The thing is, it's not actually that hard to spend at that kind of rate.
I wouldn't say this was the norm, but I have burned through £1k of tokens in a couple of days before. And, on that same gig, I realised a test I was considering running would burn £2.5k worth of tokens over the course of a few hours so spent a couple of hours of my own time re-engineering it to get that down to £150.
The point is that I don't necessarily know that spending a shitload of money on tokens really tells us anything useful. If he's getting a return on that investment, fine, whatever.
Obviously most of us couldn't afford to spend that much ourselves, no matter how much value it might deliver, and many of our employers wouldn't be too happy if we spent it on their dime either. Equally, if you can, and it's delivering real value, then I don't see why you wouldn't?
Yup, run multiple agents on expensive model in loop via API.
You can do it if your employer has endless pockets.
Example: $30/1M input tokens (I don’t count output or cache, for simplification), you have several daily agents for everything => 3M tokens daily per agent * 10 agents ~> $900/day => $328k/year (API spending)
At what point do you buy a Mac studio or AMD Gorgon Halo and try running some of these tasks in local models? Surely don’t need frontier models for all this work.
You definitely don't need frontier models for all this work.
And, in fact, I got it from £2500 to £150 by careful model selection (I ran a trial over a small dataset with different models until I found the least expensive/capable model that would reliably do what I needed), using a local model for one step, and paring down the inputs as well so the token count plummeted.
I use a supervising agent, so if my sleeping agent has insomnia, the supervisor puts it back to sleep. It's helpful to have the supervisor put on relaxing music or read it something boring [1].
If his brain is the thing malfunctioning, then his brain may not be capable of (1) correctly diagnosing the problem as a lack of sleep or (2) honestly prescribing "do things to get better sleep" as the fix.
People in psychosis don't exactly weigh all of the options with a level head. He may not recognize that he has "cyber psychosis" or that his lack of sleep is a bad thing.
My take is that disclosures like these are always humble brags and/or marketting (look at how much I can afford to spend) with minor complaints rolled in to disguise this fact.
> “It’s too expensive right now,” he said, adding that he knows the amount of money he spends on AI agents is “a crazy privilege that not everyone can do.”
> As an early OpenClaw adopter who is now a power user, Tan says one thing he’s learned is not to treat AI agents like traditional software. Some people are so worried about “repeatability and safety that they actually trade off all of the beautiful parts of working with an AI agent, which basically can be so similar to a human,” he said.
This is insane. He's turning the failure of his AI assistants to do what he wants every single time and to do it in a safe manner into a positive thing. Failure as a positive!
To be fair, using the scientific method to disprove superstitions is what the Enlightenment was all about and that is the most significant engine of growth and flourishing humankind has known.
That said, I approach AI with deep skepticism. I try to learn it, including its strengths and weaknesses. But I don't blindly trust it.
Coincidentally, my stock brokerage just yesterday sent an email reminding users that anything their agents do using the user's credentials is the responsibility of the user.
Looks like this is getting downvoted, but it is absolutely true.
Garry Tan is fully aligned with Elon Musk in going after MacKenzie Scott's charitable giving, making spurious arguments that she's doing it in the wrong way when they are all just running cover for the fact that she's one of the few at that level of wealth being charitable at all these days.
Silly woman, she should give her money away the right way, which I guess is by attempting to buy political power.
https://news.ycombinator.com/item?id=47042593 - HN discussion (5 comments) on that particular rant of his. And it looks like you were one of the few people to comment on it, so really this is for other people who are missing the context of our comments.
> ...his agent also helps him run his life. “It’s read all of my email and all of my Dropbox. It’s read, like, all of my Apple Notes, even my therapy notes going back 20 years”.
> He describes using AI agents as getting help with “almost anything that you do in your day-to-day life. (...) Almost anything you want to do, it knows you, and it’s there to help. And it will actually sort of run ahead and say, ‘What about this?’ Or it’ll help you see around corners.”
Wow, impressive. Both the capabilities and how much he's willing to share.
Is it worth $17k per month? For me, absolutely not. But people spend more on luxurious cars and such, so if you've got money to spare...
> Y Combinator is also using an agent that is “rebuilding the way we operate at YC. We now have an internal AI agent, for instance, named Stray Light that kind of has a personality, and then it has a company brain. It actually has the total context of every founder we’ve ever backed, anyone who’s ever emailed us, like all the applications.”
