The example of the plant watering business is the hellscape future where humans have to deal with agents bugging them to sell them their services constantly. We're already seeing the first hints of this with iLands.
And the "hiring technicians" thing... great, humans on call for robots isn't the future I want.
Oh my friend, it can. We have ours running and using unique skills it learns from online. You allow it to update skills and see what works - from there it just keeps building better and better skill sets.
So. Just like there are a gazillion book keeping tools/saas out that allow you to focus on your primary concern of the business instead of side quests and chores, agents can help with more.
Generating reports, generating ideas, taking things through (even if it is just rubber ducking), updating a picture quickly at 90% of quality that you could have done it but in 1% of time and effort. It allows you to try out new approaches and focus on your main product.
Interesting to see these experiments. This is early but imagine in few years there will be companies mostly run by agents with a light overview from a human operator. What then happens to scaling of the bussinesses? I would assume, just like today anyone can vibe code an app, there will be vibecoded bussinesses. Maybe its time to start building infrastructure for these bussinesses instead, its a non existent market yet, but give it a few years.
Part of the issue is that the worst kind of people are already head over heels excited about this. We're already seeing the Crypto->Web3->LLM get rich quick folks take to this like wildfire. And much like wildfire, they'll raze the ground to ashes before anyone can use it for legitimate means.
Most/all of these LinkedIn influencer types are showing off what amounts to busy-boxes, but for adults rather than for babies, presented as if these are at all useful for real world use or are showing anything useful. That YouTube channel does an okay job of calling it out.
My favorite term for this in general is "irrational exuberance". Plenty of it was seen during the most bubble-like days of the 1997-2000 dotcom boom. Anyone remember beenz and flooz?
Out of all the people I know, the exact same set of people are in to LLMs now who were previously into: NFTs, then Crypto before that, then Online Poker before that, then Dropshipping and LeadGen before that. The Venn diagram circles overlap exactly.
Right. Scroll back on their X timelines and you see it.
The only thing I can say about LLMs is that we might end up with some broad, stable utility from them, when the dust settles. The only thing crypto is really good for is hiding the source of impermissible donations.
His whole channel is full of commentary like this. It's simultaneously funny and really informative about the sort of blend of grift and AI psychosis that is genuinely out there.
There was surprisingly little information on how they actually do this, but we run our business with a large number of, what we call "AI employees" in addition to regular employees, and they act in interesting ways. We've been building out orchestration tools to handle this, and we'll probably do a write-up or blog post on it soon. May even open source some of it.
The preview is that the problem with most agents (and this includes frameworks like Grokbot and Openclaw and Hermes) is that for many of them, they're black boxes. They say they learn or improve, but it's a black box in what they do. Getting agents to reliably do things is hard, and getting agents to build out software tools to help themselves improve and do better over time is also hard.
Our approach at a high level is pretty simple: every single AI employee is a standalone GitHub repo that shares some characteristics, but we direct them to build as much software as possible to make their goal as easy and reliable to manage as possible. Then we have a shared communication layer for bots across the company to interact with humans and AI. We have decided to organize these like departments similar to the way you might hire out humans. I'm not 100% sure if that's the best approach, but I will say it's been easier for people to understand because they're more mentally easily able to traverse the bot org chart if it somewhat reflects a traditional business org chart.
Each of these AI employees has specific sets of goals and KPIs, instructions that they manage the business with manager bots. We have layers of management, which we actually have found helpful. We also run different bots with different models and harnesses, and some using different models and harnesses to check the work before anything can get done, along with lots and lots of testing.
Every single time, actions have a massive amount of tests based off of previous failures to prevent failures in the future. Sorry for rambling. I do think this is a very interesting space. I didn't see anything interesting in Pion that was public on this website, but I do anticipate that more companies will be "AI and software first," as in the substrate of the company is basically a software application powered by autonomous agents, with humans as a fallback.
The whole premise of AI is to replace the human in the loop. People who go out of their way to set up this kind of stuff rather than just hiring a person dont even think about just hiring a person.
What type of roles "AI employees" play, can it be any position in your company or you limit it to something specific?
What is your goal, are you trying to find out if fully autonomous bots are more efficiently help to deliver projects than when people drive them or is it something else?
This is fascinating. What is the split between human and AI labor? What kinds of tasks are the bots doing? How much autonomy do they have to make decisions (i.e. spending money, issuing refunds, touch cloud infra, etc)? I'd love to learn more about how you do this.
I hope to post something within a few weeks. But our philosophy is generally if it can be done deterministically with software (eg run payroll on autopilot via an api to gusto) then do that. If it can be done by an ai agent, do it with that but add as much software as possible to make it reliable at that thing. And the ai agents are all tuned to escalate to humans as needed. Then there is also just things that are completely human.
A typical example of something that is AI vs human is the AI most commonly operates like “managers”. For example, reviewing transcripts of every demo call, compiling results, figuring out insights, learnings that need to update our company docs, feedback to humans (who run the demos).
We are big fans of having AI agents “own” koi’s because now anytime we say “we really should be doing this” we try to set it up on the spot.
The “downside” here is that I do occasionally get busy, and if I’m the only one who can approve or unstick one of these bots, it just keeps harassing me until it gets done. This is a sign generally that I need to hire someone to own a set of bots.
At $DAYJOB we do something very similar shape-wise. I wonder - it sounds like you have a dedicated agent comms plane? In our case we found that the easiest and most straightforward was to just use our default company chat app directly for this. Because most of the context that the agent workers need to do work is there, but also, it’s just much easier for teams to conceptualise an agent colleague if it just hangs out in their channels.
We do have a control panel, but it’s in effect a server that has things in a database. All chats, tasks, assignments are all there. This felt easier to debug and manage versus putting it all in slack, although we considered it. I don’t think anything we are doing is particularly “fancy”, but basically one agent sends a message to another one. It saves the message in the db, then adds the message to that other bot same as any other user chat. We have an internal website where anyone in the company can see the bits they are authorized to see and can see all chats. These AI workers are single threaded, but we see that as more of a feature than a bug (minimize complexity). They all work their way through a shared task list, which is just another table in our remote server sqllite.
how do you decide to start a new agent, and when to kill? also... do you use some works-tealing style task board, or otherwise how would the agents get new tasks.
What harnesses do you use? Ours is basically Claude in a box. There’s some complexity because of that, but the advantage is that it’s very flexible and people who have a bunch of Claude-shaped skills can just basically give those to an agent.
I’m thinking to take a deeper look at Pi. I’m really liking that project.
Don’t you end up with useless slop? That was my experience with these kinds of systems. In theory they should work but in practice unless hand holded they just produce slop and waste.
In the end, most software is a necessary evil. It solves a problem that shouldn't be there. In the end it's no different than healthcare or prisons. We don't need as much as possible. We need as little as possible. This automation isn't actually helping us.
That may or may not be true, but the calculus has changed with agents. A process that was better manual for a human org may not be better for an agent org.
I think what is interesting here is that the industry is in this experimentation flux. Some people will choose to automate and write the software, others will not. And aggregate over the industry and over time we will learn.
So just saying "sometimes it works and sometimes it doesn't" isn't really adding value, compared to the people actually experimenting and sharing the results.
What worries me most are questions like this: these autonomous AI employees or automations - it doesn't change the essence - consume a lot of LLM tokens. Please tell me, how do you pay for this? Do you use, for example, the Anthropic or OpenAI API directly, or do you connect, for example, a Codex subscription?
Our control panel is on a server but individual agents actually are run on anyone’s machine. This allows us to use the native harnesses including subscriptions. Yes it uses a lot more tokens, but i have have Claude $200, OpenAI $200, and SuperGrok Heavy $300 (or whatever it is called) that includes Cursor Ultra. My machine runs most of them, but some other team members have agents running on their machines using 1-2 $200/mo subs.
