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      <description>AI Agent 工程化实践复盘：架构设计、容错与可靠性、上下文工程与成本治理。</description>
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  <item>
    <guid>https://joker1point.github.io/techlog/blog/agent-architecture-evolution-skill-restatement</guid>
    <title>我的 Agent 架构演进：Skill 压平 Sub Agent，Restatement 又把它拉了回来</title>
    <link>https://joker1point.github.io/techlog/blog/agent-architecture-evolution-skill-restatement</link>
    <description>从初代「主 Agent 编排 + 子 Agent 分工」三层架构，到用 Skill 替代冗余 Sub Agent 压平架构降低 Token，再到长任务中撞上步骤合并跳过、规则失效、输出同质化，最终靠 Restatement 机制与 Sub Agent 回归分头解决——一条完整的踩坑迭代链。</description>
    <pubDate>Tue, 15 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>agent</category><category>ai</category><category>architecture</category><category>context-engineering</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/agent-fault-tolerance-design</guid>
    <title>Agent 健壮性设计：工具调用与模型调用失败的容错与兜底</title>
    <link>https://joker1point.github.io/techlog/blog/agent-fault-tolerance-design</link>
    <description>错误分类（确定性 vs 瞬时）→ 确定性错误回传模型自我修复、瞬时错误指数退避+随机抖动重试 → 多次失败熔断 → 按能力等级优雅降级（备用工具 / 业务降级 / 转人工）。模型侧另需识别「API 返回成功但业务结果错误」的潜在失败，并在切换备用模型后持续评估。</description>
    <pubDate>Tue, 15 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>agent</category><category>ai</category><category>reliability</category><category>system-design</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/agent-prompt-injection-defense</guid>
    <title>Agent 怎么防止 Prompt 注入：四层纵深防御体系</title>
    <link>https://joker1point.github.io/techlog/blog/agent-prompt-injection-defense</link>
    <description>单靠 Prompt 加限制词防不住注入，正确做法是搭建「输入侧 → 模型侧 → 执行侧 → 输出侧」四层纵深防御体系，其中执行侧权限管控是最硬的底线。</description>
    <pubDate>Sun, 06 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>agent</category><category>security</category><category>prompt-injection</category><category>llm</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/agent-washing-why-no-value</guid>
    <title>Agent Washing：为什么大批企业升级 Agent 不会产生增值</title>
    <link>https://joker1point.github.io/techlog/blog/agent-washing-why-no-value</link>
    <description>Agent 有明确适用边界——擅长非结构化输入、路径不固定、需动态推理的任务。把确定流程强行套上自主智能是技术错配；中小企业缺数据/SOP/权限/复合人才配套地基；管理层&quot;替换人&quot;的预期错位（实际只能替换重复与信息整理类子集工作）。</description>
    <pubDate>Tue, 15 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>agent</category><category>ai</category><category>product</category><category>industry</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/agent-window-period</guid>
    <title>对Agent产品窗口期的看法</title>
    <link>https://joker1point.github.io/techlog/blog/agent-window-period</link>
    <description>Agent的窗口期会非常短——因为Agent本身就在提高开发Agent应用的效率，市场需求将迅速饱和。以月之暗面Alnative桌面级本地Agent为例，超5万行代码中92%由AI自主生成，工程师仅耗时一周完成架构优化与交互调校。</description>
    <pubDate>Sat, 06 Jun 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>agent</category><category>startup</category><category>product</category><category>opinion</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/anthropic-ai-native-startup</guid>
    <title>Anthropic官方手册：打造AI原生创业公司的核心要点</title>
    <link>https://joker1point.github.io/techlog/blog/anthropic-ai-native-startup</link>
    <description>解读Anthropic官方手册，系统阐述如何从第一天起将AI深度融入验证、构建、运营与积累等各环节，打造真正的AI原生创业公司。</description>
    <pubDate>Sat, 06 Jun 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>startup</category><category>anthropic</category><category>product</category><category>engineering</category><category>opinion</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/focus-on-firstline-practice</guid>
