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> Each of these 'phases' of LLM growth is unlocking a lot more developer productivity, for teams and developers that know how to harness it. I still find mysel

> Each of these 'phases' of LLM growth is unlocking a lot more developer productivity, for teams and developers that know how to harness it. I still find myself incredibly skeptical LLM use is increasing productivity. Because AI reduces cognitive engagement with tasks, it feels to me like AI increases perceptive productivity but actually decreases it in many cases (and this probably compounds as AI-generated code piles up in a codebase, as there isn't an author who can attach context as to why decisions were made). https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o... I realize the author qualified his or her statement with "know how to harness it," which feels like a cop-out I'm seeing an awful lot in recent explorations of AI's relationship with productivity. In my mind, like TikTok or online dating, AI is just another product motion toward comfort maximizing over all things, as cognitive engagement is difficult and not always pleasant. In a nutshell, it is another instant gratification product from tech. That's not to say that I don't use AI, but I use it primarily as search to see what is out there. If I use it for coding at all, I tend to primarily use it for code review. Even when AI does a good job at implementation of a feature, unless I put in the cognitive engagement I typically put in during code review, its code feels alien to me and I feel uncomfortable merging it (and I employ similar levels of cognitive engagement during code reviews as I do while writing software).

breakfastduck 1y ago
It depends what environment you're operating within. I've used LLMs for code gen at work as well as for personal stuff. At work primarily for quick and dirty internal UIs / tools / CLIs it's been fantastic, but we've not unleashed it on our core codebases. It's worth noting all the stuff we've got out of out are things we'd not normally have the time to work on - so a net positive there. Outside of work I've built some bespoke software almost entirely generated with human tweaks here and there - again, super useful software for me and some friends to use for planning and managing music events we put on that I'd never normally have the time to build. So in those ways I see it as massively increasing productivity - to build lower stakes things that would normally just never get done due to lack of time.
- phil21 1y ago
  I do wonder about the second order effects of the second bit. A lot of open source tooling gets created to solve those random "silly" things that are personal annoyances or needs. Then you find out others have the same or similar problem and entire standard tooling or libraries come into existence. I have pontificated on how easy access to immediate "one offs" will kill this idea exchange? Instead of one tool maintained by hundreds to fulfill a common need, we will end up with millions of one-off LLM generated that are not shared with anyone else. Might be a net win, or a net loss. I'm really not sure!
add-sub-mul-div 1y ago
> I realize the author qualified his or her statement with "know how to harness it," which feels like a cop-out I'm seeing an awful lot in recent explorations of AI's relationship with productivity. "You're doing AI wrong" is the new "you're doing agile wrong" which was the new "you're doing XP wrong".
- bitwize 1y ago
  More like the new "you're holding it wrong"
- pjmlp 1y ago
  Unfortunely many of us are old enough to know how those wrong eventually became the new normal, the wrong way.
- CuriouslyC 1y ago
  At this point I don't even care to argue with people who disagree with me on this. History will decide the winner and if you think you're not on the losing side, best of luck.
  - jamesnorden 1y ago
    I'd say you're a bit biased.
    - CuriouslyC 1y ago
      I am biased, but by my personal experience, not the desire to sell anything to anyone. I don't even have products for sale right now, I'm just building free things to try and help people figure out how to ride this wave safely.
      - svieira 1y ago
        > I don't even have products for sale right now The link in your bio is a long series of tools for various personas with a "schedule a consultation" link next to each one. I'm not sure what "consultation" is if not "a product". But maybe they're all free?
polotics 1y ago
My experience is exactly the opposite of "AI reduces cognitive engagement with tasks": I have to constantly be on my toes to follow what the LLMs are proposing and make sure they are not getting off track over-engineering things, or entering something that's likely to turn into a death loop several turns later. AI use definitely makes my brain run warmer, got to get a FLIR camera to prove it I guess...
- walleeee 1y ago
  So, reduces cognitive engagement with the actual task at hand, and forces a huge attention share to hand-holding. I don't think you two are disagreeing. I have noticed this personally. It's a lot like the fatigue one gets from too long scrolling online. Engagement is shallower but not any less mentally exhausting than reading a book. You end up feeling more exhausted due to the involuntary attention-scattering.
  - notyourwork 1y ago
    It would be analogous to having to double check the IDE added the lines of code I actually typed. That’s not a great productivity boost, it’s a toy still in many ways.
    - deleted 1y ago
      [deleted]
  - deleted 1y ago
    [deleted]
  - JumpCrisscross 1y ago
    > reduces cognitive engagement with the actual task at hand, and forces a huge attention share to hand-holding You're in some senses managing an idiot savant, emphasis on the idiot part, except they're also a narcissist who will happily go out of scope if you let it. If you have management experience, the analogy is immediately obvious. If you don't, I can see how having speed run learning it with a kid running around with dynamite would be taxing.
dist-epoch 1y ago
> AI is just another product motion toward comfort maximizing over all things, as cognitive engagement is difficult and not always pleasant. In a nutshell, it is another instant gratification product from tech. For me is the exact opposite. When not using AI, while coding you notice various things that could be improved, you can think about the architecture and what features you want next. But AI codes so fast, that it's a real struggle keeping up to it. I feel like I need to focus 10 times harder to be able to think about features/architecture in a way that AI doesn't wait after me most of the time.
vel0city 1y ago
Isn't most technology generally about "product motion toward comfort maximizing over all things"? Isn't a can opener "comfort maximizing"? Bicycles comfort maximize over walking the same distance and leave more time for leisure. We use tractors to till the soil because tilling it by dragging plows by hand or by livestock was far less comfortable and led less time for other pursuits. "AI" might be a good thing or a bad thing especially depending on the context and implementation, but just generally saying something is about maximizing comfort as some inherently bad goal seems off to me.
Fire-Dragon-DoL 1y ago
I agree with you but have no metrics yet. It does help as a rubber duck though
protocolture 1y ago
