> LLMs absolutely have some form of intent (their current task)

They have momentum, not intent. They don’t think, build a plan internally, and then start creating tokens to achieve the plan. Echoing tokens is all there is. It’s like an avalanche or a pachinko machine, not an animal.

> some form of reasoning (what else is step-by-step doing?)

I think they reflect the reasoning that is baked into language, but go no deeper. “I am a <noun>” is much more likely than “I am a <gibberish>”. I think reasoning is more involved than this advanced game of mad libs.

Apologies, I tend to use web chats and agent harnesses a lot more than raw LLMs.

Strictly for raw models, most now do train on chain-of-thought, but the planning step may need to be prompted in the harness or your own prompt. Since the model is autoregressive, once it generates a thing that looks like a plan it will then proceed to follow said plan, since now the best predicted next tokens are tokens that adhere to it.

Or, in plain english, it's fairly easy to have an AI with something that is the practical functional equivalent of intent, and many real world applications now do.