<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Agent on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/ai-agent/</link><description>Recent content in AI Agent on 黄文卓 | DevOps Engineer</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>17691281867@163.com (Wenzhuo Huang)</managingEditor><webMaster>17691281867@163.com (Wenzhuo Huang)</webMaster><copyright>© 2026 Wenzhuo Huang</copyright><lastBuildDate>Fri, 27 Feb 2026 09:52:00 +0800</lastBuildDate><atom:link href="https://socake.github.io/tags/ai-agent/index.xml" rel="self" type="application/rss+xml"/><item><title>MCP 协议实战：给 AI Agent 接上运维工具</title><link>https://socake.github.io/posts/mcp-protocol-devops/</link><pubDate>Fri, 27 Feb 2026 09:52:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/mcp-protocol-devops/</guid><description>Model Context Protocol 让 AI 能够标准化地调用外部工具。本文用 Python 实现一个运维 MCP Server，接入 kubectl、Prometheus、Loki，让 AI 直接查集群状态。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/mcp-protocol-devops/featured.jpg"/></item><item><title>LangGraph 工作流编排：构建有状态的 AI 应用</title><link>https://socake.github.io/posts/langgraph-workflow-orchestration/</link><pubDate>Sun, 15 Feb 2026 12:44:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/langgraph-workflow-orchestration/</guid><description>从LangChain Chain的局限出发，讲清楚LangGraph的状态机模型、Graph/Node/Edge的设计方式，以及条件分支、循环、人工介入、Checkpoint持久化的工程实现，最后用一个运维诊断工作流串起来所有概念。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/langgraph-workflow-orchestration/featured.jpg"/></item><item><title>AI Agent 设计模式：从单步到复杂工作流</title><link>https://socake.github.io/posts/ai-agent-design-patterns/</link><pubDate>Thu, 29 Jan 2026 09:17:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/ai-agent-design-patterns/</guid><description>Agent不是更智能的ChatGPT调用，它是一个能自主规划和执行多步骤任务的循环系统。本文拆解ReAct推理循环、Tool调用设计原则、Multi-Agent协作模式、Human-in-the-loop设计，以及告警分析Agent和巡检Agent的实战实现。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/ai-agent-design-patterns/featured.jpg"/></item></channel></rss>