>Because AI reduces cognitive engagement with tasks Just a sideways thing. Cognitive offloading is something humans do with each other quite a lot. People offload onto colleagues, underlings and spouses all the time. People engage with AI through the prism of reducing engagement with the thing they dont like, and increasing engagement with the thing they do like. It isnt a straight up productivity boost, but its more like going from being a screenwriter to a director.
tptacek 1y ago
It depends a lot on how you use it, and how much effort you put into getting a knack for using it (which is rough because you're always worried that knack might be out of date within a month or two). I use Claude, Codex, and the Gemini CLI (all "supervised command line agents"). I write Go. I am certain that agents improve my productivity in a couple common scenarios: 1. Unsticking myself from stalling at the start of some big "lift" (like starting a new project, adding a major feature that will pull in some new dependency). The LLM can get things very wrong (this happens to me maybe 20% of the time), but that doesn't matter, because for me the motion of taking something wrong and making it "righter" is much less effort than getting past a blank page, assembling all the resources I need to know how to hello-world a new dependency, that kind of thing. Along with "wrestling for weeks with timing-dependent bugs", this kind of inertia is one of like two principal components of "effort" in programming for me, so clearing it is a very big deal. I'm left at a point where I'm actually jazzed about taking the wheel and delivering the functionality myself. 2. Large mechanical changes (like moving an interface from one component to another, or major non-architectural refactors, or instrumentation). Things where there's one meta-solution and it's going to be repeated many times across a codebase. Easy to review, a lot of typing, no more kidding myself for 20 minutes that I can make just the right Emacs macro to pull it off. 3. Bug hunting. To be clear: I am talking here about code I wrote, not the LLM. I run it, it does something stupid. My first instinct now is to drop into Claude or Gemini, paste the logs and an @-reference to a .go file as a starting point, and just say "wtf". My hit rate on it spotting things is very good. If the hit rate was even "meh borderline" that would be a huge win for the amount of effort it takes, but it isn't, it's much better. I'm guessing a lot of people do not have these 3 experiences with LLM agents. I'm sorry! But I do think that if you stipulate that I'm not just making this up, it's hard to go from here to "I'm kidding myself about the value this is providing". Note that these are three cases that look nothing at all like vibe-coding.
- defatigable 1y ago
  This matches my experience exactly. #3 is the one I've found most surprising, and it can work outside the context of just analyzing your own code. For example I found a case where an automated system we use started failing due to syntax changes, despite no code changes on our part. I gave Claude the error message and the context that we had made no code changes, and it immediately and correctly identified the root cause as a version bump from an unpinned dependency (whoops) that introduced breaking syntax changes. The version bump had happened four hours prior. Could I have found this bug as quickly as Claude? Sure, in retrospect the cause seems quite obvious. But I could just as easily rabbit holed myself looking somewhere else, or taken a while to figure out exactly which dependency caused the issue. It's definitely the case that you cannot blindly accept the LLM's output, you have to treat it as a partner and often guide it towards better solutions. But it absolutely can improve your productivity.
srcreigh 1y ago
> We do not provide evidence that: > AI systems do not currently speed up many or most software developers > AI systems in the near future will not speed up developers in our exact setting > There are not ways of using existing AI systems more effectively to achieve positive speedup in our exact setting
Art9681 1y ago
It shifts your cognitive tasks to other things. Like every tool. The tool itself is an abstraction over tedium. We built it for a reason. You will spend less time thinking about some things, and more time thinking about others. In that regard, nothing will change.
naasking 1y ago
> and this probably compounds as AI-generated code piles up in a codebase, as there isn't an author who can attach context as to why decisions were made I don't see why. If anything there's more opportunity for documentation because the code was generated from a natural language prompt that documents exactly what was generated, and often why. Recording prompts in source control and linked to the generated code is probably the way to go here.
zahlman 1y ago
> increases perceptive productivity increases the perception of productivity?
enkrs 1y ago
I use LLMs (like claude-code and codex-cli) the same way accountants use calculators. Without one, you waste all your focus on adding numbers; with one, you just enter values and check if the result makes sense. Programming feels the same—without LLMs, I’m stuck on both big problems (architecture, performance) and small ones (variable names). With LLMs, I type what I want and get code back. I still think about whether it works long-term, but I don’t need to handle every little algorithm detail myself. Of course there are going to be discussions what is real programming (like I'm sure there were discussions what is "real" accounting with the onset of a calculator) The moment we stop treating LLMs like people and see them as big calculators, it all clicks.
- janalsncm 1y ago
  The issue with your analogy is that calculators do not hallucinate. They do not make mistakes. An accountant is able to fully offload the mental overhead of arithmetic because the calculator is reliable.
  - theshrike79 1y ago
    Replace calculator with the modern equivalent: Excel. It does make mistakes and is not reliable[0]. The user still needs to have a "feel" for the data. (to be pedantic "Excel" doesn't make mistakes, people trusting its defaults do) [0] https://timharford.com/2021/05/cautionary-tales-wrong-tools-cost-lives/ https://timharford.com/2021/05/cautionary-tales-wrong-tools-...
    - Jensson 1y ago
      > (to be pedantic "Excel" doesn't make mistakes, people trusting its defaults do) So what is your point? An expert that mastered excel don't have to check that excel calculated things correctly, he just need to check that he gave excel the right inputs and formulas. That is not true for LLM, you do have to check that it actually did what you asked regardless how good you are at prompting. The only thing I trust an LLM to do correctly are translations, they are very reliable at that, other than that I always verify.
athrowaway3z 1y ago
Talking about a specific set-up they use isn't the goal of the post, so I don't think it's a cop out. "How to harness it" is very clearly the difference between users right now, and I'd say we're currently bottom heavy with poor users stuck in a 'productivity illusion'. But there is the question of "what is productivity?" I'm finding myself (having AI) writing better structured docs and tests to make sure the AI can do what I ask it to. I suspect that turns into compounding interests (or lack of technical debt). For an industry where devs have complained, for decades, about productivity metrics being extremely hard or outright bullshit, I see way too many of the same people now waving around studies regarding productivity.

