Comment by wiseowise

Comment by wiseowise 21 hours ago

10 replies

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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.

didibus 21 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 17 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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      • wiseowise 6 hours ago

        > 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.

        It's not maybe, it's confirmed fact. Otherwise there wouldn't be burnout epidemic.

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        • computably 2 hours ago

          Except the causes of burnout have almost nothing to do with the type of cognitive load associated with coding, debugging, etc.

          https://www.mayoclinic.org/healthy-lifestyle/adult-health/in...

          Of the six general causes listed, four are institutional or social, having to do more with the workplace or coworkers: lack of control, lack of clarity, interpersonal conflicts, lack of support. IME, in tech, these are far more common causes and more deeply tied to the root of the issue than specifics of work.

          The remaining two are productivity-related issues: too much/little to do, problems with WLB.

          I would note these are tied into lack of control/clarity/support, and conflict. In a healthy work environment, expectations should be clear and at least somewhat flexible depending on employee feedback, and adequate support should be provided by the employer.

          That aside, it's unclear, and I would argue unlikely, that AI-related productivity gains will help with workload issues. If you do disproportionately more work in an overworked team/org, you will simply be given more work. If many people see gains in productivity, then either the bar for productivity goes up, or there's layoffs. Even if you manage to squeak by / quiet quit with much reduced cognitive load for coding, and that's most of your job, unless you are fully remote the most likely change is your butt-in-seat time will go from "mentally taxing coding" to "mentally toxic doomscrolling."

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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 18 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 8 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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