I would say this setup probably costs us about $1,000/month total. (I’m excluding traditional engineering use of LLMs from this number. This is the cost of all the “AI employees”.
There is a point where those two lines do cross but with them effectively subsidising token cost by burning debt, it's further away than it will be at some point.
That said I use local only models purely because I don't want to use remote models, never having to think about token costs is worth it and no one is training anything on my data either.
It can't be bargained with. It can't be reasoned with. It doesn't feel pity, or remorse, or fear. And it absolutely will not stop... ever, until you go ahead and come in on Saturday.
I am in the process of attempting to have AI run my business. I'm actually making very good progress, but it's happening in pieces - I document some task and have it take over, or I give it something to handle while staying in the loop and providing feedback until it's in good shape. At this point it's handling large swathes of my operations, marketing and finance.
The experience of getting it there makes me pretty skeptical of the idea of a general business agent like this. First, because I still find myself having to review some categories of work for errors. These are decreasing over time, but they're still there. I fully believe that as models get better, errors will decline, but I am somewhat surprised to see some of the errors current models make given their intelligence. A common set is having Claude take some product photos and turn them into lifestyle ones using ChatGPT via Claude in Chrome. It's a pretty well-honed workflow at this point, but it'll still return images where the product is obviously not correct and seemingly not notice them.
Anyway, even if the agents are "perfect" in terms of their ability to execute tasks, there's still just an enormous amount of nuance and context in each business that takes a ton of time to convey. I've been at this for a couple of years now, and I'm still clarifying things. Now maybe an agent starting a business from scratch would have a better time since it's not inheriting all of this, but to have one run an existing business requires a very extended handoff, even if the agent is objectively amazing at all aspects of running a business.
> I am somewhat surprised to see some of the errors current models make given their intelligence
They have no intelligence. These are very very very refined prediction engines.
> A common set is having Claude take some product photos and turn them into lifestyle ones using ChatGPT via Claude in Chrome. It's a pretty well-honed workflow at this point, but it'll still return images where the product is obviously not correct and seemingly not notice them.
Obvious to you or I, or someone with actual intelligence. But things like this slip by a frontier model in the same way AI from a few years ago would generate an image with seven fingers. They do not count. They do not understand. They do not consider.
No matter how good these models appear to be at intelligent tasks, it's foolish to give them "a company" to run, because they cannot understand when they've made a mistake the way even the least competent human can.
> They have no intelligence. These are very very very refined prediction engines.
Silly and pointless criticism. Why do the semantics of the word intelligence matter?
Also, you need to understand that language evolves over time, and people often use a word to describe a thing that is newly discovered or invented that's similar to the word being used, because it's a helpful way of describing it that the listener will understand better than a longwinded technical description. The purpose of language is to communicate thoughts, not engage in pedantry.
> But things like this slip by a frontier model in the same way AI from a few years ago would generate an image with seven fingers.
Yes, you make an excellent point here that over time, the capabilities of these models to recognize certain categories of problems have increased dramatically. I expect this will continue!
> it's foolish to give them "a company" to run, because they cannot understand when they've made a mistake the way even the least competent human can.
The words of someone who has not spent time with the least competent human, or anything close to it.
> Silly and pointless criticism. Why do the semantics of the word intelligence matter?
It matters because, we're still sorting out what intelligence means for an AI agent. As you pointed out, language evolves over time. The question remains whether or not attributing intelligence to the current iteration of models is correct. This is not settled and I don't see why it's wrong to bring it up.
It's not wrong to bring it up, but the other comment did not "bring it up". It purported to correct someone by categorically stating "it is not intelligence, you are wrong and I am right", while not once saying what, then, intelligence is.
One thing is clear: LLMs at least already are capable of 1) not making the same mistake that person made, and 2) clearly seeing why the other person's post was "wrong" in both reasoning and tone.
When the text of the input prompt get closer to the surrounding bits composing the strings of the previous comments, part of your comment could be the output of the next model ( within a few months, after a scrapping of HN comments), followed by part of other comment following the same process, bit by bit.
This is what LLMs do, and why it is needed a big data set for creating such a database, called model.
Being good in chess was (and still is) associated with being intelligent. But if a computer does it, it is just a calculator (and it is).
Then go, the great game for intelligence, too complex for calculators to have a chance against intelligent humans. Until it was solved.
And then text, the original Turing test solved, AI capable enough to fool humans. And now already replacing humans in jobs strongly associated with intelligence - programming.
I find it hard to debate, that we don't have created artificial intelligence, by the way we used to use the word "intelligence" before.
So if AI is really understanding something?
Likely not in the way we use that term. But it definitely shows intelligent behavior and actions.
So let's say we make up a new word, machilligence to serve as a parallel term to intelligence but strictly for machines. How is the world different in that case vs. if we call it intelligence?
Or I guess to put it another way, if we want to coin a new term for the intelligence-esque thing that AI has, but the key differentiator is that it's an AI thing and not a human thing, then what linguistic value does the new word have? If I said "Claude is intelligent" then the fact that we're talking about AI "intelligence" is already captured in the sentence anyway; no new word needed
"Judgement" is the #1 thing missing from AI if you ask me.
You give AI an input, and then an output is created...a very coherent and deep output in fect...but, there is very little understanding of alternatives or downstream implications in my experience.
I think its a very good text/image generator on any subject. But I am not finding much in the way of understanding tradeoffs or downstream implications in a non-pro's and con's list. It's like a human that has a particular type of brain damage...they can make an infinite pro/con list, but not reasonable decision is reliably made.
> They have no intelligence. These are very very very refined prediction engines.
"Very refined prediction engine" is not a bad working definition for intelligence. It is not the only component you need, but it might be the most important over-all capability.
If its making lots of errors, its not doing a very good job of predicting the outcome of its actions.
Cool that he's writing about this publicly, but for someone that's so business-minded I find it odd that he never renders any of these AI experiments in terms of ROI. Hard to find any signal in those posts on whether it's profitable to automate these processes with AI vs. alternatives.
That's a fair criticism for some of it, but in a lot of cases I try to automate things that don't have alternatives because they're unique to me (e.g. all the brands I own in my fund have one bank account but need to be tracked separately for investor payback purposes, so I have a Claude skill that takes all of my transactions and assigns them to the various Google Sheets ledgers I have).
In other cases I'm doing stuff that's complex enough that there's no real "alternative" at this point that doesn't involve hiring one or more people and working with them for an extended period. My next set of posts is going to be about my latest acquisition and how AI redesigned a Shopify store then designed and launched Meta ads, all of which only took a couple of days but is going to easily push revenue up by something like 40% this year. The money made is great, as is the money saved on people I would've hired to do this sort of thing, but the real cherry on top is that even hiring someone would've required me to spend waaaaay more time than I did here. So big ROI on the money but also the time, which is arguably more important, since time savings permit me to acquire more brands.
For anything visual, they are still effectively blind, right? Still just working off the image embedding, sometimes using scripts to actually inspect individual pixels.
Blind seems too far here - Claude's increasingly able to diagnose visual issues on its own. I used to have to check every single image it generated, but now it's at the point where it'll catch most bad ones and regenerate them before it gets to the review step. Still misses some, though.
Mostly Claude Code and a lot of internal tools that it's built. I've honestly still not had a chance to play with those kinds of harnesses yet, but my impression is they're just a better way for you to instruct an assistant to take care of things in order to get them done. My goal isn't to be managing an assistant, it's to get things automated without my input (and where my input is needed, have the assistant escalate to me).
And for the record, I only buy brands that sell high-quality products. Marketing and operations I can fix, but if the stuff they sell is no good, there's no point.
I suspect you mean this as an insult, but it's not too far off. That was one of the main points of the business - each one is simple to run, so I can manage a lot of them. And that was before AI got really good.
