Out of interest, what models do you find work best for producing text for live presentations based on the text for a reading deck?
I found Kimi3 (currently only a few tests) to be not to bad. Older Claude versions (did not yet test it with the 4.8-5 generation.
I do not really like (even if it is my daily driver for a lot of things) gpt-5.x for text. It really needs heavy hand holding and beating it into submission to produce readable/human sounding text.
Tbh. I am still looking for my "go to model". But the Chinese models were for my use cases significantly better than openAI models and personally I liked them better than Anthropic ones as well.
I agree with OPs commment about K3 being pretty good. Claude can be good too, but it didn’t get there until I made a writing rule. It has 4 basic sections:
* a style guide with examples for different tasks (it’s sufficient to name writers with some attributes you like if they are famous)
* mechanical formatting, output and other preferences
* a short list of the things I consider most important in different writing context, this the the squishiest overall
* a (growing) list of banned Claudisms. Nothing is really banned, but it includes things like: you may only ever use “scar tissue” in reference to actual regenerated tissue, never metaphorically
The thing is you have to be discipline with it. Every time they output something you don’t like, you’ve got to spend time verbalizing what about it you don’t like and in what context and then add it to the rules file. The first few docs you generate will take a long time, but each repeated generation gets better and by the 4th are 5 time you do this it’s like 80% of the way to where it needs to be and that generalizes well.