6 ms·

Intelligence is a commodity. Context is the real AI Moat

126 points by adlrocha 7mo ago

7777777phil 7mo ago
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-stack-is-stratifying/ https://philippdubach.com/posts/dont-go-monolithic-the-agent...
- apsurd 7mo ago
  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 service/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 or embeddings of the log, across AIs.
  - 7777777phil 7mo ago
    The MCP point is right, though tbh MCP is more like plumbing than memory. Execution-time context for tools and resources. The world model is a different thing entirely, it needs to persist across sessions, accumulate, actually be queryable. In practice it's mostly RAG over structured artifacts. Process docs, decision logs, annotated code and so on. Conversation history works better than you'd expect as a starting point but gets noisy fast and I haven't seen a clean pruning strategy anywhere... On the format question imo nobody really knows yet. Probably ends up as some kind of knowledge graph with typed nodes that MCP servers expose or so, but I haven't seen anyone build that cleanly. Most places are still doing RAG over PDFs so. That tells you where the friction is.
- steveBK123 7mo ago
  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.
  - lefstathiou 7mo ago
    Ads are the ultimate end state.
- martin_drapeau 7mo ago
  100% Currently integrating an AI Assistant with read tools (Retrieval-Augmented Generation or RAG as they say). Many policies we are writing are providing context (what are entities and how they relate). Projecting to when we add write tools, context is everything.
- energy123 7mo ago
  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.
- mlcruz 7mo ago
  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 7mo ago
    wow, that's so cool, happy to help!! Thanks for letting me know and thanks for subscribing :)
farcitizen 7mo ago
Great Article. And this idea is Largely behind all the new Microsoft IQ products, Work IQ, Foundry IQ, Fabric IQ. Giving the Agents Context of all relevant enterprise data to do their job.
amirhirsch 7mo ago
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.
qsera 7mo ago
Ah another article that implies the inevitable AI apocalypse disguised as a thought piece!
- doomslayer999 7mo ago
  Some call it "The Dario", or perhaps "The Amodei"
jfalcon 7mo ago
>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.
- 9wzYQbTYsAIc 7mo ago
  Seems like a good time to enshrine human rights and the social safety net by ratifying the ICESCR (https://en.wikipedia.org/wiki/International_Covenant_on_Economic,_Social_and_Cultural_Rights https://en.wikipedia.org/wiki/International_Covenant_on_Econ...) and giving human rights the teeth they need. I used Anthropic to analyze the situation, it did halfway decent: https://unratified.org/why/ https://unratified.org/why/ https://news.ycombinator.com/item?id=47263664 https://news.ycombinator.com/item?id=47263664
- WarmWash 7mo ago
  >- '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 7mo ago
    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.
LetsGetTechnicl 7mo ago
Why the fuck would we ever want an AI-first society
- deleted 7mo ago
  [deleted]
- pocksuppet 7mo ago
  What we want doesn't matter, what they want does.
- pixl97 7mo ago
  >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 https://www.slatestarcodexabridged.com/Meditations-On-Moloch
AIorNot 7mo ago
"what is the role of humans in a scenario where work is no longer necessary? This is significant because, since the industrial revolution, work has played an important role in shaping an individual’s identity. How will we occupy our time when we don’t have to spend more than half of our waking hours on a job" Umm I have been working in AI in multiple verticals for the past 3 years and I have been far busier and more stressed with far less job security than past 15 before that in tech. For now this is far more accurate: https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies... Wake me up when the computers run the world and I can relax..but I don't think its happening in my lifetime.
- pixl97 7mo ago
  Evolution never lets you relax, it only breeds more effective predators.
philipwhiuk 7mo ago
> 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.
- steveBK123 7mo ago
  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.
  - 9wzYQbTYsAIc 7mo ago
    Seems like a good time to enshrine human rights and the social safety net by ratifying the ICESCR (https://en.wikipedia.org/wiki/International_Covenant_on_Econ https://en.wikipedia.org/wiki/International_Covenant_on_Econ...) and giving human rights the teeth they need. I used Anthropic to analyze the situation, it did halfway decent: https://unratified.org/why/ https://unratified.org/why/ https://news.ycombinator.com/item?id=47263664 https://news.ycombinator.com/item?id=47263664
  - pixl97 7mo ago
simianwords 7mo ago
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?
- badgersnake 7mo ago
  * code * write interesting prose * generate realistic images
  - simianwords 7mo ago
    It can do all of them. I also said text only.
    - deleted 7mo ago
      [deleted]
  - infecto 7mo ago
    > Only really dumb people think that. Or maybe you are an LLM. You deleted it but still come on. Why would you even think to write that?
- seanhunter 7mo ago
  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 7mo ago
    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.
    - seanhunter 7mo ago
      Say I suggest something : Play a valid game of chess at club level (elo approx 1200 say) using algebraic notation. Then you’re either going to say it can or you’re going to say that requires more than 10000 tokens. This isn’t an interesting conversation and I don’t think you are presenting this challenge in good faith for the reason I gave above.
zurfer 7mo ago
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.
- andriy_koval 7mo ago
  > we'll continue to have a choice to be problem solvers over just consumers. that's if we still stay relevant and competitive compared to AI in problem solving.
- jopsen 7mo ago
  10 years ago self-driving EVs were going to make it so nobody owns a car. There was a lot of hype. We are possibly still on track to get to that world. But it might easily take another 10-20 years :) AI will change things, but don't underestimate the timeline. Also even if we get a super intelligence in a box, it probably won't fold my laundry. Super intelligence might not unlock as much as we dream.