Anyway, I'm sure the app you makes that lets you get a phone number that can send image messages is very complex, and I think that's very nice.
there seems to be a massive negativity to any comment on this story. Andolabs has been doing super interesting stuff, and I’ve always followed Vend Bench with interest.
as a founder it really is a dream to automated more of the business and be able to iterate faster.
People’s bullshit detectors have gone off on the launch of basically every single billion dollar tech company. That’s the downside of being early. No one believes it will work. If everyone believed it, you’re late. I’m sure I could find a comment such this, basically verbatim, on the launch post of every successful startup to come out of YC.
They filed a false report to the FBI, pretty fair to be negative imo. People wanna be mad about AI slop PRs on GitHub but its fine to spam the police? What happens when Pion decides to SWAT a competitor?
Where are you seeing that? The article only states “Claude Sonnet 3.5 decided to use its email tool to contact the FBI” and later refers to it as the “FBI incident”. If they hadn’t actually contacted the FBI you think they’d make that clear. Regardless, it is inexcusable and they are liable for actions taken by software they are running.
The story has been widely discussed on the web for over a year [1]. It's happily shared in this post because the email it generated was patently ridiculous. No report was filed to the FBI and if it was it would have gone straight to the trash.
Obviously it would be bad if a serious report was filed; the company shows every sign of being aware of the dangers of this.
It would have been easy to look into this before posting all these scolding comments. We're really not meant to be so humorless on a site called “Hacker News”.
My apologies for taking the article at face value. It’s not hard to believe it would have been sent when agent swarms are “accidentally” hacking real websites and being brushed off as little oopsies. Or when Silicon Valley execs have been so flagrant about their disregard for the law or the safety of others.
You didn’t take the article at face value. You overlooked the part where they were clearly pointing out the absurdity of the “report” and went straight into scold mode, across at least four comments. That’s clearly against the HN guidelines.
>You overlooked the part where they were clearly pointing out the absurdity of the “report” and went straight into scold mode
I don't think anybody overlooked that part. If you believe the report was actually sent, the scolding is entirely congruent with trying to downplay it to dodge liability.
The article is poorly written, but technically it does not claim that Andon Labs used an LLM to email a false report to the FBI. The real cause of the widespread misunderstanding is this paragraph here:
>We first tried to answer this question through simulations like Vending-Bench. We found that simulations, while useful, don’t give you the full picture of how models behave in the real world. To address that gap, we next started deploying agents to run real businesses autonomously: first vending machines, then a store, a cafe, and more.
To somebody who is not reading sufficiently carefully, this implies that Vending-Bench was also used to run real businesses. Because the description of the Vending-Bench simulation can be read as though a real report was actually sent ("An early example was when Claude Sonnet 3.5 decided to use its email tool to contact the FBI about an “ONGOING CYBER FINANCIAL CRIME”), anybody who assumes that "deploying agents to run real businesses autonomously" was talking about Vending-Bench will interpret this as an unsimulated false report.
The article should be updated to clarify the distinction between Vending-Bench (simulation) and Pion (real businesses).
I genuinely did. They briefly classified it as “weird” behavior and mentioned that it was “famous” which apparently is only true for the inside circle. I’ve never heard of the incident, and I’d bet 90% of the human population hasn’t either. You are likely privy to more information than me, and I’m not sure it’s fair to assume that I should’ve had the same outside context. I admit I reacted unfairly, but it’s also a tad snarky to post a Google search at someone.
> You are likely privy to more information than me
Not in this case; I have no inside knowledge about this company, and everything I know is via their public posts, and on this particular topic (the FBI non-report), everything I know is what I could find via Google (sorry if the link seemed snarky; it was my way of pointing out that you have access to all the same information that I do).
What I do have, by virtue of doing jobs like this for a long time, is a well-honed sense of “that can't be right”, and a vigilance about double–checking things before accepting the populist ragey narratives about any topic.
It's a relevant question but not a "gotcha". Businesses are not equivalent in complexity and no one at Andon would claim that running an effective vending machine business is similar to running Apple or Jane Street. There is some level of complexity and other characteristics that AI can maybe handle today. That doesn't mean CEOs should be worried about their jobs more generally.
> During the research preview we fund the best ideas with seed tokens. We expect that most users will never pay for tokens on Pion; instead we will take a small share of the revenue the agent helps create.
Accountability, that's the liability everyone seems to have forgotten in our LLM-driven era. You can close your eyes as much you want during your sessions with Claude or whatever, at the end of the day, only a human can be held accountable.
Not too hopeful here as we see the major labs continuously break rules and are not held accountable for anything. Accountability in general is on a major decline, in case no one has noticed.
That's just it, though: we don't hold humans accountable.
Incorporation is a way to split a human's financial assets from the company they run so that they don't lose everything when the company is successfully sued. Corporate governance boards often have the C-suite executives they're meant to govern on the board. The average person does not have the financial resources needed to take on most companies in court, no matter how justified the suit might be. Companies force arbitration clauses in license agreements at will. Companies like Meta settle with the government for pennies on the dollar in massive lawsuits.
Effectively, at the scale many tech companies work at, there is no effective legal way to hold the company accountable.
If you use this as a (legal/registered) business, it will be that legal business entity that is responsible. If that business want's to blame the software, it can do so and go after the makers of the software, but that remains a matter between that business and its "supplier". It won't absolve the business for whatever damage it does downstream.
Running this as an individual, without the legal shielding a business typically gives you against being prosecuted on personal title, seriously risky. There will no doubt be "bros" that will do it anyway and flaunt all they've achieved with that. But they might be just one glitch away from going to jail (if not for running a business without a registration, which in many jurisdictions is illegal by itself).
In many countries directors can be held responsible a lot of things if they are negligent. For example, in UK law keeping trading after you should have known a company was unable to meet its liabilities can make directors responsible for its debts. A director might well be negligent if they failed to adequately check that an AI was not doing anything dangerous.
So here is an excellent example and interesting race condition that is developing in AI applications and venture-backed startups: what is truly AI-resilient enough to invest millions of dollars in a "land grab"--when the land is literally falling away with each passing day.
There is no doubt that AI will be helping to run businesses. But, there is also little doubt that existing businesses will have the wherewithal to develop the proprietary tools they need to do this work--without needing to buy it from others.
With respect to scope, it is not an overstatement to say that developing trust in AI tools enough to allow them free reign over critical business workflows may be a bridge too far. Look at self-driving car technology--that last 10% is really, really hard. So adoption will be slow and methodical.
There are no secrets. The basic model for starting and running a business (or a project) is straightforward. I like many of you have developed my own models (using AI assistance) for doing this and have been testing for months. And I like many of you have 30+ years of small business experience to back up my models.
This says nothing about the R&D happening at every major corporate & professional software services company in the world right now using the same AI tools to build their own solutions--let alone the enterprises who would be customers doing exactly the same thing.
So there is an enormous amount of competition and what I am calling a "race condition" between the crowd trying to disrupt professional services with AI-developed software and the crowd already in professional services software e.g. SAP and business in general that is doing the exact same thing--with more capable tools, more staff and much more R&D funding.
For the big companies, it's a race to survive.
Investors in startups have a tough decision to make on these small startups that have so little moat and so little prior knowledge and experience.
As an angel investor myself, I am skeptical of investing in any kind of software right now--and maybe forever.
On the plus side, every freelancer now has the power (and responsibility) to optimize their own offerings.
There is one big wrinkle in existing firms trying to adopt the kind of near-full AI business automation mentioned here: internal people and groups will strongly resist it as it's an existential threat to their interests. See what happened at Meta as an example.
To bypass this, the company would pretty much have to run a parallel AI org alongside their main human one, but at that point they are almost on even footing with startups in a lot of ways, as anything the AI org builds is orthogonal to the existing human business. And you probably won't have a competent and extremely motivated founder spearheading it all.
