Agentforce的大脑内部：揭示Atlas推理引擎

In our “Engineering Energizers” Q&A series, we explore the paths of engineering leaders pushing the boundaries of innovation. Today, we spotlight Phil Mui, Senior Vice President and Head of Products and Architecture for Salesforce AI Research. Phil’s team is instrumental in powering Agentforce, the agentic layer of the Salesforce platform for deploying autonomous AI agents across any business function. Agentforce includes a set of tools to create and customize agents as well as a suite of out-of-the-box agents.

在我们的“Engineering Energizers”问答系列中，我们探索了推动创新边界的工程领导者的路径。今天，我们聚焦于 Salesforce AI Research 的高级副总裁兼产品和架构负责人 Phil Mui。Phil 的团队在推动 Agentforce 方面发挥了重要作用，Agentforce 是 Salesforce 平台的代理层，用于在任何业务功能中部署自主 AI 代理。Agentforce 包括一套创建和定制代理的工具以及一套开箱即用的代理。

Central to Agentforce’s architecture is the Atlas Reasoning Engine. This next-gen autonomous AI system enables agents to understand human intent and take action on the Salesforce platform. Acting as Agentforce’s brain, the Atlas Reasoning Engine employs reinforcement learning and feedback loops to provide accurate, context-sensitive responses. Agentforce helps customers enhance customer service and enterprise workflows by incorporating agentic reasoning.

Agentforce架构的核心是Atlas Reasoning Engine。这一下一代自主AI系统使代理能够理解人类意图并在Salesforce平台上采取行动。作为Agentforce的大脑，Atlas Reasoning Engine采用强化学习和反馈循环，提供准确、上下文敏感的响应。Agentforce通过整合代理推理帮助客户提升客户服务和企业工作流程。

Discover how Phil’s team tackled the challenges of scaling AI agents, implementing modular updates without disrupting functionality, and ensuring high standards of security. These efforts have enabled Agentforce to deliver powerful, reliable solutions across a diverse range of use cases.

了解Phil的团队如何应对扩展AI代理的挑战，实施模块化更新而不破坏功能，并确保高标准的安全性。这些努力使Agentforce能够在各种用例中提供强大、可靠的解决方案。

Incubated within Salesforce AI Research, the Atlas Reasoning Engine is set to revolutionize enterprise workflows through advanced, deliberative, autonomous agents that utilize “System 2” inference time reasoning. These agents assist Salesforce clients by deeply understanding user...