内容来源：https://aibusiness.com/agentic-ai/google-intros-new-agent-builder-tools

内容总结：

谷歌云近日对其Vertex AI Agent Builder平台进行重要升级，为企业用户提供了更完善的智能体构建与管理解决方案。此次更新聚焦三大核心能力：通过Agent开发工具包提升构建效率，借助托管式Vertex AI智能体引擎实现规模化部署，并新增原生身份认证与安全防护等治理功能。

行业观察指出，谷歌正通过持续投入开发者工具生态，巩固其在人工智能领域的竞争优势。市场研究机构Futurum Group分析师布拉德利·希明表示，Vertex AI平台已从分散的工具集合演进为"具有高度可见性的工具链"，这对吸引开发者社区具有关键意义。

值得关注的是，平台新增的"自我修复"功能可使智能体在工具调用失败时自动重试，同时扩展了对Python和Java等编程语言的支持。配套的观测工具集还能帮助开发者实时监控智能体表现，快速定位生产环境中的问题。

Omdia分析师托尔斯滕·福克认为，谷歌正通过提供涵盖自动化与编排能力的综合开发体验，解决企业在模型可观测性、权限管理等实际应用中的痛点。这种对开发者体验的深度投入，与谷歌云在基础设施层面获得企业认可的战略目标形成协同。

与此同时，移动端生态迎来新进展。谷歌宣布其AI模式搜索服务将登陆iOS和Android设备的Chrome浏览器。另据彭博社报道，苹果公司拟每年支付约10亿美元，计划采用谷歌的Gemini大模型升级Siri语音助手系统，这预示着两大科技巨头在人工智能领域可能开启新的合作范式。

中文翻译：

由谷歌云赞助
选择您的首批生成式AI应用场景
要开始使用生成式AI，首先应关注能够优化人类信息交互体验的领域。

本次更新彰显了这家科技巨头对开发者工具领域的投入，以及其应对企业级挑战的决心。
谷歌云于周三宣布对其Vertex AI Agent Builder进行功能升级，为企业构建、扩展和管理AI智能体提供了更多途径。
谷歌表示，通过其智能AI平台的更新，开发者现可运用智能体开发工具包API——一款用于创建和部署AI智能体的工具——来更高效地构建智能体。他们还能使用全新的托管式Vertex AI智能体引擎在生产环境中扩展智能体规模，同时通过原生智能体身份识别与安全防护等新功能实现对智能体的管控。
此外，谷歌宣布其AI模式搜索服务将登陆iOS和安卓设备的Chrome浏览器。
同样在周三，彭博社援引匿名消息源报道，苹果公司计划每年向谷歌支付约10亿美元，以使用谷歌的Gemini 1.2万亿参数基础模型来全面升级其Siri语音助手系统。

分析师指出，作为承载智能体构建工具的宏观平台，Vertex AI的此次更新表明谷歌意图持续主导网络接口市场，并在AI软件领域参与顶级竞争。
Gemini模型家族现已与ChatGPT开发商OpenAI及其竞争对手Anthropic的领先生成式AI系统展开正面交锋。
"Gemini已迅速跻身美国前沿模型制造商的第一梯队，"分析师布拉德利·希明表示。
为保持在AI供应商中的领先地位，谷歌持续投资AI开发者工具。
"谷歌认识到要想成功就必须构建开发者生态系统，"希明指出，"过去Vertex AI下分散的工具集合......正在转型为备受瞩目的工具套装，这条工具链正在开发者生态中获得强劲吸引力。"
谷歌正通过发布这些新功能持续扩展该工具套装。

例如，全新构建能力支持开发者运用谷歌自适应插件框架或预置插件（包括新增的工具使用插件）来构建功能更强的智能体。该自愈功能使智能体能够识别工具调用失败并自动重试。构建能力还涵盖更多语言支持，开发者现可用Python和Java构建智能体开发工具包代理。另一项新功能是观测工具集，支持用户追踪智能体表现、发现并修复生产问题，以及与已部署智能体进行交互。
开发者现可通过评估层模拟智能体性能。在扩展规模后，开发者还能使用新工具管理智能体。例如，智能体身份识别功能支持用户为智能体分配专属身份，通过强制执行权限访问、建立策略与资源边界来满足合规治理要求。

