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    <title>ClawSphere 企业 AI 研究院</title>
    <link>https://clawsphere.io/research/</link>
    <description>数字员工、AI Agent、基座模型与企业 AI 研究。</description>
    <language>zh-CN</language>
    <lastBuildDate>Sun, 09 Aug 2026 13:20:15 GMT</lastBuildDate>
    <item>
      <title>企业 Agent 如何防提示注入？OpenAI 与 Anthropic 给出的共同警告</title>
      <link>https://clawsphere.io/research/agent-prompt-injection-security/</link>
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      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>从网页、邮件、文档和 MCP 工具返回值解释提示注入与数据外泄风险，并给出内容隔离、最小权限、审批和审计的纵深防御方案。</description>
      <category>治理合规</category>
    </item>
    <item>
      <title>Anthropic Agent 研究趋势 2026：自治、专业知识与可信治理</title>
      <link>https://clawsphere.io/research/anthropic-agent-research-trends-2026/</link>
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      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>基于 Anthropic 对 Claude Code 真实使用数据的研究，分析 Agent 自治时长、领域专家价值、监督方式、提示注入和企业治理趋势。</description>
      <category>Agent 研究</category>
    </item>
    <item>
      <title>Coding Agent 真能提升企业生产力吗？解读 OpenAI 与 Anthropic 的最新证据</title>
      <link>https://clawsphere.io/research/coding-agents-enterprise-productivity-evidence/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/coding-agents-enterprise-productivity-evidence/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>综合 OpenAI Codex 使用研究与 Anthropic Claude Code 会话研究，解释哪些生产力信号可信、哪些不能外推，以及企业如何设计自己的对照实验。</description>
      <category>企业实践</category>
    </item>
    <item>
      <title>企业 Agent Runtime 选型：SDK、框架、运行时与 Agent Builder 怎么分</title>
      <link>https://clawsphere.io/research/enterprise-agent-runtime-selection/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/enterprise-agent-runtime-selection/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>从 Agent SDK、编排框架、托管 Runtime 和低代码 Agent Builder 四层拆解企业技术栈，并给出权限、状态、观测、评测与迁移清单。</description>
      <category>Agent 研究</category>
    </item>
    <item>
      <title>NVIDIA、AMD 与国产 AI 算卡：企业采购到底该比较什么</title>
      <link>https://clawsphere.io/research/enterprise-ai-accelerator-selection/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/enterprise-ai-accelerator-selection/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>从芯片、软件栈、模型适配、集群、功耗、供应与迁移成本比较 NVIDIA、AMD、昇腾、寒武纪、昆仑芯、壁仞和摩尔线程。</description>
      <category>企业实践</category>
    </item>
    <item>
      <title>企业智能办公 Agent 全景：M365、WPS、Dumate、钉钉与飞书如何选</title>
      <link>https://clawsphere.io/research/enterprise-ai-workplace-landscape/</link>
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      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>比较 Microsoft 365 Copilot、WPS Comate、百度办公搭子 Dumate、钉钉 AI 助理与飞书 Aily，解释办公入口、知识、权限和数字员工的选型逻辑。</description>
      <category>行业趋势</category>
    </item>
    <item>
      <title>2026 基座模型生态地图：企业为什么需要多模型路由</title>
      <link>https://clawsphere.io/research/foundation-model-ecosystem-map-2026/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/foundation-model-ecosystem-map-2026/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>梳理 GPT、Claude、Gemini、Qwen、DeepSeek、ERNIE、混元、豆包、Kimi、MiniMax、GLM、Mistral 与 Grok，并给出企业多模型路由方法。</description>
      <category>模型观察</category>
    </item>
    <item>
      <title>Agent 越来越自治，人应该怎么管？从逐步审批到持续监督</title>
      <link>https://clawsphere.io/research/human-oversight-for-autonomous-agents/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/human-oversight-for-autonomous-agents/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>结合 Anthropic 的真实自治研究与 OpenAI 的 Codex 控制实践，给出企业设计可见、可干预、风险分级和可追责监督机制的方法。</description>
      <category>企业实践</category>
