit jobs and solve my simple problem in five minutes instead of two weeks. Think of how many hundreds of thousands people are doing this nonsense just in the property management industry alone. 5% is nothing.
- bradleyjg 5mo ago> That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. We all have our own observations and mine don’t significantly diverge. But that’s bottom up. At this point shouldn’t we be seeing it top down? If we are beyond potential and into significant productivity gains, why isn’t that showing up for the customers? Why didn’t delta airlines get significantly more operationally efficient in the last 3 months due to the introduction of better software? This is a genuine question, I am seeing a disconnect.
- simonw 5mo ago> Why didn’t delta airlines get significantly more operationally efficient in the last 3 months due to the introduction of better software? The coding agents got good in November. Most individual engineers didn't fully clock this until January/February. This means that companies didn't really figure it out until March/April. Assuming companies like Delta have adopted coding agents (which would be pretty fast) it still takes months from adopting a new tool to the code results of that tool rolling out to production. I expect (and would hope) Delta's software development culture is very conservative. Since nobody can confidently tell Delta "here are proven practices for using this tech to produce high quality, more secure code" yet it would be surprising if they were blasting full-steam ahead. I expect that even companies that got on board with coding agents in January will only just be starting to ship user-facing features that benefited from those new tools. Shipping software takes a long time, no matter how much faster the "typing the code in" bit gets!
- nchie 5mo ago>The coding agents got good in November. Maybe irrelevant to your point, but I'd argue they were really good already in May if one used the right workflow (planning etc.). They've become better, but they're not saving me significantly more time now than they did 12 months ago.
- narnarpapadaddy 5mo agoAnecdotally, my take on this is that biggest value lever is strategy and alignment, not implementation. The typical company is dozens of little vectors pointed in different directions, and they cancel each other out. Scaling up the magnitude of each is still net zero. I was recently consulting at org where two separate engineering teams were all in on two different, incompatible deployment platforms and using AI to accelerate adoption of each. Management was mystified why their engineering leads kept telling them they couldn’t deploy a complete implementation of their solution.
- nl 5mo ago> They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. I find it disappointing that a completely wrong statement like this ends up the top comment on HN. It is wrong in both the math, the logic about public markets and understanding accounting. > $5t to $10t to make back in the next 5 years I don't know where this number comes from, but it has gone unchallenged. OpenAI and Anthropic combined have raised around $100B. This is an investment so isn't something the have to "pay back" from earnings - instead investors expect to make that back from the share price being higher than what they paid for it. > or the hardware buildouts will start getting written down. The hardware buildouts get written down anyway!! That is a good thing for investors because as the value gets written down they can book a tax loss. ANd it turns out that generally agreed depreciation schedule for GPUs (used to be 3 years, now 5 years by places like Coreweave) is still too conservative since GPU rental prices for 5 year old chips are higher now than when they were new (!!) All of this makes the rest of the math in the comment incorrect by at least an order of magnitude and under some scenarios possibly 2 orders of magnitude! That's not a small error!
- manquer 5mo agoOne factor to consider , the base will not remain the same over the next 5 yearts. Every generation of developer tooling that increase of absolute code throughput creates a new class of developers (and users). Always been the case since first compilers, through eras of frameworks to today, and the skill level needed to be one has dropped. In mid/late 80s only Master / Doctorate level Comp Sci professional could write any applications. It dropped to undergrad and just Information Technology engineers and comp sci theory became mostly optional and dropped further to any college level educated with some training and has been trending below with no/low code tools like retool pre 2022, that was before agent codegen services such as v0/replit and so on. The next generation developers will not produce applications and architecture as previous generations did, just as we most of us here don't produce the level of quality that pg did when building this platform[1] , but as long as the user can find value it doesn't matter as countless enterprise applications of middling quality already prove today. All this to say the 200M/30M numbers will not remain the same is the thesis for these businesses, will it change by large enough at a fast enough pace to justify the capex, I don't think so either. However web 1 then 2.0 , saas and mobile revolutions were pretty quick with new class of users and developers so not completely unrealistic . [1] While HN is a heavy outlier with its custom lang lisp implementation, there are any number of examples from previous eras that are more moderate in choices but written with solid architecture with skill levels would be hard to find in today's generation founders.
