I don't know if Ed Zitron is right about allhis analysis, but it's nice to have an alternative, well-argued narrative to the gushing torrent of AI company propaganda.
Ed may be right about some of his claims, but he is 100% a crank, and he makes so many incoherent claims I'd say that if he's right, it's in the nature of a broken clock.
For years he was all-in on "AI is useless, it has no business value at all" claims, and then when that was decisively disproven by Claude Code, he didn't spend one second on self-reflection on why he was wrong and whether this might mean he is wrong about other things. He just smoothly pivoted to "AI companies will never be profitable, tokens are hugely subsidized". And now that that's about to be disproven (word on the street is that Anthropic will soon report profitability, and both Anthropic and OAI have repeatedly said inference is profitable), he's pivoting again to "tokens are too expensive and the ROI isn't there for business". No correction, no reflection, just "we're at war with Eurasia, we've always been at war with Eurasia".
Even if he’s sometimes right, there are better analysts out there who are also right and have the honesty, humility and integrity that Zitron lacks.
No such disproval has happened. Claude Code does not provide business value, it provides the illusion of value. Just like everything else LLMs do.
I'm not qualified enough myself to judge Zitron's reporting, nor this criticism. But George Pearkes is a reasonably respected financial analyst.
I actually think Zitron would be better off focusing on those deals where there is clearly something weird going on (SpaceX IPO, Oracle/OpenAI/NVIDIA triangle, the neoclouds, and so on), than picking a fight with the one company that actually seems to be trying to play it straight in this sector (Anthropic), and I can see how he's covering the whole field with the same cynicism which might not be appropriate.
That said, I'm not entirely convinced that some of Pearkes' analysis deserves us all to align to the rosy bullish view he takes either.
Time will tell, it always does, but at least you've put forward some data unlike anyone else, so thank you for that.
> it straight in this sector (Anthropic)
https://stephenfollows.com/p/what-just-happened-to-thenumber...
Search for "Anthropic crawls over 38,000 pages for every single visitor".
If they can't get their bots to work correctly, what makes you think Anthropic is doing anything else correctly?
>And yes, that sound you hear is the slow deflation of the bubble I've been warning you about since March...
>How does GPT – a transformer-based model that generates answers probabilistically (as in what the next part of the generation is most likely to be the correct one) based entirely on training data – do anything more than generate paragraphs of occasionally-accurate text?
etc.
Basically the essence is he's skeptical of AI / LLMs being any good so thinks all the investment is down the drain. Meanwhile AI progresses such that Fable can probably beat most humans and IQ tests, maths and the like. And the 'bubble' didn't deflate yet.
My take is that as a PR guy, used to people hyping stuff and not that up on comp-sci he fundamentally doesn't get what's going on. He assumes it's all hype rather than the steady progress in computing reaching brain equivalent levels and beyond.
Fable scoring OK on some benchmarks does not the mean the investment has financially paid off, because that's not how ROI works.
You're right that no bubble has deflated, but I think we can all see that a) there seems to be a bubble - I'm old enough to remember the dot-com era bubble, and this definitely feels like that, b) the only company clearly making a profit on AI right now is NVIDIA, and c) the net economic value of the sector as a whole (i.e. money out > money in), is still unproven
It's not even obvious to me as somebody who is up on comp-sci, that this isn't all hype, that the progress is/will be steady, and that reaching brain equivalent levels and beyond using these architectures will be economically viable.
I can create a perfectly good human brain in 9 months, train it in ~20 years, and have it pay off economically in a more proven way than [waves hands] all of this.
For some reason we've decided paying a hyperscaler the equivalent of a year's salary to do a job in a a day that a similarly paid and skilled human could do in a month is value for money.
You could probably give everyone in the US free healthcare for life and a free ride through college for less money than has been pumped into AI in the last 5 years, and have a more proven economic model.
Sure, time value is a thing, but given the error rates, the energy issues... this direction is not exactly a slam dunk as a net benefit, and I think that's all he's called out in any of the writing I've seen of his.
I also happen to agree with his take on Oracle, as it happens - they're only going to survive if it turns out they're a part of critical national infrastructure deep in the bowels of the US government. They look totally over-leveraged otherwise.
If you are making the case that he is full of shit, please provide some actual evidence of his main thesis that AI companies are not going about this in any sustainable way
The point isn't that his thesis is fucked, just that his analysis tends to be free with details in a way that shouldn't inspire confidence, e.g. mixing up EBIT and EBITDA.
Someone elsewhere in this thread referenced this guy [1]. His takes properly summarise the lack of care Zitron appears to display for getting detailed arguments right.
