Jev is the FIRST of a Whole New Class of AI Models (Here's How to Actually Use It)
Cole Medin explains Jev, TypeSafe's fast decision-making AI model trained with RLCD. He demonstrates practical implementations including PR triage, model routing, and game loop decision-making, comparing Jev's speed, cost, and reliability against traditional LLM structured outputs.
Original by Cole MedinAgent workflowsIntermediate17 min 13 secPublished Source reviewed
Before you press play
What you’ll find in the video
Represent the situation and allowed questions explicitly; Jev returns bounded answers and probabilities rather than prose.
The demonstrations place Jev at routing and classification points while leaving generation to an LLM.
Cole contrasts one general decision model used across PR triage, games, and routing with a classifier trained for just one task.
Worth knowing
Auto-generated English captions reviewed with Gemini. Fast latency and deterministic schema adherence do not guarantee correct or optimal decisions; vendor cost/speed graphs are claims and non-deterministic confidence shifts can occur.