Comment by alin23
13 hours ago
My main gripe with LLMs is the cringe AI phrasings that they use in UI elements. Pompous things like "Your keys, supercharged" or weird yoda-speak stuff like "searches the app remembers" instead of just naming the thing "Learned searches".. you know, proper GUI copy like it was done for the past decades.
I jumped when I saw a mention about "writing style improvements" so I gave it a try on a recent feature in rcmd [0]. I prompted Fable 5.1 to find these wordings and propose simpler plain language.
For context, I recently worked with Fable to give users a way to fuzzy search and focus any browser tabs, terminal panes etc. but the UI was still a prototype full of AI writings.
It took every string including the ones I already rewrote by hand, and proposed even more weird LLM speak. Like for "Left Command conflict detected" it proposed "This keyboard can't tell left from right".
It's a very capable coding agent, but I can't understand how it can be so bad at writing. Where are all these verbal tics coming from and why is it so hard to get rid of them?
> Pompous things like "Your keys, supercharged" or weird yoda-speak stuff like "searches the app remembers"...
It's copywriting. They fed these models the internet, which is loaded with it.
And turns out, the "frontier" labs have no human oversight of the training data going into these models... Explains so much
There is no realistic path to human oversight for the vast quantities of data these models are trained on. Imagine the cost of having every Reddit comment ingested human reviewed. Insane.
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It's watermarking.
This style provides a high entropy basis distribution, so they can from a bigger pool to pick from and phrases to watermark the sentence.
You have much bigger variation of this idiotic phrases and words, which states a simple fact in that sophisticated and twisted manner.
> Where are all these verbal tics coming from and why is it so hard to get rid of them?
It’s a side effect of post-training for effectiveness and efficiency at technical tasks.
Over time the models learn to pack as much information as possible into their available context window, because that’s one way to increase the effective intelligence.
Humans do this too with industry jargon, dense tech-talk, etc.
We have a limited capacity so packing it densely maximises what we can do with it.
If you’ve ever heard a “non technical” manager complain about the terminology in an IT meeting — this is why.
Yeah that was what I was most worried about when I read the top comment here. I found the use of language a feature not a bug. I don’t care how good it reads. If I can communicate with it concicely it’s enough to get my work done. I don’t hate the language for copy either, but yeah different users, different problems.
Makes sense. Then maybe we would need a separate simpler LLM trained on UI copy and good UX to decide this stuff and let frontier models do the implementation.
But who has both the compute power and the motivation to do such a thing?
I guess I'll just continue rewriting the UI one word at a time for the time being.
Each time you re-write keep a copy of the before and after with some notes on why. Then with a few good examples of this turn it into a skill to review/fix new UI copy.
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