Holy anthropomorphization. But besides that, what's the goal of doing this? Keeping a handy overview of when and why someone said something?
Still doesn't explain where $17k of tokens is going. I can believe someone could burn that many tokens, but most of what he's described there could be managed pretty easily on one of the $100-200 a month subscriptions I'd think.
The only way I can imagine to burn that many tokens is just to run every task fully through the most expensive LLM with no real strategy. Like indexing emails should be a combo of scripts and small summarizing prompts I'd think.
Naming your internal AI agent after the massive run down home of an uber rich but probably insane family of confusing clones who made god level AIs (from Neuromancer)... Classy.
> Holy anthropomorphization. But besides that, what's the goal of doing this? Keeping a handy overview of when and why someone said something?
You'd be surprised how important such an overview can be in relationship-based businesses. People spend a lot of time trying to track down a vague memory they have of someone telling them something. CRM platforms are big for a reason, after all.
Is that how these figures are being calculated? Because if so, that's laughable. I always interpret those to mean that they are literally paying $200k/year to Anthropic, not ~$2k.
Not only that. They simply multiply tokens used with API price per token, but ignore that about 90% of tokens are cached ones that are significantly cheaper.
Headline aside, I agree with him wholeheartedly that the future of AI is personal agents, and that costs have to come down for that to happen.
Not cloud costs, though; consumer costs. These agents must run on-device for privacy protections, because anything less will be a global non-starter. That means we need models that excel on phones, tablets, laptops, and desktops; we need home compute modules to run larger, “frontier”-class models for bigger tasks but without guzzling electricity (the Mac Mini’s power envelope is an ideal target); we need smart harnesses that can foist off inference to bigger models elsewhere on your private network of devices as needed without the user prompting for specific thinking modes or model names. All of this has to happen automatically, privately, securely, without leaking data to advertisers or surveillance companies.
It’s hard work, but it’s definitely the future of AI. I would argue the business case is solved with being able to build bespoke stacks of kit and run models through neocloud providers with ZDR policies. It’s the consumer angle that’s hard to crack, because everyone wants a repeat of Web 2.0 for ad-dollars instead of a privacy-centric modern tech stack that forces companies into lower revenue streams.
I don’t think the privacy-centric vision is going to happen. Very few non-tech people care enough about their privacy to figure out the necessary infrastructure.
The future of personal assistants is most likely akin to Muse Spark, and yes I expect Meta is training on all of those interactions and using them to target ads.
Counter-point, they can't serve as a knowledgeable discussion partner, programmer, search engine, or your personal psychologist. Not saying that they should.
That usage probably comes from a couple of 200$ a month subscriptions. Hardware to run something that approaches frontier at acceptable speed is at least a million.
> Please don't complain about tangential annoyances—e.g. article or website formats, name collisions, or back-button breakage. They're too common to be interesting.
The common trope is, "keep an eye on what the rich want."
Gary is rich. Let's assume now, he spends between $10-20K/month USD on tokens. Whether he gets overwhelming tangible value out of that token spend is immaterial.
What he's getting out of it is a mix of social signaling value and actual perceived productivity. I don't know, but I doubt he has measuring the ROI on the token investment.
Much like someone gets various kinds of value out of a a personal tutor for their child. Or a high powered executive who continues to request budget for a "Chief of Staff" and related personnel in 2026.
The question is whether this is signal, or noise. Will everyone who has the budget aspire to spend money on tokens as a subtle way of projecting value with some tangible benefit? How long of a runway does this have?
Much like a Chief of Staff office, there's more to manage...but you you get some tangible benefit by having people to whom you can [in theory] delegate tasks and trust they will be completed. To some degree none of this matters, value is in the eye of the beholder.
What a time to be alive. Rich people continue to spend money with abandon, just on different things.
Edit: I work at technology company. If I were spending $10-20K/month USD in tokens I would immediately get flagged by Finance and receive a note from my EVPs Chief of Staff/Business Admin. My usage and prompts would get audited and I would be asked to create a report justifying the business impact of the spend.
Note, however, that Garry also holds a much longer lever in his hands. It's very likely that he does get a huge ROI from the token spend because if it helps him make just one slightly better investment decision per year, that's millions in return.
The rich always have leverage. The questions I'm asking are broader market questions...
Does it matter that he's spending this much money on tokens? What's the derived signal?
Why isn't he spending more?! Spend on intelligence seems to have no limit, and he's rich after all right?
