2026年Anthropic在Google Cloud Next上讲了什么？AI代理将如何改变企业软件？
AIAI Summary (BLUF)
This article is a recap of an Anthropic session at Google Cloud Next '26, covering topics such as Anthropic's 54% coding market share in 2025, the evolution from chat to code to cowork, the definition
Session Overview / 会议概览
This is the third post in my Google Cloud Next '26 (Las Vegas) recap series. You can find the previous posts here 👇
这是我 Google Cloud Next '26（拉斯维加斯）回顾系列的第三篇文章。你可以在这里找到前两篇 👇
- Part 1: [Google Cloud Next '26 Recap #1] Hands-On with the Agentic Hack Zone
- Part 2: [Google Cloud Next '26 Recap #2] Three Unique Booths I Tried at the EXPO
In Parts 1 and 2, I covered my experiences on the EXPO floor. This time, I'd like to switch gears and share one of the sessions I attended at Next '26 — specifically, an especially memorable session by Anthropic.
在第一和第二部分中，我分享了在展区的体验。这次我想换个角度，谈一谈我在 Next '26 参加的一场 会议——特别是 Anthropic 举办的一场令人印象深刻的 演讲。
Session Overview / 会议概览
The session I attended was in the Spotlights category.
我参加的那场会议属于 焦点演讲（Spotlights） 类别。
- Title: After software: Anthropic's vision for the next era of enterprise AI
- Speaker: Eric Burns (Anthropic)
- Session ID: SPTL021
- 标题：After software: Anthropic's vision for the next era of enterprise AI
- 演讲人：Eric Burns (Anthropic)
- 会议 ID：SPTL021
What is a "Spotlight" session? / 什么是焦点演讲？
According to Next's session type definitions, Spotlights are described as follows:
根据 Next 的会议类型定义，焦点演讲的描述如下：
Take part in these dedicated keynote-style sessions featuring live demos, new tech, and customer success stories, delivered by Google leaders and partners.
参加这些专属的主题演讲式会议，内容包括现场演示、新技术和客户成功案例，由 Google 领导者和合作伙伴呈现。
In other words, Spotlights are positioned as special, keynote-style sessions packed with live demos, the latest technology, and customer stories. The session video is available on the Google Cloud Next page.
换句话说，焦点演讲被定位为 特殊的主题演讲式会议，充满 现场演示、最新技术和客户故事。会议视频在 Google Cloud Next 页面上可以观看。
The session's premise / 会议的前提
Quoting from the YouTube video description, the session's premise was as follows:
引用 YouTube 视频描述中的内容，会议的前提如下：
Enterprise software will change more in the next two years than it has in the past twenty. The model is being inverted. Top-down planning, where organizations define and prioritize what to build, is shifting to bottom-up execution, where AI agents rapidly solve problems as teams discover them. Anthropic shares what's happening at the frontier. Teams are already deploying agents on Vertex AI that autonomously define, build, and iterate. We make this vision concrete, grounded in real examples and practical frameworks.
企业软件在未来两年的变化将超过过去二十年。模型正在被反转。自上而下的规划——组织定义和优先构建什么——正在转向自下而上的执行，AI 智能体在团队发现问题时快速解决。Anthropic 分享了前沿的动态。团队已经在 Vertex AI 上部署能够自主定义、构建和迭代的智能体。我们用真实的实例和实用框架使这一愿景具体化。
A pretty bold message, I'd say. From here on, I'll walk through the points that especially stood out to me during the session.
我不得不说，这是一个相当大胆的信息。接下来，我将回顾会议中让我印象特别深刻的要点。
Highlights from the Session / 会议亮点
Anthropic's presence in the coding market / Anthropic 在编码市场的存在
The first thing that grabbed my attention was the figure that Anthropic holds 54% of the 2025 coding market share. The vague sense of "Anthropic is well-supported by developers" was reinforced by an actual number.
