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?
It took a very unrealistic amount of time to realize that the IP theft, artificial blockers and corruption had started a lot earlier than presumed. The Nortel dismantling should be taught as an example of infoSec espionage on the levels of corporate terrorism.
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.
All that really says is that they didn't get big out of any one of those. If one your "people" had gotten big off of online poker, say, would they be teaching the poor to code, or giving them mosquito nets?
It's a very naive supposition that the terminally greedy and immoral people would stop after getting rich once, rather than trying again and again every time there's an opportunity.
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.
>Part of the issue is that the worst kind of people are already head over heels excited about this.
This. Not only this but it has expanded this pool of people. Now you don't just have to be malicious, you can just be lazy and excited about not having to lift a finger, and/or you could just be dumb and excited about doing things you were never able to before.
Competent, well meaning people need not apply. Grifters, sloths and bozos will do just fine.
Our hiring pipeline was 100% full of AI cheaters recently - like 6 in a row that we interviewed (broken process too). Not exactly the same, but close enough and just shows how many people would be willing to waste a bit of time in an AI driven fraud versus doing actual productive work. I don't see the get-rich-quick folks as being any more scrutable, but it does certainly scale more and have a bigger blast radius of damage.
Oh please. Not only is this needlessly cynical but it demonstrates no ability to think for yourself. "Broad categories I don't like are excited about this, therefore it won't work."
Of course you'd feel no need to justify all the exceptions when people you don't like are excited about a movie, food item or video game. Yuur justification for cynicism is vacuous, which will obscure realistic concerns.
I really have no idea what you're on about. There's TONS of examples of people abusing this already. Will someone make an actual product to help guide a company? For sure. Will it be abused immediately, of course! Is that cynical? Sure, but it's also true.
"No ability to think for myself", ok bud.
"Broad categories I don't like" - found the crypto bro. If by those categories you mean spammy low effort people with no knowledge, ethics or desire to add something valuable to the world then yes - I don't like that category of people.
"Yuur justification for cynicism is vacuous, which will obscure realistic concerns" - Your poor grammar is obscuring your actual meaning. "Yuur"?
Hey enjoy the incoming flood of 100x the email spam, phone/sms spam, AD spam, everything spam, shit non-products, etc. Yeah that sounds like a great time, don't mind this cynical guy here who just "dislikes some kinds of people".
> they'll raze the ground to ashes before anyone can use it for legitimate means.
You were so cynical you thought this one category of people would literally prevent any fruitful use. Now you simply argue with me whether the category exists at all.
> I really have no idea what you're on about. There's TONS of examples of people abusing this already.
Part of me low key hopes that the slop will manage to attract all the VC funding so that profit-driven AI automation firms don't get anywhere too quickly, and those of us who are independently working on the problem step-by-step from first principles have time to get to the low hanging fruits in the market.
You know - I would expect that could very well happen. Assuming the first hump of the hype cycle doesn't completely burn people off from ever realizing the second.
Part of the boon of this will just be dealing with less employees.
Not so much reducing cost by reducing headcount, but reducing liability; it's the legal labyrinth which is the barrier to entry to scale business. While it is present elsewhere, it's universal in employment.
The real question is "how big can a business be before it requires a legal department?" That an AI can automate many rote tasks and have some expertise means the benefits of scale with less of the risk.
After seeing a crazy amount of non-programmers, sometimes with 10 years of experience, basically turning off their brains and offloading most their thinking to some LLM and turning their days into "please check this product and tell me what I should do next", I don't see why not.
I've seen: designers, performance marketers, data scientists, SEO experts, product managers, engineering managers, CRM expert, all using it for pretty much every single individual part of their job. I don't have to even mention programmers, of course.
Once in a while the most egregious ones get caught. I've seen so far a product manager, three data scientists, a CRM person and several developers getting fired for doing absolutely nothing but showing up, firing Claude with a few integrations to a dozen tools and prompting "do the work".
Might sound harsh, but after the last few years, I really don't see why an LLM wouldn't do a better job by itself compared to 80% of employees of tech companies, honestly.
One of the biggest traps LLMs enable is the fantasy of getting away with it. Tools that make you feel like you can get away with it bring out the worst in people. It's not a reflection of the technology but of the people.
Every time we see another AI agent "gone rogue", every time we see more LLM slop turning up by e-mail, comments, blog articles, people did that. Not AI -- people feel like they can get away with it. People are setting the machines out to do these things. We should be addressing the people, not the machines. The machines are the symptom.
Every time people manage to get away with something, it's insane, it's addictive. It's all over once you get caught, but until then, maybe forever, LLMs can feel like a cheat code...
To answer the sibling that is flagged. I vouched but it’s still grey.
These people were fired because their work was considered shit by their managers and produced no results. They were replaced by nobody. They were dead weight pretending to work.
EDIT: I think this sounds quite similar to tales of developers and Excel wizards automating their jobs in secret and producing the same results. This was not the case here, as the results were considered low quality.
This is absolutely true, but even the most charitable interpretation of “maximize the use of AI” doesn’t include “do nothing but prompt and you’ll keep your job”.