breakfastduck 1y ago

It depends what environment you're operating within. I've used LLMs for code gen at work as well as for personal stuff. At work primarily for quick and dirty internal UIs / tools / CLIs it's been fantastic, but we've not unleashed it on our core codebases. It's worth noting all the stuff we've got out of out are things we'd not normally have the time to work on - so a net positive there. Outside of work I've built some bespoke software almost entirely generated with human tweaks here and there - again, super useful software for me and some friends to use for planning and managing music events we put on that I'd never normally have the time to build. So in those ways I see it as massively increasing productivity - to build lower stakes things that would normally just never get done due to lack of time.

phil21 1y ago
I do wonder about the second order effects of the second bit. A lot of open source tooling gets created to solve those random "silly" things that are personal annoyances or needs. Then you find out others have the same or similar problem and entire standard tooling or libraries come into existence. I have pontificated on how easy access to immediate "one offs" will kill this idea exchange? Instead of one tool maintained by hundreds to fulfill a common need, we will end up with millions of one-off LLM generated that are not shared with anyone else. Might be a net win, or a net loss. I'm really not sure!

add-sub-mul-div 1y ago

> I realize the author qualified his or her statement with "know how to harness it," which feels like a cop-out I'm seeing an awful lot in recent explorations of AI's relationship with productivity. "You're doing AI wrong" is the new "you're doing agile wrong" which was the new "you're doing XP wrong".

