I’m not claiming you can’t get some of the properties in some ways with LLMs, just that Jev is the sum of its parts, not just one or two properties.

LLMs can produce structured output by limiting the next token based on a grammar, that ensures correctly formed output.

But (presumably, again I haven’t seen Jev’s insides) Jev doesn’t need to do that, it just has to output probabilities for each answer, and can do it natively without artificially limiting output tokens.

So jev is cheap, fast, never produces malformed output, its output always carries correct semantic meaning (but this doesn’t mean it always answers correctly), and it separates correct from prompt (which if it truly does that is the most exciting part).