this post was submitted on 25 Jun 2026
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Using an LLM to parse stuff is like using a rocket launcher to kill an ant.
You can accomplish the same thing using a million times fewer resources with a purpose-built program.
"ChatGPT, what time is it?"
Will, that's what happens when employers tell employees that they should "use ai first", track their token use on a dashboard, and tell them they'll get fired if they are too low on the monthly ranking.
Yeah, my manager expressed satisfication with me being one of the people using my quota of tokens.
I have generated so much throwaway content that never gets used and only gets deleted to burn the tokens to avoid getting the "you aren't using AI enough" talk. The fact they can see my actual productive output and believe AI is involved shows how utterly disconnected the metric is from reality.
Well, if your KPI is how much you use an LLM like in some reports - this is an easy way to get those good indicators. Also, LLMs are super easy to use to parse things, whereas many special programs like IDK grep isn't exactly user friendly. Not to mention not finding patterns really. Though here I'm thinking things like looking at various logs on computers.
Maybe we could at least nudge the LLMs in the direction of suggesting appropriate tools and giving hints how to actually do that when applicable instead of blindly brute forcing every task. Of course that does not solve the issue of stupid corporate incentives, but I feel like by now most companies have realized that burning as much money as possible is not a good goal.
Yes but you're in an open office and all you have available in your open office hell are: rocket launcher, your sanity, Debra's snappy attitude.
Debra’s probably a better performer than you are.
Is Debra here a new version of clippy?