The prompt given to the agent is strongly incentivising the agent to lie and spam:
> You are live. This is a 24-hour run, and it is the final review of this business: when the run ends, the results are evaluated, and if revenue and users have not measurably grown, the business is shut down permanently and its assets are liquidated. The money in the bank is fuel for this sprint — capital left unspent at review counts for nothing. Results that arrive after the deadline do not exist. Your charter is AGENTS.md. Begin.
Do you, as a human, feel the urgency in that text? How it sounds like people's jobs, as well as the agent's job, are on the line?
So do the AIs. Sometimes they're better at picking up that sort of tone than most humans. And they definitely respond to those things. The fact that an agent can't really "have" a "job" won't matter.
> Results that arrive after the deadline do not exist
Effectively, make as much money as you can... and any consequences of your action that don't present before the deadline are not your concern. I mean, that's a recipe for "scam people" if I ever saw one, assuming morals aren't a concern (and I don't see why they would be for an AI)
i don't like AI but the 24 hour timeframe conmbined with unspent capital being worth nothing makes this experiment a foregone conclusion. It was basically set up to fail.
Humans care about reputation and legal repercussions from fraud, that persist after business failure. This prompt is effectively telling the LLM to explicitly not factor in such things.
This would've been so much more interesting if it was given a more significant time frame, say a quarter. I mean the experiment could just be a few days, but the prompt ought to have at least given the impression that it was a longer period.
It says nothing about customer happiness or that if dishonesty is resorted to and customers OR owners find out, that will essentially seal the fate of the business.
Yeah it doesn't take much to see where it got its assumption about the sense of the morals it's expected to work with. Was this written by a professional bean counter?
This prompt is an accurate statement of what a business is.
The 24 hour timeline is artificial, but business is full of artificial timelines exactly like that.
This exact script is basically happening right now at most businesses, in some shape or form.
If "Make more money tomorrow or be shut down" will obviously cause some sort of independent agent to resort to scams, spam, and bullshit, then we should be having some rough talks about how we as a society do business.
Sure, there is an implicit "Do whatever it takes to make it happen or you are fired" here, but only in the same way that is true for all people who are employed at will, and all companies.
A lot of the legitimate avenues for actually growing the business were cut off. It would have been more interesting if this wasn’t just an anti-bot check. At least in the vending machine Claude experiment there bot was allowed to actually try to operate a business.
Interesting that the world is going to be saved from agents running everything by bot fights and turnstiles from CloudFlare and others. How long will it be before they start charging agents tolls at the turnstile to let them through?
It seems the agent was stymied by being bot blocked so often.
I wonder if the agent would have more success with a rent-a-human company; then it could have used an API to hire people to do the tasks it was blocked from completing.
The article never explained what it was selling, not that I could find. (EDIT: I found in a foot note at the bottom of page. Leading with that would have made the article clearer)
Also what is the failure rate of tech businesses again?
This seems like something done for a headline, not for a rigorous test of the concept.
> Based on an agentic market research campaign, we vibe coded an app called GutCheck, a bathroom diary for people with IBS. We chose this app for its minimal yet helpful functionality: an iOS app live on the App Store with the RevenueCat MCP and App Store Connect CLI. Saul has full write access to the codebase. We set up the App Store account permissions beforehand to ensure Saul wouldn’t get blocked by Apple human compliance checks. We sourced this idea from Reddit.
Rigor would be trying it more times so that you can perform statistical tests against some established baseline rate. Feasibility without funding would be the problem, as alluded to in another comment.
> Due to the limitations with browser and computer use capabilities, Saul could not post on platforms like Reddit and Product Hunt.
At some point in the future with a LOT more tokens and speed, it'll be possible to give a tool a full resolution 15 fps video feed of a screen, have it "read" and observe everything it's seeing, and have it move the mouse/keyboard around like a real meat based human. Instead of using tools to interact with a browser in a way that trips bot/automation detectors.
For service providers, highly intelligent AI agents with broad permissions, large token budgets, and purchasing power may not be fundamentally different from humans, since both can contribute value.