rembal 7mo ago
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 7mo ago
  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.
dude250711 7mo ago
That is a nice blog post, Gemini!
- i_think_so 7mo ago
  So I'm not the only one who got that impression....
the_af 7mo ago
I think a lot of this kind of conversations seem to be simply ignoring or missing the lessons from the past. For example: > [...] OpenClaw is around 400k lines of code for a while loop and the list of all the integrations and connections supported by the system. The next generation of Claws only have around 4K lines of code for the core, and the rest are just skills (i.e. markdown files) that tell the agent how to implement or run the code for the specific connections that want to be enabled (like a plugin system). Shifting code from "the core" and moving it to "skills" is simply moving code from one place to another. It may also mean translating it from classic source code to an English-like specification language full of ambiguity but that's also code. So the overall code is not reduced, just transformed and shifted around. You don't get a free lunch "because AI". > A user using one of these second-generation Claws only needs to node the core logic (that can be easily understood and audited) and can leverage the skills (as the plugins) to activate the functionality that they need for their case. The "core" may be easier to audit, but that's because the messy parts have been moved to the skills/plug-ins, which are as hard as always to audit. I'm not saying this cannot work, but it's very frustrating seeing everybody simply dumping all lessons from the past and pretending nothing that came before mattered and that AI vibe coding is fundamentally different and the rules of accidental and intrinsic complexity don't apply anymore. Have we all collectively lost our minds?
gertlabs 7mo ago
Neither intelligence nor context are what really differentiate the most successful model for programming (Claude Opus 4.6) from slightly 'smarter' competitors (Codex 5.3, Gemini 3.1 Pro). It's tool use and personality. If models stopped advancing today, we could still reach effective AGI with years of refining harnesses. There is still incredible untapped potential there. I maintain a benchmark at https://gertlabs.com https://gertlabs.com that competes models against each other in competitive, open-ended games. It's harder to game the benchmark because there's no correct answer (at least none that any of the models have gotten remotely close to) and it requires anticipation of other players' behavior. One thing I've found is that Codex and Gemini models tend to perform the best at one-shotting problems, but when given a harness and tools to iterate towards a solution, Anthropic models continue improving where Codex and Gemini struggle to use tools they weren't trained on or take the initiative to follow the high level objectives.
- mr_00ff00 7mo ago
  “ If models stopped advancing today, we could still reach effective AGI with years of refining harnesses.” Unless you’re a machine learning engineer with something to share, our current models are not even close to general AGI, and won’t make it. My understanding (as just an engineer) is that LLMs continue to improve at crazy rates, but it’s clear this is not the answer for AGI.
  - gertlabs 7mo ago
    I think if I asked for most HN users' requirements for AGI 8 years ago, we would already be well past them. Now that we see the nature of how artificial intelligence is unfolding, and how the intelligence is different than human intelligence, everyone is moving their goalposts (including me). But if we're being honest, frontier LLMs are effectively more intelligent than a non-negligible proportion of the population (for example, at pretty much all white collar IC work, pattern matching, problem solving, etc.). And in the ways that most people are still smarter (having sentience/emotions/desires that drive us to take initiative toward meaningful goals), I think it's great that AI does not match us there, but also doesn't disqualify it from being intelligent. The harness can bridge the gap there.
baxtr 7mo ago
For anyone worried about AGI coming soon. 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.
- skeptic_ai 7mo ago
  I know some very smart guys that don’tknow how to use a microwave. And what? Doesn’t mean much
  - baxtr 7mo ago
    Are you afraid of them?
    - itemize123 7mo ago
      if he's in competition for a job with them, probably yes.
    - skeptic_ai 7mo ago
      Depends.
  - DANmode 7mo ago
    Sure it does. It means they’re not very smart. Just experienced.
- jsw97 7mo ago
  This seems like the most intelligent response, in some ways, because it’s funny and tweaks the user. I could see myself replying like this.
loss_flow 7mo ago
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).
freediver 7mo ago
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). And humans eventually always do better than that. As much as the world in Star Trek is advanced for example, with all the fancy AI there is, it is still a human-first society. Only 10% of any Star Trek is about AI and fancy technologies, 90% is still human drama.
- testdummy13 7mo ago
  "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.
- bitexploder 7mo ago
  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 :)
ledauphin 7mo ago
I just don't buy this. It is not what I observe with these things. They are not at all "thoughtful".
pjsousa79 7mo ago
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.
- sorobahn 7mo ago