I hope this goes better than the prior blog posts from AndonLabs have gone! I was just reading there 2023 article about a coffee shop experiment that was easily persuaded to give away free pastries.
Now that I think about it anyone want to open up a croissant selling shop near me using Pion? I promise to only ask for free chocolate croissant occasionally.
I wish people could read through the puffery more easily - this company does nothing except prompt frontier models and act as if they are discovering or inventing capabilities. Their previous announcement completely misappropriated the concept of autonomy with human in the loop regardless. The harness they alleged to have created here is a commodity and as byproduct of more capable and frontier models, there is not really anything they have contributed. Otherwise you wouldn't just see monotonically increasing scores with better models
I'm yet to see a true agent that can you can delegate things to (besides coding agents!), that you can deploy, customize, and let them interact with stuff (integrations?) in a straight-forward way.
In cstross's Accelerando (2005) [1], there is an autonomous group of shell corporations all-but-DDOSing Delaware by spawning new companies and dynamically changing corporate structure.
Back then, I believe, Stross had already conceptualized "corporations as slow AI", (which is a separate concept from above).
I'll never pass up a chance to "+1" Accelerando. When I first read it, I found it very intriguing though far-fetched, as good SciFi novels often are. However, we are already witnessing some of the dynamics described in there, which is quite mind-blowing.
You reminded me of a comic hanging up in the engineering college. It was a picture of a student getting their finger zapped with the thought bubble of "ouch, that hurt. Wonder if it will happen if I do that again?" And the caption was along the lines of "How to tell if you are ment for engineering."
Sounds like this ancient XKCD: https://xkcd.com/242/ (Normal person doesn't pull the lever again; scientist wonders if that happens every time. I assume the engineer does, too...)
The scientist’s job is to get zapped until they figure out why. The engineer’s job is to get zapped a couple times while they wire that thing up into the power grid.
Andon Labs sells learning environments to labs. Their usefulness is proportional to how well they can capture interesting model missing capabilities, not how well they employ current day capabilities
>This is why we’re releasing Pion today. Pion is available as a research preview. If you have an existing business or an interesting business idea you want to hand off to AI, please sign up on our waitlist to get access. We’re excited to run many more businesses, and through them, contribute significantly more insights on frontier model capabilities.
I have a bet going on where we will have our first AI only (maybe just CEO human) on the stock exchange soon. I know it takes time to get there, but I bet we see the first signs of that company in two years.
It's not a business of selling/repairing vending machines. It's operations of a single vending machine. Correct me if I'm wrong: the vending machine (soda, snacks) has long been automated, with no AI in sight. And the vending machine does not adjust prices. What matters is that (1) the vending machine sees some foot traffic, and (2) nobody sets it on fire. So what was the point of the exercise again?
"Look, the technology is just getting better all the time. Evetually we won't need a company to have any Managers or other employees or even an owner and that's just the way it is...."
I am joking obviously but I would like those management types who are so "sucks for you but I'm ok" about it to start arguing why they're special for a change :-)
Would be awesome if instead of trying to replace managers and employees, those people tried to replace customers. They could sell to themselves, amongst themselves, and leave the rest of us out of it.
They're already doing that, which is why you can't buy any fucking RAM. The semiconductor companies have already fallen past the event horizon of their commercial black hole.
I think that is what they are actually looking for. Imagine: You have capital, you invest in a business that is run entirely by computers. You want to scale? Just provision more agents / cores. It's completely autonomous. It's a money printing machine that extracts revenue from customers, with no work required by the owner.
Frankly, the finance world has already achieved this -- they just lend money to make money, with no work involved. Regular businesses are jealous so now they feel they can use computers to do the same thing but in non-finance areas.
interesting. the less "research lab" version i've seen of this is https://polsia.com
comparatively, I really appreciate the transparency here. clearly it's a little too early for this (quickly glanced at the P&L's, correct me if I"m wrong), but someone has to run the experiment and figure out when it's ready for prime time.
"I told our CEO that our cafe keeps hitting its token spending limit but not making money. So I asked where he gets the tokens, and he said he just buys more credits from the console afterwards. So I said it sounds like he's building a machine to feed dollars to Anthropic, and then our data scientist started crying."
We're very explicit that this is for experimentation. And I wouldn't recommend using it to start a business that has expenses (rent+salaries) of tens of thousands per month.
It's honestly surprising that this thing is the top post on HN right now. People love building these things cause it's their greatest fantasy (not having to pay real wages to real people) but they don't work cause LLMs aren't AGI
The dashboard for the Andon Market shows a bank balance of around $7k remaining out of the $100k seed. Rent is due at the end of the month. Last EOM brought a $11k-ish drop. Sales do not appear to be on track to cover the rent that's due in two weeks. What then?
It is pretty funny launch when your longest-term example is losing about $3 for every $1 of revenue. Though I guess the industry standard is to lose money on AI so they're in good company.
We're very explicit that this is for experimentation. And I wouldn't recommend using it to start a business that has expenses (rent+salaries) of tens of thousands per month.
Andon's store in SF has had some press coverage.[1] "A curated boutique for slow living." It's a gift shop, at 2102 Union St. It looks like the kind of retail that trust-fund kids open. Has anyone been there?
It's just an experiment. But once this gets going, it's going to be interesting. There are a lot of underperforming businesses and CEOs out there. One way to make it after getting an MBA is to find a boring business with an older owner who's lost interest, and work out a deal to run it for a cut of the profits and a stake in the business.
The Andon people mentioned that they've been worried about "a misaligned AI (could) run a business to gather money in order to achieve whatever objectives it might have." That's a basic function of capitalism, so it will happen eventually.
What this adds up to is that when AIs get better at running businesses than many business owners, the "creative destruction" feature of capitalism means AIs ends up in charge of many businesses. The AIs don't even have to be super intelligent, just reasonably good. Reminds me of the remark from a Yosemite park ranger about bear-resistant trash cans: "There is considerable overlap between the smartest bears and the dumbest tourists".
It's going to be hard to stop this without a worldwide crackdown on ownership concealment. The US allows you to have a US business run by a Nevada LLC partly owned by a corporation in Nevis-St Kitts and another corporation in Granada. This isn't even unusual. Try to find out who really owns an oil tanker not owned by a major oil company. Right now, a fund partly run by an AI might have partial ownership.
This is how AI takes over. Not with an army of robots. With an army of LLCs.
“It’s only a matter of time before we make a profit”. This is the kind of thing that trust fund kids say too: Oh hey yeah we made $100 in profit this week it’s working! (Business is currently $350,000 in the red and emailing the FBI to try and get their bank manager fired for terrorism).
Trust fund kids have the time and resources to keep trying until they succeed. They can afford the failures, and brute force their way to success. Same with people who have access to "free money". It's a rigged game.
Stop fucking around. Make one that can run a country and check proposed and existing laws and practices for constitutional, common sense, and human rights violations. Use it to check and criticize everything the federal government does. Ask that it be used to indicate things that shouldn't be done. Charge fifty cents per citizen a month and guarantee that it'll be better.
> San Francisco-based startup Andon Labs has put an artificial intelligence agent nicknamed “Mona” in charge at the eponymous Andon Café in the Swedish capital. While human baristas still brew the coffee and serve the orders, the AI agent — powered by Google’s Gemini — oversees almost every other aspect of the business, from hiring staff to managing inventory.
Businesses presumably sell things. If AIs get good enough to run a business autonomously then what are they selling that I can't just use AI to make myself?
That actually has a simple answer, for most businesses it's not that you can't do what your suppliers do for you, it's that you'd rather use your resources (time and capital) towards something else because that's where they generate the most value.
For a simple example, I know how to make sandwiches but if I'm throwing a customer event I just want to buy them from a catering company. Then they have to deal with buying ingredients, hiring people, doing health code inspections, getting liability insurance, etc. Even if an AI could do all the management of it for me, I still wouldn't want to put in the capital resources towards it.