What's the limiting rate of return on token spend for the rich?
Does Gary represent an archetype of other rich people who also want to spend money on tokens at that rate? ...if not more?!
The thing is, it's not actually that hard to spend at that kind of rate.
I wouldn't say this was the norm, but I have burned through £1k of tokens in a couple of days before. And, on that same gig, I realised a test I was considering running would burn £2.5k worth of tokens over the course of a few hours so spent a couple of hours of my own time re-engineering it to get that down to £150.
The point is that I don't necessarily know that spending a shitload of money on tokens really tells us anything useful. If he's getting a return on that investment, fine, whatever.
Obviously most of us couldn't afford to spend that much ourselves, no matter how much value it might deliver, and many of our employers wouldn't be too happy if we spent it on their dime either. Equally, if you can, and it's delivering real value, then I don't see why you wouldn't?
> would burn £2.5k worth of tokens over the course of a few hours
details please, if it's interesting
Evaluation loops do this easily. You have to run hundreds of reasoning jobs in parallel and very quickly you can torch thousands of dollars.
Yeah, it was basically this, and running a whole lot of agents concurrently to churn through the dataset faster.
Yup, run multiple agents on expensive model in loop via API.
You can do it if your employer has endless pockets.
Example: $30/1M input tokens (I don’t count output or cache, for simplification), you have several daily agents for everything => 3M tokens daily per agent * 10 agents ~> $900/day => $328k/year (API spending)
Any 3D work in blender can burn that easily. Add video editing to that mix in any capacity.
At what point do you buy a Mac studio or AMD Gorgon Halo and try running some of these tasks in local models? Surely don’t need frontier models for all this work.
You definitely don't need frontier models for all this work.
And, in fact, I got it from £2500 to £150 by careful model selection (I ran a trial over a small dataset with different models until I found the least expensive/capable model that would reliably do what I needed), using a local model for one step, and paring down the inputs as well so the token count plummeted.
YC seems big on quantitative metrics. Is there anything that says he is more efficient than 3 or 4 years ago. Is YC as a whole?
> he’s suffered from “cyber psychosis” and sometimes barely sleeps
Sleep is one of the most important things in the world. Why not have the agents work while you sleep?
> Why not have the agents work while you sleep?
Even better, why not have the agents sleep for you?
EDIT: for those who say this is not realistic, I've had Claude sleep for 10 hours in just 30 seconds. Saved me an entire night.
Care to share your agent setup and harness? I've been trying to do something similar but my Claude only sleeps for about 2 hours before waking up.
I use a supervising agent, so if my sleeping agent has insomnia, the supervisor puts it back to sleep. It's helpful to have the supervisor put on relaxing music or read it something boring [1].
[1] https://www.amazon.com/Million-Plus-Random-Digits-Symbols-Gu...
If his brain is the thing malfunctioning, then his brain may not be capable of (1) correctly diagnosing the problem as a lack of sleep or (2) honestly prescribing "do things to get better sleep" as the fix.
People in psychosis don't exactly weigh all of the options with a level head. He may not recognize that he has "cyber psychosis" or that his lack of sleep is a bad thing.
That's probably exactly why. Some of my latest nights have been attempting to prepare a long-running overnight task for an agent.
It was productive, but as you say, it's dangerous to gamble with sleep.
I can't recall software being conspicuous consumption until the advent of the AI token. Maybe the first "I am rich" app in the app store for $999.
Pretty sure Joel Spolsky said “we purchase the best machines money can buy for our developers” like 20 years ago. So it’s hardly a new concept.
I personally recall hardware flexing going back to SGI, but nothing like "look at my salesforce spend".
I've seen the other side of that coin: "my program is blazing fast in my machine, I don't know why those naggy users are complaining!"
Superchats and other livestream gifts
Agree I meant mostly in the vein of "look how much I can spend on XYZ because I'm rich and I can" with questionable value.
AWS spend and other service bills?
My take was when people would post those large bills it was mostly to complain about Amazon or a process having gone wild for comedic purposes.
My take is that disclosures like these are always humble brags and/or marketting (look at how much I can afford to spend) with minor complaints rolled in to disguise this fact.
> “It’s too expensive right now,” he said, adding that he knows the amount of money he spends on AI agents is “a crazy privilege that not everyone can do.”