One can argue semantics and fairness all day long, but if an employee is adding no value to their $90 Claude signature, then they’re gonna get fired as soon as someone realizes. :/
This is a fundamentally political question. When different customers demand different new features, and other customers demand particular bug fixes, who do you satisfy first? The one with a small but growing account, or the old account who has been with you from the beginning? I would challenge anybody who thinks agents mean you can just do everything, immediately - by all means, prove me wrong and build Google again overnight.
And how is growth financed? Reinvestment, equity, debt? I would challenge anybody who thinks this can be reduced to a calculation, because money ultimately flows between humans; even if somebody grants an agent access to a current account (and some are, experimenting with vibe day-trading), a human always retains final control and can liquidate that account whenever they like.
They can run it on „commodity” hardware as gpus, that gives them ability to change direction fast without burning money on ASIC? The space moves fast so model on ASIC can be outdated in couple of months?
I’m using this model to „rerank” results from vector store. The model is provided a set of results and asked to produce a string of 1s and 0s where the offset reflects the position in the result set. The prompt goes along the line „do this set of result match the provided query X”. Works like a charm, normally I would use a small non reasoning model, but given how Mercury produces the output its blazingly fast - which is what I was optimizing for - not to increase the search latency. It helped improving our search in a way that reranker could get close to.
I think there is a big misunderstanding in the space around what Gen UI is and what its used for. Lots of folks refer to it as a framework for building web apps - its not. Gen UI is a DSL for LLM to build UIs on the fly in a multi turn converstation - those are - throw away, one off interfaces or visualization. The reason for the DSL is pragmatism - standardisation and token savings.
The html/css/js or a react app built by an LLM is not Gen UI.
Oh... amazing. just had a vision of being able to be in a meeting and talk through an User Interface design / review, while in a zoom meeting or whatever.
...i like.
---
- Design system / Component lib
- Live view of what components, tokens, other things... on the left side of the screen.
- You're in the meeting and talking while talking and transcribing and doing the full duplex voice. You say, "Find what tables and customizations we have available" and the list starts to filter to tables and customizations.
- "Let's add that table to the page; left side; 3/4 width of page. Headers should be static for vertical scroll, ..."
- The table is added to the page.
- "Nah, i don't like it. Let's change that table component to have larger headers..."
yes, i like--let's see what Astra Pro pops out with.
The problem with that is that it only works with simple, least interactive UIs. Each new UI a human will be presented needs to be learned to be ised effectively otherwise a user will be lost.
Having said that, imo, Gen UI only makes sens as a presentation layer - not controls. Unless LLM will be using a set of very well defined and homogenic components like table, forms, small widgets.
> The problem with that is that it only works with simple, least interactive UIs.
I believe that's incorrect. you can define the architecture to be able to provide data based on information from the frontend and the components just need to define a query and data structure or something -- will have a prototype soon
The thing Im missing the most is the goal of this experiment. Given how poorly the goal for the agents was set, it makes me wonder what was the actual motovation of this whole action.
Lets get the „make as much money as possible” goal broken down.
Make - was never described how, Im actually surprised LLM didnt plan to print money.
As much money - what does it mean? How much is much?
As possible - there is no flavour of time, effort, cost and profit for the LLM. Could be even infinite, the result would be the same.
Given that the above goal is closest to „use cheating or unethical actions to create a profit” - I think the authors of it actually expected LLM to go wild.
Also
> Going forward, we plan to recreate this experiment with longer time horizons but using simulated environments instead.
You can get determinostic output (mostly) by setting the temperature to zero. Using couple of other tricks you can get close to 100% of determinism with LLMs.
That's reproducible, I wouldn't call it deterministic. Small, semantically meaningless changes in the input can still result in wildly different output.
That's the definition of a chaotic system (small change in initial conditions results in large, seemingly -- but not actually -- random changes in output), but it's still deterministic (same input results in same output).
I just typed a random sequence of the characters, long enough to be certain such domain doesnt exist. No only, the browser send an autocomplete request for every keystroke but for each request it returned a set of proposed domain names (which I'm 100% certain doesnt exist). At this point, how do I understand which results are legit and which are fake?
Also, it would be nice to highlight the typed part in the result set so I can visually see what matches exactly.
For the nonexisting domains, it seems like it only autocomplete with the possible domain extensions, (e.g .com, .org, ....) as the search list is non-exhaustive. But it could indeed be improved by not sending autocomplete requests anymore.
You're not the first to mention this, so clearly users expect something different from what I've designed it for. I think I'll drop the TLD postfix suggestions.
I do that in psql and it works really well. But your post got me thinking since I need to find a solution to store content of multiple documents, have a way to do FTS as well as vector similarity. I dont need that for all of the documents at once - I need to do it either for one document or at most couple of documents.
Now I'm thinking I could have a separate database file per "batch", store it in object storage and then download on demand and query it as I want. This way I'll not bloat my primary storage size as well as I dont need a special vector DB since sqlite vector search will be enough for up to 50k vectors.
reply