At Meta, Microsoft, Salesforce and other large companies, devs are purposefully burning tokens (and money!) to inflate their AI usage and hit AI usage metrics which they treat as targets.
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?
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.
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.
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?
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.
I love this story:
Because middle manglement has a constant compulsive need to justify their existence by finding new ways and metrics to “manage”.
You would be surprised to know how many managers still rely on this metric, even if it’s not part of their KPIs.
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