给 agent 加决策层的七步指南与 Jev 对比

kazurai @k4zxbt原推发布于 2026.10.02

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OpenAI just entered the decision-model race that Jev made popular how to give your agent a decision layer that picks every next step, in this guide: step 1 -> find the decisions: mark every step in 20 traces where your agent picks from a short list step 2 -> write each answer as a condition a stranger could apply, plus a none option for the gaps step 3 -> set floors per action: 0.6 to act on a read, 0.85 before money moves without a confirm step 4 -> on Jev, ask every question in one call, then let code ignore what doesn't apply step 5 -> send everything under the floor to code, a bigger model or a person step 6 -> replay a few hundred real decisions through each engine - Every's two tests split the win step 7 -> pin the model version - a floor tuned on one model is a guess on the next 76 vs 73 correct steps of 78, OpenAI's Decisions against Jev, in Every's first test the result: each call comes back in under a second, and the big model only sees the hard cases a must-have for anyone building agents, read the full guide below

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