If you're deeply familiar with financial jargon, I think he's fine. But if you're not, it's easy to get whisked into woo-woo nonsense that's falsely precise due to mis-using (and in some cases, very clearly mis-understanding) core financial and economic concepts.
what i see at $employer is wanting to do everything with ai from start to finish (and i mean everything) but from looking at the output (or lack of) of coworkers i'm thinking that perspective may be closer to the truth...
He's right about some things -- off the top of my head:
-- OAI's perpetual fundraising, due to their losses
--Coreweave
--Circular financing
--Revenue/capex imbalance
...all forensic economics analyses.
He's often wrong when on the topic of capabilities and adoption -- he mistakes a snapshot for a trajectory, and treats current limitations as permanent:
--Hallucination/unreliability an unsolvable problem
--OpenAI failing
--AI capabilities have plateaued / models will stop getting better
--Saying Microsoft's cancelled leases meant the bubble was popping
--Agents a marketing fad
--Gross miscalculation of OAI 2025 revenue
--Lack of adoption
--AI not getting more efficient (compared to 10-40x reduction in inference costs YoY)
--Repeating "95% of pilots fail" but ignoring massive bottoms-up adoption
Christensen got this right when he had the insight to judge a technology by its rate of improvement relative to what a market needs, not by whether it's good enough today.
Put Zitron back at the early days of the integrated circuit and imagine what he would have written about the technology.
Some open predictions:
--Bubble is going to burst -- I tend to agree with the thesis that "there is some marginal capacity being planned/built today that will never pay back its capex"
--Losses mean there's no viable business here -- the recent moves by all of the players to some form of usage based pricing show there's price discovery occurring. I don't know of anyone who is stopping using LLMs because of the pricing changes...it's just changing their behavior.
That isn’t to say that he’s right, that’s just to say that while he gets creative in his phrasing numbers don’t lie and I haven’t seen anyone else present competing numbers that make sense.
If anyone has them to the degree with which he provides them then please, by all means, I’m interested.
I'm a web developer to myself who has done zero game or systems programming so I can't speak to that side of it, but you reminded me of it!
You should probably understand Thomas' comment in part as a reaction to Zitron attacking Thomas in a pretty low-brow fashion, essentially for saying "hey folks, AI coding works and you should be using it":
https://www.wheresyoured.at/how-to-argue-with-an-ai-booster/
The bottom line is that Ed Zitron, like Gary Marcus, built their entire brand on being AI contrarians; they can't say anything positive about it without qualifying it with a more damning negative. There's nothing wrong about having voices like that, but it makes them unreliable narrators. I am apprehensive about AI and its externalities, but I don't want to be caught citing either of them for that reason.
Sure, but an ad hominem is still an ad hominem regardless of one's personal feelings (it took me a good minute to figure out who "Thomas" is).
Otherwise, I agree, and I try not to cite extremists or bullies on either side. I don't even really care that much about defending Zitron, but I do put him on in the background because he does so many podcasts as I find it soothing to listen to someone rant and rave against the tech bro overlords, even if some of the shit he says annoys me. But he does show his work sometimes and wanted to point that out.
My argument here is just that Zitron says things that are wrong all the time.
You could fairly rebut me by saying I didn't substantiate that argument. That's true! That doesn't make the argument fallacious; it just means it isn't facially dispositive.
And I agree that he says things that are wrong much of the time, but not all the time. I also don't like him enough to care, but I do care enough to bring it up when I see multiple random attacks.
Really? I think we've heard C-suite blabbermouths and borderline nontechnical tech CEOs being amplified by social media making these assertions, but boy did the weakly efficient market deliver a relatively swift correction to that mindset, no?
Q: "What would it take to change your point of view?" A: "[AI] would have to solve all hallucinations forever, which they are completely incapable [of]."
Can you produce a human that is infallible? I'll wait.
Finally: https://martinalderson.com/posts/no-it-doesnt-cost-anthropic...
My hot take is AI is increasingly less unprofitable as the cost of serving tokens drops and Nvidia's ongoing offers to guarantee profitability is a sign that it isn't stopping anytime soon.
https://newsletter.semianalysis.com/p/nvidia-gpu-debt-backst...
You either believe in the underlying science and technology or you don't. But in a world where AI is a fad like cabbage patch kids and beanie babies, what's next?
AI will almost certainly not be a fad for software developers, or at the very least for web developers, but it's certainly possible that other industries will look back on "experimental AI days" and chuckle.
Even if there is a financial bubble (that pops), the technology is still not going away.
As for what's next, I dunno. I've heard people talking about similar tech that doesn't use neural nets/etc, but that is out of my wheelhouse.
