Treating Jev as the decision layer: Choice, Score and Noul explained
The author explains how Jev Engineering separates the decision layer from execution, using Choice, Score and Noul outputs to drive the agent loop, and claims it is 193x faster and 444x cheaper.
Jev Engineering is what turns an agent from a prompt chain into a 193x faster and 444x cheaper decision engine Jev Engineering separates the decision layer from execution. for every state: Choice → which route wins? Score → how good is each option? Noul → how likely is the condition true? then the rest of the system handles: tools → execution → verification → memory → feedback so instead of one model trying to think, decide and execute everything, you get: state → Jev decision → action → result → updated state that separation is what makes the agent loop easier to benchmark, optimize and scale. full Jev Engineering breakdown below ↓
This post quotes another post: “Jev as an agent decision layer: millisecond routing instead of costly LLM calls”