I really can't tell what is going on with AI these days. I hear AI labs claiming theyre profitable or close to it. I hear companies say they're dubious the juice is worth the squeeze. I've seen anecdotal claims of a measurable increase in productivity of 2x in PRs created and merged coming in at cost 20% of engineering employee budget. Others say they're still getting no value (which I doubt). Simon Willison's recent post went into debunking the AI sticker shock claims somewhat. Either way this seesawing between new golden era and the greatest VC money furnace is becoming exhausting. I'd like to see real numbers at this point. Talk is far cheaper than tokens and I'd like to have a workflow that I can rely on being there in six months.
When tokens get correctly priced, all of the insane over-investment in capital will need to draw back: buying data centers, semiconductors, and politicians.
Even then, it won't be right-priced with regard to actual costs. The environmental impact should have been priced in from the beginning. There seems to be a parallel with subsidizing fossil fuels, under pricing them which encourages over dependence, ignoring the real costs society will pay later.
It rather looks like chatgpt/antrophic enterprise tokens and API calls are too expensive. Competition is quite strong on openrouter.
However, the real problem is running wild with token burning. With parallel agents calling subagents you can burn lots of tokens per minute. Especially with thousands of engineers.
We are since at least the 2000s when the world wide web revolution finally made it possible for Google, Apple, Amazon etc... to become the behemoths they are. And maybe even before that.
And the answer is no, because when chief officers succeed it's because of their genius and forward thinking posture, but when they fail it's none of their fault, so they are shielded in an echo chamber that produces such delusions and psychosis.
We use GH Copilot at work and this week sat for a presentation by GH about optimizing token usage and maximizing ROI on tokens used. Anyone else get this presentation? They didn’t have time for questions because they had to run and give it to the next big enterprise on their list…
They basically said that everything is too expensive, you have to watch it like a hawk. It was as if they poured a bucket of cold water on the room. People were wondering how they could do anything faster with all these strategies. And then “sorry no questions. Bye!”
We did not have any presentation yet, but the first serious discussion about the cost of tokens has started on the documentation level. Looking forward to seeing these presentations!
Overheard recently: "Thanks to AI we're producing more code and more MRs, faster than ever, but the milestones aren't getting hit any sooner. Actually the opposite, if anything."
I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...
Goodharts law. The metrics were always measuring the wrong thing, and now that we've finally optimized for the wrong thing successfully management will be forced to admit it and move on to another, slightly different, metric that doesn't actually equate to shareholder value.
It doesn't matter what the line actually measures, just that it goes up.
This is almost entirely on Anthropic and the stupid C suite people trying to push TokenMaxxing. GPT5.5 is much more token efficient, other models are much cheaper, and if used in moderation rather than than trying to get everyone to OpenClaw 24/7 with token leaderboards, it's much more economical.
Also ironically, a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI rollouts by burning tokens on stupid shit. It seems to be working.
The other day I had to read a C-suite guy share how he had an epiphany that spending more tokens did not linearly align with more useful features being output by the teams. He was describing it as this breakthrough moment for him, as if it wasn't glaringly obvious that making the KPI "spend more tokens" would result in inefficient token spending, not massive value for the customer.
It's baffling how these people have entirely shut their ears to all the obvious warnings about this, and are now congratulating themselves for their slightly less psychotic outlook and pivoting to blaming the workers for inefficient usage, after specifically forcing them to tokenmaxx.
>It's baffling how these people have entirely shut their ears to all the obvious warnings about this, and are now congratulating themselves for their slightly less psychotic outlook and pivoting to blaming the workers for inefficient usage, after specifically forcing them to tokenmaxx.
It's not baffling. They are a caste, wholly insulated from the consequences of their own actions.
Almost every company is run in a basic dictatorial way. We almost never discuss it, when there is a wide corpus of political Science analysing the pros and cons of governance models that certainly puts it at the bottom.
(Meaning that it's not just business school indoctrination, but a dynamic they've been raised to expect and uphold. Fixing it isn't simply about convincing them of the folly of their approach, because you're attacking their personal sense of self in doing so. Which, I'm to understand, is a no-no, professionally.)