    <title>在 AI 时代，聚焦一线从业</title>
    <link>https://joker1point.github.io/techlog/blog/focus-on-firstline-practice</link>
    <description>在 AI 时代，信息数量的增量远大于信息质量的增量。永远聚焦一线从业，坚持实操上手，最小 MVP，避免无效输入。</description>
    <pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>opinion</category><category>engineering</category><category>mindset</category>
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  <item>
    <guid>https://joker1point.github.io/techlog/blog/github-trending-2026-09</guid>
    <title>2026 年 9 月 GitHub 热门项目分析：追踪大模型应用领域技术动态</title>
    <link>https://joker1point.github.io/techlog/blog/github-trending-2026-09</link>
    <description>2026 年 9 月 GitHub 月榜 Top 10 逐项拆解——从 archify（把 AI 生成的架构图变成可验证制品）到 OpenViking（Agent 上下文数据库），并归纳出 Agent 输出制品化、上下文工程、Rust 工具化、AI 与教育/桌面交叉四条趋势。</description>
    <pubDate>Thu, 17 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>github</category><category>open-source</category><category>ai</category><category>agent</category><category>trending</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/ide-agent-vs-ai-assistant</guid>
    <title>IDE Agent 开发体验：为什么直接操作代码比通用 AI 助手更靠谱</title>
    <link>https://joker1point.github.io/techlog/blog/ide-agent-vs-ai-assistant</link>
    <description>对比 IDE 内置 Agent 与通用 AI 编程助手在代码开发场景中的体验差异，探讨代码硬约束、模型幻觉抑制、精准代码定位等关键优势。</description>
    <pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>ide</category><category>agent</category><category>devtools</category><category>opinion</category><category>developer-experience</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/rag-pipeline-architecture</guid>
    <title>RAG 链路全解析：从文档入库到混合记忆的实战架构</title>
    <link>https://joker1point.github.io/techlog/blog/rag-pipeline-architecture</link>
    <description>详述 RAG（检索增强生成）的完整技术链路，包括文档入库、向量化、召回重排、Prompt 拼接，以及基于 Node.js + ChromaDB + SQLite 的三层混合记忆进阶方案。</description>
    <pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>rag</category><category>ai</category><category>llm</category><category>embedding</category><category>chromadb</category><category>nodejs</category><category>architecture</category><category>engineering</category><category>vdb-news</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/rag-vs-agent-retrieval-decision-framework</guid>
    <title>RAG 还必要吗：从 130 条技术评论里提炼出的选型决策框架</title>
    <link>https://joker1point.github.io/techlog/blog/rag-vs-agent-retrieval-decision-framework</link>
    <description>围绕「向量 RAG vs LLM Wiki + grep / Agent 自主检索」的四派立场梳理（谨慎派、混合派、场景决定论派、演进视角派）、四个辩论冲突点，以及一组可直接落地的决策框架：按更新频率、查询频率、数据规模、领域特性决定上不上 RAG。</description>
    <pubDate>Tue, 15 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>rag</category><category>agent</category><category>ai</category><category>research</category><category>vdb-news</category>
  </item>

  <item>
    <guid>https://joker1point.github.io/techlog/blog/workflow-vs-agent-7-dimensions</guid>
    <title>Workflow vs Agent：用 7 维度框架定位你的项目</title>
    <link>https://joker1point.github.io/techlog/blog/workflow-vs-agent-7-dimensions</link>
    <description>以 MoneyPrinterTurbo 为例，用 7 个 agent 架构维度审视一个固定管线项目：它几乎一个都不占，但这不是缺陷，而是项目性质使然。能说清&quot;为什么这里不需要 agent&quot;，比硬说&quot;这里有 agent&quot;更显研究深度。</description>
    <pubDate>Sun, 06 Sep 2026 00:00:00 GMT</pubDate>
    <author>birenwenmou@qq.com (眠月)</author>
    <category>ai</category><category>agent</category><category>workflow</category><category>architecture</category><category>llm</category>
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