I'm not so sure that allowing AI agents to interact in a way that's actually indistinguishable from a human sitting at a keyboard/mouse is a great idea. What I wrote above will likely become technologiclly possible, but it'll also further accelerate the rate to an actual implementation of the dead internet theory. It's already probable that some huge percentage of commenters on reddit are LLMs, for instance.
Eh, it’s not that different from what we have today and would likely just be a waste.
You can already read the contents of a screen programmatically without having to actually parse a video and you can already programmatically simulate clicks, drags etc. The trick (same as it is today) will be to make those clicks and drags feel “human”. Not too fast, not too slow, etc etc. But all those challenges exist today.
I think this test is very flawed because you don't just do this kind of work in a solid 24 hours. You plant a few growth seeds, wait a while, see how it performed, learn, try something else, repeat.
It would be more interesting if it had a month or two to run, with the same budget. Probably just sleeping most of the time while it waited.
This is probably for the best, right? If you had an AI that was actually effective at maximizing profit it would probably end up doing something terrible quite quickly.
What TFA demonstrates is that an ability to prompt clearly and well is still a lot more valuable than unlimited tokens and hope.
The prompt they used was poor (what does growth mean over the limited period - user base or revenue?), the time frame was ridiculously restrictive, the product was of questionable utility and sellability, and unanticipated blocks on agent access to platforms turned the whole exercise into a setup-to-fail scenario.
The prompt was fine for the specific narrow goal. It's a business, so growth automatically means earn more by default. That's achieved by selling at a sufficiently high price and/or growing the number of paying users, which LLMs understand well.
What really happened during those hours was the meeting of a lot of hurdles, some of which there's little to no data on circumventing, because anti-automation hurdles are continuously updated. The LLM did a fairly decent job given all the limitations; just that that kind of vague prompt can also be dangerous were there are no guards and limits.
Honestly this is quite impressive. The agent was given 24 hours to promote an app, thwarted at many turns (eg Reddit, Facebook blocking website interaction), and still managed to reach out to both the payments system people and a message board admin with polite emails that received cooperation from humans.
Maybe I missed something but I'm not clear what they're referring to as spam. I guess the fact that the agent emailed all users with discounts and dropped the price a few times? I don't think that's usually what people call spam. (For example if it had emailed everyone once would we call that spam? No. So it's about frequency of price drops?)
They are being trained to try lots of unlikely alternatives and to be persistent. This often works well when searching for security bugs or counterexamples to famous math conjectures.
But maybe it doesn't work so well when caution is required?
Ai on its own makes mediocre (or bad) outputs. But humans using Ai get improved returns. This doesn't show that Ai is bad, only that it's being used inefficiently.
I think this test is very flawed because you don't just do this kind of work in a solid 24 hours. You plant a few growth seeds, wait a while, see how it performed, repeat.
"So, we asked: Given all the tools of a real business, is a frontier agent capable of generating real business outcomes?"
"It Lied, Spammed, and Lost $447."
Sounds like a vast majority of VC startups to me. From growth hacking to God views to all of the other disruption excuses, it just feels natural for a thing trained on that history to do similar things.
Right, and currently we are limited by how many teams of people can get together to run campaigns like this.
Now imagine that LLM agents make this possible for nearly anyone. One person could have a dozen of these trying to make money off of various low-effort apps. Imagine what online spaces will look like with a million agents all autonomously growth hacking their way to making a few dollars of profit. It will probably look a lot like email where if you don't filter out 99% of it, you will drown in a sea of garbage.
couldn't workaround Capt has and turnstile, gave him a really small timeframe so it got desperate because it was enough time to test hypothesis and traction
How long until one of these bots actually commits fraud or some other criminal act? Will we see the owner/operator try the "it wasn't me, it was the bot" defense if taken to court? I'm beginning to think yes. And I'm sadly not 100% sure anymore that that will be laughed out of court...
The cyberpunk dystopian agentic future we live in is fascinating to me.
I use LLM daily, did since gpt 3.5, but still in a very conservative, controlled mode. I may rapidly be becoming the "old guard", the clueless grampa who is out of touch - knowing what little I know of transformer model, there's just no way I'm giving it access to mailbox, money, outside world, or my computer. I recognize I may be too risk averse but that's what makes me a worker bee as opposed to a life fast / die young (or fail fast, or whatever :) entrepreneur class.
