7-minute video explains how Jev's decision layer fits into agents
A video breakdown of Jev as a decision layer sitting between an agent and every model, tool, browser action and human escalation, covering 40-200x speed, the choice/score/null primitives and why narrow models help.
Caleb Writes Code just dropped a 7-minute breakdown of Jev, a new type of AI model built for fast decisions, not chat: one Jev decision layer can sit between your agent and every model, tool, browser action and human escalation. 0% → 0:00 – Why Jev challenges how we optimize LLMs 25% → 1:48 – Speed: 40–200x faster, 70–500 ms end-to-end (per TypeSafe) 59% → 4:14 – Structured input, probability distribution as output 66% → 4:46 – The primitives: choice, score, null 91% → 6:34 – Why narrow, specialized models are a net positive A quick way to understand what Jev is actually for, and why it's not an LLM replacement. Watch it, then read article below
This post quotes another post: “Jev could become the control layer AI agents have been missing”