After ejecting anyone who spoke out or were even publicly hesistant against the hard swerve into "just do maximal amounts of AI stuff above all else", they're now surprised to find that everyone that remains is dutifully excited about the emperor's new clothes, and yet he remains mysteriously exposed to the breeze.
> Almost every company is run in a basic dictatorial way. We almost never discuss it, when there is a wide corpus of political Science analysing the pros and cons of governance models that certainly puts it at the bottom.
Is it not wild that in the Freedom Loving West, we all spend the vast majority of our time as adults living inside tiny totalitarian states?
I think this persists largely because the people atop those tiny states are also the ones behind most of our media apparatus, so they can make it look and feel pretty normal. But that may be a little tinfoil hat of me.
I'm with you that people are insanely hyped about Claude Code in particular when e.g. Codex isn't far behind (and with recent models I actually prefer it).
But I'm going to need a citation for this:
> a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI
The 3 people on reddit doing this don't even register on a company budget. What seems more plausible to me is that budgets were calibrated to spending before agents were actually useful, and late '25/early '26 changed the pattern significantly.
Codex is actually significantly better than Claude Code now, assuming you have a clear idea of what you want to do and how. Claude's secret sauce is that it'll run off and do stuff that's mostly right without a lot of prompting, but that also makes it willful/disobedient and causes it to be bad for "finishing" work, since it'll circle around your objective in an opinionated way.
Yeah, everything is fine until you don’t want to use AI for something because it sucks at that task and then you end up on a PiP because your token burn is low. Why the f*ck are AI Token Use Leaderboards even a thing.
Features that used to take months are now expected in days. Oh you didn’t merge 40 pull requests and deploy to prod 15 times today? Aren’t you using Opus the greatest thing since the invention of the wheel?! What do you mean it’s hard to review 100 merge requests per day? Just have Claude review it! That’s a PiP.
Oh prod is down because people keep deploying code that nobody even freakin’ read? Just have Claude fix it! What do you mean it’s doesn’t work well? Just burn more tokens or you’re on a PiP.
Surely there wouldn’t be malicious compliance by people that would prefer to use the right tool for the job instead of having this crap shoved down our throats by management by threat of termination.
Counterpoint: based on a lot of anecdotes here, the most likely people to burn tokens aren’t GenZ but managers using ChatGPT to respond to questions or otherwise as an outsourcing of their job. There aren’t enough GenZ in the workforce to back your claim in my opinion.
Token efficiency where instead of the AI burning money at 1:3 instead of 1:5 isn’t quite a winning argument.
There's no way managers using LLMs to answer emails are burning tokens at a comparable rate someone trying to utilize inference in production systems is.
Excessive token burning as a tactic to annoy your employer probably does the opposite - it probably makes your employer money.
The more tokens you burn, the more demand for hardware there will be. More demand for hardware means higher stock prices -> more money in your employer's pocket.
The only question is how long that can last. If taken to an extreme, the output of the AI will get worse over time, and if it gets bad enough, for long enough, people will use it less and less, and demand will slowly evaporate.
My point is NOT: I hope this all comes crashing down.
My point IS: tokenmaxing is bad. AND weaponizing it will not have the intended effect, but in fact, it will, in the short term, do the opposite.
> The more tokens you burn, the more demand for hardware there will be. More demand for hardware means higher stock prices -> more money in your employer's pocket.
If you work for NVIDIA, sure, but otherwise, this makes no sense to me.
I'm guessing you aren't invested in any of these stocks. I'm also guessing, to take the perspective of a tokenamxxing GenZ employee, that their bosses are.
Just a week ago, Anthropic barely breaking even was hailed as AI companies being close to profitability much earlier than forecast.
In fact it is all smoke and mirrors, pure mania from C-level executives out of their depth trying to one-up each other with company money, and they aren't even close.
>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns.
This isn't surprising. Ive recently run into quite a few rabbit holes where AI is bad enough that its much more efficient to do it myself. I wanted to refactor some code, gave it a design pattern to go towards, some specific classes and methods, etc. making it a well described problem. AI just couldn't do it satisfactorily. The code was ugly, overly verbose, and after multiple tries with multiple prompts saying to keep things simple. They still would introduce new classes, useless fields, etc.
"An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees."