He’s gotta pump those numbers up, those are rookie numbers in this racket
> As an early OpenClaw adopter who is now a power user, Tan says one thing he’s learned is not to treat AI agents like traditional software. Some people are so worried about “repeatability and safety that they actually trade off all of the beautiful parts of working with an AI agent, which basically can be so similar to a human,” he said.
This is insane. He's turning the failure of his AI assistants to do what he wants every single time and to do it in a safe manner into a positive thing. Failure as a positive!
To be fair, using the scientific method to disprove superstitions is what the Enlightenment was all about and that is the most significant engine of growth and flourishing humankind has known.
That said, I approach AI with deep skepticism. I try to learn it, including its strengths and weaknesses. But I don't blindly trust it.
Coincidentally, my stock brokerage just yesterday sent an email reminding users that anything their agents do using the user's credentials is the responsibility of the user.
Just 200k a year? If this amount is for some folks news worthy get a reality check.
That's only 1 SWE or half with sloppy results.
So what has he built?
A site where he complains about rich people being charitable, among other things.
Looks like this is getting downvoted, but it is absolutely true.
Garry Tan is fully aligned with Elon Musk in going after MacKenzie Scott's charitable giving, making spurious arguments that she's doing it in the wrong way when they are all just running cover for the fact that she's one of the few at that level of wealth being charitable at all these days.
Silly woman, she should give her money away the right way, which I guess is by attempting to buy political power.
https://news.ycombinator.com/item?id=47042593 - HN discussion (5 comments) on that particular rant of his. And it looks like you were one of the few people to comment on it, so really this is for other people who are missing the context of our comments.
https://garryslist.org/posts/mackenzie-scott-s-26-billion-su... - The rant itself.
"Garry's List" for dark money (this is an established political term, look it up!) donations. Basically you can donate anonymously to a SuperPac.
Software? I'm not aware of anything.
Psychosis?
> So what has he built?
"Garry, this is a text file".
https://www.youtube.com/watch?v=Q6nem-F8AG8
Finally, the perfect yes-man, the thing execs and VCs always wanted.
a bubble.
> ...his agent also helps him run his life. “It’s read all of my email and all of my Dropbox. It’s read, like, all of my Apple Notes, even my therapy notes going back 20 years”.
> He describes using AI agents as getting help with “almost anything that you do in your day-to-day life. (...) Almost anything you want to do, it knows you, and it’s there to help. And it will actually sort of run ahead and say, ‘What about this?’ Or it’ll help you see around corners.”
Wow, impressive. Both the capabilities and how much he's willing to share.
Is it worth $17k per month? For me, absolutely not. But people spend more on luxurious cars and such, so if you've got money to spare...
> Y Combinator is also using an agent that is “rebuilding the way we operate at YC. We now have an internal AI agent, for instance, named Stray Light that kind of has a personality, and then it has a company brain. It actually has the total context of every founder we’ve ever backed, anyone who’s ever emailed us, like all the applications.”
Holy anthropomorphization. But besides that, what's the goal of doing this? Keeping a handy overview of when and why someone said something?
Still doesn't explain where $17k of tokens is going. I can believe someone could burn that many tokens, but most of what he's described there could be managed pretty easily on one of the $100-200 a month subscriptions I'd think.
The only way I can imagine to burn that many tokens is just to run every task fully through the most expensive LLM with no real strategy. Like indexing emails should be a combo of scripts and small summarizing prompts I'd think.
Naming your internal AI agent after the massive run down home of an uber rich but probably insane family of confusing clones who made god level AIs (from Neuromancer)... Classy.
That was my thought --- an odd and offputting choice of identity
When they show you what they are, believe them.
“ Holy anthropomorphization. But besides that, what's the goal of doing this?”
Because they can. It’s as simple as that. To find meaning, to feel in control, to win. To dominate.
> Holy anthropomorphization. But besides that, what's the goal of doing this? Keeping a handy overview of when and why someone said something?
You'd be surprised how important such an overview can be in relationship-based businesses. People spend a lot of time trying to track down a vague memory they have of someone telling them something. CRM platforms are big for a reason, after all.
He must be the most annoying person to try to interact with. Clodslop for days.
Come on. If you have a Claude Max 20x plan ($200/month) you're massively subsidized and your API cost is anywhere from $5000-14000 per month.
(Figures vary, see e.g. https://www.linkedin.com/posts/christham_4-weeks-on-claude-2... for $13,700/mo.)
If you hit your limits on two Max 20x plans, you could very well be exceeding $300k/yr in token use at current API rates.
