You can’t strip arbitrary words from the input because you can’t assume their context. The word could be an explicit part of the question or a piece of data the user is asking about.
Each call goes through an LLM-lite categorizer (NNUE mixed with Deeplearning) and the resulting body has something along the lines of a "politenessNeededForSense: boolean". If it is false, you can trust we remove all politeness before engaging with Claude 4. Saved roughly $13,000,000 this FY
Seems like you could detect if this was important or not. If it is the first or last word it is as if the user is talking to you and you can strip it; if not it's not.
It's very naive but worth looking into. Could always test this if it is really costing so much money for one word. Or build another smaller model that detects if it is part of the important content or not.
There are hundreds of other opportunities for cost savings and efficiency gains that don’t have a visible UX impact. The trade-off just isn’t worth it outside of some very specialized scenarios where the user is sophisticated enough to deliberately omit the word anyway.
It'd run in to all sorts of issues. Although AI companies losing money on user kindness is not our problem; it's theirs. The more they want to make these 'AIs' personable the more they'll get of it.
I'm tired of the AIs saying 'SO sorry! I apologize, let me refactor that for you the proper way' -- no, you're not sorry. You aren't alive.
The obsequious default tone is annoying, but you can always prepend your requests with something like "You are a machine. You do not have emotions. You respond to exactly my questions, no fluff, just answers. Do not pretend to be a human."
Prompts such as 'the importance of please and thank you' 'How did this civilization please their populus with such and such' I'm sure with enough engineering it can be fixed, but there's always use cases where something like that would be like 'Damn, now we have to add an exeption for..' then another exception, then another.
