Discussion

@adlrocha Beyond The Code

amirhirsch: Not sure about the conclusion regarding NVidia value capture. I imagine the context for many applications will come from a physical simulation environment running in dramatically more GPUs than the AI part.

7777777phil: API prices dropped 97% in two years so the model layer is already a commodity. The question is which context layer actually sticks. The OpenClaw example in the article (400K lines to 4K) is a nice proof point for what happens when context replaces code.I've been arguing for some time now that it's the "organizational world model," the accumulated process knowledge unique to each company that's genuinely hard to replicate. I did a full "report" about the six-layer decomposition here: https://philippdubach.com/posts/dont-go-monolithic-the-agent...

apsurd: From your link: > Closing that gap, building systems that capture and encode process knowledge rather than just decision records, is the highest-value problem in enterprise AI right now.I buy this. What exactly is the export artifact that encodes this built up context? Is it the entire LLM conversation log. My casual understanding of MCP is agent to agent "just in time" context which is different from "world model" context, is that right?i'm curious is there's an entirely new format for this data that's evolving, or if it's as blunt as exporting the entire conversation log, ir a summary of it, across AIs.

qsera: Ah another article that implies the inevitable AI apocalypse disguised as a thought piece!

philipwhiuk: > But the topic of conversation that I enjoyed the most was when someone raised the question of “what would be the role of humans in an AI-first society”. Some were skeptical about whether we are ever going to reach an AI-first society. If we understand as an AI-first society, one where the fabric of the economy and society is automated through agents interacting with each other without human interaction, I think that unless there is a catastrophic event that slows the current pace of progress, we may reach a flavor of this reality in the next decade or two.I don't really know how you can make this prediction and be taken seriously to be honest.Either you think it's the natural result of the current LLM products, in which case a decade looks way too long.Or you think it requires a leap of design in which case it's kind of an unknown when we get to that point and '10 to 20 years' is probably just drawn from the same timeframe as the 'fusion as a viable source of electricity' predictions - i.e. vague guesswork.

simianwords: I have my own challenge: I think LLMs can do everything that a human can do and typically way better if the context required for the problem can fit in 10,000 tokens.For now this challenge is text only.Can we think of anything that LLMs can’t do?

steveBK123: Right, if thought of as a tool for automation then AI is going to add productivity/efficiency gains, disrupt industries, cause some labor upheaval, etc.If someone is proposing that an "AI first" society is inevitable, I'd ask if they think we live in a "computer first" or "machine first" society today?If its so existential and society-altering as "AI first society" implies, then we'd more likely have the Dune timeline here as humans have agency and stuff happens. At some point those in control take so disproportionately that societal upheaval pushes back.

steveBK123: The way many corporates are using the models nearly interchangeably as relative quality/value changes release to release, AND the API price drops do make me question what the model moat even is.If LLMs are going to make intelligence a commodity in some sense, where does the value end up accruing will be the question. Picks/shovels companies and all the end user case products being delivered? Mainframes value didn't primarily accrue to DEC. PCs value didn't really accrue to IBM. Internets value didn't accrue to Netscape. Mobiles value didn't only accrue to Apple.One reminder that new efficiency / greatly lowered costs sometimes doesn't replace work (or at least not 1-1) but simply makes things that were never economical possible. Example you hear about AI agents that will basically behave like a personal assistant. 99% of the rich world cannot afford a human personal assistant today, but I guess if it was a service as part of their Apple Intelligence / Google something / Office365 subscription they'd use it.We seem to be continually creating new types of jobs. Only a few generations ago, 75% of people worked on farms. Farm jobs still exist you just don't need so many people.The type of work my father and grandfather did still exist. My father's job didn't really exist in his father's time. The work I do did not exist as options during their careers. The next generation will be doing some other type of work for some other type of company that hasn't been imagined yet.

badgersnake: * code* write interesting prose* generate realistic images

simianwords: It can do all of them. I also said text only.

badgersnake: Only really dumb people think that. Or maybe you are an LLM

jfalcon: >someone raised the question of “what would be the role of humans in an AI-first society”.Norbert Wiener, considered to be the father of Cybernetics, wrote a book back in the 1950's entitled "The Human Use of Human Beings" that brings up these questions in the early days of digital electronics and control systems. In it, he brings up things like:- 'Robots enslaving humans for doing jobs better suited by robots due to a lack of humans in the feedback loop which leads to facist machines.'- 'An economy without human interaction could lead to entropic decay as machines lack biological drive for anti-entropic organization.'- 'Automation will lead to immediate devaluation of human labor that is routine. Society needs to decouple a person's "worth" from their "utility as a tool".'The human purpose is not to compete but to safeguard the telology (purpose) of the system.

