You're talking about "thinking" models which are mostly regular LLMs trained to output a "<thinking></thinking>" token delimiter before the answer that will be shown to the user, and that's a clever use of the Chain of Thought idea. All of which I'm completely familiar with.
GP was saying
> That would be true of non-iterative models that just emit an output from beginning to end.
The disagreement here seems to be a confusion between the pure model behavior and the behavior that users experience, which is the model wrapped in a harness. It’s normal and natural now to refer to the whole system as ‘the model’ informally, even though that is technically not accurate. That ship sailed a while ago.
Since the LLM is now designed to run in a harness, it’s really not even wrong any more.
GP was saying
> That would be true of non-iterative models that just emit an output from beginning to end.
Which suggests that there are
- "iterative" models
which
- do not output "from beginning to end"
which AFAIK is science-fiction.