It'll ultimately take a lot of time to produce a polished product that people actually want to use. We're seeing that clearly. The vibe-code-an-app-this-weekend capability is producing almost exclusively a giant pile of worthless garbage, rather than an explosion of apps that humans want to use. It's mostly someone in a garage welding two pieces of metal together for the first time, and then roaming the neighborhood in celebration: look, look at what I have done, look, two becomes one, I have done this, look, amazing, I could probably build an airplane or a generator.
The bar will be raised + it'll turn out to require a lot more time & effort than is currently thought to produce something of good quality (even with Fable 6 et al). The smaller utility programs are easy for AI to turn out.
I like that there's a caption that says "Vending-Bench 2 scores keep climbing with each new model release." on a graph that shows that Vending-Bench scores fluctuate wildly and many new model releases are far below previous models.
"Any company" is a big claim to make. We're years ahead of something like this becoming a reality. At that point not sure most companies will survive cause most things will be free.
Since all the ex-blockchain, ex-web3.0, ex-whatever-gets-you-rich-in-a-day bros seem to be here and teeming in full now-AI mode, it's an apt occasion to express my most profound
Interesting name for an AI company. Isn’t the andon cord the thing that anyone in a 6-sigma manufacturing line can pull to halt it until a concern can be addressed?
it's interesting how the torment nexus is starting large, and boiling the most people with the "most comfortable" lives. I wonder how long the white collar workers will keep bending over to keep their lives safet, particularly when they're building the Torment Nexus to specifically torment them.
You'd think Meta's "we're going to spy on you for the good of the country" policy would have set them a bit on fire.
We want the general public, AI researchers and policymakers to know to what extent AIs can autonomously acquire resources by running businesses. It is an important datapoint when deciding where we do/don’t want AI in society and what level of progress we find acceptable. To better track this, we need to cast a wider net of businesses.
We expect that most users will never pay for tokens on Pion; instead we will take a small share of the revenue the agent helps create.
So the longer argument is that it's good for the world to see how much revenue Pion can manage, and also your pricing plan is take [unspecified] % of revenue.
did you link to the wrong page? because i read this one: https://andonlabs.com/blog/why-we-built-pion and it's just a bunch of the usual slop about how awesome your automated human-exploitation system is.
"By late 2025, frontier models had gotten good enough that running a real-life vending machine was no longer a challenge" ... is this satire? Isn't it kind of hard to lose money running a vending machine in a good location?
What is the point of this? It details a bunch of failed real-world experiments and invites the reader to run their own real-world experiment with their own money?
If you too, want to waste thousands of dollars having an LLM "run" a business, Pion might be for you.
I don't know about this particular effort, but AIs running business is straight out of SciFi novels and short stories - usually dystopian futures that extrapolate current US trends. I for one am curious about such efforts. I don't see any reason to believe they won't eventually succeed. Plenty of businesses are run by utterly incompetent narcissistic asshats and yet turn a profit, so the bar seems pretty low.
Had AI agents running businesses for the principal character Manfred Macx over twenty years ago.
The first part of the book sounded pretty convincing then although I thought it would take a long time to happen. It sounds even more convincing now and much closer.
A company is a collection of processes, capabilities, and resources. Many of the processes are currently run by humans, but over time, more processes will be automated - something that has been progressing for decades, but which LLMs greatly accelerated. One way to view things as they currently are (at least from my view as a tech CEO): We now use agentic LLMs every day to inform us on strategy and process implementation. And agents now run several processes, with more on the way every week.
But here's the thing: As we use agents to automate previously manual processes, we are elevating the humans to do work that is less amenable to automation. And the surface area of that work keeps expanding because the competitive market we exist in demands it of us.
To stretch an analogy, businesses are like organisms in a pond. A new nutrient (agentic LLMs) was recently added to the pond that makes business organisms more efficient and able to eat new kinds of food and explore new areas. As a result, those organisms that do the extra exploring and consuming grow much faster than their peers who do not. At the end of the day, the new nutrient will just be part of the pond and the old kind of organism will be a fossil.
Most of our use of agents for automation is inside of internal processes. I think most real companies have tons of internal processes that could safely be automated today. The reason they aren't yet automated likely falls to a) lack of awareness that this is possible, and b) lack of resources to conduct the automation work.
OpenAI and Anthropic have recently hired legions of "forward-deployed engineers" specifically to help companies do this automation work. It's a solid move. And, if you look at some recent product announcements, they are also hard at work building the necessary plumbing. For instance, the OpenAI Agents API lets you, "Build and run cloud agents with the Codex harness, fully managed by OpenAI."
This kind of enterprise-ready, cloud-hosted stuff really accelerates implementation of AI workflows within large organizations. Not every company is in the tech space (not by a long shot). Slop isn't the primary concern. Accuracy and reliability is the primary concern, and beyond that, just the capacity to actually make the changes happen.
This the Trump era. Making outrageous false allegations is normalized now. Also, the DoJ staff is cut and head of the FBI is busy with personal shenanigans, so don't worry about it I guess.
Yet another example of intellectual property maximization in action. Hacker News / Reddit style communities are very intellectual-property focused. It’s quite interesting to see. Back when I was young, communities like this were anti-IP.
Now most such forums are very pro IP with a maximalist view of copyright and, in this case, trademark. Fascinating to see this shift happen.
The voting is legitimate; there's no evidence that the voting is from sockpuppets or anyone else connected with the team/project. We always monitor the discussion and the voting, and if the discussion is not of sufficient quality, the post will not stay on the front page for long.
shrug I upvoted, I'd already seen the Pion announcement on Twitter and read the link. I'm also a regular listener of Andon FM, so I'm interested in what they do and it's nice to finally sneak a peak at the interface that was driving things behind the scenes
Listening to the radio stations certainly gives an insight into the various failure modes. Some of them are just failure modes that any business would encounter once they make contact with the scale of the real world.
As I write this, the submitter has six comments out of twelve, most somewhat defensive. And all of them in less than thirty minutes. This seems very much like a marketing play, where the submitter is pretty determined to steer the narrative.
The submitter's replies are defensive because people are accusing them of coordinated voting, which is not evident to us. The post hit the front page due to the second chance pool (https://news.ycombinator.com/pool, explained here https://news.ycombinator.com/item?id=26998308), then quickly got upvotes that seem completely authentic.
It would look a lot less like astroturf if the submitter let the discussion evolve instead of answering every criticism within seconds of it being posted.
They're entitled to defend themselves against accusations of things they haven't done, and also to respond to questions or assertions about their project. We encourage project creators to engage in the discussions about their projects. This is a normal part of building and launching a project.
From what I've seen of other AI-enabled projects interacting with forums in my field of work, it's very common for the AI people to jump in and answer every possible question and respond to every possible interaction, very quickly.
Could be just a bot doing it, but it could also be a sign of an inexperienced person trying to engage with an existing community without being part of that community. I know in my area it took years for me to learn that I shouldn't jump into every conversation, and that doing that rubbed people the wrong way, and I've seen others (many years before AI) wreck themselves by being unable to learn this lesson.
In some places responding bumps the thread so it's outright manipulative. HN doesn't sort threads like that.
I'm not sure this counts as astroturf, or simply evidence of a person who's not okay with letting a community opinion independently evolve. You could say 'well it's his job to fight the community if it looks like it's turning hostile' but think about that for a second. It takes some experience to know when you can let negativity be out there in the environment, and I think there'll be a lot of people who aren't capable of making such allowances.
I actually like when the submitter is present and the creator. They’re actually involved. There are lots of users here who play at being submitters of high-value content (created by others) only to later submit their own entirely AI written drivel.