But I think AI is here to stay and it has already proven useful. And sure, we will look back on today's models like we look back upon Gordon Gekko and his giant early cell phone. And I cannot fathom how one can not separate AI the science and technology from AI tech bros and CEOs. I agree the latter are going to go through some things as the AGI fails to arrive on their schedule, but IMO there's no turning back on the technology nor should there be.
Yes, I said as much. I've said this is two other places in this thread, but when they are talking AI being useful, they aren't just talking about for software development. The software industry is seeing far more AI adoption, by a very large margin, than any other industry, and the success of the current companies hinges on it being heavily adopted everywhere. I don't really care to defend Zitron because he does speak out of his lane far too much, especially when it comes to software, and those are the points the HN crowd latches onto. But that's not the bulk of what he talks about.
I didn't have a lot sympathy for the guy who described the Internet as a series of tubes yet I believe Al Gore caught far more flack for that bit about inventing the Internet than he deserved given the inventor of the Internet defended that very claim.
https://en.wikipedia.org/wiki/Al_Gore_and_information_techno...
So if the bulk of what Zitron's talking about is valid, then what are the main points that aren't self-evident i.e. there's definitely either a buildout or a bubble in CapEx and only time will answer that question, not hot air and blatant market manipulation. What is he bringing to the conversation that we're all missing? Seriously, educate me.
> So then what is the deadline for AI reaching into all these new industries?
Obviously the "deadline" would before the US companies go bust (again, IF they do). And I'm confused about your use of "new" here but I'm going to assume you mean "other existing industries that haven't adopted yet." The discussions around this are that several industries already jumped on AI then walked it back, so it's more that we're already past the "reaching in" stage. I don't have links for you but there have been several articles about companies firing people "because AI" then hiring them back. I suppose AI drive-thru order takers would work as another example. Again, I don't have the numbers on this myself. And again-again, none of this is "in defence of Ed Zitron" or "this is why Ed Zitron is great" or any such thing, but these are the things he talks about (and once again, no, it's nothing groundbreaking).
> FWIW I avoid AI shills and doomers myself and focus on developing my skills working with the technology.
I did a bit of that but I'm no longer employed and have been taking a break from programming for a few months.
Those sorts of numbers apply to the common folk like you and me IMO.
They do not apply to the billionaire class. They just don't. The CapEx play either pays out when the buildout is justified or it soft lands for them with a bailout like we just saw NVDA do today with OpenAI. No matter what, in the end, we'll be holding any bar tab in our retirement accounts if they're being "managed." How many times must this game play out for the unchanging outcome to settle in?
What I do think is that datacenters will now end up in other less-regulated countries just like California's plastic "recycling" ends up getting burned as garbage in the third world. So there's that I guess.
https://www.thenewlede.org/2025/07/postcard-from-california-...
Oh, I understand that. I'm not American, but I know I will still be affected if this all goes bust. I'm not in the best state of mind right now, though, and the thought of everything burning to the ground isn't really concerning me.
Also, interesting article. I was aware about plastics getting shipped to other countries but had no idea they were starting to refuse.
I don't think the AGI is nigh, it may even be far, but there was an article today that demonstrated something close to the path I've long believed AI will take into industry and it scares the Bejesus out of Anthropic and OpenAI because it reduces them to glorified neoclouds in the long run if one can replicate this process with open weight models. And oh no, Dario Amodei and his ilk will have to settle for being centi-millionaires. Tragic.
Yep! I'm a pretty self-aware dude, I like to think :)
The YouTuber I actually pay attention to is House of El who is an up-and-comer, doesn't pander to either side of the debate, and is very pro-AI software engineer. She also shows her work.
> 2008 sucked and the failure to clean it up and punish the guilty is the road to 2026
I'm in Canada which was not hit as hard but ya, I hope your next administration actually holds the guilty accountable. Though I've seen people loudly argue that will result in an endless war of retaliation? Honestly, I only started paying real attention to American politics in January 2025.
> I don't think the AGI is nigh, it may even be far
Not according to Sam Altman as of today! Just in the nick of time too when the cheap Chinese models showed up! What luck! XD
I have not yet read the article you shared but have it opened in a tab for later. Probably should have waited to respond until later but trying to reduce my screen time today.
Nobody has the patience to read a comprehensive point by point rebuttal to any of it, it's just too tedious.
You say "numbers don't lie". But they do, when the numbers being presented have been adversarially chosen. You just find numbers (no matter how low quality) that fit the chosen narrative, you throw out the numbers (no matter how high quality) that rebut it. If you're trying to predict the future, you can't afford that of bias. If you're an anti-AI grifter, you can't afford to not have that bias, your entire livelihood depends on only showing things that support the narrative.
