我们是如何构建我们的多智能体研究系统的

Claude now has Research capabilities that allow it to search across the web, Google Workspace, and any integrations to accomplish complex tasks.

Claude现在具有研究能力，可以在网络、Google Workspace和任何集成中进行搜索，以完成复杂任务。

The journey of this multi-agent system from prototype to production taught us critical lessons about system architecture, tool design, and prompt engineering. A multi-agent system consists of multiple agents (LLMs autonomously using tools in a loop) working together. Our Research feature involves an agent that plans a research process based on user queries, and then uses tools to create parallel agents that search for information simultaneously. Systems with multiple agents introduce new challenges in agent coordination, evaluation, and reliability.

这个多代理系统从原型到生产的旅程教会了我们关于系统架构、工具设计和提示工程的重要课程。一个多代理系统由多个代理（LLMs 自主循环使用工具）共同工作。我们的研究功能涉及一个根据用户查询规划研究过程的代理，然后使用工具创建并行代理同时搜索信息。具有多个代理的系统引入了代理协调、评估和可靠性的新挑战。

This post breaks down the principles that worked for us—we hope you'll find them useful to apply when building your own multi-agent systems.

这篇文章分解了对我们有效的原则——我们希望您在构建自己的多代理系统时能发现它们的用处。

Benefits of a multi-agent system

多代理系统的好处

Research work involves open-ended problems where it’s very difficult to predict the required steps in advance. You can’t hardcode a fixed path for exploring complex topics, as the process is inherently dynamic and path-dependent. When people conduct research, they tend to continuously update their approach based on discoveries, following leads that emerge during investigation.

研究工作涉及开放性问题，在这些问题中，提前预测所需步骤非常困难。你无法为探索复杂主题硬编码一条固定路径，因为这个过程本质上是动态的，并且依赖于路径。当人们进行研究时，他们往往会根据发现不断更新他们的方法，跟随在调查过程中出现的线索。

This unpredictability makes AI agents particularly well-suited for research tasks. Research demands the flexibility to pivot or explore tangential connections as the investigation unfolds. The model must operate autonomously for many turns, making decisions about which directions to pursue based on intermediate findings. A linear, one-shot pipeline cannot handle these tasks.

这种不可预测性使得AI代理特别适合研究任务。研究要求在调查展开时具备灵活性，以便进...