Like physically, how could this even happen?
Just wait until companies are dependent on on it. When their employees can't think without it. When their AI generated codebase is such a mess they'd need a rewrite to understand it without AI. When they've got AI embedded in all their internal processes and tools. Then massive price hikes will come because they've been bent over a barrel and they'll have no alternative that isn't at least as painful in the short-term as letting the AI company fuck them. The long term won't matter then because any company capable of seeing past the short term wouldn't let themselves get into that position in the first place.
Well, if AI has a massive sticker shock attributed, so we should target the high value roles and should save money, right?
So im looking at CEO, CTO, CFO, and all the chief-something-officer. If LLMs are that totally amazing at thinking, then we should be targeting upper management, not the workers.
That would save a LOT of money for the shareholders! /snark
So it goes. Wage theft dwarfs the amount lost to street-level theft, robbery, burglary, etc., combined. The economic stimulus from correcting even a portion of annual wage theft would represent complete coverage of those violent thefts - economically-speaking, there would be no reason for criminals to carry them out. Why rob a gas station to get your drug money? Everyone around you is making enough extra at work that bumming a dollar here and there covers it. That sort of thing.
But good forbid we actually correct a major social ill at the expense of the people who profit from it.
> Instead, they should focus on using AI to drive revenue.
There is a complete disconnect between wages of employees and company's revenue => Why aren't employees working towards revenue? What a mystery. Children, let's help Elmo solve this mystery.
And then random mass layoffs to make numbers for shareholders look great in quarterly reports. Surely this motivates people work to their fullest potential and to care for company's revenue.
I found this claim interesting so I looked into it. Everything I can find shows that the intuition is accurate.
Companies with EOSP programs outperform those that do not in the market by about 17%.[0] Companies that perform layoffs, despite short-term stock boosts, underperform on a period of years showing a 14% decline in their Return on Assets (ROA) in the years following the layoffs.[1]
Even better there’s a complete disconnect between revenues and metrics we use to measure productivity. Corporate wants to believe there’s numbers you can use to measure knowledge workers like widget makers where there’s really not much that’s effective beyond revenue.
CFO: “Um, this is costing a ton and we’re not seeing savings or efficiency materialize.”
CEO: “Are we getting any value out of this?”
COO: “Not really, and frankly I’m getting annoyed at all the AI slop turning up all over.”
CEO: “OK, well, let’s do a big layoff and then I’ll just say it was because of AI. Hopefully folks won’t blame me for the mess and I’ll just talk about how amazing AI is.”
Lesson #1 from business school : take all credits, put the blame on others, if there no easy scapegoat blame the "economical context"
Lesson #2 and beyond : just see lesson #1, it's enough. You've made it and it's ALL thanks to this amazing business school degree you got, now go profits with your new already wealthy peers.
I really can't tell what is going on with AI these days. I hear AI labs claiming theyre profitable or close to it. I hear companies say they're dubious the juice is worth the squeeze. I've seen anecdotal claims of a measurable increase in productivity of 2x in PRs created and merged coming in at cost 20% of engineering employee budget. Others say they're still getting no value (which I doubt). Simon Willison's recent post went into debunking the AI sticker shock claims somewhat. Either way this seesawing between new golden era and the greatest VC money furnace is becoming exhausting. I'd like to see real numbers at this point. Talk is far cheaper than tokens and I'd like to have a workflow that I can rely on being there in six months.
https://simonwillison.net/2026/May/27/product-market-fit/#th...
This is an important inflection point.
When tokens get correctly priced, all of the insane over-investment in capital will need to draw back: buying data centers, semiconductors, and politicians.
Even then, it won't be right-priced with regard to actual costs. The environmental impact should have been priced in from the beginning. There seems to be a parallel with subsidizing fossil fuels, under pricing them which encourages over dependence, ignoring the real costs society will pay later.
It rather looks like chatgpt/antrophic enterprise tokens and API calls are too expensive. Competition is quite strong on openrouter.
However, the real problem is running wild with token burning. With parallel agents calling subagents you can burn lots of tokens per minute. Especially with thousands of engineers.
>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns.
We should start to question whether soaring CEO salary spending is delivering meaningful results.