- hgoel 5mo agoThe fuck is going on with HN that a comment making up completely fantastical numbers is on top?
- orphea 5mo agoPerhaps it's not only CEOs who are delusional.
- davnicwil 5mo ago> Most people I know cite +20%-40% velocity Seems roughly right, that does seem to be about the boost in the most well-suited cases where you essentially know exactly how to solve the problem, the problem won't change much, and it's truly a matter of just churning out the implementation. In that case precisely prompting, doing the review & nudge loop, can be a pretty nice (nice, still not game changing) speed boost over literally typing out the code to match the design in your head. The less optimistic view though is that most things you build aren't like that. Even if they seem like it first. These things get booked as a nice speed boost, but you'll only find out much later they weren't. A confounding factor is that it seems like many people not in the detail of building software do seem to think of most to all things are like that, even before AI assisted coding. Not much need to say more - see the entire history of the 'agile' movement for evidence of this. And because most things aren't like that, I actually struggle to see fundamentally how more than 20-40% will ever be achieved (short of the ever-present deus ex machina of AGI argument), simply because the generation is already really good for these types of things. So since things like this aren't going to increase in overall proportion of things to be done, I don't see where the overall extra gains come from by models improving at this point.
- ai_fry_ur_brain 5mo agoAlso hardware will be obsolete or dead in 5 years, and warrantys are 3 years from Nvidia. Ask crypto miners how these kind of hardware economics work. Numbers have to keep going up all around. Its a fundamentally broken business model unless prices increase 10x
- notepad0x90 5mo agoconsider cloud spending vs on-prem before the great cloud migrations. people are spending a lot more for cloud services now. I hear conflicting things about finances, some have a different opinion, that it won't be written down so long as more funding comes in and revenue keeps increasing. it isn't like how you take mortgage or business loan, it isn't even a loan it's an investment funded by loans. So long as the investment is still promising, what are they going to do? destroy its value by calling in trillion dollar loans?
- rsalus 5mo agothey need to make 5t-10t back, but not necessarily through selling tokens. as we can see, the frontier labs are making vertically integrated products. their revenue is no longer strictly tied to inference.
- gz5 5mo agothere are many paths towards ROI and ruin. but towards ROI: + LLM-powered robotics, autonomous, IoT, smart manufacturing + LLM-powered biotech, healthcare, genetic engineering, medicine + Recursive model improvement + Multiply the # of devs (software truly eats world) + Exponential increases in model performance / cost decrease (algorithms, power, infra, chips, architectures, etc.)
- zaphirplane 5mo ago> 200m knowledge workers in the world, 30m developers 1 in 6 knowledge worker is a developer ! Surely that’s too high thou explains the job market
- unmole 5mo ago> They've got, ballpark, $5t to $10t What are you basing this on? For reference, Anthropic raised ~$70 billion in total and OpenAI ~$190 billion. Why do they need to make 20-40x that?
- asfkasdfasdadf 5mo ago[dead]
- aaron695 5mo ago[dead]
- oblio 5mo agoAll the planned infrastructure commitments. At least for OpenAI I think they're supposed to spend $300+bn in the next few years.
- unmole 5mo agoI still don't understand why that means they need to make 5-10 trillion over the next 5 years.
- oblio 5mo agoI think the original argument is too limited in its scope. The wider AI market, which is primarily fueled by OpenAI, Anthropic, Google and the large frontier labs (are there any other in the West, except for these 3?) is spending how much... $900bn this year in DC buildouts? After the spent $500bn last year and they're probably planning to spend just as much the next few years if things go remotely their way. So yeah, I wouldn't be shocked that in the 2023 - 2033 timespan total AI investment worldwide will be around $5tn, maybe even going towards $10tn. All that money will have to be repaid, and it will have to be repaid 10x, otherwise heads will roll. The enshittification we've seen so far is nothing compared to what's coming.
