Jev Engineering：把决策抽成独立一层
主张在 LLM 推理与工具执行之间加一层专门做决策，作者实测最高快 193 倍、便宜 444 倍，并给出 state→decision→action→verification 的完整蓝图。
Jev Engineering is the layer most agent stacks are still missing. state → decision → action → verification → next state up to 193x faster and 444x cheaper in our tests. everyone is optimizing the model. Jev Engineering optimizes what happens between model calls. every agent eventually hits the same fork: state → multiple possible actions → one route has to win instead of sending every decision back to an expensive LLM call, Jev turns that into a dedicated layer: so the loop becomes: LLM → reason Jev → decide tools / agents → execute state → update Jev → decide again once decisions become their own engineering layer, you can benchmark, batch and verify them separately. full blueprint in article ↓
这条是引用着另一条写的：「长文：Jev 或成 AI agent 缺失的控制层」