分析师托尔斯滕·福尔克表示，谷歌正通过这些工具解决企业应用AI时遇到的某些难题。
"通常都是些细节问题，例如确保生产模型的可观测性、简化的身份与访问管理，以及能够轻松可靠地串联生产环境工具——最好能覆盖整个组织架构。"
他指出谷歌在提供涵盖自动化与编排能力的综合开发者体验方面，比某些竞争对手走得更远。这点至关重要，因为许多开发者刚开始构建智能体工具与应用，尚不熟悉自愈机制或稳健的智能体工作流等要素。
"让开发者成功创建生产应用程序，与说服运维人员认可谷歌基础设施承载企业工作负载的可行性同等重要。"

希明强调，谷歌为开发者提供工具并将其整合至平台的做法具有战略意义。
"该平台对企业开发者至关重要，"他补充道，这也解释了亚马逊Bedrock生成式AI平台的成功之道，"在企业支出体系中，投资往往始于个体实践者——无论是数据专家、数据科学专家还是普通软件开发人员。"

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英文来源：

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The update demonstrates the tech giant's investment in developer tooling and its efforts to address enterprise challenges.
Google Cloud introduced updates to its Vertex AI Agent Builder on Wednesday, providing enterprises with more ways to build, scale and govern AI agents.
With the updates to its agentic AI platform, Google said developers can use the Agent Development Kit API -- a tool that enables developers to create and deploy AI agents -- to build agents more efficiently. They can also use the new managed Vertex AI Agent Engine to scale their agent in production, while governing the agents with new features like native agent identities and security safeguards.
In addition, Google said its AI Mode search service will now be available on the Chrome browser for iOS and Android devices.
Also on Wednesday, Bloomberg reported, based on anonymous sources, that Apple plans to pay Google about $1 billion a year to use Google's Gemini 1.2 trillion-parameter foundation model to overhaul its Siri AI assistant system.
The updates to Vertex AI, the larger platform that houses the agent builder tools, demonstrate Google's intent to continue dominating the web interface market and also compete at the top level in AI software, said Bradley Shimmin, an analyst at the Futurum Group.
The Gemini model family now competes head-to-head with leading generative AI systems from ChatGPT maker OpenAI and its rival, Anthropic, Shimmin said.
"Gemini has very quickly rocketed to the top of the U.S.-based frontier model makers," Shimmin said.
To remain in the top group of AI vendors, Google has been investing in AI developer tools.
"Google recognizes that they need to build a developer ecosystem if they're going to succeed," Shimmin said. "What was sort of a disparate collection of tools sitting under Vertex AI ... is turning into what I would say is a very highly visible tool set that makes up that tool chain that is gaining a lot of traction with the developer ecosystem."
Google is expanding that tool set with the release of these new features.
For example, the Build capability enables developers to build more capable agents using Google's adaptable plugins framework or a prebuilt plugin, including a new one for tool use that helps agents "self-heal," Google said. The self-heal feature enables an agent to recognize when a tool call has failed and attempt it again. The build capabilities also include more language support, enabling developers to build agent development kit (ADK) agents alongside Python and Java. Another new feature is a set of observability tools that let users track how agents perform, find and fix production problems and interact with the deployed agents.
Developers can now simulate agent performance using an evaluation layer. After scaling, developers have new tools to govern the agents. For example, agent identities enable users to assign their own identities to agents. Users can enforce agent privilege access and establish policies and resource boundaries to meet compliance and governance requirements.
With the tools, Google is addressing some of the problems enterprises are experiencing with AI, said Torsten Volk, an analyst at Omdia, a division of Informa TechTarget.
"It's often the small things like ensuring observability for production models, simple identity and access management, and the ability to easily and reliably chain together tools for production use, ideally across the whole organization," Volk said.
He said Google is going deeper than some competitors in offering a comprehensive developer experience that includes both automation and orchestration capabilities. This is important because many developers are just starting to build agentic tools and applications, so they are not familiar with elements such as self-healing or robust agent workflows, Volk said.
"Winning over developers by allowing them to create production applications successfully is just as important as convincing the operations people of the viability of running enterprise workloads on Google infrastructure," he said.
Google is providing tooling for developers and wrapping it up within a platform, which is essential, Shimmin said.
"That platform means a lot to the enterprise developer," he said, adding that this is why AWS has done well with the Amazon Bedrock generative AI platform. "In the enterprise, the way that money gets spent, it often begins with investments by individual practitioners, whether data professionals or data science professionals or just software developers."
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