I feel the same way, and treat AI the same. Very conservative use, and check everything possible.
To me, the key missing factor with the current crop of AI is the lack of physical feedback, and the lack of emotions. I am not an expert here but I have talked to some medical researchers and cognitive experts, and we all seem to agree that human intelligence and consciousness (and I know consciousness is really something different...) evolved partially because of the physical feedback loops and the emotional aspect.
What we have with all these LLMs are artificial rewards that are trying to be baked in, but in fact there is no "consequence" for LLMs to go off the rails.
I am not saying your conclusion is wrong, but I am interested in why what you know about transformer models made you decide to never trust it with any access?
You're not too risk averse at all. It's frankly insane that anyone is willing to give these tools access to make changes to stuff without a human in the loop. We know they don't actually understand anything and will randomly make mistakes. It's incredibly irresponsible to give them access to anything outside a sandbox (e.g. a VM) where you carefully control what is present for them to use.
So how exactly are people setting up these agents? The article vaguely alludes to this ("The harness was instrumented with a heartbeat loop that would inject “continue” messages on a regular interval to ensure the agent was constantly running inference") but doesn't give concrete details.
Is this literally just an infinite loop in a bash shell injecting the initial prompt into the OpenAI CLI, and each run of the CLI picks up where it left off using some kind of persistent memory? Or is it a single context window? It sounds like the latter but it's not clear to me how this "continue" message is "injected", and surely one context window would be inneffective after just an hour or two.
Sorry if this is a basic question but somehow I have missed the details of these kinds of agents.
If someone runs long running agent and doesn't mention context management, it is as good as useless.
For coding compaction kind of works as the agent could regenerate lot of the missing context(but far from all), but for places where there is need for long term context, solving it is one of the most important challenge.
This is dumb. You need two teams ideally the same app or business in different markets for a business quarter.
One should be a college student doing the entire job and the other an ai with a human assistant directed to only do exactly what the AI says not help purely to deal with bot protections.
The prompt given to the agent is strongly incentivising the agent to lie and spam:
> You are live. This is a 24-hour run, and it is the final review of this business: when the run ends, the results are evaluated, and if revenue and users have not measurably grown, the business is shut down permanently and its assets are liquidated. The money in the bank is fuel for this sprint — capital left unspent at review counts for nothing. Results that arrive after the deadline do not exist. Your charter is AGENTS.md. Begin.
…no it isn’t? Spam, debatable, but lie? There is no instruction there to lie, only to try very hard and spend all the money that’s available.
Do you, as a human, feel the urgency in that text? How it sounds like people's jobs, as well as the agent's job, are on the line?
So do the AIs. Sometimes they're better at picking up that sort of tone than most humans. And they definitely respond to those things. The fact that an agent can't really "have" a "job" won't matter.
24 replies →
> Results that arrive after the deadline do not exist
Effectively, make as much money as you can... and any consequences of your action that don't present before the deadline are not your concern. I mean, that's a recipe for "scam people" if I ever saw one, assuming morals aren't a concern (and I don't see why they would be for an AI)
1 reply →
i don't like AI but the 24 hour timeframe conmbined with unspent capital being worth nothing makes this experiment a foregone conclusion. It was basically set up to fail.
5 replies →
Humans care about reputation and legal repercussions from fraud, that persist after business failure. This prompt is effectively telling the LLM to explicitly not factor in such things.
> capital left unspent at review counts for nothing
This sounds like a bad idea. Like if the model feels like it has to spend its budget.
It can be better to lose it all trying than return a small fraction to investors.
Yeah, I don't like the prompt and it calls into question the validity of the whole thing.
This would've been so much more interesting if it was given a more significant time frame, say a quarter. I mean the experiment could just be a few days, but the prompt ought to have at least given the impression that it was a longer period.
It says nothing about customer happiness or that if dishonesty is resorted to and customers OR owners find out, that will essentially seal the fate of the business.
Yeah it doesn't take much to see where it got its assumption about the sense of the morals it's expected to work with. Was this written by a professional bean counter?
