Don't Build Agents, Build Skills Instead – Barry Z

章节 1：从构建智能体到“代码即万物”的范式转变

📝 本节摘要：

本章作为开场，演讲者Barry首先回顾了上次演讲以来行业的快速变化，指出现有的智能体（Agents）虽然具备智力，但往往缺乏实际工作所需的专业技能（Expertise）。他引出了Anthropic的新战略重心：停止构建针对特定领域的独立智能体，转而在“代码即万物”（Code is all we need）的理念下，打造一种模型与运行时环境紧密结合的通用架构。他论证了代码不仅仅是一个用例，而是通往数字世界的通用接口，这使得智能体的底层架构可以变得极度精简和可扩展。

[原文] [Barry]: all right good morning and thank you for having us again last time we were here we're still figuring out what an agent even is

[译文] [Barry]: 好了，大家早上好，感谢再次邀请我们。上次我们来这里的时候，我们还在摸索到底什么是智能体（Agent）。

[原文] [Barry]: today many of us are using agents on a daily basis but we still notice gaps we still have slots right agents have intelligence and capabilities but not always expertise that we need for real work

[译文] [Barry]: 如今，我们许多人每天都在使用智能体，但我们仍然注意到了差距，仍然存在一些空缺，对吧？智能体拥有智力和能力，但并不总是具备我们实际工作所需的专业技能（Expertise）。

[原文] [Barry]: i'm Barry this is Mahes we created agent skills in this talk we'll show you why we stopped building agents and started building skills instead

[译文] [Barry]: 我是Barry，这位是Mahesh，我们开发了“智能体技能”（Agent Skills）。在本次演讲中，我们将向大家展示为什么我们停止构建智能体，转而开始构建技能。

[原文] [Barry]: a lot of things have changed since our last talk mcp became the standard for agent connectivity cloud Code our first coding agent launched to the world and our cloud agent SDK now provides a production ready agent out of the box

[译文] [Barry]: 自上次演讲以来，很多事情都发生了变化。MCP（模型上下文协议）成为了智能体连接的标准；Claude Code——我们的第一个编程智能体——面向全球发布了；而且我们的Claude Agent SDK现在提供了一个开箱即用的、生产就绪的智能体。

[原文] [Barry]: we have a more mature ecosystem and we're moving towards a new paradigm for agents that paradigm is a tighter coupling between the model and a runtime environment put simply we think code is all we need

[译文] [Barry]: 我们拥有了一个更成熟的生态系统，并且我们正在迈向智能体的新范式。这个范式是指模型与运行时环境之间更紧密的耦合。简单来说，我们认为“代码即是我们所需的一切”（Code is all we need）。

[原文] [Barry]: we used to think agents in different domains will look very different each one will need its own tools and scaffolding and that means we'll have a separate agent for each use case for each domain

[译文] [Barry]: 我们过去认为不同领域的智能体看起来会截然不同，每一个都需要其独特的工具和脚手架（scaffolding），这意味着我们需要为每个用例、每个领域构建一个独立的智能体。

[原文] [Barry]: well customization is still important for each domain the agent underneath is actually more universal than we thought what we realized is that code is not just a use case but the universal interface to the digital world

[译文] [Barry]: 虽然针对每个领域的定制化仍然很重要，但底层的智能体实际上比我们想象的要更加通用。我们意识到，代码不仅仅是一个使用场景（use case），而是通往数字世界的通用接口。

[原文] [Barry]: after we built cloud code we realized that cloud code is actually a general purpose agent think about generating a financial report the model can call the API to pull in data and do research it can organize that data in the file system it can analyze it with Python and then synthesize the insight in old file format all through code

[译文] [Barry]: 在构建了Claude Code之后，我们意识到Claude Code实际上是一个通用目的的智能体。试想一下生成财务报告的场景：模型可以调用API来拉取数据并进行调研，它可以在文件系统中组织这些数据，用Python进行分析，然后将洞察综合成旧的文件格式——所有这些都是通过代码完成的。

[原文] [Barry]: the core scaffolding can suddenly become as thin as just bash and file system which is great and really scalable

[译文] [Barry]: 核心的脚手架突然间可以变得像Bash（命令行）和文件系统一样轻量，这非常棒，而且极具可扩展性。