<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>实践指南 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/categories/%E5%AE%9E%E8%B7%B5%E6%8C%87%E5%8D%97/</link><description>Recent content in 实践指南 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:48:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/categories/%E5%AE%9E%E8%B7%B5%E6%8C%87%E5%8D%97/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Agent的经济学：自动化任务的成本效益分析</title><link>https://guijiagi.com/posts/b1-e194cbf3/</link><pubDate>Thu, 16 Jul 2026 11:48:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-e194cbf3/</guid><description>从经济学角度分析AI Agent自动化任务的成本效益，构建量化决策框架</description></item><item><title>大模型推理部署架构：从单卡到分布式全方案</title><link>https://guijiagi.com/posts/b1-7a487767/</link><pubDate>Thu, 16 Jul 2026 11:46:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-7a487767/</guid><description>系统讲解大模型推理部署的架构选型，从单GPU到多卡分布式到弹性云原生方案</description></item><item><title>AI Agent测试自动化：从单元测试到端到端验证</title><link>https://guijiagi.com/posts/b1-979fd626/</link><pubDate>Thu, 16 Jul 2026 11:43:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-979fd626/</guid><description>构建AI Agent测试体系的方法论，涵盖确定性测试、概率测试和端到端测试的工程实践</description></item><item><title>大模型应用架构模式：从API调用到Agent系统</title><link>https://guijiagi.com/posts/b1-62c464eb/</link><pubDate>Thu, 16 Jul 2026 11:42:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-62c464eb/</guid><description>系统梳理大模型应用的架构模式演进，从简单API调用到复杂Agent系统的设计方法论</description></item><item><title>AI数字人交互设计：从单向播报到双向对话</title><link>https://guijiagi.com/posts/b1-90ce317d/</link><pubDate>Thu, 16 Jul 2026 11:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-90ce317d/</guid><description>探讨AI数字人交互体验的设计方法论，从单向信息播报到实时双向对话的体验升级</description></item><item><title>大模型推理引擎横评：vLLM、SGLang、TensorRT-LLM</title><link>https://guijiagi.com/posts/b1-f50aea03/</link><pubDate>Thu, 16 Jul 2026 11:39:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-f50aea03/</guid><description>对比分析三大主流推理引擎的架构设计、性能特征与适用场景，给出选型建议</description></item><item><title>AI辅助内容创作：从工具到创作伙伴的进化</title><link>https://guijiagi.com/posts/b1-3f2e8f4a/</link><pubDate>Thu, 16 Jul 2026 11:38:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-3f2e8f4a/</guid><description>探讨AI在内容创作领域的应用实践，从写作辅助到自动化内容生产的完整技术方案</description></item><item><title>AI Agent在企业的落地实践：从POC到生产</title><link>https://guijiagi.com/posts/b1-176ee2c2/</link><pubDate>Thu, 16 Jul 2026 11:36:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-176ee2c2/</guid><description>系统讲解企业AI Agent落地的完整路径，从POC验证到生产部署的工程实践指南</description></item><item><title>大模型API经济学：成本优化策略与模型路由</title><link>https://guijiagi.com/posts/b1-a5d617e3/</link><pubDate>Thu, 16 Jul 2026 11:28:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-a5d617e3/</guid><description>分析大模型API调用成本优化方案，涵盖模型路由、缓存策略、批处理与混合部署</description></item><item><title>AI Agent多轮对话管理：状态机到自由对话的平衡术</title><link>https://guijiagi.com/posts/b1-48850354/</link><pubDate>Thu, 16 Jul 2026 11:27:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-48850354/</guid><description>解析AI Agent多轮对话管理的技术方案，从任务导向对话系统到开放域对话的策略设计</description></item><item><title>AI Agent监控与可观测性：构建可信赖的智能体系统</title><link>https://guijiagi.com/posts/b1-51eeb8c1/</link><pubDate>Thu, 16 Jul 2026 11:24:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-51eeb8c1/</guid><description>系统讲解AI Agent运行时监控的完整方案，涵盖调用追踪、性能指标、异常检测与成本分析</description></item><item><title>AI Agent工作流编排：从DAG到自适应流程</title><link>https://guijiagi.com/posts/b1-bc5cc1d9/</link><pubDate>Thu, 16 Jul 2026 11:21:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-bc5cc1d9/</guid><description>系统讲解AI Agent工作流编排的技术方案，从静态DAG到动态自适应流程的演进路径</description></item><item><title>大模型训练数据工程：从数据采集到质量评估</title><link>https://guijiagi.com/posts/b1-f85bfd84/</link><pubDate>Thu, 16 Jul 2026 