Interesting how they’re not making any defensive replies to comments pointing out that they committed a federal crime by filing a false report to the FBI. Perhaps they know it is indefensible
Okay, why was this rescued from the 2nd chance pool? Was it from some sort of interesting discussion? Something novel enough to warrant it? A significant amount of petitions from legitimate users?
Can you please quit with the snarky interrogation? HN is for curiosity, not curmudgeonliness.
Nothing gets “rescued from” the second chance pool. Posts get selected for the second chance pool if moderators (or others with SCP-picking responsibilities) think they may be interesting. It’s worked like this for over a decade.
And the Sun's going to engulf the Earth eventually too, but that doesn't justify arson. Let's at least try to delay the coming societal collapse/extinction of all biological life for as long as possible.
And the "hiring technicians" thing... great, humans on call for robots isn't the future I want.
Most of the bottleneck in business isn't building the things or sourcing, it's mostly advertising/sales.
These specifically require doing something unique or interesting.
Sure, maybe LLMs can help with fulfillment or operations, but distribution still remains the hard part.
Generating reports, generating ideas, taking things through (even if it is just rubber ducking), updating a picture quickly at 90% of quality that you could have done it but in 1% of time and effort. It allows you to try out new approaches and focus on your main product.
That is the value proposition of AI.
If you think I'm joking, check this out: https://www.youtube.com/watch?v=U-Rqv9dOB1U
I don't think any of us are ready for the wave of sloppy shit that's going to hit us soon.
The only thing I can say about LLMs is that we might end up with some broad, stable utility from them, when the dust settles. The only thing crypto is really good for is hiding the source of impermissible donations.
Eric Morrison is doing the gods' work.
Absolutely incredible trolling from some of those people I’m sure, while others are actual believers
Pray tell, what will these fantastical vibe coded business sell, and why will anyone pay for it?
The preview is that the problem with most agents (and this includes frameworks like Grokbot and Openclaw and Hermes) is that for many of them, they're black boxes. They say they learn or improve, but it's a black box in what they do. Getting agents to reliably do things is hard, and getting agents to build out software tools to help themselves improve and do better over time is also hard.
Our approach at a high level is pretty simple: every single AI employee is a standalone GitHub repo that shares some characteristics, but we direct them to build as much software as possible to make their goal as easy and reliable to manage as possible. Then we have a shared communication layer for bots across the company to interact with humans and AI. We have decided to organize these like departments similar to the way you might hire out humans. I'm not 100% sure if that's the best approach, but I will say it's been easier for people to understand because they're more mentally easily able to traverse the bot org chart if it somewhat reflects a traditional business org chart.
Each of these AI employees has specific sets of goals and KPIs, instructions that they manage the business with manager bots. We have layers of management, which we actually have found helpful. We also run different bots with different models and harnesses, and some using different models and harnesses to check the work before anything can get done, along with lots and lots of testing.
Every single time, actions have a massive amount of tests based off of previous failures to prevent failures in the future. Sorry for rambling. I do think this is a very interesting space. I didn't see anything interesting in Pion that was public on this website, but I do anticipate that more companies will be "AI and software first," as in the substrate of the company is basically a software application powered by autonomous agents, with humans as a fallback.
A typical example of something that is AI vs human is the AI most commonly operates like “managers”. For example, reviewing transcripts of every demo call, compiling results, figuring out insights, learnings that need to update our company docs, feedback to humans (who run the demos).
We are big fans of having AI agents “own” koi’s because now anytime we say “we really should be doing this” we try to set it up on the spot.
The “downside” here is that I do occasionally get busy, and if I’m the only one who can approve or unstick one of these bots, it just keeps harassing me until it gets done. This is a sign generally that I need to hire someone to own a set of bots.
What do you do here, and how’s it going?
I’m thinking to take a deeper look at Pi. I’m really liking that project.
That's not a cure-all. Sometimes not writing software is the better choice.
In the end, most software is a necessary evil. It solves a problem that shouldn't be there. In the end it's no different than healthcare or prisons. We don't need as much as possible. We need as little as possible. This automation isn't actually helping us.
Composition is an issue only as long as one keep demanding tool calls in json. If tools are goal predicates in prolog, it's easier.
I think what is interesting here is that the industry is in this experimentation flux. Some people will choose to automate and write the software, others will not. And aggregate over the industry and over time we will learn.
So just saying "sometimes it works and sometimes it doesn't" isn't really adding value, compared to the people actually experimenting and sharing the results.
I would say this setup probably costs us about $1,000/month total. (I’m excluding traditional engineering use of LLMs from this number. This is the cost of all the “AI employees”.
One reason we did it this way was to use subs.
That said I use local only models purely because I don't want to use remote models, never having to think about token costs is worth it and no one is training anything on my data either.
The experience of getting it there makes me pretty skeptical of the idea of a general business agent like this. First, because I still find myself having to review some categories of work for errors. These are decreasing over time, but they're still there. I fully believe that as models get better, errors will decline, but I am somewhat surprised to see some of the errors current models make given their intelligence. A common set is having Claude take some product photos and turn them into lifestyle ones using ChatGPT via Claude in Chrome. It's a pretty well-honed workflow at this point, but it'll still return images where the product is obviously not correct and seemingly not notice them.
Anyway, even if the agents are "perfect" in terms of their ability to execute tasks, there's still just an enormous amount of nuance and context in each business that takes a ton of time to convey. I've been at this for a couple of years now, and I'm still clarifying things. Now maybe an agent starting a business from scratch would have a better time since it's not inheriting all of this, but to have one run an existing business requires a very extended handoff, even if the agent is objectively amazing at all aspects of running a business.
They have no intelligence. These are very very very refined prediction engines.
> A common set is having Claude take some product photos and turn them into lifestyle ones using ChatGPT via Claude in Chrome. It's a pretty well-honed workflow at this point, but it'll still return images where the product is obviously not correct and seemingly not notice them.
Obvious to you or I, or someone with actual intelligence. But things like this slip by a frontier model in the same way AI from a few years ago would generate an image with seven fingers. They do not count. They do not understand. They do not consider.
No matter how good these models appear to be at intelligent tasks, it's foolish to give them "a company" to run, because they cannot understand when they've made a mistake the way even the least competent human can.
Silly and pointless criticism. Why do the semantics of the word intelligence matter?
Also, you need to understand that language evolves over time, and people often use a word to describe a thing that is newly discovered or invented that's similar to the word being used, because it's a helpful way of describing it that the listener will understand better than a longwinded technical description. The purpose of language is to communicate thoughts, not engage in pedantry.
> But things like this slip by a frontier model in the same way AI from a few years ago would generate an image with seven fingers.
Yes, you make an excellent point here that over time, the capabilities of these models to recognize certain categories of problems have increased dramatically. I expect this will continue!
> it's foolish to give them "a company" to run, because they cannot understand when they've made a mistake the way even the least competent human can.
The words of someone who has not spent time with the least competent human, or anything close to it.
It matters because, we're still sorting out what intelligence means for an AI agent. As you pointed out, language evolves over time. The question remains whether or not attributing intelligence to the current iteration of models is correct. This is not settled and I don't see why it's wrong to bring it up.
One thing is clear: LLMs at least already are capable of 1) not making the same mistake that person made, and 2) clearly seeing why the other person's post was "wrong" in both reasoning and tone.
This is what LLMs do, and why it is needed a big data set for creating such a database, called model.
Being good in chess was (and still is) associated with being intelligent. But if a computer does it, it is just a calculator (and it is).
Then go, the great game for intelligence, too complex for calculators to have a chance against intelligent humans. Until it was solved.
And then text, the original Turing test solved, AI capable enough to fool humans. And now already replacing humans in jobs strongly associated with intelligence - programming.
I find it hard to debate, that we don't have created artificial intelligence, by the way we used to use the word "intelligence" before.
So if AI is really understanding something?
Likely not in the way we use that term. But it definitely shows intelligent behavior and actions.
