Comment by nerevarthelame

Comment by nerevarthelame 21 hours ago

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> I think people are getting addicted to not having to expend brain energy to solve problems, and they're mistaking that for productivity.

I think that's a really elegant way to put it. Google Research tried to measure LLM impacts on productivity in 2024 [1]. They gave their subjects an exam and assigned them different resources (a book versus an LLM). They found that the LLM users actually took more time to finish than those who used a book, and that only novices on the subject material actually improved their scores when using an LLM.

But the participants also perceived that they were more accurate and efficient using the LLM, when that was not the case. The researchers suggested that it was due to "reduced cognitive load" - asking an LLM something is easy and mostly passive. Searching through a book is active and can feel more tiresome. Like you said: people are getting addicted to not having to expend brain energy to solve problems, and mistaking that for productivity.

[1] https://storage.googleapis.com/gweb-research2023-media/pubto...

wiseowise 20 hours ago

You’re twisting results. Just because they took more time doesn’t mean their productivity went down. On the contrary, if you can perform expert task with much less mental resources (which 99% of orgs should prioritize for) then it is an absolute win. Work is extremely mentally draining and soul crushing experience for majority of people, if AI can lower that while maintaining roughly same result with subjects allocating only, say, 25% of their mental energy – that’s an amazing win.

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  • didibus 20 hours ago

    If I follow what you are saying, employers won't see any benefits, but employees, while they will take the same time and create the same output in the same amount of time, will be able to do so at a reduced mental strain?

    Personally, I don't know if this is always a win, mostly because I enjoy the creative and problem solving aspect of coding, and reducing that to something that is more about prompting, correcting, and mentoring an AI agent doesn't bring me the same satisfaction and joy.

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    • Vinnl 16 hours ago

      Steelmanning their argument, employers will see benefits because while the employee might be more productive than with an LLM in the first two hours of the day, the cognitive load reduces their productivity as the day goes on. If employees are able to function at a higher level for longer during their day with an LLM, that should benefit the employer.

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      • didibus 8 hours ago

        I think we are all working without data here, it's all conjecture.

        I went with OP's hypothesis that you are not faster, you throw things at the wall, wait, and see if it sticks, or re-throw it until it does. This reduces your cognitive load, but might not actually make you more productive.

        I'm assuming here that "you are not more productive" already accounted for what you are saying. Like in a 8h day, without AI, you get X done, and with AI you also get X done, likely because during the peak productivity hours of your day you get more done without AI, but when you are mentally tired you get less done, and it evens out with a full day of AI work.

        There's no data here, it's all just people's intuition and impression, not actually measuring their productivity in any quantifiable way.

        What you hypothesize could also be true, it the mental load is reduced, can you sustain a higher productivity for longer? We don't know, maybe.

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    • 0x500x79 8 hours ago

      Great tools should be: 1. More efficient 2. Better Quality 3. Allow you to be lazier

      AI hits 3, but not the other two. Given the current human condition, this is a dangerous combination! It will win, but at the cost of the other two.

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    • tsurba 17 hours ago

      And how long have you been doing this? Because that sounds naive.

      After doing programming for a decade or two, the actual act of programming is not enough to be ”creative problem solving”, it’s the domain and set of problems you get to apply it to that need to be interesting.

      >90% of programming tasks at a company are usually reimplementing things and algorithms that have been done a thousand times before by others, and you’ve done something similar a dozen times. Nothing interesting there. That is exactly what should and can now be automated (to some extent).

      In fact solving problems creatively to keep yourself interested, when the problem itself is boring is how you get code that sucks to maintain for the next guy. You should usually be doing the most clear and boring implementation possible. Which is not what ”I love coding” -people usually do (I’m definitely guilty).

      To be honest this is why I went back to get a PhD, ”just coding” stuff got boring after a few years of doing it for a living. Now it feels like I’m just doing hobby projects again, because I work exactly on what I think could be interesting for others.

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      • didibus 7 hours ago

        I think you make a good point. There is an issue of people talking over each other. The reality is, we don't all do the same work. It's possible my job and someone else's involves having to deliver very different code where the challenges to it differ.

        One person might feel like their job is just coding the same CRUD app over and over re-skinned. Where-as I feel my job is to simplify code by figuring out better structures and abstractions to model the problem domain which together solve systemic issues with the delivered system and enables more features to work together without issue and be added to the system, as well as making changes and new features/use-cases delivery faster.

        The latter I find a creative exercise, the former I might get bored and wish AI could automate it away.

        I think what it is you are tasked with doing exactly at your job will also mean that your use of agentic AI actually makes you more productive or not.

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