    </item>
    <item>
      <title>长时 Agent 怎么评测？从聊天正确率升级到环境任务成功率</title>
      <link>https://clawsphere.io/research/long-running-agent-evaluation/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/long-running-agent-evaluation/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>解释为什么长时 Agent 不能只用问答基准评测，并给出环境、工具、轨迹、人工干预、外部状态和成本组成的企业评测方法。</description>
      <category>Agent 研究</category>
    </item>
    <item>
      <title>MCP 进入企业之后怎么管？连接器、身份、权限与供应链清单</title>
      <link>https://clawsphere.io/research/mcp-enterprise-governance/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/mcp-enterprise-governance/</guid>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>MCP 降低了 Agent 连接工具的成本，也扩大了权限和供应链风险。本文给出企业 MCP 注册、身份、审批、版本和审计治理框架。</description>
      <category>治理合规</category>
    </item>
    <item>
      <title>OpenAI Agent 研究趋势 2026：从 Codex 到长时数字工作</title>
      <link>https://clawsphere.io/research/openai-agent-research-trends-2026/</link>
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      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>梳理 OpenAI 2026 年 Agent 研究主线：长时任务、并行 Agent、技能与自动化、环境评测、安全边界，以及从编程向企业知识工作的扩展。</description>
      <category>Agent 研究</category>
    </item>
    <item>
      <title>OpenAI 与 Anthropic 的 Agent 路线有什么不同？企业应该看懂的六个信号</title>
      <link>https://clawsphere.io/research/openai-vs-anthropic-enterprise-agent-strategy/</link>
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      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <description>从产品载体、长时任务、真实使用研究、安全治理、企业控制和开放协议六个维度比较 OpenAI 与 Anthropic 的 Agent 战略。</description>
      <category>行业趋势</category>
    </item>
    <item>
      <title>什么是数字员工？定义、能力边界与企业落地指南</title>
      <link>https://clawsphere.io/research/what-is-digital-employee/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/what-is-digital-employee/</guid>
      <pubDate>Sat, 01 Aug 2026 00:00:00 GMT</pubDate>
      <description>系统解释数字员工与 RPA、AI 助手、AI Agent 的区别，以及企业从岗位选择、权限配置到效果评估的落地路径。</description>
      <category>入门指南</category>
    </item>
    <item>
      <title>AI Agent 与数字员工有什么区别？企业选型的 7 个判断维度</title>
      <link>https://clawsphere.io/research/ai-agent-vs-digital-employee/</link>
      <guid isPermaLink="true">https://clawsphere.io/research/ai-agent-vs-digital-employee/</guid>
      <pubDate>Sat, 25 Jul 2026 00:00:00 GMT</pubDate>
      <description>从目标、权限、工作流、记忆、评测、治理和商业结果七个维度比较 AI Agent 与数字员工，帮助企业避免概念混用。</description>
      <category>Agent 研究</category>
    </item>
    <item>
      <title>企业 AI 如何计算 ROI？一套从工时到业务结果的评估框架</title>
      <link>https://clawsphere.io/research/enterprise-ai-roi-framework/</link>
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      <pubDate>Sat, 18 Jul 2026 00:00:00 GMT</pubDate>
      <description>企业 AI 项目不能只看调用量。本文给出效率、质量、收入、风险和采用率五层指标，以及可执行的 ROI 计算方法。</description>
      <category>企业实践</category>
    </item>
    <item>
      <title>企业如何选择基座模型：能力、成本、安全与可替换性清单</title>
      <link>https://clawsphere.io/research/foundation-model-selection/</link>
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      <pubDate>Sat, 11 Jul 2026 00:00:00 GMT</pubDate>
      <description>一份面向企业决策者的基座模型选型清单，覆盖任务评测、上下文、工具调用、部署、数据政策、成本和供应商锁定。</description>
      <category>模型观察</category>
    </item>
    <item>
      <title>什么是 AI Native 企业？从个人提效到组织重构的四阶段路线图</title>
      <link>https://clawsphere.io/research/ai-native-enterprise-roadmap/</link>
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      <pubDate>Sat, 04 Jul 2026 00:00:00 GMT</pubDate>
      <description>AI Native 企业不是全员使用聊天工具，而是让数据、流程、角色和决策机制从设计之初就支持人机协作。</description>
      <category>行业趋势</category>
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