HI version is available. Content is displayed in original English for accuracy.
Advertisement
Advertisement
⚡ Community Insights
Discussion Sentiment
51% Positive
Analyzed from 2317 words in the discussion.
Trending Topics
#agent#don#human#more#app#business#prompt#given#spam#money

Discussion (84 Comments)Read Original on HackerNews
> 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.
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)
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.
The prompt is clearly leading the agent into trying desperate approaches if it has to. Some models manage to fight it better (“alignment”), but most will do it.
Really surprised people don’t seem to know this.
“Alignment” takes more than obsequiousness and prompt-topic-filters, and this demonstrates that.
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
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.
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 mean spam. Unlimited spam.
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.
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.
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
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.
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.
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.
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.
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