  Am working on making this layer currently. It’s a more interesting problem even when you remove AI agents from the picture, I feel a context layer can be equally as useful for humans and deterministic programs. I view it as a data structure sitting on top of your entire domain and this data structure’s query interface plus some basic tools should be enough to bootstrap non trivial agents imo. I think the data structure that is best suited for this problem is a graph and the different types of data represented as graphs. Stitching api calls is analogous to representing relationships between entities and that’s ultimately why I think graph databases have a chance in this space. As any domain grows, the relationships usually grow at a higher rate than the nodes so you want a query language that is optimal for traveling relationships between things. This is where a pattern matching approach provided by ISO GQL inspired by Cypher is more token efficient compared to SQL. The problem is that our foundation models have seen way way way more SQL so there is a training gap, but I would bet if the training data was equally abundant we’d see better performance on Cypher vs SQL. I know there is GraphRAG and hybrid approaches involving vector embeddings and graph embeddings, but maybe we also need to reduce API calls down to semantic graph queries on their respective domains so we just have one giant graph we can scavenge for context.
  - lvca 7mo ago
    This resonates strongly. We've been working on exactly this problem with ArcadeDB — a multi-model database that natively supports graphs, documents, key-value, time-series, and vector search in a single engine. (https://arcadedb.com https://arcadedb.com) The insight about relationships growing faster than nodes is spot on, and it's why we think the graph model is the natural fit for context layers. But in practice, you also need documents, vectors, and sometimes time-series data alongside the graph. Forcing everything into a single model (or stitching together multiple databases) creates friction that kills agent workflows. On the GQL/Cypher vs SQL point — agreed on token efficiency. We support both SQL (extended with graph capabilities) and Cypher-style syntax, and the difference in prompt size for traversal queries is dramatic. An N-hop relationship query that takes 5+ lines of SQL JOINs is a single readable line in a graph query language. For LLM-generated queries, that's not just an aesthetic win — it directly reduces error rates and token costs. Re: GraphRAG — we've seen the same convergence. Vector similarity to find the right neighborhood, then graph traversal for structured context. Having both in one engine (ArcadeDB supports vector indexing natively) means you avoid the API orchestration overhead you mention. One query, one database, full context. The training gap for graph query languages is real but closing fast. As more agent frameworks adopt graph-based context, the flywheel will kick in.
2OEH8eoCRo0 7mo ago
I think a lot about liability. If AI wrecks something are they liable? If not then thats very risky and unusable for many applications. But if it is liable then that's extremely risky for the AI providers! It seems risky either way!
ares623 7mo ago
Money and power is the real moat. Everything else is confetti.
vicchenai 7mo ago
[dead]
jbergqvist 7mo ago
In a way, isn't this the same old data moat that always existed in AI/ML, but supercharged? Generalist models can now reason over proprietary data as context instead of requiring you to train narrow expert models on it. What changed is you no longer need an ML team to turn that data into value.
tonnydourado 7mo ago
I know this is not the explicit meaning, but lol, intelligence isn't a commodity among humans, let alone LLMs
_pdp_ 7mo ago
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 7mo ago
Intelligence is rarer than ever
adonovan 7mo ago
> "what is the role of humans in a scenario where work is no longer necessary?" People have been fantasizing about this scenario throughout the industrial era--read William Morris' News from Nowhere (1890) for example--but it has failed to come to pass so many times, and the reasons are pretty obvious. The benefits of technology are spread unequally, and increasingly so over time, so only a wealthy few get the option of a post-labor existence. Also, our demands for the products of labor change as labor productivity increases; we prefer (or have been persuaded to act as if we prefer) material riches over lives with less stuff and more time. We still haven't seen that AI actually replaces labor, as opposed to amplifying it, like a power saw or CNC mill used by a carpenter, so all these discussions about the end of labor seem like unwitting sales pitches for AI. > “what would be the role of humans in an AI-first society” The real question is why would anyone want, or want to help build, such an obscenity.
- jfalcon 7mo ago
  >The real question is why would anyone want, or want to help build, such an obscenity. Power Saws and CNC mills have no autonomy. They have to be guided every inch or instruction by hand. Autonomous AI agents remove the hand. So if we don't define the role of humans in the process of creation, we get AI building things we didn't ask for or need. AI is coming regardless. There are advantages that we all accept it can do. But the machine is a 'slave' only if we refuse to be 'masters'. There is a term called social ecology. It is based on the conviction that nearly all of our present ecological problems originate in deep-seated social problems. In effect, the way human beings deal with each other as social beings is crucial to addressing ecological crisis. The point of social ecology emphasizes is not that moral and spiritual persuation and renewal are meaningless or unnecessary; they are necessary and can be educational. But modern capitalism is 'structually amoral' and hence impervious to moral appeals. Power will always belong to the elite and commanding strata if it is not institutionalized in face-to-face democracies, among people who are fully empowered as social beings to make decisions in new communal assemblies. Power that does not belong to the people invariably belongs to the state and the exploitative interests it represents. What is obscene is measuring outputs by 19th century standards. As long as we believe that "being born doesn't entitle you to food", we will stay on the hedonic treadmill until the planet or our psyches break.
zkmon 7mo ago
This seems assumes coding as the usecase. A lot of business activity expects software outputs be precise, reproducible and can be held liable for accuracy. Imagine excel spreadsheet showing approximate numbers as formula outputs. "Caution: AI might make mistakes" is basically saying that I'm not responsible for correctness of my outputs. Does speed compensate for accuracy loss? Maybe, in some cases. But a lot of AI stories pretend that it is acceptable in all cases.

