Before you press play
What you’ll find in the video
- Jev acts as a specialized decision model that selects options, scores rubrics, or yields probabilities from predefined candidate choices rather than generating freeform conversational prose.
- Because Jev is text-based and completely stateless, it retains no prior session memory, requiring developers to provide explicit state, questions, criteria, and pre-extracted modality data on each call.
- Form-fitting structured output does not guarantee factual correctness; human-in-the-loop workflows must route low-confidence scores or high-stakes edge cases back to human review.
Worth knowing
Gemini-assisted video/transcript review. Jev only evaluates text representations and does not execute code, inspect raw multi-modal files directly, or guarantee correct decisions simply because outputs conform to target schemas.