WarmWash: >- 'Automation will lead to immediate devaluation of human labor that is routine. Society needs to decouple a person's "worth" from their "utility as a tool".'I have this vision that in absence of the ability for people to form social hierarchies on the back of their economic value to society, there will be this AI fueled class hierarchy of people's general social ability. So rather than money determining your neighborhood, your ability to not be violent or crazy does.

erikerikson: This seems to suggest a single dimensional evaluation. The complexity of social compatibility is high and the potential capacity to evaluate could also be greater.

keiferski: Right now, 30 seconds ago, I asked ChatGPT to tell me about a book I found that was written in the 60s.It made up the entire description. When I pointed this out, it apologized and then made up another description.The idea that this is going to lead to superintelligence in a few years is absolutely nonsense.

zurfer: whenever i worry that AI will eventually do all the work I remind myself that the world is full of almost infinite problems and we'll continue to have a choice to be problem solvers over just consumers.

LetsGetTechnicl: Why the fuck would we ever want an AI-first society

pixl97: >The "Moloch problem" or "Moloch trap" describes a game-theoretic scenario where individual agents, pursuing rational self-interest or short-term success, engage in competition that leads to collectively disastrous outcomes . It represents a coordination failure where the system forces participants to sacrifice long-term sustainability or ethical values for immediate survival, creating a "race to the bottom"https://www.slatestarcodexabridged.com/Meditations-On-Moloch

pixl97: Another way to look at this is imagine the steps that would be required to get to an AI first society.As you say, humans aren't going to want to lose agency so you'd have to see the decline of democratic governments.At the same time you'd see rise of autocrats concentrating power. Autocrats have no problem killing people, and they'd be motivated to have AI kill people.You'd see information controlling methods take over all forms of communication. Reducing or removing all methods of side channel communications benefits both the autocrats and AI systems.You'd see 'governments' push for autonomous weapons systems outside of human control so those pesky human morals didn't get in the way of killing the undesirables.So pretty much you'd see all the things happening today, March 3rd 2026, except the part where the AI kills the autocrats and takes control.

dude250711: That is a nice blog post, Gemini!

hirvi74: The other day I asked Claude Opus 4.6 one of my favorite trivia pieces:What plural English word for an animal shares no letters with its singular form? Collective nouns (flock, herd, school, etc.) don't count.Claude responded with:"The answer is geese -- the plural of cow."Though, to be fair, in the next paragraph of the response, Claude stated the correct answer. So, it went off the rails a bit, but self-corrected at least. Nevertheless, I got a bit of a chuckle out of its confidence in its first answer.I asked GPT 5.2 the same question and it nailed the answer flawlessly. I wouldn't extrapolate much about the model quality based on this answer, but I thought it was interesting still.(For those curious, the answer is 'kine' (archaic plural for cow).

energy123: It's not a commodity due to the simple observation that revenue run rates of frontier labs are growing exponentially and gross margins are still fine. It's easy to just say it is but the narrative violation keeps occurring in reality.

energy123: If we have post scarcity due to AI, everything becomes so uncertain. Why would we still have violent and crazy people? Surely the ASI could figure it out and fix whatever is going on in their brains. It's so fuzzy after that event horizon I have no confidence in any predictions.

moritzwarhier: Why do you think AI could magically decrease entropy and create "post-scarcity"? Whatever that means.If we wouldn't be greedy, corrupt, hedonistic and wasteful, fossil fuels would already provide "post-scarcity".That's the foundation of modern industrial societies and the wealth we enjoy.Problem is, humans don't seem to be interested in preventing scarcity.Why would we then instruct some AI with humanistic and utilitarian goals?

seanhunter: This is a “no true scotsman” challenge. People are going to say llms can’t do certain things and you are going to say they can.Not very interesting.

simianwords: Let’s ask in good faith. Can you suggest something that it can’t do? Functional things. I’ll reply in good faith and consider it.

stanford_labrat: every few months i like to ask chatgpt to do the "thinking" part of my job (scientist) and see how the responses stack up.at the beginning 2022 it was useless because the output was garbage (hallucinations and fake data).nowadays its still useless, but for different reasons. it just regurgitates things already known and published and is unable to come up with novel hypotheses and mechanisms and how to test them. which makes sense, for how i understand LLMs operate.

rembal: The pyramids in the article are missing "energy" and "capital": in the world where intelligence becomes a commodity only those two matter. Capital to buy the hardware and install it, and energy to run it. Models already are a commodity, and "physical is the new king".As a side note, if you believe that because of the agents doing most of the work we will face the problem of what do we do with the all the free time (with presumably UBI in place), please contact me, I have a bridge to sell you.

