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[–] 55 points 3 months ago (5 children)

Most people have learned by now, that “lines of code“ is a terrible metric for evaluating productivity. Why are we doing the exact same thing with AI tokens now?

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  • [–] 12 points 3 months ago (2 children)

    I’m no developer, just so some casual scripting for my job, but lines of code being a performance metric is a hilarious notion. Like, the indicator of good code is that it’s efficiently written in a small number of lines. It’s similarly just as easy to waste tokens on nothing of value.

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  • [–] 3 points 3 months ago

    I love this story:

    A division of AppleComputer started having developers report LinesOfCode written as a ProductivityMetric. The guru, BillAtkinson, happened to be refactoring and tuning a graphics library at the time, and ended up with a six-fold speedup and a much smaller library. When asked to fill in the form, he wrote in NegativeLinesOfCode. Management got the point and stopped using those forms soon afterwards.

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  • [–] 1 point 3 months ago

    I wouldn't mind seeing lines of comments and external documentation as metrics. Perhaps as a ratio to functions or sections. I know, requiring it would just lead to crappy documentation, but that's typically better than none at all, and there's a lot of folks out there just too busy with their brilliance to write up what they just coded.

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  • [–] 2 points 3 months ago

    Before ai, my company’s misguided kpi was the number of merge requests

    At least that one worked well for me since I’m generally making many small changes to an existing code base

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  • [–] 1 point 3 months ago

    Because companies have been talking up how their adoption of AI is going to make them faster and more able to capitalise on opportunities in order to prop up their valuations for a while now and it seems to work as far as share price goes.

    Being able back up this talk with metrics showing that their employees are all in on AI reinforces this, since the share price is the metric the business optimises for over product development employee reviews will index on this over cost effectiveness, and at most big tech companies engineers are very much making every decision with an eye to performance review optimisation (i.e. how it will affect their next review rather than the product they are building)

    There is also some lesser incentives in that meta employees care directly about the meta share price since a lot of their compensation is in the form of RSUs.

    I'm not condonig this as a desirable state of affairs, just explaining the incentive curve that the actors are following.

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