- neural_thing 5mo ago
- jatora 5mo agoimo if your developers arent at least 2x as productive, then something is being done wrong on the employees part and/or the organization's. cli tools are ridiculously powerful provided you were an actual developer before using AI. Maybe it's just me being (trigger warning from me providing an honest self assessment) very intelligent + a generalist, but i went from only full stack webdev and .NET to being able to implement an end-to-end LLM training pipeline (data curation, tokenizer, pretrain, sft, DPO - using ~$100 in cloud compute to train a class-competitive 1B STEM model)...and a full economic financial modeling and quant analysis application that pulls up to date economic, economic, news, stock data from the entire world and uses Dagster to orchestrate tech ical indicators and fundamentals and signals... and i did these things for learning and for fun. i built my own sublime text and obsidian replacement. i built my own reddit/twitter/hackernews/substack/news aggregator. i built countless other useful tools and utilities for me personally and for work I build more that empowers multiple departments. Ive built 2 browser games, one already released to great reviews and 100k+ hours played. Ive built a tool on top of claude code that does ~60% of my job. Ive run data analysis on company financials for forecasting that have been refined and are producing very accurate predictions. Ive built competitive analysis tools and trackers. All of this in 3 years. The projects are all clean, documented, with great code practices and modularity. A purist would surely consider some of the code slop. But it all works completely and fills real needs. This is a huge shift. Anyone not realizing it yet is just simply behind the curve. I would not have accomplished 1/10 of this without AI coding. I went from copying code into and out of browser chats for 2 years before getting on the CLI train, and it is absolutely ridiculous the ROI you get from subscriptions to Claude or Codex.
- jauntywundrkind 5mo agoGiven what costs are and availability of parts, that 5 year write down is not in practice going to be the case. Maybe tax wise perhaps but especially for big fancy expensive multi million dollar 100-500kW racks these things are going to stick around for a while, I think.
- kopirgan 5mo agoDepreciation starts on day 1 and most likely they IMHO dont have 5 years. They dodged the deepseek bullet but who knows what is out there that will make all of this investment essentially worthless?
- QuiEgo 5mo agoAt some point, if we reach stability on the models, we'll start getting silicon optimized for individual models. They are optimizing for time to market, not efficiency right now. I don't know how much it will move the needle on the cost math, but at this scale any improvement has a crazy multiplier.
- cm2187 5mo agoBut that means going back to "80% profit margin" Jensen and further digging your capex hole. The benefits would have to pay not only for current capex but also past capex. But by then, I will be able to go one line down in my dropdown menu to switch to a newer LLM provider who doesn't have to amortize those past capex.
- QuiEgo 5mo agoYes, the whole thing feels dot comish. I’m betting there will be a few (maybe only 1-2, like what happened to search) winners, and everyone else is in for a bad time. It’s the same dynamic too: the winners are going to win so big that everyone wants to get their money in for a chance at a piece of the pie.
- quality_life 5mo agoAlso, with announcements of replacing developers with AI and consequent job losses, who is going to use the tokens? AI using its own tokens to produce code?
- AndrewKemendo 5mo agoYour severely underestimating the idea that people are just not going to use developers for certain things in the future For example I don’t anticipate somebody making a living off of making website ever again Somebody with absolutely no technical experience who needs a website for their business can now make one with almost no money whatsoever. That’s good enough for their business. and the code can be totally shit and it does not matter because it’s meeting their business objectives. I am seeing this in the wild and I’m paying money to companies that have these types of websites and because it doesn’t matter I don’t need for the website to work perfectly on all my devices all I need to be able to do is pay them through the website which is what they need me to do and our transaction is done. Don’t forget ultimately the people who pay technologists right now are primarily advertisers work on hard problems is going to continue to be some tiny fraction percentage of the software engineering discipline just expect a total bloodbath because the goal isn’t developer productivity the goal is that “I don’t need to pay somebody $200,000 a year to build a website authoring tool like WordPress.”
