The AI industry's claims about AI coding assistants boosting productivity significantly appear to be massively overblown, per a new report.

cross-posted from: https://lemmy.zip/post/49954591

“No Duh,” say senior developers everywhere.

The article explains that vibe code often is close, but not quite, functional, requiring developers to go in and find where the problems are - resulting in a net slowdown of development rather than productivity gains.

Then there’s the issue of finding an agreed-upon way of tracking productivity gains, a glaring omission given the billions of dollars being invested in AI.

To Bain & Company, companies will need to fully commit themselves to realize the gains they’ve been promised.

“Fully commit” to see the light? That… sounds more like a kind of religion, not like critical or even rational thinking.

  • flatbield@beehaw.orgEnglish
    1·
    10 months ago

    I have a friend that is a professional programmer. They think AI will generate lots of work fixing the shit code it creates. I guess we will see.

    • thingsiplay@beehaw.org
      1·
      10 months ago

      I actually think a new field of “real” programmers will emerge, in which they are specialized at looking for Ai problems. So companies using Ai and get rid of programmers, will start hiring programmers to get rid of Ai problems.

      • blarghly@lemmy.worldEnglish
        1·
        10 months ago

        Idk, that was basically 90% of my last job. At least the ai code will be nicely formatted and use variable names longer than a single character.

  • droans@midwest.socialEnglish
    1·
    10 months ago

    It’s been clear that the best use of AI in a professional environment is as an assistant.

    I don’t want something doing my job for me. I just want it to help me find something or to point out possible issues.

    Of course, AI isn’t there yet. It doesn’t like reading through multiple large files. It doesn’t “learn” from you and what you’re doing, only what it’s “learned” before. It can’t pick up on your patterns over time. It doesn’t remember what your various responsibilities are. If I work in a file today, it’s not going to remember in a month when I work on it again.

    And it might never get there. We’ve been rapidly approaching the limits of AI with two major problems. First, scaling is becoming exponential. Doubling the training data and computing resources won’t produce a model that’s twice as good. Second, overtraining is now a concern. We’re discovering that models can produce worse results if they receive too much training data.

    And, obviously, it’s terrible for the environment and a waste of resources and electricity.

  • majster@lemmy.zipEnglish
    1·
    10 months ago

    I’m a dev at a tech startup. Most devs at the company are pretty impressed by claude code and find it very useful. Hence the company has a pretty hefty budget allocated for it.

    What I need to do is think trough the problem at hand and claude will do the code->build->unit test cycles until it satisfies the objective. In the meantime I can drink cofee in peace and go to bathroom.

    To me and to many of my coworkers its a completley new work paradigm.