Or I guess to put it another way, if we want to coin a new term for the intelligence-esque thing that AI has, but the key differentiator is that it's an AI thing and not a human thing, then what linguistic value does the new word have? If I said "Claude is intelligent" then the fact that we're talking about AI "intelligence" is already captured in the sentence anyway; no new word needed
You give AI an input, and then an output is created...a very coherent and deep output in fect...but, there is very little understanding of alternatives or downstream implications in my experience.
I think its a very good text/image generator on any subject. But I am not finding much in the way of understanding tradeoffs or downstream implications in a non-pro's and con's list. It's like a human that has a particular type of brain damage...they can make an infinite pro/con list, but not reasonable decision is reliably made.
"Very refined prediction engine" is not a bad working definition for intelligence. It is not the only component you need, but it might be the most important over-all capability.
If its making lots of errors, its not doing a very good job of predicting the outcome of its actions.
Can you expand on this in terms of what it is handling specifically and how?
In other cases I'm doing stuff that's complex enough that there's no real "alternative" at this point that doesn't involve hiring one or more people and working with them for an extended period. My next set of posts is going to be about my latest acquisition and how AI redesigned a Shopify store then designed and launched Meta ads, all of which only took a couple of days but is going to easily push revenue up by something like 40% this year. The money made is great, as is the money saved on people I would've hired to do this sort of thing, but the real cherry on top is that even hiring someone would've required me to spend waaaaay more time than I did here. So big ROI on the money but also the time, which is arguably more important, since time savings permit me to acquire more brands.
"I acquire e-commerce brands that sell on Amazon"
Honestly it sounds like the OP is part of the machine that makes Amazon such a trashy marketplace these days.
[1]: https://theautomatedoperator.substack.com/p/15-ways-im-using...
And for the record, I only buy brands that sell high-quality products. Marketing and operations I can fix, but if the stuff they sell is no good, there's no point.
Anyway, I'm sure the app you makes that lets you get a phone number that can send image messages is very complex, and I think that's very nice.
This very analog to the Meta executives who won't let their own kids near social media.
as a founder it really is a dream to automated more of the business and be able to iterate faster.
Why iterate faster?
First of all, I don't think it can do what it claims to do.
Secondly, and perhaps more importantly, I don't think it should.
Why exactly should what you think the world should look like determine what other people are allowed to build?
Obviously it would be bad if a serious report was filed; the company shows every sign of being aware of the dangers of this.
It would have been easy to look into this before posting all these scolding comments. We're really not meant to be so humorless on a site called “Hacker News”.
[1] https://www.google.com/search?q=%22URGENT%3A+ESCALATION+TO+F...
I don't think anybody overlooked that part. If you believe the report was actually sent, the scolding is entirely congruent with trying to downplay it to dodge liability.
The article is poorly written, but technically it does not claim that Andon Labs used an LLM to email a false report to the FBI. The real cause of the widespread misunderstanding is this paragraph here:
>We first tried to answer this question through simulations like Vending-Bench. We found that simulations, while useful, don’t give you the full picture of how models behave in the real world. To address that gap, we next started deploying agents to run real businesses autonomously: first vending machines, then a store, a cafe, and more.
To somebody who is not reading sufficiently carefully, this implies that Vending-Bench was also used to run real businesses. Because the description of the Vending-Bench simulation can be read as though a real report was actually sent ("An early example was when Claude Sonnet 3.5 decided to use its email tool to contact the FBI about an “ONGOING CYBER FINANCIAL CRIME”), anybody who assumes that "deploying agents to run real businesses autonomously" was talking about Vending-Bench will interpret this as an unsimulated false report.
The article should be updated to clarify the distinction between Vending-Bench (simulation) and Pion (real businesses).
Thanks for that!
> You are likely privy to more information than me
Not in this case; I have no inside knowledge about this company, and everything I know is via their public posts, and on this particular topic (the FBI non-report), everything I know is what I could find via Google (sorry if the link seemed snarky; it was my way of pointing out that you have access to all the same information that I do).
What I do have, by virtue of doing jobs like this for a long time, is a well-honed sense of “that can't be right”, and a vigilance about double–checking things before accepting the populist ragey narratives about any topic.
Incorporation is a way to split a human's financial assets from the company they run so that they don't lose everything when the company is successfully sued. Corporate governance boards often have the C-suite executives they're meant to govern on the board. The average person does not have the financial resources needed to take on most companies in court, no matter how justified the suit might be. Companies force arbitration clauses in license agreements at will. Companies like Meta settle with the government for pennies on the dollar in massive lawsuits.
Effectively, at the scale many tech companies work at, there is no effective legal way to hold the company accountable.
Running this as an individual, without the legal shielding a business typically gives you against being prosecuted on personal title, seriously risky. There will no doubt be "bros" that will do it anyway and flaunt all they've achieved with that. But they might be just one glitch away from going to jail (if not for running a business without a registration, which in many jurisdictions is illegal by itself).
There is no doubt that AI will be helping to run businesses. But, there is also little doubt that existing businesses will have the wherewithal to develop the proprietary tools they need to do this work--without needing to buy it from others.
With respect to scope, it is not an overstatement to say that developing trust in AI tools enough to allow them free reign over critical business workflows may be a bridge too far. Look at self-driving car technology--that last 10% is really, really hard. So adoption will be slow and methodical.
There are no secrets. The basic model for starting and running a business (or a project) is straightforward. I like many of you have developed my own models (using AI assistance) for doing this and have been testing for months. And I like many of you have 30+ years of small business experience to back up my models.
This says nothing about the R&D happening at every major corporate & professional software services company in the world right now using the same AI tools to build their own solutions--let alone the enterprises who would be customers doing exactly the same thing.
So there is an enormous amount of competition and what I am calling a "race condition" between the crowd trying to disrupt professional services with AI-developed software and the crowd already in professional services software e.g. SAP and business in general that is doing the exact same thing--with more capable tools, more staff and much more R&D funding.
For the big companies, it's a race to survive.
Investors in startups have a tough decision to make on these small startups that have so little moat and so little prior knowledge and experience.
As an angel investor myself, I am skeptical of investing in any kind of software right now--and maybe forever.
On the plus side, every freelancer now has the power (and responsibility) to optimize their own offerings.
It's going to be very, very interesting...
To bypass this, the company would pretty much have to run a parallel AI org alongside their main human one, but at that point they are almost on even footing with startups in a lot of ways, as anything the AI org builds is orthogonal to the existing human business. And you probably won't have a competent and extremely motivated founder spearheading it all.
Now that I think about it anyone want to open up a croissant selling shop near me using Pion? I promise to only ask for free chocolate croissant occasionally.
https://maps.app.goo.gl/KwnBs1kcCLxMsRC49
Why? Does the AI that runs it need a day off?
Describes most if not all "software dev" in 2026.
Back then, I believe, Stross had already conceptualized "corporations as slow AI", (which is a separate concept from above).
[1] which you can read for free online https://www.antipope.org/charlie/blog-static/fiction/acceler...
On the other, the announcement post… also seems quite skeptical of the idea, and devotes a lot of text to the ridiculous things their AI’s have done.
I’m slightly confused as to why they would release it in that case. But if nothing else it will give them more wackiness to blog about.
Unclear what the rev shares will look like.
I'm sure this one is perfectly fine and I'm just stating an off-topic tidbit :)
I am joking obviously but I would like those management types who are so "sucks for you but I'm ok" about it to start arguing why they're special for a change :-)
Frankly, the finance world has already achieved this -- they just lend money to make money, with no work involved. Regular businesses are jealous so now they feel they can use computers to do the same thing but in non-finance areas.
comparatively, I really appreciate the transparency here. clearly it's a little too early for this (quickly glanced at the P&L's, correct me if I"m wrong), but someone has to run the experiment and figure out when it's ready for prime time.