第一个引起我注意的数据是：Anthropic 占据了 2025 年编码市场 54% 的份额。那种“Anthropic 深受开发者支持”的模糊感觉得到了一个具体数字的印证。
On top of that, the evolution of how AI is used at work was framed with these keywords:
此外，会议用以下关键词概括了 AI 在工作中的使用演变：
- 2023: Chat
- 2025: Code
- 2026: Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。
- 2023: 聊天
- 2025: 编码
- 2026: 协作
And the phrase that symbolizes where things are heading was "No terminal". Claude's benefits won't stay confined to engineers — they'll extend into non-engineering domains as well. That possibility came through clearly.
而象征未来方向的短语是 “无终端”。Claude 的好处不会只局限于工程师——它将扩展到 非工程领域。这种可能性清晰地展现了出来。
The evolution of Claude in a single video / 一个视频看尽 Claude 的进化
For the evolution of Claude itself, the session played this YouTube video: 🎥 https://www.youtube.com/watch?v=PnX30ZXxKco
关于 Claude 自身的进化，会议播放了这个 YouTube 视频： 🎥 https://www.youtube.com/watch?v=PnX30ZXxKco
The video gives the same task — "clone claude.ai" — to each generation of Claude models and compares the results. The progress of Claude across generations was packed into a short clip, and you could clearly see the quality of the output rising with each version.
这个视频给 每一代 Claude 模型相同的任务——“克隆 claude.ai”——并比较结果。Claude 跨代的进步被浓缩在短短的视频中，你可以清楚地看到输出质量随着每个版本而提升。
"The Intelligence Explosion" (AI's growth curve) / “智能爆炸”（AI 的增长曲线）
Next came the "The Intelligence Explosion" section.
接下来是 “智能爆炸” 部分。
Under the heading "The artificial intelligence exponential", the session walked through AI's growth using emblematic LLM products from various companies across each year.
在 “人工智能指数” 标题下，会议用每年来自不同公司的代表性 LLM 产品展示了 AI 的增长。
When it comes to interpreting AI's growth curve, on one hand there's the view of: The Pure Exponential, while on the other hand, there are skeptical views that frame it as: The Sigmoid (an S-curve) and The Hard Ceiling.
在解读 AI 的增长曲线时，一方面有 纯指数增长 的观点，另一方面也有怀疑论者将其描述为 S 型曲线 和 硬天花板。
Which curve AI will actually trace from here is genuinely thought-provoking.
AI 实际上将沿着哪条曲线发展，这确实发人深省。
"The Dawn of Agents" (What is an AgentIn AI, a system that perceives its environment and takes actions to achieve specific goals, often used in conversational contexts.?) / “智能体的黎明”（什么是智能体？）
The following "The Dawn of Agents" section finally dove into the discussion of Agents.
接下来的 “智能体的黎明” 部分终于深入探讨了智能体。
The definition of AgentIn AI, a system that perceives its environment and takes actions to achieve specific goals, often used in conversational contexts. introduced here was particularly memorable for me:
这里介绍的智能体的定义让我尤其印象深刻：
An AgentIn AI, a system that perceives its environment and takes actions to achieve specific goals, often used in conversational contexts. is a Large Language Model that uses tools in a loop to pursue a goal
智能体是一个使用工具在循环中追求目标的大型语言模型
Simple, but it captures the essence of an AgentIn AI, a system that perceives its environment and takes actions to achieve specific goals, often used in conversational contexts. neatly — a phrasing I find genuinely useful as a mental anchor.
简单，但清晰地抓住了智能体的本质——这种表述我觉得非常有用来作为思维锚点。
"The Solutions Machine一种AI驱动的解决方案生成框架，输入问题和资本，通过迭代工作和测试产生自我改进的解决方案。" (AgentIn AI, a system that perceives its environment and takes actions to achieve specific goals, often used in conversational contexts.-driven problem solving in practice) / “解决方案机器”（智能体驱动的实际问题解决）
The next section, "The Solutions Machine一种AI驱动的解决方案生成框架，输入问题和资本，通过迭代工作和测试产生自我改进的解决方案。", presented concrete real-world examples of Agents in action.
