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Comment by ponector

10 months ago

Chatgpt very useful for adding softness and politeness to my sentences. Would you like more straight forward text which probably will be rude for regular american?

Yes. I can't stand waffle from native or non-native speakers. Waste of electrons and oxygen :-) that might just be me however. Know your audience ;-)

If we can detach content and presentation, then the reader can choose tone and length.

At some point we will stop making decisions about what future readers want. We will just capture the concrete inputs and the reader's LLM will explain it.

  • I don't think form and function can be separated so cleanly in natural language. However you encode what's between your ears into text, you've made (re)presentational choices.

    A piece of text does not have a single inherently correct interpretation. Its meaning is a relation constructed at run- (i.e. read-)time between the reader, the writer, and (possibly) the things the text refers to, that is if both sides are well enough aligned to agree on what those are.

    Words don't speak, they only gesture.

    • My LLM workflow involves a back-and-forth clarification (verbose input -> LLM asks questions) that results in a rich context representing my intent. Generating comments/docs from this feels lossy.

      What if we could persist this final LLM context state? Think of it like a queryable snapshot of the 'why' behind code or docs. Instead of just reading a comment, you could load the associated context and ask an LLM questions based on the original author's reasoning state.

      Yes, context is model-specific, a major hurdle. And there are many other challenges. But ignoring the technical implementation for a moment, is this concept – capturing intent via persistent, queryable LLM context – a valuable problem to solve? I feel it would be.

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>which probably will be rude

as long as the text isn't at risk of being written up by HR, I don't particularly care about the tone of the message.