用 Jev-as-a-Judge 做智能体评估：低成本分流到前沿模型的组合玩法
Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev us...
讲了个省钱思路：评估智能体时用 Jev 当裁判，拿不准再升级到 GPT-6 或 Opus 5.5，准确率和成本都能兼顾。
作者在测试 Jev-as-a-Judge 用于智能体评估，认为 Jev 天然适合做 Judge，但不该到处都用。早期结果显示一条兼顾准确率和成本的优化流程：高置信度场景用 Jev 判定，低置信度时升级到前沿模型 GPT-6 或 Opus 5.5。完整写作指南正在整理中，作者征集问题。
Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev us...
Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a natural fit as a Judge, but it doesn't mean you use it everywhere. Similarly, you shouldn't use frontier models for evals everywhere. I'm running lots of tests on this atm, but early results point to an optimized flow (balancing accuracy and cost) that combines Jev and frontier models. Concretely, use Jev in high-confidence situations, and escalate to a frontier model (GPT-6 or Opus 5.5) in low-confidence verdicts. Entire write-up coming soon. Let me know if you have questions as I build the full guide. 💬 2 🔄 1 ❤️ 6 👀 584 📊 3 ⚡
