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@elvis (@omarsar0)
观点：自建并掌控 agent harness，可改善输出与成本
一条 X 帖子主张开发者应自建并优化 agent harness，而非依赖开箱即用方案。作者称最小化 harness 也能较快见效，可改善代码、输出、成本与写作质量，并以系统提示词优化解决输出冗长为例；同时提到 Pi 的采用增长，以及 Eve、Exo、Prime Agent 等开源项目，并预期自改进算法与本地模型端到端调优会降低优化难度。
AI推荐理由 作者提出自建并优化 agent harness 的观点，指出可改善输出冗长、成本与代码质量，并点名 Pi、Eve、Exo、Prime Agent 等开源项目；但内容为个人经验与观点，未给出可验证数据或具体实现细节，'self-improving algorithms' 属未来预期而非已证实能力，互动量仅作传播信号。
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Build and own your harness, folks.
Very few people understand the magic behind customizing and optimizing an agent harness for your work.
You can start seeing incredible results quickly, even with a minimal harness. Just better code, better outputs, better costs, better writing, and so on.
As an example, I see way too many people complain that they are tired of their out-of-the-box agent harness producing verbose outputs. If you built a harness, that's easier to fix with a system prompt optimized for you.
This is why Pi is getting insane adoption these days. You want to control your harness. I agree that it's hard to optimize where things stand, but self-improving algorithms will make it easier to learn from trajectories. And if you use local models, you can tune all of that end-to-end (through a co-evolution of the harness and the models) as you work with them.
Look into open-source projects like Eve, Exo, and Prime Agent, and you will see what I mean.