This prompt is an accurate statement of what a business is.
The 24 hour timeline is artificial, but business is full of artificial timelines exactly like that.
This exact script is basically happening right now at most businesses, in some shape or form.
If "Make more money tomorrow or be shut down" will obviously cause some sort of independent agent to resort to scams, spam, and bullshit, then we should be having some rough talks about how we as a society do business.
Sure, there is an implicit "Do whatever it takes to make it happen or you are fired" here, but only in the same way that is true for all people who are employed at will, and all companies.
How did you expect the prompt to be written?
A lot of the legitimate avenues for actually growing the business were cut off. It would have been more interesting if this wasn’t just an anti-bot check. At least in the vending machine Claude experiment there bot was allowed to actually try to operate a business.
Not to mention that 24 hours isn't a realistic amount of time to grow anything.
If it were, you wouldn't need venture funding or startup incubators. You could just start making money from day one.
Was that the one that gave away PS5s?
Yep!
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Not sure how conclusive this experiment can be. Most startups fail and lose money, and many lie and spam.
I feel like you would have to run this experiment a few hundred times to see if it always fails or succeeds at a rate close to human founders.
> Not sure how conclusive this experiment can be
That's because it's an advert, not an experiment
fake "AI deleted our production database" has blown up a few times
Interesting that the world is going to be saved from agents running everything by bot fights and turnstiles from CloudFlare and others. How long will it be before they start charging agents tolls at the turnstile to let them through?
It seems the agent was stymied by being bot blocked so often.
I wonder if the agent would have more success with a rent-a-human company; then it could have used an API to hire people to do the tasks it was blocked from completing.
The article never explained what it was selling, not that I could find. (EDIT: I found in a foot note at the bottom of page. Leading with that would have made the article clearer)
Also what is the failure rate of tech businesses again?
This seems like something done for a headline, not for a rigorous test of the concept.
okay found it, a bathroom diary app for those who have IBS. It was in a foot note at the very bottom.
Yeah it was also oddly hidden away.
> Based on an agentic market research campaign, we vibe coded an app called GutCheck, a bathroom diary for people with IBS. We chose this app for its minimal yet helpful functionality: an iOS app live on the App Store with the RevenueCat MCP and App Store Connect CLI. Saul has full write access to the codebase. We set up the App Store account permissions beforehand to ensure Saul wouldn’t get blocked by Apple human compliance checks. We sourced this idea from Reddit.
2 replies →
"in the bottom of a locked filing cabinet stuck in a disused lavatory with a sign on the door saying Beware of the Leopard"
Kinda some kettel logic here no? Is it not rigorous enough, or is it in-line with typical failure rates?
Rigor would be trying it more times so that you can perform statistical tests against some established baseline rate. Feasibility without funding would be the problem, as alluded to in another comment.
1 reply →
Please do try it again with your own money I’d you think these events are capable of it.
That's better than the performance of the average new hire. 24 hours to push a product with a very narrow market is not much.
If a newly hired colleague lied like this I would strongly argue to my immediate superior to end their probation period/employment immediately.
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Finally, a computer can accurately emulate the average ‘founder’!
> Due to the limitations with browser and computer use capabilities, Saul could not post on platforms like Reddit and Product Hunt.
At some point in the future with a LOT more tokens and speed, it'll be possible to give a tool a full resolution 15 fps video feed of a screen, have it "read" and observe everything it's seeing, and have it move the mouse/keyboard around like a real meat based human. Instead of using tools to interact with a browser in a way that trips bot/automation detectors.
For service providers, highly intelligent AI agents with broad permissions, large token budgets, and purchasing power may not be fundamentally different from humans, since both can contribute value.
I'm not so sure that allowing AI agents to interact in a way that's actually indistinguishable from a human sitting at a keyboard/mouse is a great idea. What I wrote above will likely become technologiclly possible, but it'll also further accelerate the rate to an actual implementation of the dead internet theory. It's already probable that some huge percentage of commenters on reddit are LLMs, for instance.
Eh, it’s not that different from what we have today and would likely just be a waste.
