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It will be strictly worse in all cases, for all users, all developers, all maintainer, and all licence holders for the foreseeable future unless there is a massive improvement in the tools. They are good enough to make things that are just bad enough to be an enormous pain in the ass, especially when people who think they know a lot more than they do are using them.
WITH THE MASSIVE EXCEPTION OF: It is wild to tell the robot to write me a little piece of shit that does some shitty little task where i don't care how it works and it doesn't need to touch anything. productivity app providers in shambles, etc etc.
There are definitely some stupid developers harming projects with LLMs by adding loads of unmaintainable spaghetti slop, but "strictly worse in all cases" is strictly wrong.
LLMs aren't capable of fully structuring a project on their own, but they're more than capable of implementing a well-encapsulated algorithm or throwaway script. Also, many real-world codebases are already spaghetti, but it's adequate especially for small projects: for example Undertale and Balatro, all of Undertale's dialogue is in one switch statement and Balatro has this monstrosity among many more bad design decisions. Would the median LLM-assisted developer write worse?
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If AI programming was so awful for users and developers, nobody would be paying tens of billions of dollars for it.
Statements by the utterly deranged! I guess lots of people might be getting emotional about self-driving cars, car accident lawyers for instance or race car enthusiasts... The same goes for AI programming but that's no excuse to let it cloud judgement.
Here's a fact that sounds fake but isn't: the best AI developer (Anthropic) had less revenue than Ebay last fiscal year.
Yes, it was roughly $5B in 2025 to Ebay's $11B, also interestingly the best guess for Anthropics revenue in June 2026 was also $5B. Things are moving quickly and Anthropic is projected to have ~$60B in revenue over 2026 with error bars as low as $45B and as high as $80B. Putting it in the class of Goldman Sachs, Intel and IBM as far as revenue is concerned. And well, the straight lines on graphs interpretation makes this year to year change pretty interesting.
Is that with GAAP accounting?
Of course not, but neither is the comparison to ebay. There aren't audited numbers so we're all estimating based on available information.
"You really think a startup would do that? Just go on the internet and tell lies about their revenue!?"
I'm not the one who originally tried to make some point about what the speculative revenue tells us about Anthropic.
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Going a little further back, in Jan 2024 Anthropic had $87 million ARR, by May 2026 they were at $47 billion ARR
Some have questioned this accounting, whether ARR is representative of realized revenue over the whole year. We shall have to wait for the IPO for more detailed accounting. But it seems likely that Anthropic is the fastest growing company in history.
Yeah, I am very interested in the IPO. OpenAI lost nearly 40 billion last year and may be undershooting its goals this year, which I don't think bodes well for the US frontier labs.
But Anthropic might not be fated to the same destiny as OpenAI - for one thing, it explicitly kept its hands away from the advertising cookie jar.
OpenAI may indeed be undershooting in ads. But do we really think the ad market for chatbots is a mere $5 billion? What does that even mean? At what point in time?
A lot of emotive language in the article...
If I go to the front page of Futurism, I find these article headlines about AI:
The only time when AI is good is when it's bad for US companies it seems.
If AI psychosis is so significant that it deserves a whole category of Futurism articles about it, surely that indicates there is some significant advertising power in AI, some ability to change minds? Only the technology hasn't been fully developed yet. And what about the google AI summary at the start of nearly all searches? There are ads above, below and within it. There are all kinds of effects going on, revenue shifting between Google Adsense and Search. I think it's a lot more complicated and a lot less one-sided than Futurism would have us think.
I am not OpenAI's top guy, I think the company is a negative force in the world and AI development is an extremely serious matter with the gravest possible implications for humanity. But this totally negative view that some outlets push is a distortion.
Case in point, the nearly 40 billion loss for OpenAI. That's true from a certain perspective but a good chunk of it is an accounting loss from the shift from non-profit to for-profit company, moving control around. That shift is reprehensible but means the 'true' financial loss is closer to $10-20 billion.
Where is the headline about AI disproving the Jacobian conjecture the other day? That's roughly Fields Medal worthy in mathematics, albeit of little practical relevance. These systems are extremely capable but that doesn't fit the narrative that the media wants. Journalists are extremely threatened by AI, as are media companies. Why would I want to look up articles and read them (let alone pay a j**rnalist!) when I can just ask an AI about OpenAI's losses? Why would a journalist want to get a real job when they could instead try to hyperstition an AI bubble into existence and stick it to their hated class enemies? Not all journos... but many.
I agree with Shrike on the other points, but to clarify a misunderstanding:
While very impressive, nobody is claiming that a counterexample to the Jacobian conjecture for N > 2 would have merited a Fields Medal.
Daniel Litt, probably one of the most AI-involved mathematicians right now, agrees that it would have been a notable accomplishment for a mathematician, but not anything close to a Fields Medal worthy achievement.
https://xcancel.com/littmath/status/2079091534159298769
Litt is almost certainly correct that "Fields Medal" is overselling it, but I think "very impressive" is still underselling it. This was roughly a top-50 open problem in mathematics, one famous for attracting flawed "proofs". A restricted version of the conjecture had been open for nearly a century before being proven. The full conjecture was open for over 80 years. One of the most successful 21st century number theorists had his math career derailed by spending his PhD on the Jacobian conjecture with unimpressive results.
I think my biggest reason for epistemic caution here is that this wasn't a case of "AI disproving the Jacobian conjecture", it's a case of "AI led by a Princeton math PhD disproving the Jacobian conjecture", and I haven't yet seen which half of that team was responsible for which ideas in the derivation. From a quick glance at Alpöge's dissertation and senior thesis, I guess he seems to be more of an Algebraic-geometry guy than an algebraic-Geometry guy, but he still seems to be comfortable with the sorts of algebraic geometry tools that were likely used to derive his example. It's possible that Fable did most of the heavy lifting and Alpöge's critical contribution was "being an Anthropic employee with unlimited Fable access", but it might not be a total coincidence that he's not a number theorist or a topologist or something.
Steve Smale (a Fields Medal winner) listed it as #16, and I'm not finding other famous lists definitively disagreeing. That still doesn't mean its solution ranks as #16, of course - at this point people were expecting a proof requiring brilliant new mathematical techniques, whereas the general ideas leading to the counterexample appear to fit in a tweet - but it does mean that it was a problem that some of the best minds in the world were considering, over the course of decades.
Just learned his PhD advisor was Manjul Bhargava, a Fields Medal winner for algebraic geometry work. Bhargava's work also seems to be more interested in geometry with number fields other than with boring old ℂ, though.
Apparently GPT reverse-engineered the ideas in that tweet above after looking at the counterexample's equations? Again, the guy prompting it is an algebraic geometer, but he still had to prompt it.
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My personal belief has actually been that the online ad market is inflated, so chatbots not having a high ad ceiling wouldn't surprise me.
True, there was some weird accounting there. What strikes me is that they made $13 billion but spent $7.5 billion on cost of revenue - inference, most likely - and nearly $6 billion in advertising. Or in other words, their business was not profitable before you factor in R&D and training.
I do think this is true, at least partially - I think that journalists were souring on Silicon Valley before AI kicked off, so some of them are going to be biased against it. But I also do think that OpenAI (and Anthropic) are more than happy to dangle substantially false narratives to promote their businesses - and these narratives flatter the interests of investors. In particular, I think that people underappreciated the massive difference between software and AI - the cost of providing software is vastly lower than that of providing compute. But I think there was insufficient appreciation of that with AI, although I do think that is now changing.
This is relevant insofar as I absolutely think investors could be wrong.
souring? They've openly hated Silicon Valley for a very long time.
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