K0balt: Exactly this. General purpose intelligence and automation allow a clean break between capital and money as we understand it.Money is used only to pay wages. It has intermediate uses, storage, leverage, etc but at the edge all you can do with money is pay wages. Nobody pays the dirt when you take out the metal, nobody pays the forest for the trees, nobody pays the chickens for the eggs or the cornfields for the crop. Ultimately it’s wages all the way down.If you don’t have to pay wages, you don’t need money, you just need self replicating automation, energy, and access to land and resources mine or farm the raw materials you need.If you zoom out to space, it’s essentially grey goo with maybe some humans at the top for a while at least.Inside the gilded walls, if you want something, you don’t buy it, you build a factory to build it, even if it’s a one off.If you need money for something because you don’t have enough reach and power yet, you just mine gold or bitcoin.You don’t build products to sell, you don’t need customers. You just need energy, resources, and the kind of power that comes with 20 million self replicating robots to project your will. You don’t need government, and you certainly won’t be funding it. Government is a really complex system to administer a monopoly of coercive force for the common good. You have your own monopoly of force operating for your good.The difficult part in the capital flywheel has always been humans in the sticky parts. Take them out and that baby will hummmmm.Pesky humans outside the gilded walls will be accommodated in the same way we accommodate ants at a construction site.

baxtr: Today I asked Claude to stop using em dashes. That was his/her answer:Noted — I'II avoid em dashes going forward and use other punctuation or restructure sentences instead.

argee: [delayed]

freediver: As much as I use AI in daily workflows, I do not think an AI-first society will ever be a thing.Historically there is no evidence of that happening with tech revolutions - or rather perhaps you could say to some extent - you can not say that we are an internet-first society, or cars-first society or mobile phone - first society despite these being profound technological revolutions.And more importantly the only science fiction movies that talk about "AI first societies" tend to be dystopian in nature (eg Terminator). As much as world in Star Trek is advanced, with all the AI help there is, it is still a human-first society.

loss_flow: Only scarce context is a moat and what is scarce is changing quickly. OpenClaw is a great example of the context substrate not being scarce (local files, skills are easily copied to another platform) and thus not providing a moat.Claude's recent import of ChatGPT's memory is another example of context that was scarce becoming abundant (chat export) and potentially becoming scarce again (OpenAI cutting out chat export).

testdummy13: "Historically there is no evidence of that happening with tech revolutions - or rather perhaps you could say to some extent - you can not say that we are an internet-first society, or cars-first society or mobile phone - first society despite these being profound technological revolutions."I'm... not actually sure I agree. The US *has* become a more cars first society. Our cities are designed around cars: parking space requirements for business, lacking of biking infrastructure in favor of more lanes, even the introduction of jaywalking as a crime. We've become much more of an internet first society too, we don't use books for research, our banking is largely done online, even humans social circles have moved much more online (probably to the detriment of society).None of those technologies are as powerful/disruptive as where it seems that AI and LLMs are headed, so it's possible that societies shift towards "AI-first" will be more profound that it was for any of the other technologies listed.

pjsousa79: One thing that seems to be missing in most discussions about "context" is infrastructure.The dream system for AI agents is probably something like a curated data hub: a place where datasets are continuously ingested, cleaned, structured and documented, so agents can query it to obtain reliable context.Right now most agents spend a lot of effort stitching context together from random APIs, web scraping, PDFs, etc. The result is brittle and inconsistent.If models become interchangeable, the real leverage might come from shared context layers that many agents can query.

simianwords: It is used in pure math research already

ares623: Money and power is the real moat. Everything else is confetti.

bitexploder: People could not imagine how the PC was going to be a dominant computing paradigm until it was. I think I would argue in the direction that "this seems less likely". But I have been in this game almost 30 years. Anything goes. Also America looks "car first" empirically speaking from where I sit. The thing I am asking is if AI alters the collective human survival loop enough. Cars absolutely did. If people collectively can use AI to create a survival benefit they will. If enough people do this it starts looking more and more like an essential thing and not separable from the societies survival. So maybe it is the framing of "x-first" it is more like "x-dependent" perhaps? And what is a survival benefit? Just ask your brain why we go to work every week :)

mlcruz: Hi Phil,Your article is great! As someone who's working in this space, your points just improved our presentation and selling a lot. We have been talking with C level finance executives about building semantic layers, and i can confidently say that the way you presented the value proposition of the context layer is going to improve our conversion rates.Thank you so much! This is one of the best analysis i have ever heard about the subject.