接下来是 “解决方案机器” 部分，展示了智能体在实际中的具体例子。
Example 1: Building a C compiler with multiple Agents in parallel / 示例 1：使用多个智能体并行构建 C 编译器
A case study in which multiple Agents are run in parallel to build a C compiler. You can read the details here: 🔗 https://www.anthropic.com/engineering/building-c-compiler
一个并行运行多个智能体构建 C 编译器的案例。详情可在此阅读： 🔗 https://www.anthropic.com/engineering/building-c-compiler
Example 2: Phased development by 3 role-specialized AI Agents / 示例 2：由三个角色专用 AI 智能体进行分阶段开发
A case where three role-specialized AI Agents collaborated to develop software in phases. The full write-up is here: 🔗 https://www.anthropic.com/engineering/harness-design-long-running-apps
三个角色专用 AI 智能体合作分阶段开发软件的案例。完整文章在此： 🔗 https://www.anthropic.com/engineering/harness-design-long-running-apps
The mental model behind the Solutions Machine一种AI驱动的解决方案生成框架，输入问题和资本，通过迭代工作和测试产生自我改进的解决方案。 / 解决方案机器背后的思维模型
What I found especially compelling was the mental model used to describe the Solutions Machine一种AI驱动的解决方案生成框架，输入问题和资本，通过迭代工作和测试产生自我改进的解决方案。:
我发现特别有吸引力的是用来描述解决方案机器的思维模型：
Feed in Problems and Capital, then iterate Work and Test to produce a Self-improving solution
输入 问题 和 资本，然后迭代 工作 和 测试，产生一个 自我改进的解决方案
Just throw in problems and capital, and Agents will autonomously experiment and refine the solution — that future image came into much sharper focus.
只需投入问题和资本，智能体就会自主实验并完善解决方案——那个未来图景变得清晰了许多。
"The Great InversionAI时代价值中心的翻转：从实施和维护成本高转变为问题定义和解决成本高。" (the center of value flips) / “大反转”（价值中心翻转）
Next is the "The Great InversionAI时代价值中心的翻转：从实施和维护成本高转变为问题定义和解决成本高。" section.
接下来是 “大反转” 部分。
In the traditional approach to problem-solving:
- "Identify, define, and scope the problem; Decide to solve it" was relatively cheap, while
- "Implement, validate, deploy, and maintain the solution" carried the heavy cost.
在传统的解决问题方式中：
- “识别、定义和确定问题范围；决定解决它” 相对便宜，
- 而 “实现、验证、部署和维护解决方案” 承担了高昂的成本。
But in the new pyramid at 10x Scale, this cost structure is being inverted.
但在 10 倍规模 的新金字塔中，这种 成本结构正在被反转。
As someone who works at a company traditionally rooted in SI (Systems Integration), this was a slightly uncomfortable message to sit with. The weight of implementation, deployment, and operations is shrinking, while the importance of deciding "what to solve" is growing — and we, too, will need to evolve in response to this shift.
作为一名在传统上扎根于系统集成（SI）的公司工作的人，这个信息让我略感不安。实施、部署和运维 的权重正在缩小，而 决定“解决什么” 的重要性正在增长——我们也需要顺应这一变化而进化。
"The Three DoorsAnthropic提出的三个AI应用方向：赋能员工、加速软件开发、创造收入。" (Three compounding opportunities ahead) / “三道门”（未来的三重复利机会）
In the latter half of the session, "The Three DoorsAnthropic提出的三个AI应用方向：赋能员工、加速软件开发、创造收入。" introduced "Three compounding opportunities" — three directions for putting AI to use going forward:
在会议的后半部分，“三道门” 介绍了 “三重复利机会”——未来使用 AI 的三个方向：
- Empower every employee
- Supercharge software development
- Create revenue streams
- 赋能每一位员工
- 加速软件开发
- 创造收入流
What stood out was that the framing goes beyond engineering efficiency to include empowering every employee across the organization and creating new sources of business value. I'll definitely want to refer back to this framework when thinking about future AI strategy.
