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> fixing spelling and grammatical errors should involve humans in the process, so you really can't automate this

This is an interesting observation to me. I would have expected that, since LLMs evolved from autocomplete/autocorrect algorithms, correcting spelling mistakes would be one of their strong suits. Do you have examples of cases where they fail?

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If you look at my post history, you can see an example of how claude and openai can not tell that GitHub is spelled correctly. The end result won't make a difference but it raises questions regarding how else it can misinterpret things.

At this moment I would not trust AI to automatically make changes.

My answer to this in my own pet project is to mask terms found by the NER pipeline from being corrected, replacing them with their entity type as a special token (e.g. [male person] or [commercial entity]). That alone dramatically improved grammar/spelling correction, especially because the grammatical "gist" of those masked words is preserved in the text presented to the LLM for "correction".

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