# Better Harness: A Recipe for Harness Hill-Climbing with Evals

Canonical URL: https://www.traeai.com/articles/18348b74-a00d-413c-8902-d66db1952409
Original source: https://blog.langchain.com/better-harness-a-recipe-for-harness-hill-climbing-with-evals/
Source name: LangChain Blog
Content type: article
Language: 未知
Score: 8.5
Reading time: 未知
Published: 2026-04-08T19:30:20+00:00
Tags: LLM Agent, 评估系统, 系统工程, LangChain

## Summary

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## Key Takeaways

- 评估集是Agent Harness优化的核心信号，需像训练数据般严格把控质量与标注。
- 防止Agent优化过拟合需依赖高质量Holdout集验证，并结合人工审查确保泛化能力。
- Harness改进属复合系统工程，应建立数据收集、实验设计、优化迭代与人工验收的闭环。

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