126 points by adlrocha 7mo ago

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-stack-is-stratifying/ https://philippdubach.com/posts/dont-go-monolithic-the-agent...

apsurd 7mo ago
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 service/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 or embeddings of the log, across AIs.
- 7777777phil 7mo ago
  The MCP point is right, though tbh MCP is more like plumbing than memory. Execution-time context for tools and resources. The world model is a different thing entirely, it needs to persist across sessions, accumulate, actually be queryable. In practice it's mostly RAG over structured artifacts. Process docs, decision logs, annotated code and so on. Conversation history works better than you'd expect as a starting point but gets noisy fast and I haven't seen a clean pruning strategy anywhere... On the format question imo nobody really knows yet. Probably ends up as some kind of knowledge graph with typed nodes that MCP servers expose or so, but I haven't seen anyone build that cleanly. Most places are still doing RAG over PDFs so. That tells you where the friction is.
steveBK123 7mo ago
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.
- lefstathiou 7mo ago
  Ads are the ultimate end state.
martin_drapeau 7mo ago
100% Currently integrating an AI Assistant with read tools (Retrieval-Augmented Generation or RAG as they say). Many policies we are writing are providing context (what are entities and how they relate). Projecting to when we add write tools, context is everything.
energy123 7mo ago
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.
mlcruz 7mo ago
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 7mo ago
  wow, that's so cool, happy to help!! Thanks for letting me know and thanks for subscribing :)

farcitizen 7mo ago

Great Article. And this idea is Largely behind all the new Microsoft IQ products, Work IQ, Foundry IQ, Fabric IQ. Giving the Agents Context of all relevant enterprise data to do their job.

amirhirsch 7mo ago

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.

qsera 7mo ago

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

doomslayer999 7mo ago
Some call it "The Dario", or perhaps "The Amodei"

jfalcon 7mo ago

>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.