Is that how these figures are being calculated? Because if so, that's laughable. I always interpret those to mean that they are literally paying $200k/year to Anthropic, not ~$2k.
Not only that. They simply multiply tokens used with API price per token, but ignore that about 90% of tokens are cached ones that are significantly cheaper.
Kind of low isn't it?
I wonder how many of those agents get lost in a loop and just uses tokens, asking the same questions over and over and responding and asking
Headline aside, I agree with him wholeheartedly that the future of AI is personal agents, and that costs have to come down for that to happen.
Not cloud costs, though; consumer costs. These agents must run on-device for privacy protections, because anything less will be a global non-starter. That means we need models that excel on phones, tablets, laptops, and desktops; we need home compute modules to run larger, “frontier”-class models for bigger tasks but without guzzling electricity (the Mac Mini’s power envelope is an ideal target); we need smart harnesses that can foist off inference to bigger models elsewhere on your private network of devices as needed without the user prompting for specific thinking modes or model names. All of this has to happen automatically, privately, securely, without leaking data to advertisers or surveillance companies.
It’s hard work, but it’s definitely the future of AI. I would argue the business case is solved with being able to build bespoke stacks of kit and run models through neocloud providers with ZDR policies. It’s the consumer angle that’s hard to crack, because everyone wants a repeat of Web 2.0 for ad-dollars instead of a privacy-centric modern tech stack that forces companies into lower revenue streams.
I don’t think the privacy-centric vision is going to happen. Very few non-tech people care enough about their privacy to figure out the necessary infrastructure.
The future of personal assistants is most likely akin to Muse Spark, and yes I expect Meta is training on all of those interactions and using them to target ads.
> because anything less will be a global non-starter.
I beg to differ.
I spend that much at API rates with a couple subscriptions
"Do my job, make no mistakes"
That's basically gstack
hmm isn't that the job of a concierge, or an assistant ?
Didn't you mean to use past tense? "Wasn't that the job ...."
Touché.
Counter-point, they can't serve as a knowledgeable discussion partner, programmer, search engine, or your personal psychologist. Not saying that they should.
Why not buy hardware at that point?
That usage probably comes from a couple of 200$ a month subscriptions. Hardware to run something that approaches frontier at acceptable speed is at least a million.
he just needs to put the finishing touches on g-stack and then programming will be solved. just another $50k will do it i think!
Website looks still like shit
I think it looks neat and simple.
Also...
> Please don't complain about tangential annoyances—e.g. article or website formats, name collisions, or back-button breakage. They're too common to be interesting.
https://news.ycombinator.com/newsguidelines.html
The common trope is, "keep an eye on what the rich want."
Gary is rich. Let's assume now, he spends between $10-20K/month USD on tokens. Whether he gets overwhelming tangible value out of that token spend is immaterial.
What he's getting out of it is a mix of social signaling value and actual perceived productivity. I don't know, but I doubt he has measuring the ROI on the token investment.
Much like someone gets various kinds of value out of a a personal tutor for their child. Or a high powered executive who continues to request budget for a "Chief of Staff" and related personnel in 2026.
The question is whether this is signal, or noise. Will everyone who has the budget aspire to spend money on tokens as a subtle way of projecting value with some tangible benefit? How long of a runway does this have?
Much like a Chief of Staff office, there's more to manage...but you you get some tangible benefit by having people to whom you can [in theory] delegate tasks and trust they will be completed. To some degree none of this matters, value is in the eye of the beholder.
What a time to be alive. Rich people continue to spend money with abandon, just on different things.
Edit: I work at technology company. If I were spending $10-20K/month USD in tokens I would immediately get flagged by Finance and receive a note from my EVPs Chief of Staff/Business Admin. My usage and prompts would get audited and I would be asked to create a report justifying the business impact of the spend.
Note, however, that Garry also holds a much longer lever in his hands. It's very likely that he does get a huge ROI from the token spend because if it helps him make just one slightly better investment decision per year, that's millions in return.
The rich always have leverage. The questions I'm asking are broader market questions...
Does it matter that he's spending this much money on tokens? What's the derived signal? Why isn't he spending more?! Spend on intelligence seems to have no limit, and he's rich after all right? What's the limiting rate of return on token spend for the rich? Does Gary represent an archetype of other rich people who also want to spend money on tokens at that rate? ...if not more?!
He has a vested interest in hyping AI / spend because YC overwhelmingly invests in AI startups.