This is the crux of my argument: Zitron provides numbers and he provides a lot of them sourced from reliable and trustworthy sources. He provides counterarguments to numbers-sparse arguments by using even more actual, real numbers with a logical theory formed from them.
This should make it rather easy to dispute his claims, no? So then where are the equally rational disputes?
Just this article has a dozen instances of numbers being used to prop up the argument. They're mostly irrelevant to whatever argument Zitron is trying to make at the time. Some others are straight up misrepresentations. HN really is not a good forum for point by point rebuttals for that many cases. Do you think there's a particularly high impact use of numbers in this article?
Either way it looks like he didn't just "repeat the numbers". He updated them and provided more data to back them up.
Especially if part two of your theory comes to fruition and they have to raise prices. I might of forgotten my Netflix subscription when it was 10 dollars a month but certainly not if it was 200 you know?
Having a subscription might make people run agents overnight, or casually generate images for fun, or start more coding projects. The reason gym memberships work is that people like the idea of going to the gym a lot but don't really enjoy actually doing it very much and fall off over time, leaving the gym for the rare person who's really into fitness to use it cheaply.
is AI like that where most users will get bored? or is it like movies where they'll try to get their money's worth?
User's getting bored will also spell trouble for the subscription model. I don't think we'll see a world where the average normie is going to be running agents in a loop overnight to make software. They'll get bored use it to cheat on their homework and as a Google replacement, generate silly images for a week then get bored of that, and then realize the have no actual reason to be spending $100/month and drop down to a lower tier or just cancel all together and live within the free-tier limits.
So if that happens, the labs are now left only with power users that can actually generate asymmetric cost. The market will bifurcate into free-tier users and "get their money's worth" users. So the risk isn't that the top 5% of users use more tokens than the subscription has any right to give you, it's that everyone else cancels their plans and only those top 5% of users remain.
The labs will have to put stricter rate limiting and token limits on the subscription plans to avoid MoviePass style burn.
Gyms get away with it because most don't let you cancel easily. You pay monthly, but are locked in for 6 months or a 1 year at a time (Adobe subscription style). Maybe the labs will start to do the same? Let you pay $20/month, but you are forced into an annual commitment?
Another point against your gym analogy. When people don't have that much disposable income why would they subscribe to something they semi regularly use? And if it becomes more expensive why would they not cancel it?
I don't see where the difference is with gym subscriptions here.
I mean you can say he’s not a “science guy” but he’s undeniably “smart”.
Implying there is a "gushing torrent" of pro AI narrative is bizarrely out of touch. We both know this isn't true.
the pro-AI side on the other hand has poured billions into ads and marketing and CEOs are forcing it on people due to a combo of FOMO, personal investments in AI (CEO, board, investor), etc
folks in the US have been pretty aware that bubbles based on political opinions -- we're all surrounded by news from "our side" yet we know the other side exists in some other bubble. but for AI, we're all either surrounded by pro- or anti- opinions and its a little shocking to learn that theres a parallel internet with the opposite stance. especially shocking when you find somebody that lives in teh same political bubble but opposite AI bubble.
Happy to read why is he wrong, and change my mind, as long as the arguments provide the same level of analysis he provides.
My professional opinion is that LLM technology doesn't work very well for software development and I'm not interested in hemming and hawing over its supposed benefits any longer.
This comment is so obviously false (in my experience) I'm wondering what sort of niche environment you're working in
This is less agreeable. You kind of just made statements without even having claims (even without requirement of evidence or details) to back them up.
This is like the illusion of contribution.
i have yet to have an LLM beat me. i am forced to try regularly so i don't look like an AI anti at a company that is very much SV pilled
Some developers work better with LLMs in their workflows than others. Some problems are easier for LLMs to generate a reasonable solution for than others. Some folks prompt minimally and see what the vibes bring. Others start with a detailed architecture and implementation plan.
The individual results will depend quite a lot on the person, the problem, and the approach. It's not a guaranteed winning formula for everyone.
This is pretty rude!
He said his version of this observation is "your agents are only as good as you are." I think he's right, and the key is to practice and build the skill.
that doesn't sound like a net benefit at all. I think mostly people just enjoy playing with these toys, and good developers are still good with them, bad developers still bad
I am sympathetic to some of his criticisms that the enthusiasm and financial commitment has run far ahead what can be delivered. But I don't quite share his intensity over the doom and gloom. There probably will be a correction. It will probably sting. But I don't expect it to be the near wipe-out that Ed's passionate voice seems to steer towards.