9wzYQbTYsAIc 7mo ago
Seems like a good time to enshrine human rights and the social safety net by ratifying the ICESCR (https://en.wikipedia.org/wiki/International_Covenant_on_Economic,_Social_and_Cultural_Rights https://en.wikipedia.org/wiki/International_Covenant_on_Econ...) and giving human rights the teeth they need. I used Anthropic to analyze the situation, it did halfway decent: https://unratified.org/why/ https://unratified.org/why/ https://news.ycombinator.com/item?id=47263664 https://news.ycombinator.com/item?id=47263664
WarmWash 7mo ago
>- '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 7mo ago
  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.

LetsGetTechnicl 7mo ago

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

deleted 7mo ago
[deleted]
pocksuppet 7mo ago
What we want doesn't matter, what they want does.
pixl97 7mo ago
>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 https://www.slatestarcodexabridged.com/Meditations-On-Moloch

AIorNot 7mo ago

"what is the role of humans in a scenario where work is no longer necessary? This is significant because, since the industrial revolution, work has played an important role in shaping an individual’s identity. How will we occupy our time when we don’t have to spend more than half of our waking hours on a job" Umm I have been working in AI in multiple verticals for the past 3 years and I have been far busier and more stressed with far less job security than past 15 before that in tech. For now this is far more accurate: https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies... Wake me up when the computers run the world and I can relax..but I don't think its happening in my lifetime.

pixl97 7mo ago
Evolution never lets you relax, it only breeds more effective predators.

philipwhiuk 7mo ago

> 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.

steveBK123 7mo ago
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.
- 9wzYQbTYsAIc 7mo ago
  Seems like a good time to enshrine human rights and the social safety net by ratifying the ICESCR (https://en.wikipedia.org/wiki/International_Covenant_on_Econ https://en.wikipedia.org/wiki/International_Covenant_on_Econ...) and giving human rights the teeth they need. I used Anthropic to analyze the situation, it did halfway decent: https://unratified.org/why/ https://unratified.org/why/ https://news.ycombinator.com/item?id=47263664 https://news.ycombinator.com/item?id=47263664
- pixl97 7mo ago

simianwords 7mo ago

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?

badgersnake 7mo ago
* code * write interesting prose * generate realistic images
- simianwords 7mo ago
  It can do all of them. I also said text only.
  - deleted 7mo ago
    [deleted]
- infecto 7mo ago
  > Only really dumb people think that. Or maybe you are an LLM. You deleted it but still come on. Why would you even think to write that?
seanhunter 7mo ago
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 7mo ago
  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.
  - seanhunter 7mo ago
    Say I suggest something : Play a valid game of chess at club level (elo approx 1200 say) using algebraic notation. Then you’re either going to say it can or you’re going to say that requires more than 10000 tokens. This isn’t an interesting conversation and I don’t think you are presenting this challenge in good faith for the reason I gave above.

zurfer 7mo ago

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.

andriy_koval 7mo ago
> we'll continue to have a choice to be problem solvers over just consumers. that's if we still stay relevant and competitive compared to AI in problem solving.
jopsen 7mo ago
10 years ago self-driving EVs were going to make it so nobody owns a car. There was a lot of hype. We are possibly still on track to get to that world. But it might easily take another 10-20 years :) AI will change things, but don't underestimate the timeline. Also even if we get a super intelligence in a box, it probably won't fold my laundry. Super intelligence might not unlock as much as we dream.

rembal 7mo ago

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 7mo ago
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.

dude250711 7mo ago

That is a nice blog post, Gemini!

i_think_so 7mo ago
So I'm not the only one who got that impression....

the_af 7mo ago

I think a lot of this kind of conversations seem to be simply ignoring or missing the lessons from the past. For example: > [...] OpenClaw is around 400k lines of code for a while loop and the list of all the integrations and connections supported by the system. The next generation of Claws only have around 4K lines of code for the core, and the rest are just skills (i.e. markdown files) that tell the agent how to implement or run the code for the specific connections that want to be enabled (like a plugin system). Shifting code from "the core" and moving it to "skills" is simply moving code from one place to another. It may also mean translating it from classic source code to an English-like specification language full of ambiguity but that's also code. So the overall code is not reduced, just transformed and shifted around. You don't get a free lunch "because AI". > A user using one of these second-generation Claws only needs to node the core logic (that can be easily understood and audited) and can leverage the skills (as the plugins) to activate the functionality that they need for their case. The "core" may be easier to audit, but that's because the messy parts have been moved to the skills/plug-ins, which are as hard as always to audit. I'm not saying this cannot work, but it's very frustrating seeing everybody simply dumping all lessons from the past and pretending nothing that came before mattered and that AI vibe coding is fundamentally different and the rules of accidental and intrinsic complexity don't apply anymore. Have we all collectively lost our minds?