Ah, that's not how it works : CEOs are rich so they are successful. They are successful so they are rich. Q.E.D.
Maybe in your fantasy world.
In reality people are rarely rich based on merit alone.
EDIT: Sorry it was a really clever joke.
It's sarcasm, obviously.
I think you missed the joke.
We are since at least the 2000s when the world wide web revolution finally made it possible for Google, Apple, Amazon etc... to become the behemoths they are. And maybe even before that.
And the answer is no, because when chief officers succeed it's because of their genius and forward thinking posture, but when they fail it's none of their fault, so they are shielded in an echo chamber that produces such delusions and psychosis.
We use GH Copilot at work and this week sat for a presentation by GH about optimizing token usage and maximizing ROI on tokens used. Anyone else get this presentation? They didn’t have time for questions because they had to run and give it to the next big enterprise on their list…
They basically said that everything is too expensive, you have to watch it like a hawk. It was as if they poured a bucket of cold water on the room. People were wondering how they could do anything faster with all these strategies. And then “sorry no questions. Bye!”
We did not have any presentation yet, but the first serious discussion about the cost of tokens has started on the documentation level. Looking forward to seeing these presentations!
Overheard recently: "Thanks to AI we're producing more code and more MRs, faster than ever, but the milestones aren't getting hit any sooner. Actually the opposite, if anything."
I wonder how widespread that phenomenon is. Perhaps it's no wonder the prominent actors are trying to rush to IPO...
Goodharts law. The metrics were always measuring the wrong thing, and now that we've finally optimized for the wrong thing successfully management will be forced to admit it and move on to another, slightly different, metric that doesn't actually equate to shareholder value.
It doesn't matter what the line actually measures, just that it goes up.
This is almost entirely on Anthropic and the stupid C suite people trying to push TokenMaxxing. GPT5.5 is much more token efficient, other models are much cheaper, and if used in moderation rather than than trying to get everyone to OpenClaw 24/7 with token leaderboards, it's much more economical.
Also ironically, a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI rollouts by burning tokens on stupid shit. It seems to be working.
Are you saying that making a leaderboard of who is spending the most is going to be expensive?
They couldn't see that coming, but for sure they can predict how the future will be when it's time to sell their "visions" of the world.
Meanwhile, sheep's are going to believe and max their token usage with their own wallet. "You are so be left behind if you're not".
It's a mass psychosis. The only winners here are the hardware manufacturers, like nvidia for instance.
The other day I had to read a C-suite guy share how he had an epiphany that spending more tokens did not linearly align with more useful features being output by the teams. He was describing it as this breakthrough moment for him, as if it wasn't glaringly obvious that making the KPI "spend more tokens" would result in inefficient token spending, not massive value for the customer.
It's baffling how these people have entirely shut their ears to all the obvious warnings about this, and are now congratulating themselves for their slightly less psychotic outlook and pivoting to blaming the workers for inefficient usage, after specifically forcing them to tokenmaxx.
>It's baffling how these people have entirely shut their ears to all the obvious warnings about this, and are now congratulating themselves for their slightly less psychotic outlook and pivoting to blaming the workers for inefficient usage, after specifically forcing them to tokenmaxx.
It's not baffling. They are a caste, wholly insulated from the consequences of their own actions.
Almost every company is run in a basic dictatorial way. We almost never discuss it, when there is a wide corpus of political Science analysing the pros and cons of governance models that certainly puts it at the bottom.
>They are a caste
Sometimes literally.
(Meaning that it's not just business school indoctrination, but a dynamic they've been raised to expect and uphold. Fixing it isn't simply about convincing them of the folly of their approach, because you're attacking their personal sense of self in doing so. Which, I'm to understand, is a no-no, professionally.)
I should have perhaps said "galling" instead.
After ejecting anyone who spoke out or were even publicly hesistant against the hard swerve into "just do maximal amounts of AI stuff above all else", they're now surprised to find that everyone that remains is dutifully excited about the emperor's new clothes, and yet he remains mysteriously exposed to the breeze.
> Almost every company is run in a basic dictatorial way. We almost never discuss it, when there is a wide corpus of political Science analysing the pros and cons of governance models that certainly puts it at the bottom.