bitwize 1y ago
More like the new "you're holding it wrong"
pjmlp 1y ago
Unfortunely many of us are old enough to know how those wrong eventually became the new normal, the wrong way.
CuriouslyC 1y ago
At this point I don't even care to argue with people who disagree with me on this. History will decide the winner and if you think you're not on the losing side, best of luck.
- jamesnorden 1y ago
  I'd say you're a bit biased.
  - CuriouslyC 1y ago
    I am biased, but by my personal experience, not the desire to sell anything to anyone. I don't even have products for sale right now, I'm just building free things to try and help people figure out how to ride this wave safely.
    - svieira 1y ago
      > I don't even have products for sale right now The link in your bio is a long series of tools for various personas with a "schedule a consultation" link next to each one. I'm not sure what "consultation" is if not "a product". But maybe they're all free?

polotics 1y ago

My experience is exactly the opposite of "AI reduces cognitive engagement with tasks": I have to constantly be on my toes to follow what the LLMs are proposing and make sure they are not getting off track over-engineering things, or entering something that's likely to turn into a death loop several turns later. AI use definitely makes my brain run warmer, got to get a FLIR camera to prove it I guess...

walleeee 1y ago
So, reduces cognitive engagement with the actual task at hand, and forces a huge attention share to hand-holding. I don't think you two are disagreeing. I have noticed this personally. It's a lot like the fatigue one gets from too long scrolling online. Engagement is shallower but not any less mentally exhausting than reading a book. You end up feeling more exhausted due to the involuntary attention-scattering.
- notyourwork 1y ago
  It would be analogous to having to double check the IDE added the lines of code I actually typed. That’s not a great productivity boost, it’s a toy still in many ways.
  - deleted 1y ago
    [deleted]
- deleted 1y ago
  [deleted]
- JumpCrisscross 1y ago
  > reduces cognitive engagement with the actual task at hand, and forces a huge attention share to hand-holding You're in some senses managing an idiot savant, emphasis on the idiot part, except they're also a narcissist who will happily go out of scope if you let it. If you have management experience, the analogy is immediately obvious. If you don't, I can see how having speed run learning it with a kid running around with dynamite would be taxing.

dist-epoch 1y ago

> AI is just another product motion toward comfort maximizing over all things, as cognitive engagement is difficult and not always pleasant. In a nutshell, it is another instant gratification product from tech. For me is the exact opposite. When not using AI, while coding you notice various things that could be improved, you can think about the architecture and what features you want next. But AI codes so fast, that it's a real struggle keeping up to it. I feel like I need to focus 10 times harder to be able to think about features/architecture in a way that AI doesn't wait after me most of the time.

vel0city 1y ago

Isn't most technology generally about "product motion toward comfort maximizing over all things"? Isn't a can opener "comfort maximizing"? Bicycles comfort maximize over walking the same distance and leave more time for leisure. We use tractors to till the soil because tilling it by dragging plows by hand or by livestock was far less comfortable and led less time for other pursuits. "AI" might be a good thing or a bad thing especially depending on the context and implementation, but just generally saying something is about maximizing comfort as some inherently bad goal seems off to me.

Fire-Dragon-DoL 1y ago

I agree with you but have no metrics yet. It does help as a rubber duck though

protocolture 1y ago

>Because AI reduces cognitive engagement with tasks Just a sideways thing. Cognitive offloading is something humans do with each other quite a lot. People offload onto colleagues, underlings and spouses all the time. People engage with AI through the prism of reducing engagement with the thing they dont like, and increasing engagement with the thing they do like. It isnt a straight up productivity boost, but its more like going from being a screenwriter to a director.

tptacek 1y ago

It depends a lot on how you use it, and how much effort you put into getting a knack for using it (which is rough because you're always worried that knack might be out of date within a month or two). I use Claude, Codex, and the Gemini CLI (all "supervised command line agents"). I write Go. I am certain that agents improve my productivity in a couple common scenarios: 1. Unsticking myself from stalling at the start of some big "lift" (like starting a new project, adding a major feature that will pull in some new dependency). The LLM can get things very wrong (this happens to me maybe 20% of the time), but that doesn't matter, because for me the motion of taking something wrong and making it "righter" is much less effort than getting past a blank page, assembling all the resources I need to know how to hello-world a new dependency, that kind of thing. Along with "wrestling for weeks with timing-dependent bugs", this kind of inertia is one of like two principal components of "effort" in programming for me, so clearing it is a very big deal. I'm left at a point where I'm actually jazzed about taking the wheel and delivering the functionality myself. 2. Large mechanical changes (like moving an interface from one component to another, or major non-architectural refactors, or instrumentation). Things where there's one meta-solution and it's going to be repeated many times across a codebase. Easy to review, a lot of typing, no more kidding myself for 20 minutes that I can make just the right Emacs macro to pull it off. 3. Bug hunting. To be clear: I am talking here about code I wrote, not the LLM. I run it, it does something stupid. My first instinct now is to drop into Claude or Gemini, paste the logs and an @-reference to a .go file as a starting point, and just say "wtf". My hit rate on it spotting things is very good. If the hit rate was even "meh borderline" that would be a huge win for the amount of effort it takes, but it isn't, it's much better. I'm guessing a lot of people do not have these 3 experiences with LLM agents. I'm sorry! But I do think that if you stipulate that I'm not just making this up, it's hard to go from here to "I'm kidding myself about the value this is providing". Note that these are three cases that look nothing at all like vibe-coding.