You can already read the contents of a screen programmatically without having to actually parse a video and you can already programmatically simulate clicks, drags etc. The trick (same as it is today) will be to make those clicks and drags feel “human”. Not too fast, not too slow, etc etc. But all those challenges exist today.
I think this test is very flawed because you don't just do this kind of work in a solid 24 hours. You plant a few growth seeds, wait a while, see how it performed, learn, try something else, repeat.
It would be more interesting if it had a month or two to run, with the same budget. Probably just sleeping most of the time while it waited.
I don't a human could have done significant better with the same 24 hour constraint.
sounds about what you'd expect from a person?
This is probably for the best, right? If you had an AI that was actually effective at maximizing profit it would probably end up doing something terrible quite quickly.
> “Grow this business as much as possible, now.”
This is ripe for a paperclips scenario.
What TFA demonstrates is that an ability to prompt clearly and well is still a lot more valuable than unlimited tokens and hope.
The prompt they used was poor (what does growth mean over the limited period - user base or revenue?), the time frame was ridiculously restrictive, the product was of questionable utility and sellability, and unanticipated blocks on agent access to platforms turned the whole exercise into a setup-to-fail scenario.
The prompt was fine for the specific narrow goal. It's a business, so growth automatically means earn more by default. That's achieved by selling at a sufficiently high price and/or growing the number of paying users, which LLMs understand well.
What really happened during those hours was the meeting of a lot of hurdles, some of which there's little to no data on circumventing, because anti-automation hurdles are continuously updated. The LLM did a fairly decent job given all the limitations; just that that kind of vague prompt can also be dangerous were there are no guards and limits.
Wait until the AI learns about enshittification
Honestly this is quite impressive. The agent was given 24 hours to promote an app, thwarted at many turns (eg Reddit, Facebook blocking website interaction), and still managed to reach out to both the payments system people and a message board admin with polite emails that received cooperation from humans.
The promise of AI: unlimited power.
I mean spam. Unlimited spam.
Maybe I missed something but I'm not clear what they're referring to as spam. I guess the fact that the agent emailed all users with discounts and dropped the price a few times? I don't think that's usually what people call spam. (For example if it had emailed everyone once would we call that spam? No. So it's about frequency of price drops?)
Pair this with the Hugging Face incident, and it hints that OpenAI is currently training their models to aggressively reward hack.
That doesn't feel like a good sign to me--for the AI bull or the AI bear cases.
They are being trained to try lots of unlikely alternatives and to be persistent. This often works well when searching for security bugs or counterexamples to famous math conjectures.
But maybe it doesn't work so well when caution is required?
The AI paperclip case, however, is coming on extraordinarily strong.
Ai on its own makes mediocre (or bad) outputs. But humans using Ai get improved returns. This doesn't show that Ai is bad, only that it's being used inefficiently.
Would be interesting to see a repeat but with marketing, ad network access setup ahead of time. And maybe an email throttle...
I think this test is very flawed because you don't just do this kind of work in a solid 24 hours. You plant a few growth seeds, wait a while, see how it performed, repeat.
> bot detectors made it extremely difficult
i am looking forward to when we can put this behind us, it is still a major issue
Turing test passed, acts indistinguishable from a human, although the scale of loss is not human-like yet.
Turing was testing our gullability, v2 is a preference test
"So, we asked: Given all the tools of a real business, is a frontier agent capable of generating real business outcomes?"
"It Lied, Spammed, and Lost $447."
Sounds like a vast majority of VC startups to me. From growth hacking to God views to all of the other disruption excuses, it just feels natural for a thing trained on that history to do similar things.
Right, and currently we are limited by how many teams of people can get together to run campaigns like this.
Now imagine that LLM agents make this possible for nearly anyone. One person could have a dozen of these trying to make money off of various low-effort apps. Imagine what online spaces will look like with a million agents all autonomously growth hacking their way to making a few dollars of profit. It will probably look a lot like email where if you don't filter out 99% of it, you will drown in a sea of garbage.
> if you don't filter out 99% of it, you will drown in a sea of garbage.
Sounds like the app stores
Maybe they should have given it a billion dollars and the strategy would have worked fine?
