Your Language Model Is Not-So-Secretly a System 1 Model

Sure, that's what language model pre-training gives you - a reactive model where any input elicits an automatic built-in response.

Of course you'd like an AI to be capable of system 2 thinking as well, proactive planning and reasoning, which is more where they fall short, other than "reactive reasoning" (coming from the pre-training data), and pre-trained narrow reasoning (coming from RL post-training).

So, sure, in as much as an LLM can do system 1 thinking out of the box, it can compete with Jev, and how well it scores will depend on the type/quantity of data each was trained on (which can change in a future release).

It seems fashionable to say "look, my LLM can do Jev too!", but IMO this is completely missing the point. Any LLM, however dumb, can do system 1 thinking, and if it's too dumb then just use a bigger or better trained model. The competitive edge of Jev (especially for the high volume business automation market it is targeting) is not to do something that couldn't be done with an LLM, but rather to do it a lot cheaper and faster based on a more specialized architecture (with the bonus of reliable structured output and calibrated responses).