Your agent waits a full second to send the number 3

Description and use

Jev speeds up agent decision steps, cutting latency to 225 ms and cost to $0.018 per 1k judgments while keeping accuracy.

Problem

Agent loops waste time generating prose for simple decision steps, causing latency and cost inefficiencies.

Outcome

Jev reduces decision latency by ~3× and cost by ~16× compared to properly constrained LLM calls, while maintaining comparable decision accuracy.

Workflow

• 1. Identify decision steps that require only a choice or yes/no.
• 2. Route those steps to Jev via jev-use plugin, passing the current state and typed question.
• 3. For steps that need text output, keep the LLM (e.g., Claude).
• 4. Handle Jev responses: if "escalate:true" forward to LLM; otherwise use the answer and confidence.
• 5. Continue the agent loop, using Jev for decisions and LLM for text generation.

Evidence

Jev gets 86 decisions in 20 s; claude‑haiku‑4.5 gets 6 and gemini‑3‑flash 3 — all three called the way agent loops usually call them, which is the wrong way.

Source

The honest latency lead is 3×, not 14×. What survives the fair fight is cost — 5× cheaper than the constrained Gemini call and 16× cheaper than the constrained Haiku one.

Source