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> “Most People Do Not Switch Models Mid-Session” I do, quite regularly. Because different models have different strength (for example when producing text for l

> “Most People Do Not Switch Models Mid-Session” I do, quite regularly. Because different models have different strength (for example when producing text for live presentations based on the text for a reading deck). Or when it comes to other aspects of the work. I regularly switch between open wheight models and closed models. I know, I am a tiny minority here. And this behavior only ever started a few weeks ago. But it quickly became a habbit, to CTRL-L in pi and change the model.

iwassayinbourns 2mo ago
Out of interest, what models do you find work best for producing text for live presentations based on the text for a reading deck?
- sdoering 2mo ago
  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.
- springtimesun 2mo ago
  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.
NamlchakKhandro 2mo ago
switching models mid session kills your KV cache. you should fork or handoff or start a new one and tell the new one to read the old session.jsonl
esafak 2mo ago
If you use subagents this is perfectly normal.

iwassayinbourns 2mo ago

Out of interest, what models do you find work best for producing text for live presentations based on the text for a reading deck?

sdoering 2mo ago
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.
springtimesun 2mo ago
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.

NamlchakKhandro 2mo ago

switching models mid session kills your KV cache. you should fork or handoff or start a new one and tell the new one to read the old session.jsonl

esafak 2mo ago

If you use subagents this is perfectly normal.