Jev or a general LLM?

Use Jev when your code already knows the allowed outputs and needs a probability-aware signal. Examples include choosing a support queue or scoring urgency. The question design is part of the application contract.

Use a generative LLM when the output must be a draft, explanation, plan, or code. Many workflows need both: Jev decides a narrow branch, then a language model writes the response. Compare end-to-end accuracy and cost with your own examples.