- simonw 5mo agoWhy would a small business use a coding agent to build a custom website when they could use something like Squarespace or Shopify with prebuilt templates that mean they have to know even less than if they were to use some kind of chat UI?
- AndrewKemendo 5mo agoCause it’s still easier and cheaper apparently This is the most recent example I found last week for a local barber: https://news.ycombinator.com/item?id=48166050 https://news.ycombinator.com/item?id=48166050 They seem to be using Manus: https://manus.im/ https://manus.im/ And my other assumption is that it immediately integrates with IG/Facebook which is where they do a lot of their marketing I see no reason that trend is going to slow, especially if you can go to meta to manage your entire business marketing. Regular people running business just want fast cheaps and good enough.
- fulafel 5mo agoThe most often cited figure for knowledge workers seems to be 1B, an order of magnitude difference to your assumption. Also, according to https://isaiprofitable.com/ https://isaiprofitable.com/ total industry spend is also an order of magniture less than what your assumption is. So in your model 0.2% of knowledge worker salaries instead of 5%, IF all the AI players win the investing gamble and do infact make back their money.
- bwhiting2356 5mo ago> 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. When you break it down like that it seems reasonable. I'm spending about $5k/mo on tokens, seems more and more normal.
- 3abiton 5mo agoNot to mention the competition: chinese open-weight models and open-source harnesses. Qwen3.6-(27B and 35B) have proven to be worthy and capable of running locally. I am confident more SMEs would look into this as a solution given the ballooning costs of API usage. You get a decent setup with an RTX 6000 Pro.
- karlkloss 5mo ago"5% of every knowledge workers salary to go into tokens. 20% if you're a developer" Not unreasonable. I'm a hardware developer, and my employer spends ~10% of my salary on software tools. Add hardware tools and their maintenance and it's more like 30%.
- vayup 5mo ago> They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. Depreciation and write-offs are about accounting models. Hardware will still be running after five years and still be making money. They may not be as efficient as the new hardware, but they will still be making real money even though they are valued at $0 in the books.
- oblio 5mo agoGPUs are driven really hard plus they use up a ton of energy and water, they cost a ton to run.
- sberens 5mo ago> They've got, ballpark, $5t to $10t to make back in the next 5 years OpenAI's spending commitment is in the ~1T range for the next 5 years, and Anthropic is ~300B. If they continue to show strong growth, they likely need to be at 100-300B in revenue/yr to support their yearly payments + financing, not 1T.
- __alexs 5mo agoI don't think the unit economics are too terrible. Expensive, but not impossible. 200m knowledge workers in US and EU. Total salary around $15T/year. $1T/year in token spending is about $5k/year per person. A big number, but not totally mad. That's the low end for office space per person for example. Probably close to the existing SaaS spend per person for a lot of roles. We are still early in the deployment cycle for these tools so I would expect them to get better and also cheaper too.
- AdamN 5mo agoIt's worth noting that if each developer is 20% more productive with AI (let's take that as a premise and not dispute it), then it makes sense to go even further and reduce human headcount by more since the communication overhead of having 25% fewer developers is in and of itself a force multiplier. tldr; 10 developers with 20% more 'productivity' can be replaced by 7.5 ideal developers and more like 6 or 7 developers due to the benefits of simply requiring less organizational communication. I still think the ideal team size is unchanged however and that's 7-10 people. Note that teams aren't necessarily the same as direct reports. A CEO for instance has a certain number of reports and a leadership 'team' but they're not a team in the traditional sense since they are more about making good decisions and collaborating on specific things but mostly about leading their own orgs that have vastly different skillsets from eachother.