Is it not wild that in the Freedom Loving West, we all spend the vast majority of our time as adults living inside tiny totalitarian states?
I think this persists largely because the people atop those tiny states are also the ones behind most of our media apparatus, so they can make it look and feel pretty normal. But that may be a little tinfoil hat of me.
Is it too late to scratch your final sentence?
You get what you measure.
I'm with you that people are insanely hyped about Claude Code in particular when e.g. Codex isn't far behind (and with recent models I actually prefer it).
But I'm going to need a citation for this:
> a lot of GenZ and young Millenials who were already bitter at their employers have used the tokenmaxxing push to sabotage the AI
The 3 people on reddit doing this don't even register on a company budget. What seems more plausible to me is that budgets were calibrated to spending before agents were actually useful, and late '25/early '26 changed the pattern significantly.
Codex is actually significantly better than Claude Code now, assuming you have a clear idea of what you want to do and how. Claude's secret sauce is that it'll run off and do stuff that's mostly right without a lot of prompting, but that also makes it willful/disobedient and causes it to be bad for "finishing" work, since it'll circle around your objective in an opinionated way.
https://finance.yahoo.com/sectors/technology/articles/nearly...
I’m an “old millenial” and the excessive burning of tokens will continue until working conditions improve.
Working conditions are fine, I simply am not incentivized to be efficient with tokens.
Yeah, everything is fine until you don’t want to use AI for something because it sucks at that task and then you end up on a PiP because your token burn is low. Why the f*ck are AI Token Use Leaderboards even a thing.
Features that used to take months are now expected in days. Oh you didn’t merge 40 pull requests and deploy to prod 15 times today? Aren’t you using Opus the greatest thing since the invention of the wheel?! What do you mean it’s hard to review 100 merge requests per day? Just have Claude review it! That’s a PiP.
Oh prod is down because people keep deploying code that nobody even freakin’ read? Just have Claude fix it! What do you mean it’s doesn’t work well? Just burn more tokens or you’re on a PiP.
Surely there wouldn’t be malicious compliance by people that would prefer to use the right tool for the job instead of having this crap shoved down our throats by management by threat of termination.
Counterpoint: based on a lot of anecdotes here, the most likely people to burn tokens aren’t GenZ but managers using ChatGPT to respond to questions or otherwise as an outsourcing of their job. There aren’t enough GenZ in the workforce to back your claim in my opinion.
Token efficiency where instead of the AI burning money at 1:3 instead of 1:5 isn’t quite a winning argument.
There's no way managers using LLMs to answer emails are burning tokens at a comparable rate someone trying to utilize inference in production systems is.
There's the cost to do productive work, and the proportion of work which is actually productive.
GPT5.5 medium is ~20% the cost of Opus and 27% the cost of Sonnet on a task by task basis. That's a material difference.
Citation needed.
Excessive token burning as a tactic to annoy your employer probably does the opposite - it probably makes your employer money.
The more tokens you burn, the more demand for hardware there will be. More demand for hardware means higher stock prices -> more money in your employer's pocket.
The only question is how long that can last. If taken to an extreme, the output of the AI will get worse over time, and if it gets bad enough, for long enough, people will use it less and less, and demand will slowly evaporate.
My point is NOT: I hope this all comes crashing down.
My point IS: tokenmaxing is bad. AND weaponizing it will not have the intended effect, but in fact, it will, in the short term, do the opposite.
> The more tokens you burn, the more demand for hardware there will be. More demand for hardware means higher stock prices -> more money in your employer's pocket.
If you work for NVIDIA, sure, but otherwise, this makes no sense to me.
I'm guessing you aren't invested in any of these stocks. I'm also guessing, to take the perspective of a tokenamxxing GenZ employee, that their bosses are.
Just a week ago, Anthropic barely breaking even was hailed as AI companies being close to profitability much earlier than forecast.
In fact it is all smoke and mirrors, pure mania from C-level executives out of their depth trying to one-up each other with company money, and they aren't even close.
>Corporate leaders are starting to question whether soaring AI spending is delivering meaningful returns.
