Routing repeated agent decisions through Jev to speed up the loop
A five-step formula: trace the loop, route repeated decisions like tool use, retries, and completion checks through Jev, fall back to the model for uncertain cases, then verify and compare time and cost.
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 ↓
This post quotes another post: x.com/0xmorlex/status/2101268094387704311