突出的一点是，这个框架超越了工程效率，涵盖了 赋能组织内的每一位员工 和 创造新的业务价值来源。在思考未来 AI 策略时，我肯定会参考这个框架。
All in all, it was a dense, learning-packed session.
总的来说，这是一场内容密集、充满学习收获的会议。
Bonus: "Introducing Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。" at the Anthropic EXPO Booth / 附加内容：Anthropic 展区的 “Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 介绍”
Now back to the EXPO for a moment. Anthropic also had a booth at the EXPO, where a number of in-booth sessions were running throughout the event. I attended one of them, so let me briefly share that as well.
现在回到展区一下。Anthropic 在展区也有一个展位，整个活动期间，展位内举办了许多小型会议。我参加了一场，所以也简单分享一下。
The session I joined was titled "Introducing Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。". The content covered an explanation of how Claude Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 works along with a live demo of producing Word, Excel, and PowerPoint deliverables with Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。. Watching documents come together right in front of me was genuinely exciting — a demo that perfectly embodied the "2026 is the year of Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。" message from earlier in the day.
我参加的那场会议标题是 “Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 介绍”。内容解释了 Claude Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 的工作原理，并进行了 使用 Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 生成 Word、Excel 和 PowerPoint 交付物的现场演示。亲眼看着文档在眼前生成，真的令人兴奋——这场演示完美体现了当天早些时候“2026 年是 Cowork计算机操作助手，编程智能体的图形界面版本，通过自然语言指挥AI生成底层代码并执行，自动操作本地计算机完成任务。 之年”的信息。
The Anthropic booth ran several other sessions as well, with crowds large enough that people were standing in the back. The level of attention Anthropic was getting from attendees was tangible.
Anthropic 展区还举办了几场其他会议，人群拥挤到有人站在后面。Anthropic 从参会者那里获得的关注度是实实在在的。
Wrap-Up / 总结
The Anthropic session I covered today was packed with content:
今天介绍的 Anthropic 会议内容丰富：
- The dramatic changes coming in the next 2 years
- The essence of Agents and the "Solutions Machine一种AI驱动的解决方案生成框架，输入问题和资本，通过迭代工作和测试产生自我改进的解决方案。" concept
- "The Great InversionAI时代价值中心的翻转：从实施和维护成本高转变为问题定义和解决成本高。" of where value sits
- Concrete opportunities through "The Three DoorsAnthropic提出的三个AI应用方向：赋能员工、加速软件开发、创造收入。"
- 未来两年出现的巨大变化
- 智能体的本质和“解决方案机器”概念
- 价值所在位置的“大反转”
- 通过“三道门”带来的具体机会
It was a learning-packed session that nudged me to reconsider what "after software" might look like — and how my own work might need to adapt.
这是一场充满学习的会议，促使我重新思考“软件之后”可能会是什么样子——以及我自己的工作可能需要如何适应。
The session video is publicly available, so if any of this caught your interest, definitely give it a watch. To be continued in #4.
会议视频是公开的，所以如果其中任何内容引起了你的兴趣，一定要去看看。敬请期待 第四部分。
常见问题（FAQ）
Anthropic在编码市场的份额是多少？
2025年Anthropic占据编码市场54%份额，表明其深受开发者支持。
AI工作模式从2023到2026如何演变？
2023聊天，2025编码，2026协作，象征"无终端"，扩展至非工程领域。
什么是AI代理？
AI代理是能自主定义、构建和迭代的智能体，推动从自上而下规划到自下而上执行的转变。
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