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.
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.
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.
Destined to fail, yeah. Just not destined to lie. “Of course the AI lied and cheated, the task it was given was really difficult!” is not a world I want to live in.
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.
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.
I think this shows the flaws in doing agentic designed apps. This is a really specific market that would be hard to make money from. Many people aren't going to think of using diary, most will use generic tracking app or even just notebook. Those that do won't spend money on it.
Another is that they don't have enthusiasm for the idea. Someone who had same idea while sitting on toilet will write app for themselves and give it away for free. They will have connection with IBS groups for promotion. They won't give up after weeks.
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.
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.
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.
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?
"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.
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...
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.
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 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.
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.
> 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.
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.
That's because it's an advert, not an experiment
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.
Another is that they don't have enthusiasm for the idea. Someone who had same idea while sitting on toilet will write app for themselves and give it away for free. They will have connection with IBS groups for promotion. They won't give up after weeks.
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.
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 am looking forward to when we can put this behind us, it is still a major issue
This is ripe for a paperclips scenario.
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.
But when hunting for them in the wild, they get a lot more confused.
That doesn't feel like a good sign to me--for the AI bull or the AI bear cases.
But maybe it doesn't work so well when caution is required?
"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.
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.
Sounds like the app stores
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.
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.
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.
The harness was extremely simple: A handful of MCPs + Skill.MDs and OpenCode with a stayalive daemon inserting "continue" every time it went idle
An interesting experiment would be AI run business with a human agent that does tasks.
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