That's one dimension. Another is how much you care.

For my own projects, little productivity apps for my own needs, I'm easily 20x more productive. I'm building so many more of them, and at a much higher level of polish. But that's simply because I don't care about the code, long-term maintenance, or anything else. I just need them to do a thing, and if they do the thing, I'm good. I used to make an effort calculation before building these things, but now I just tell Claude "hey, build this", and two hours later it's built well enough to be useful.

OTOH, at work, I'm probably about as fast as I was before, maybe even a bit slower. But the quality of my work has increased quite a bit, because I no longer take the shortcuts I used to take to push things out. I'm spending much more time in planning and in code reviews rather than actually typing code.

Either way, the idea that these obvious changes are just people fooling themselves is, at this point, no longer a reasonable position. And the claim that "AI will run out of money and just be turned off due to the huge operational cost" is so implausible that I would feel ashamed of myself if I used this as a straw man for what AI skeptics believe.

> So for somebody evaluating things based on what they do at work (where they're probably quite competent) or on personal projects well within their own domain, then it's 'hey what's all the hype about?' But if you're doing things outside your domain then it's a revolutionary game-changer.

They may also be seen as a revolutionary game-changer by people who actually kinda suck at their job.

And a lot of software engineers actually kinda suck at their jobs.

> For things you're already highly skilled at LLMs can be handy but the overall gains, after all is accounted for, are not so clear.

Preposterous. I can tell 5.6 Sol to do something like "optimize this entire subsystem to have no ongoing memory allocations, fix these 5 bugs, implement these 2 features" and go work on other code or do something else entirely, and it does it all flawlessly. All things I could have done myself but nowhere near as fast and right the first time with such thorough test cases. We've reached the point where the AI is usually faster and always less effort overall compared to the old days, even if you have to send a few followup prompts.

It has taken me a few months to get productive with them. I did not pick it up easily.

> That there is no evidence (not personal anecdotes but the numbers) of productivity increase?

The blog tries to cite a 2025 METR study as evidence of no productivity increase, but they ignored the newer 2026 study by the same group that did show a productivity increase with the newer tools.

I also think it's funny that there have become these hard demands for studies and proof of increased productivity. We never saw the same standard of evidence applied to previous advancements like different programming languages or using git for version control. We don't argue with people when they say they're personally more productive in emacs than in VS Code or vice versa. It's only when the topic of AI comes up that the bar for evidence gets raised to the sky

> Which ones?

The ones that shout about that one METR study, use it to imply that millions of developers are deceiving themselves in believing that tools they use every day are useful, then admit that they don't like and don't use the tools themselves.

There is no longer, in my opinion, any scope for reasonable debate that AI models like Fable 5 are net productivity increases for many, if not most, if not ALL, programming tasks. Anyone can, or should be able to, prove this to themselves in about 5 minutes.

And so if someone like the author is trying to argue the contrary, that leads me to believe they either: (1) have not bothered to spend even 5 minutes validating their belief or (2) do not care to test their beliefs against reality, for whatever reason. Either one is a bit of a red flag.

Using LLMs in a similar way to already existing IDE features like refactor, find/replace, search is unambiguously a productivity increase. Whether using them for actual task completion purposes is good or not is unknown.

But imagine that Ctrl+F was just introduced as a feature and you had a bunch of people saying "All these people saying Ctrl+F is increasing their productivity are fooling themselves", it's just a silly thing to say.

"do not fool yourself" proceeds to fool himself... if you are honest about your bias that's still fooling yourself if your conclusions are just demonstrably wrong.

The entire thing is an AI skeptic saying “I’m skeptical I found some outdated anecdata that supports my point”. Feynman’s quote is meant for the author of this post, not people using AI to execute better day to day. It’s not reasonable to point at a chatgpt subscription and say “look the entire industry isn’t sustainable”. We all know those are subsidized just like uber was. And there are plenty of people paying API rates for tokens and getting along just fine. Further, if there was a single point in history where an environmental concern killed an entire industry please point me to it. What happens in reality is that humans compromise and innovate under new sets of constraints.

The part that says

> AI will just be turned off.

Citing a study published in '25, and thus conducted before that, basically before AI got good.

Yeah this article is safe to ignore

>pump out stable features

>data corruption...urgent fix required

Do you people hear yourselves?

I find it fascinating how humans search for meaning in the unlikeliest of places, and how ancient tribal instincts will turn anything, anything at all, into an excuse for an in-group, an out-group, and a search for kinship on the most ridiculous little hill. This "Pro AI Social Club" is just the latest example, and reality has nothing to do with it. Denying reality might just be the whole point. It's a very human thing really.