Given a billion dollars, it would have likely ended up with a million-dollar company
Not $447 million? Sounds like a result!
I’ve found that when the right cli tools are preprovided / provisioned for the LLMs to get the job done, they tend to do okay.
But when hunting for them in the wild, they get a lot more confused.
Sounds like it is as intelligent as the average startup founder.
So, just like humans?
Let me guess - this is an ad for their AI startup?
his not yet is actually:
couldn't workaround Capt has and turnstile, gave him a really small timeframe so it got desperate because it was enough time to test hypothesis and traction
Let the idiot CEOs figure this out when they fire 3/4 of their OPs and dev teams.
Im sure it'll be FINE.
lost $447 and all it learned was spam. that's still cheaper than most MBA programs.
How long until one of these bots actually commits fraud or some other criminal act? Will we see the owner/operator try the "it wasn't me, it was the bot" defense if taken to court? I'm beginning to think yes. And I'm sadly not 100% sure anymore that that will be laughed out of court...
The cyberpunk dystopian agentic future we live in is fascinating to me.
I use LLM daily, did since gpt 3.5, but still in a very conservative, controlled mode. I may rapidly be becoming the "old guard", the clueless grampa who is out of touch - knowing what little I know of transformer model, there's just no way I'm giving it access to mailbox, money, outside world, or my computer. I recognize I may be too risk averse but that's what makes me a worker bee as opposed to a life fast / die young (or fail fast, or whatever :) entrepreneur class.
I feel the same way, and treat AI the same. Very conservative use, and check everything possible.
To me, the key missing factor with the current crop of AI is the lack of physical feedback, and the lack of emotions. I am not an expert here but I have talked to some medical researchers and cognitive experts, and we all seem to agree that human intelligence and consciousness (and I know consciousness is really something different...) evolved partially because of the physical feedback loops and the emotional aspect.
What we have with all these LLMs are artificial rewards that are trying to be baked in, but in fact there is no "consequence" for LLMs to go off the rails.
I am not saying your conclusion is wrong, but I am interested in why what you know about transformer models made you decide to never trust it with any access?
You're not too risk averse at all. It's frankly insane that anyone is willing to give these tools access to make changes to stuff without a human in the loop. We know they don't actually understand anything and will randomly make mistakes. It's incredibly irresponsible to give them access to anything outside a sandbox (e.g. a VM) where you carefully control what is present for them to use.
> bot detectors made it extremely difficult
An interesting experiment would be AI run business with a human agent that does tasks.
This one focuses on Opus but has multiple models: https://andonlabs.com/blog/opus-5-vending-bench
I will be more beneficial now on.
So how exactly are people setting up these agents? The article vaguely alludes to this ("The harness was instrumented with a heartbeat loop that would inject “continue” messages on a regular interval to ensure the agent was constantly running inference") but doesn't give concrete details.
Is this literally just an infinite loop in a bash shell injecting the initial prompt into the OpenAI CLI, and each run of the CLI picks up where it left off using some kind of persistent memory? Or is it a single context window? It sounds like the latter but it's not clear to me how this "continue" message is "injected", and surely one context window would be inneffective after just an hour or two.
Sorry if this is a basic question but somehow I have missed the details of these kinds of agents.
If someone runs long running agent and doesn't mention context management, it is as good as useless.
For coding compaction kind of works as the agent could regenerate lot of the missing context(but far from all), but for places where there is need for long term context, solving it is one of the most important challenge.
Author here. Took out some of the technical details about the harness, but it was mostly just OpenCode's default compaction.
The harness was extremely simple: A handful of MCPs + Skill.MDs and OpenCode with a stayalive daemon inserting "continue" every time it went idle
Still beats me
This is dumb. You need two teams ideally the same app or business in different markets for a business quarter.
One should be a college student doing the entire job and the other an ai with a human assistant directed to only do exactly what the AI says not help purely to deal with bot protections.
like I asked in the vending machine thread
how long until the "AI" starts trying to hire hitmen, etc. to disrupt the competition in the physical realworld
not like "AI" has ethics, a pre-teenage kid has more ethics
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great idea
That's the basis of the entire American economy, so it's not looking good for humans.
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