The other argument Doctorow gives for the limits of LLMs is the example of typo-squatting. This isn't an attack that's new to LLMs and, while I don't know if anyone has done a study, I suspect it's already the case in January 2026 that a frontier model is no more susceptible to this than the median human, or perhaps less; certainly in general Claude is less likely to make a typo than I am. There are categories of mistakes it's still more likely to make than me, but the example here is already looking out of date, which isn't promising for the wider argument.
*to be fair, it's clearly not aimed at a technical audience.
> This is another key to understanding – and thus deflating – the AI bubble. The AI can’t do your job, but an AI salesman can convince your boss to fire you and replace you with an AI that can’t do your job.
> Now, AI is a statistical inference engine. All it can do is predict what word will come next based on all the words that have been typed in the past. That means that it will “hallucinate” a library called lib.pdf.text.parsing,
I think it is a convenient, palatable, and obviously comforting lie that lots of people right now are telling themselves.
To me, all the ‘nuance’ in this article is just because the coyote in Doctorow has begun looking down but still cannot quite believe it. He is still leaning on the same tropes of statistical autocomplete that have been a mainstay of the fingers-in-ears gang for the last 3 years.
I'm working directly with these tools and have several colleagues who do as well. Our collective anecdotal experience keeps coming back to the conclusion that the tech just isn't where the marketing is on its capabilities. There's probably some value in the tech here, which leads others like yourself to be so completely sold on it, but it's just not materializing that much in my day-to-day outside of creating the most basic code/scaffolding where I then have to go back and fix/correct because there are subtle errors. It's actually hard to tell if my productivity is better because I have to spend time fixing the generated output.
Maybe it would help to recognize that your experience is not the norm. And if the tech were there, where are the actual profits from selling it? It's increasingly more common for it to be "under development" for selling to consumers or only deployed as a chatbot in scenarios where it's acceptable to be wrong and warnings to verify output yourself.
If my other replies come off as aggro, I apologize - I definitely can struggle with moderating tone in comments to reflect how I actually feel.
> Our collective anecdotal experience keeps coming back to the conclusion that the tech just isn't where the marketing is on its capabilities. There's probably some value in the tech here, which leads others like yourself to be so completely sold on it
Let me be clear - I am not so completely sold on the current iteration. But I think there has been a significant improvement even since the midpoint of last year, the number of diffs I am returning mostly unedited is sharply increasing, and many people I am talking to are privately telling me they are no longer authoring any code themselves except for minor edits in diffs. Given that this has only been 3 years since chatgpt, really I am just looking at the curve and saying ‘woah.’
It's unfortunately the case that even understanding what AI can and cannot do has become a matter of, as you say, "ideological world view". Ideally we'd be able to discuss what's factually true of AI at the beginning of 2026, and what's likely to be true within the next few years, independently of whether the trends are good for most humans or what we ought to do about them. In practice that's become pretty difficult, and the article to which we're all responding does not contribute positively.
Frequency is important too.
>independently of whether the trends are good for most humans or what we ought to do about them.
This whole article is about the trends and of they are good for humans. I was pleasantly surprised that this was not yet another argument of "AI is (not) good enough" since people at this point have their fences set on that. I don't think it's too late to talk about how we as humans can manage pandora's box before it opens.
Responses like this dismissing the human element seem to want to isolate themselves from societal effects for some reason. The box will affect you.
> I was pleasantly surprised that this was not yet another argument of "AI is (not) good enough"
The article does assert that, and that's important for its argument that ordinary workers just need to convince decisionmakers that things will go poorly if they replace us.
"Now, if AI could do your job, this would still be a problem... But AI can’t do your job."
This isn't ambiguous.
>independently of whether the trends are good for most humans or what we ought to do about them.
Saying "the writer shouldn't talk about this" is about as dismissive of a topic as you can be. You could have simply said "this topic isn't as interesting to delve into", but the framing that "the article to which we're all responding does not contribute positively." suggests that.
>This isn't ambiguous.
It's also talking about the present. The article already made clear it is not going to predict the future of tech in the very beginning. Its looking at the here and now for AI and the human element for any possible futures on whether or not that remains the case or not.
Also note this response. It is again trying to focus on the tech arguments. This isn't the focus of this argument
As for the Doctorow article, I don't understand exactly what you're trying to say about "focus", but it's incoherent to read the discussion about replacement of your current job as talking purely about the present - since the job is currently yours, the replacement must happen in the future.
> Think of AI software generation: there are plenty of coders who love using AI. Using AI for simple tasks can genuinely make them more efficient and give them more time to do the fun part of coding, namely, solving really gnarly, abstract puzzles. But when you listen to business leaders talk about their AI plans for coders, it’s clear they are not hoping to make some centaurs.