做 Agent 开发的团队终于有了可落地的评估方法论——Trace 数据不再是日志垃圾，而是构建评估的黄金矿，建议做生产级 Agent 的开发者点开看看具体怎么用。
LangChain 的 Adam Łucek 分享了如何利用 Agent 运行时的 Trace 数据来构建生产级评估。Trace 数据记录了 Agent 的输入、输出、执行步骤和元数据，是优化 Agent 行为的关键。通过分析 Trace，可以识别低效环节，并用于构建更复杂的评估体系。文章介绍了两种利用 Trace 构建评估的具体方法，帮助团队快速迭代和提升 Agent 的可靠性。
.@AdamRLucek on how we use traces to build evals for production agents.
. @AdamRLucek on how we use traces to build evals for production agents. Adam Łucek @AdamRLucek Trace data is literally worth its weight in gold these days, if you know what to do with it! As has been established, creating effective agents requires shipping early, observing behavior, and iterating quickly. At the core of this are your agent traces capturing exact inputs, outputs, steps, and metadata along the way. Analyzing traces helps surface inefficiencies and areas for improvement, but they can also be used in more sophisticated ways to set up robust evaluations. Here's two of the ways we use traces to build evals for production agents 👇 🔗 View Quoted Tweet 💬 3 🔄 2 ❤️ 8 👀 1491 📊 3 ⚡