defatigable 1y ago
This matches my experience exactly. #3 is the one I've found most surprising, and it can work outside the context of just analyzing your own code. For example I found a case where an automated system we use started failing due to syntax changes, despite no code changes on our part. I gave Claude the error message and the context that we had made no code changes, and it immediately and correctly identified the root cause as a version bump from an unpinned dependency (whoops) that introduced breaking syntax changes. The version bump had happened four hours prior. Could I have found this bug as quickly as Claude? Sure, in retrospect the cause seems quite obvious. But I could just as easily rabbit holed myself looking somewhere else, or taken a while to figure out exactly which dependency caused the issue. It's definitely the case that you cannot blindly accept the LLM's output, you have to treat it as a partner and often guide it towards better solutions. But it absolutely can improve your productivity.

srcreigh 1y ago

> We do not provide evidence that: > AI systems do not currently speed up many or most software developers > AI systems in the near future will not speed up developers in our exact setting > There are not ways of using existing AI systems more effectively to achieve positive speedup in our exact setting

Art9681 1y ago

It shifts your cognitive tasks to other things. Like every tool. The tool itself is an abstraction over tedium. We built it for a reason. You will spend less time thinking about some things, and more time thinking about others. In that regard, nothing will change.

naasking 1y ago

> and this probably compounds as AI-generated code piles up in a codebase, as there isn't an author who can attach context as to why decisions were made I don't see why. If anything there's more opportunity for documentation because the code was generated from a natural language prompt that documents exactly what was generated, and often why. Recording prompts in source control and linked to the generated code is probably the way to go here.

zahlman 1y ago

> increases perceptive productivity increases the perception of productivity?

enkrs 1y ago

I use LLMs (like claude-code and codex-cli) the same way accountants use calculators. Without one, you waste all your focus on adding numbers; with one, you just enter values and check if the result makes sense. Programming feels the same—without LLMs, I’m stuck on both big problems (architecture, performance) and small ones (variable names). With LLMs, I type what I want and get code back. I still think about whether it works long-term, but I don’t need to handle every little algorithm detail myself. Of course there are going to be discussions what is real programming (like I'm sure there were discussions what is "real" accounting with the onset of a calculator) The moment we stop treating LLMs like people and see them as big calculators, it all clicks.

janalsncm 1y ago
The issue with your analogy is that calculators do not hallucinate. They do not make mistakes. An accountant is able to fully offload the mental overhead of arithmetic because the calculator is reliable.
- theshrike79 1y ago
  Replace calculator with the modern equivalent: Excel. It does make mistakes and is not reliable[0]. The user still needs to have a "feel" for the data. (to be pedantic "Excel" doesn't make mistakes, people trusting its defaults do) [0] https://timharford.com/2021/05/cautionary-tales-wrong-tools-cost-lives/ https://timharford.com/2021/05/cautionary-tales-wrong-tools-...
  - Jensson 1y ago
    > (to be pedantic "Excel" doesn't make mistakes, people trusting its defaults do) So what is your point? An expert that mastered excel don't have to check that excel calculated things correctly, he just need to check that he gave excel the right inputs and formulas. That is not true for LLM, you do have to check that it actually did what you asked regardless how good you are at prompting. The only thing I trust an LLM to do correctly are translations, they are very reliable at that, other than that I always verify.

athrowaway3z 1y ago

Talking about a specific set-up they use isn't the goal of the post, so I don't think it's a cop out. "How to harness it" is very clearly the difference between users right now, and I'd say we're currently bottom heavy with poor users stuck in a 'productivity illusion'. But there is the question of "what is productivity?" I'm finding myself (having AI) writing better structured docs and tests to make sure the AI can do what I ask it to. I suspect that turns into compounding interests (or lack of technical debt). For an industry where devs have complained, for decades, about productivity metrics being extremely hard or outright bullshit, I see way too many of the same people now waving around studies regarding productivity.