- raxxorraxor 5mo agoPlus, at some point there are less tokens because local models being optimised and can work with protected information. For enterprises that want an AI with a knowledge base of internal documents, this becomes more interesting by the day.
- kdheiwns 5mo agoWe're going to reach a point where these companies stop asking for money and start mandating it. They've got a vice grip around the nuts of many governments and loads of companies have gone all in on investing in these slop heaps. At some point, companies are going to start removing basic features. Governments and essential services are going to make people go through chatbots to get basic service. They're going to require AI to validate stuff that's already automated and working fine. Google search? That'll be all AI (and I guess they're already rolling it out). Dentist appointment? Going to need to do it through some AI app that requires an account and tokens "for a better patient experience". Verifying your ID when buying alcohol? Going to need AI to scan it and take 90 seconds to determine whether it's real. And it'll say you're an 7 year old farm worker in rural Botswana, so you can't get alcohol. And they're going to milk money at every level of this.
- AYBABTME 5mo ago[dead]
- smrtinsert 5mo agoLet's skip to the part where they put the taxpayer on the hook for a bailout as an industry since they integrated everywhere with big promises
- rgrieselhuber 5mo agoI hear this and I keep wondering what I’m missing. My productivity has shot through the roof over the last year as a result of having these tools. I’ve been able to unlock projects that I’ve wanted to do for years.
- onceonceonce 5mo agoThe "+20% velocity" framing misses what's actually shifting.
- tim333 5mo agoI don't think the maths works like that. They have raised ~$200bn so far and need to make that back. Saying they need to make $5 to $10tn isn't really real. They might need that to meet some extravagant Altman projections but not to justify what they have actually spent.
- lsy 5mo agoYeah, claiming “product-market fit” on coding assistants for this multi-trillion dollar capital expenditure seems premature. Anthropic will post one and only one quarter of “operating profit” (aka losses after taxes and debt obligations) on the back of free-for-all spending by enterprise and engineer tokenmaxxing, neither of which will last. The investment was commensurate to a world-eating AGI, and if all that comes out of it is coding agents and slightly better enterprise software, I don’t think that makes up for the money spent.
- btown 5mo agoThe real question is: can you incentivize a non-tokenmaxxing Uber to spend the same amount on AI as they were when tokenmaxxing, just with fewer tokens and higher per-token costs? Even with plateauing improvement in frontier models? I think the answer may be yes. And part of my reasoning for this is: the only system capable of actually fixing bugs in vibe-created code is an LLM. If we humans couldn't write it without assistance, we certainly won't be able to debug it without assistance. So there's a real stickiness here. We're signing pacts with demons - we have to, if we want to outcompete the other warlocks - and those pacts are written in the very size of our codebases.
- antonvs 5mo ago> ... against the actual work their company cares about doing. [...] stuff that matters This is a key point. Some engineers are having fun doing e.g. greenfield stuff with AI that they never would have had time for otherwise. Whether the company cares about that is another question. It's related to Goodhart’s Law. If AI token usage is a target, then you're going to get a lot of token usage, but it's not likely to correlate well to improved business outcomes.
- missedthecue 5mo agoWhy 5 years? What happens in year 6?
- j45 5mo agoThere's a lot more things that are going to be built that weren't built before as well.
- lucamark 5mo ago[flagged]
- projectazorian 5mo ago> That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. 20-40% sounds about right for me, today. Maybe 40-60% on a good day. But a lot of the reason it's not higher comes from harness gaps and org processes that haven't caught up. All of that will get fixed with time.
- lofaszvanitt 5mo agoDoesn't matter, it will be pushed and forced down people's throats because someone invisible thinks it's the new way forward. And for that you need more money for NVDA and the like, and now people have to be made cultists in order to let the money flow in. Same happened and happens in gaming. The gamers "invested" into NVDA by eating all the bullshit about ray tracing and the like. And they kept buying all the crappy 1000$+ gpus because youtubers said that the extra 1000 dollars worth those +15 fps plus the ray tracing....