This isn't surprising. Ive recently run into quite a few rabbit holes where AI is bad enough that its much more efficient to do it myself. I wanted to refactor some code, gave it a design pattern to go towards, some specific classes and methods, etc. making it a well described problem. AI just couldn't do it satisfactorily. The code was ugly, overly verbose, and after multiple tries with multiple prompts saying to keep things simple. They still would introduce new classes, useless fields, etc.
"AI" is "bad" and "just couldn't do it"? Specifics w model and harness would lend more credence.
"An AI consultant tells Axios one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on Claude licenses for employees." Like physically, how could this even happen?
Agents. An agent is a system for spinning up processes that use tokens, talking to other processes that use tokens.
I wonder how many megawatts that waste represented. Just one guy, worse than a small air force of private jets.
This could happen with a large number of integrations or agent swarms working 24/7 with high throughput and long contexts.
Maybe the AI consultant gets a cut of that half billion?
https://www.merriam-webster.com/dictionary/sticker%20shock oh. i thought it was about people putting up stickers like https://mastodon.social/@spellingmistakescostlives@mastodon....
I am Jack's total lack of surprise :-/
https://archive.is/crTG8
Just wait until companies are dependent on on it. When their employees can't think without it. When their AI generated codebase is such a mess they'd need a rewrite to understand it without AI. When they've got AI embedded in all their internal processes and tools. Then massive price hikes will come because they've been bent over a barrel and they'll have no alternative that isn't at least as painful in the short-term as letting the AI company fuck them. The long term won't matter then because any company capable of seeing past the short term wouldn't let themselves get into that position in the first place.
Well, if AI has a massive sticker shock attributed, so we should target the high value roles and should save money, right?
So im looking at CEO, CTO, CFO, and all the chief-something-officer. If LLMs are that totally amazing at thinking, then we should be targeting upper management, not the workers.
That would save a LOT of money for the shareholders! /snark
We all know why they wont.
So it goes. Wage theft dwarfs the amount lost to street-level theft, robbery, burglary, etc., combined. The economic stimulus from correcting even a portion of annual wage theft would represent complete coverage of those violent thefts - economically-speaking, there would be no reason for criminals to carry them out. Why rob a gas station to get your drug money? Everyone around you is making enough extra at work that bumming a dollar here and there covers it. That sort of thing.
But good forbid we actually correct a major social ill at the expense of the people who profit from it.
> Instead, they should focus on using AI to drive revenue.
There is a complete disconnect between wages of employees and company's revenue => Why aren't employees working towards revenue? What a mystery. Children, let's help Elmo solve this mystery.
And then random mass layoffs to make numbers for shareholders look great in quarterly reports. Surely this motivates people work to their fullest potential and to care for company's revenue.
I found this claim interesting so I looked into it. Everything I can find shows that the intuition is accurate.
Companies with EOSP programs outperform those that do not in the market by about 17%.[0] Companies that perform layoffs, despite short-term stock boosts, underperform on a period of years showing a 14% decline in their Return on Assets (ROA) in the years following the layoffs.[1]
[0] https://www.nceo.org/employee-ownership-blog/new-study-shows... [1] https://www.researchgate.net/publication/277473996_Financial...
Even better there’s a complete disconnect between revenues and metrics we use to measure productivity. Corporate wants to believe there’s numbers you can use to measure knowledge workers like widget makers where there’s really not much that’s effective beyond revenue.
Playing out in company after company right now:
CEOs: “Get me some of that GenAI”
CTO: “OK, we have all the GenAI”
CEOs: “Employees, it’s AI or bust”
Employees: Tokenmax
CFO: “Um, this is costing a ton and we’re not seeing savings or efficiency materialize.”
CEO: “Are we getting any value out of this?”
COO: “Not really, and frankly I’m getting annoyed at all the AI slop turning up all over.”
CEO: “OK, well, let’s do a big layoff and then I’ll just say it was because of AI. Hopefully folks won’t blame me for the mess and I’ll just talk about how amazing AI is.”
> Hopefully folks won’t blame me for the mess
Lesson #1 from business school : take all credits, put the blame on others, if there no easy scapegoat blame the "economical context"
Lesson #2 and beyond : just see lesson #1, it's enough. You've made it and it's ALL thanks to this amazing business school degree you got, now go profits with your new already wealthy peers.