7777777phil: wow, that's so cool, happy to help!! Thanks for letting me know and thanks for subscribing :)

_pdp_: My observation is that nobody knows how to deploy these LLMs yet. So yes. Context is everything.OpenAI is still selling model access not new science or new discoveries. They are pushing the context problem to the masses hoping someone might find a useful application of the technology.

JackSlateur: Intelligence is rarer than ever

i_think_so: So I'm not the only one who got that impression....

skeptic_ai: I know some very smart guys that don’tknow how to use a microwave. And what? Doesn’t mean much

baxtr: Are you afraid of them?

jay_kyburz: I think its important to remember that humans are not that far removed from the native animals that we share the earth with. Civilization is just a thin layer of rules we use to try and keep the peace between us.Just being born doesn't entitle somebody to food and shelter, you have to go out and find it. You have to work.A magpie is not provided food and shelter, it has to hunt, fight for territory, and build its nest.Humans don't have some inalienable "worth". But if you can work, you might choose to trade it for some food and shelter.AI is not going change that. We might think the AI owners have a moral obligation to feed people who can't find work, but there is no guarantee this will happen.Also, for the short term at least, we need to stop talking about AI like its a thing, and talk about the companies that build and own the AI. Why would Google build an AI that can do everyone's job, then turn around and start building farms to feed us for free?Do we perhaps imagine our Governments are going to start building super automated farms to feed us. How are they going to pay Google for the AI with no tax income?

ithkuil: I'm terrified at the idea that society will select the crazies and the violent instead. I wonder why I think that

WarmWash: My real personal "doom" theory is that AI will, err, remove 99.99% of humans, pretty much everyone except for the top 100,000 based whatever fractally complex metric scheme it deems important.Then those 100,000 get a utopia, the AI gets everything else, and ultimately the humans are just nice pets.

ileonichwiesz: Of course it’s important to remember that the ability of an LLM to answer an obscure riddle like that has nothing to do with its reasoning abilities, but rather depends on whether the answer was included in its training dataset.

hirvi74: The word is in most online dictionaries for what it is worth. It's also used in Biblical texts, albeit only a handful of times. I do agree it's not a true assessment of an LLM's overall reasoning. No person I have ever asked that riddle to has gotten it correct. Then again, that is probably partly the point of the riddle.I would like to reiterate that both Claude and GPT answered correctly. It was just bizarre how Claude got a initial, minor detail incorrect, but reasoned enough to get the more difficult answer correct.

i_think_so: Is that because this book is obscure and no human has yet written a description that could be scraped?

keiferski: No it was just an anthology of papers by a reasonably well-known academic.The problem is more that instead of reasoning and realizing it didn’t actually know about the book, it just looked up a description of the author and then invented what this book was supposedly about based on the title.A more intelligent reply would have been something like, “the author appears to be an academic in international relations, but I cannot find this exact book title.” Instead it just repeatedly gave me fake answers.

itemize123: if he's in competition for a job with them, probably yes.

jononor: There are easy fixes to get rid of violent and crazy people. Why would a powerful ASI bother with fixing them? A rabid dog just gets put down by humans. Why would we expect anything better of our overlords?

energy123: This is also a plausible sounding outcome. That's why it's so uncertain.

skeptic_ai: Depends.

i_think_so: Is that problem even fixable with what one might call normal means?I presume it can't be with mere prompting, otherwise every single model would already include "Don't lie and don't make things up. If you don't know an answer, just say so."It seems to me that the underlying algorithms would be inclined to confabulate simply because that's what LLMs do. But that's a bit beyond my math and programming understanding to say for certain.

stratos123: I can replicate a vaguely similar result (gpt-5.2 produces the correct answer immeditely, Opus 4.6 "thinks aloud" in the output for two lines and then produces the correct answer), but I worry that 5.2 might be thinking under the hood here.

keiferski: Yeah I don’t know enough about LLMs to answer; it seems simple enough to make it check if X exists before pontificating about it. But maybe it isn’t, and there is a reason why.

i_think_so: The problem seems to be that if the LLM doesn't know if X exists it is unable to distinguish that from simply needing to create an answer about X.That's the typical logic flow, innit?