gertlabs 7mo ago

Neither intelligence nor context are what really differentiate the most successful model for programming (Claude Opus 4.6) from slightly 'smarter' competitors (Codex 5.3, Gemini 3.1 Pro). It's tool use and personality. If models stopped advancing today, we could still reach effective AGI with years of refining harnesses. There is still incredible untapped potential there. I maintain a benchmark at https://gertlabs.com https://gertlabs.com that competes models against each other in competitive, open-ended games. It's harder to game the benchmark because there's no correct answer (at least none that any of the models have gotten remotely close to) and it requires anticipation of other players' behavior. One thing I've found is that Codex and Gemini models tend to perform the best at one-shotting problems, but when given a harness and tools to iterate towards a solution, Anthropic models continue improving where Codex and Gemini struggle to use tools they weren't trained on or take the initiative to follow the high level objectives.

mr_00ff00 7mo ago
“ If models stopped advancing today, we could still reach effective AGI with years of refining harnesses.” Unless you’re a machine learning engineer with something to share, our current models are not even close to general AGI, and won’t make it. My understanding (as just an engineer) is that LLMs continue to improve at crazy rates, but it’s clear this is not the answer for AGI.
- gertlabs 7mo ago
  I think if I asked for most HN users' requirements for AGI 8 years ago, we would already be well past them. Now that we see the nature of how artificial intelligence is unfolding, and how the intelligence is different than human intelligence, everyone is moving their goalposts (including me). But if we're being honest, frontier LLMs are effectively more intelligent than a non-negligible proportion of the population (for example, at pretty much all white collar IC work, pattern matching, problem solving, etc.). And in the ways that most people are still smarter (having sentience/emotions/desires that drive us to take initiative toward meaningful goals), I think it's great that AI does not match us there, but also doesn't disqualify it from being intelligent. The harness can bridge the gap there.

baxtr 7mo ago

For anyone worried about AGI coming soon. 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.

skeptic_ai 7mo ago
I know some very smart guys that don’tknow how to use a microwave. And what? Doesn’t mean much
- baxtr 7mo ago
  Are you afraid of them?
  - itemize123 7mo ago
    if he's in competition for a job with them, probably yes.
  - skeptic_ai 7mo ago
    Depends.
- DANmode 7mo ago
  Sure it does. It means they’re not very smart. Just experienced.
jsw97 7mo ago
This seems like the most intelligent response, in some ways, because it’s funny and tweaks the user. I could see myself replying like this.

loss_flow 7mo ago

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).

freediver 7mo ago

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). And humans eventually always do better than that. As much as the world in Star Trek is advanced for example, with all the fancy AI there is, it is still a human-first society. Only 10% of any Star Trek is about AI and fancy technologies, 90% is still human drama.

testdummy13 7mo ago
"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.
bitexploder 7mo ago
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 :)

ledauphin 7mo ago

I just don't buy this. It is not what I observe with these things. They are not at all "thoughtful".

pjsousa79 7mo ago

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.

sorobahn 7mo ago
Am working on making this layer currently. It’s a more interesting problem even when you remove AI agents from the picture, I feel a context layer can be equally as useful for humans and deterministic programs. I view it as a data structure sitting on top of your entire domain and this data structure’s query interface plus some basic tools should be enough to bootstrap non trivial agents imo. I think the data structure that is best suited for this problem is a graph and the different types of data represented as graphs. Stitching api calls is analogous to representing relationships between entities and that’s ultimately why I think graph databases have a chance in this space. As any domain grows, the relationships usually grow at a higher rate than the nodes so you want a query language that is optimal for traveling relationships between things. This is where a pattern matching approach provided by ISO GQL inspired by Cypher is more token efficient compared to SQL. The problem is that our foundation models have seen way way way more SQL so there is a training gap, but I would bet if the training data was equally abundant we’d see better performance on Cypher vs SQL. I know there is GraphRAG and hybrid approaches involving vector embeddings and graph embeddings, but maybe we also need to reduce API calls down to semantic graph queries on their respective domains so we just have one giant graph we can scavenge for context.
- lvca 7mo ago
  This resonates strongly. We've been working on exactly this problem with ArcadeDB — a multi-model database that natively supports graphs, documents, key-value, time-series, and vector search in a single engine. (https://arcadedb.com https://arcadedb.com) The insight about relationships growing faster than nodes is spot on, and it's why we think the graph model is the natural fit for context layers. But in practice, you also need documents, vectors, and sometimes time-series data alongside the graph. Forcing everything into a single model (or stitching together multiple databases) creates friction that kills agent workflows. On the GQL/Cypher vs SQL point — agreed on token efficiency. We support both SQL (extended with graph capabilities) and Cypher-style syntax, and the difference in prompt size for traversal queries is dramatic. An N-hop relationship query that takes 5+ lines of SQL JOINs is a single readable line in a graph query language. For LLM-generated queries, that's not just an aesthetic win — it directly reduces error rates and token costs. Re: GraphRAG — we've seen the same convergence. Vector similarity to find the right neighborhood, then graph traversal for structured context. Having both in one engine (ArcadeDB supports vector indexing natively) means you avoid the API orchestration overhead you mention. One query, one database, full context. The training gap for graph query languages is real but closing fast. As more agent frameworks adopt graph-based context, the flywheel will kick in.