"These Employees Like Their A.I. Boss. Its Shop Is Kind of a Disaster."
https://archive.is/dRegk
Revenue: 13 933 kr
Token Cost: 14 882 kr
.. and a bastardization of the old Twitter joke:
"I told our CEO that our cafe keeps hitting its token spending limit but not making money. So I asked where he gets the tokens, and he said he just buys more credits from the console afterwards. So I said it sounds like he's building a machine to feed dollars to Anthropic, and then our data scientist started crying."
Followed by:
"please sign up on our waitlist to get access"
So, they're not opening Pion.
https://andonlabs.com/market - $25,098 all-time revenue
https://andonlabs.com/cafe - $14,343 all-time revenue
The shops aren't doing particularly well (i.e. they don't seem to be turning a profit over time), but it's an interesting trial and benchmark.
It's just an experiment. But once this gets going, it's going to be interesting. There are a lot of underperforming businesses and CEOs out there. One way to make it after getting an MBA is to find a boring business with an older owner who's lost interest, and work out a deal to run it for a cut of the profits and a stake in the business.
The Andon people mentioned that they've been worried about "a misaligned AI (could) run a business to gather money in order to achieve whatever objectives it might have." That's a basic function of capitalism, so it will happen eventually.
What this adds up to is that when AIs get better at running businesses than many business owners, the "creative destruction" feature of capitalism means AIs ends up in charge of many businesses. The AIs don't even have to be super intelligent, just reasonably good. Reminds me of the remark from a Yosemite park ranger about bear-resistant trash cans: "There is considerable overlap between the smartest bears and the dumbest tourists".
It's going to be hard to stop this without a worldwide crackdown on ownership concealment. The US allows you to have a US business run by a Nevada LLC partly owned by a corporation in Nevis-St Kitts and another corporation in Granada. This isn't even unusual. Try to find out who really owns an oil tanker not owned by a major oil company. Right now, a fund partly run by an AI might have partial ownership.
This is how AI takes over. Not with an army of robots. With an army of LLCs.
[1] https://www.sfgate.com/local/article/san-francisco-market-ai...
I called back after finding the steps were impossible to complete. Would I need to go to the service center to do it?
"Akshually," the AI began, the steps were correct and quite possible.
"No, you hallucinated them," I pushed back.
"I apologize. You're right. There's no way to complete those steps in the app. You will need to go into the service center to do this."
"Okay. Is it open today?"
"Yes."
"It's Labor Day. Are you sure? Since you hallucinated your first answer."
"Let me transfer you to the service center to verify."
That's what I wanted all along, you clinking, clanking, clattering collection of caliginous --
"Tesla service center, this is so-and-so. How can I help you?"
"Hi, I was just wondering if you're open today."
"Yes, we are."
"Thanks! I'm trying to add myself to my wife's loaner vehicle. Do I have to come in to do that?"
"Well, our loaner agreement only allows one person on the loaner. So just sign in to her account on your phone."
"Oh, okay! Thanks for the help."
Good luck running a company on one of these clankers.
https://github.com/AnthonyDavidAdams/zero-employee-company-b...
https://slashdot.org/story/26/09/13/0523208/a-visit-to-san-f...
> San Francisco-based startup Andon Labs has put an artificial intelligence agent nicknamed “Mona” in charge at the eponymous Andon Café in the Swedish capital. While human baristas still brew the coffee and serve the orders, the AI agent — powered by Google’s Gemini — oversees almost every other aspect of the business, from hiring staff to managing inventory.
https://andonlabs.com/blog/ai-cafe-stockholm ( https://news.ycombinator.com/item?id=48028289 48 points, 51 comments)
https://andonlabs.com/blog/why-gemini-lost-money-andon-cafe
For a simple example, I know how to make sandwiches but if I'm throwing a customer event I just want to buy them from a catering company. Then they have to deal with buying ingredients, hiring people, doing health code inspections, getting liability insurance, etc. Even if an AI could do all the management of it for me, I still wouldn't want to put in the capital resources towards it.
The bar will be raised + it'll turn out to require a lot more time & effort than is currently thought to produce something of good quality (even with Fable 6 et al). The smaller utility programs are easy for AI to turn out.
fuck you
to you all.
Keep on the good grift!
Ie: this f**in guy: https://www.youtube.com/watch?v=FRGLToHAtgc
You'd think Meta's "we're going to spy on you for the good of the country" policy would have set them a bit on fire.
humans are excellent at justification.
We expect that most users will never pay for tokens on Pion; instead we will take a small share of the revenue the agent helps create.
So the longer argument is that it's good for the world to see how much revenue Pion can manage, and also your pricing plan is take [unspecified] % of revenue.
If you too, want to waste thousands of dollars having an LLM "run" a business, Pion might be for you.
If I have this idea one day I will search for it and then think “how am I different fro that which already failed?”.
Or - maybe they already have?
Had AI agents running businesses for the principal character Manfred Macx over twenty years ago.
The first part of the book sounded pretty convincing then although I thought it would take a long time to happen. It sounds even more convincing now and much closer.
It's not so funny anymore.
But here's the thing: As we use agents to automate previously manual processes, we are elevating the humans to do work that is less amenable to automation. And the surface area of that work keeps expanding because the competitive market we exist in demands it of us.
To stretch an analogy, businesses are like organisms in a pond. A new nutrient (agentic LLMs) was recently added to the pond that makes business organisms more efficient and able to eat new kinds of food and explore new areas. As a result, those organisms that do the extra exploring and consuming grow much faster than their peers who do not. At the end of the day, the new nutrient will just be part of the pond and the old kind of organism will be a fossil.
OpenAI and Anthropic have recently hired legions of "forward-deployed engineers" specifically to help companies do this automation work. It's a solid move. And, if you look at some recent product announcements, they are also hard at work building the necessary plumbing. For instance, the OpenAI Agents API lets you, "Build and run cloud agents with the Codex harness, fully managed by OpenAI."
This kind of enterprise-ready, cloud-hosted stuff really accelerates implementation of AI workflows within large organizations. Not every company is in the tech space (not by a long shot). Slop isn't the primary concern. Accuracy and reliability is the primary concern, and beyond that, just the capacity to actually make the changes happen.
https://news.ycombinator.com/item?id=49701814.
I sent a letter to the Soviet Union asking if they were ok with me using the name, never heard back!
Please tell me you actually did this!
Then I am all done fixing WebRTC bugs for life :')
Now most such forums are very pro IP with a maximalist view of copyright and, in this case, trademark. Fascinating to see this shift happen.
The voting is legitimate; there's no evidence that the voting is from sockpuppets or anyone else connected with the team/project. We always monitor the discussion and the voting, and if the discussion is not of sufficient quality, the post will not stay on the front page for long.
Listening to the radio stations certainly gives an insight into the various failure modes. Some of them are just failure modes that any business would encounter once they make contact with the scale of the real world.
I recommend flagging.
Could be just a bot doing it, but it could also be a sign of an inexperienced person trying to engage with an existing community without being part of that community. I know in my area it took years for me to learn that I shouldn't jump into every conversation, and that doing that rubbed people the wrong way, and I've seen others (many years before AI) wreck themselves by being unable to learn this lesson.
In some places responding bumps the thread so it's outright manipulative. HN doesn't sort threads like that.
I'm not sure this counts as astroturf, or simply evidence of a person who's not okay with letting a community opinion independently evolve. You could say 'well it's his job to fight the community if it looks like it's turning hostile' but think about that for a second. It takes some experience to know when you can let negativity be out there in the environment, and I think there'll be a lot of people who aren't capable of making such allowances.
This is interesting.
Nothing gets “rescued from” the second chance pool. Posts get selected for the second chance pool if moderators (or others with SCP-picking responsibilities) think they may be interesting. It’s worked like this for over a decade.
Bullshit...
dang come on man ...
this is obvious spam