用 Jev 路由重复决策来加速 Agent 循环
作者给出五步公式：先追踪日志，再把「用不用工具/要不要重试/做完了吗」这类重复判断交给 Jev 路由，只把不确定的情况退回大模型，最后验证并对比耗时与成本。
Adding Jev to an AI agent does not automatically make the loop faster the speed comes from finding decisions the agent makes over and over, then routing them deliberately. formula: Faster Agent Loop = Trace + Jev Routing + Model Fallback + Verification 10% -> capture the loop. log model calls, tool actions, retries, latency and cost so you know where time goes. 24% -> group repeated decisions. identify choices like “use a tool?”, “retry?” and “is this done?”, then define the correct outcome for each. 56% -> give Jev the relevant state and clear criteria. let it route routine decisions without sending the entire conversation through a deep model. 82% -> set confidence thresholds. uncertain or novel cases go back to the deeper model. 100% -> verify and measure. check the result, then compare total loop time, cost and errors against your baseline. Jev handles the repeated choices. The deeper model handles hard problems. Verification catches bad routes before they become bad actions. I visualized the full Jev Engineering loop below ↓
这条是引用着另一条写的：x.com/0xmorlex/status/2101268094387704311