Agent

Over the past year, we’ve worked with dozens of teams building large language model (LLM) agents across industries. Consistently, the most successful implementations weren’t using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns.

过去一年，我们与数十个团队合作，构建了跨行业的LLM大型语言模型代理。始终如一的是，最成功的实现并没有使用复杂的框架或专门的库。相反，他们使用简单、可组合的模式进行构建。

In this post, we share what we’ve learned from working with our customers and building agents ourselves, and give practical advice for developers on building effective agents.

在这篇文章中，我们将分享我们从与客户合作和构建代理的过程中学到的知识，并为开发者提供构建有效代理的实用建议。

What are agents? 代理是什么？

“Agent” can be defined in several ways. Some customers define agents as fully autonomous systems that operate independently over extended periods, using various tools to accomplish complex tasks. Others use the term to describe more prescriptive implementations that follow predefined workflows. At Anthropic, we categorize all these variations as agentic systems, but draw an important architectural distinction between workflows and agents: