编排差距:为什么你的 AI 代理无法相互发现

📄 中文摘要

在构建多个 AI 代理后,虽然每个代理在独立运行时表现良好,但在尝试将它们有效地串联时却面临挑战。问题在于,这些代理之间并不知道彼此的存在。当一个代理的代码中硬编码了对另一个代理的调用时,实际上已经在设计上限制了多代理系统的灵活性。这种硬编码关系使得在替换或添加代理时,系统的可扩展性和适应性受到影响。解决这一问题需要重新思考代理之间的交互方式,以实现真正的协作和动态响应。

📄 English Summary

The Orchestration Gap: Why Your AI Agents Can't Find Each Other

Building multiple AI agents can lead to challenges when trying to effectively chain them together. Each agent may perform well in isolation, but the core issue arises from the fact that these agents are unaware of each other's existence. When a call to another agent is hardcoded into the code of one agent, it limits the flexibility of the multi-agent system by establishing a fixed relationship at design time. This hardcoding complicates the process of replacing or adding agents, impacting the system's scalability and adaptability. Addressing this issue requires a rethinking of how agents interact to achieve true collaboration and dynamic responsiveness.

Powered by Cloudflare Workers + Payload CMS + Claude 3.5

数据源: OpenAI, Google AI, DeepMind, AWS ML Blog, HuggingFace 等