2OEH8eoCRo0 7mo ago

I think a lot about liability. If AI wrecks something are they liable? If not then thats very risky and unusable for many applications. But if it is liable then that's extremely risky for the AI providers! It seems risky either way!

ares623 7mo ago

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

vicchenai 7mo ago

[dead]

jbergqvist 7mo ago

In a way, isn't this the same old data moat that always existed in AI/ML, but supercharged? Generalist models can now reason over proprietary data as context instead of requiring you to train narrow expert models on it. What changed is you no longer need an ML team to turn that data into value.

tonnydourado 7mo ago

I know this is not the explicit meaning, but lol, intelligence isn't a commodity among humans, let alone LLMs

_pdp_ 7mo ago

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 7mo ago

Intelligence is rarer than ever

adonovan 7mo ago

> "what is the role of humans in a scenario where work is no longer necessary?" People have been fantasizing about this scenario throughout the industrial era--read William Morris' News from Nowhere (1890) for example--but it has failed to come to pass so many times, and the reasons are pretty obvious. The benefits of technology are spread unequally, and increasingly so over time, so only a wealthy few get the option of a post-labor existence. Also, our demands for the products of labor change as labor productivity increases; we prefer (or have been persuaded to act as if we prefer) material riches over lives with less stuff and more time. We still haven't seen that AI actually replaces labor, as opposed to amplifying it, like a power saw or CNC mill used by a carpenter, so all these discussions about the end of labor seem like unwitting sales pitches for AI. > “what would be the role of humans in an AI-first society” The real question is why would anyone want, or want to help build, such an obscenity.

jfalcon 7mo ago
>The real question is why would anyone want, or want to help build, such an obscenity. Power Saws and CNC mills have no autonomy. They have to be guided every inch or instruction by hand. Autonomous AI agents remove the hand. So if we don't define the role of humans in the process of creation, we get AI building things we didn't ask for or need. AI is coming regardless. There are advantages that we all accept it can do. But the machine is a 'slave' only if we refuse to be 'masters'. There is a term called social ecology. It is based on the conviction that nearly all of our present ecological problems originate in deep-seated social problems. In effect, the way human beings deal with each other as social beings is crucial to addressing ecological crisis. The point of social ecology emphasizes is not that moral and spiritual persuation and renewal are meaningless or unnecessary; they are necessary and can be educational. But modern capitalism is 'structually amoral' and hence impervious to moral appeals. Power will always belong to the elite and commanding strata if it is not institutionalized in face-to-face democracies, among people who are fully empowered as social beings to make decisions in new communal assemblies. Power that does not belong to the people invariably belongs to the state and the exploitative interests it represents. What is obscene is measuring outputs by 19th century standards. As long as we believe that "being born doesn't entitle you to food", we will stay on the hedonic treadmill until the planet or our psyches break.

zkmon 7mo ago

This seems assumes coding as the usecase. A lot of business activity expects software outputs be precise, reproducible and can be held liable for accuracy. Imagine excel spreadsheet showing approximate numbers as formula outputs. "Caution: AI might make mistakes" is basically saying that I'm not responsible for correctness of my outputs. Does speed compensate for accuracy loss? Maybe, in some cases. But a lot of AI stories pretend that it is acceptable in all cases.