一条推文推荐了一篇关于构建现代 harness、实现更自主智能体系统的深度文章,作者称这是其使用自定义 harness 驱动智能体团队以来读过的最佳论述。核心设计是让智能体持续运行并跨任务保持产出,需要协调-执行架构,这得益于 LLM 智能体在协调和持久上下文上的进步。
Highly recommended read.
It's an absolute masterclass in building a modern harness and enabling more autonomous agent systems.
This is the best write-up I have read on how I have been working with my agent teams powered by my custom harness.
In simple terms, you want a design that lets the agent operate continually and stay productive across tasks.
This requires a coordination-execution architecture. This is possible now, as LLM agents have gotten better at coordination and maintaining persistent context.
Once you get the core architecture right, you can explore proactive components (event triggering, acting ahead, etc.) and interesting ways to communicate with agents seamlessly (e.g., an asynchronous ReAct Loop).
On top of that, the design scales through state management and sandboxes. Target a design that separates state, compute, and environment. And build something that can persist and is always available across devices.
Btw, you can do this with other existing harnesses too. It doesn't have to be DeepSeek Harness.
As agent capabilities improve, you should find new ways to interact with them and avoid getting in the agents' way.
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来源:elvis · x.com