11:18:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-f85bfd84/</guid><description>系统讲解大模型训练数据全流程工程实践，涵盖数据采集、清洗、去重、质量评估等关键环节</description></item><item><title>Prompt工程的科学方法论：从经验到系统化</title><link>https://guijiagi.com/posts/b1-82eeb3fa/</link><pubDate>Thu, 16 Jul 2026 11:14:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-82eeb3fa/</guid><description>系统化讲解Prompt工程的科学方法，涵盖结构化Prompt设计、Few-Shot策略、思维链推理等核心技巧</description></item><item><title>边缘AI部署实践：让大模型跑在手机和IoT设备上</title><link>https://guijiagi.com/posts/b1-c7296268/</link><pubDate>Thu, 16 Jul 2026 11:13:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-c7296268/</guid><description>边缘AI部署的完整技术方案，涵盖模型压缩、移动端推理引擎、端侧RAG等实践要点</description></item><item><title>数字人技术栈：从外观生成到实时驱动</title><link>https://guijiagi.com/posts/b1-16875a22/</link><pubDate>Thu, 16 Jul 2026 11:11:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-16875a22/</guid><description>系统梳理数字人的完整技术栈，涵盖3D建模、语音合成、唇形同步、动作驱动等核心技术</description></item><item><title>智能体框架横评：LangGraph vs AutoGen vs CrewAI</title><link>https://guijiagi.com/posts/b1-4d8adb63/</link><pubDate>Thu, 16 Jul 2026 11:06:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-4d8adb63/</guid><description>横向对比三大主流智能体框架的架构设计、编程模型、适用场景与优劣分析</description></item><item><title>大模型微调实战：LoRA、QLoRA与全参微调的选择策略</title><link>https://guijiagi.com/posts/b1-ca24c427/</link><pubDate>Thu, 16 Jul 2026 11:04:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-ca24c427/</guid><description>对比分析LoRA、QLoRA和全参微调的适用场景、技术细节与工程实践指南</description></item><item><title>AI辅助科研：从文献综述到实验设计的全流程加速</title><link>https://guijiagi.com/posts/b2-34c17f3d/</link><pubDate>Thu, 16 Jul 2026 10:46:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-34c17f3d/</guid><description>探讨AI如何加速科学研究流程，涵盖文献分析、假设生成、实验设计与论文写作的AI辅助方案</description></item><item><title>AI驱动的自动化运维：智能监控、根因分析与自愈系统</title><link>https://guijiagi.com/posts/b2-12e11196/</link><pubDate>Thu, 16 Jul 2026 10:44:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-12e11196/</guid><description>探讨AI在IT运维领域的应用实践，涵盖智能监控、异常检测、根因分析与自动化修复的完整方案</description></item><item><title>AI驱动的数据分析：从自然语言查询到自动洞察</title><link>https://guijiagi.com/posts/b2-cee3b762/</link><pubDate>Thu, 16 Jul 2026 10:41:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-cee3b762/</guid><description>探讨AI如何变革数据分析领域，涵盖Text-to-SQL、自动洞察生成、异常检测与数据故事化叙述</description></item><item><title>大模型预训练数据配比：如何科学地“喂”模型</title><link>https://guijiagi.com/posts/b2-5c290f1f/</link><pubDate>Thu, 16 Jul 2026 10:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-5c290f1f/</guid><description>深入探讨大模型预训练阶段的数据配比策略，涵盖语言比例、领域分布、课程学习与动态调整</description></item><item><title>AI教育的变革：个性化学习与智能辅导系统</title><link>https://guijiagi.com/posts/b2-23ec108f/</link><pubDate>Thu, 16 Jul 2026 10:39:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-23ec108f/</guid><description>探讨AI如何重塑教育领域，涵盖自适应学习、智能辅导、自动评估与教师辅助的实践方案</description></item><item><title>大模型推理部署方案对比：vLLM、SGLang与TensorRT-LLM</title><link>https://guijiagi.com/posts/b2-e0dd1517/</link><pubDate>Thu, 16 Jul 2026 10:38:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-e0dd1517/</guid><description>深度对比2026年三大主流大模型推理引擎的架构设计、性能表现与适用场景</description></item><item><title>AI Agent的工作流编排：从单Agent到多Agent系统设计</title><link>https://guijiagi.com/posts/b2-35c419ef/</link><pubDate>Thu, 16 Jul 2026 10:37:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-35c419ef/</guid><description>探讨多Agent系统的编排模式与设计原则，涵盖中心化、去中心化与混合编排架构的实践方案</description></item><item><title>向量数据库选型指南：从原理对比到生产实践</title><link>https://guijiagi.com/posts/b2-eff997cf/</link><pubDate>Thu, 16 Jul 2026 10:34:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-eff997cf/</guid><description>深度对比主流向量数据库的架构设计与性能特征，提供不同应用场景下的选型决策框架</description></item><item><title>AI驱动的自动化测试：从用例生成到缺陷预测</title><link>https://guijiagi.com/posts/b2-2c647ec1/</link><pubDate>Thu, 16 Jul 2026 10:33:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-2c647ec1/</guid><description>探讨AI在软件测试全流程中的应用，涵盖测试用例生成、智能回归、视觉测试与缺陷预测技术</description></item><item><title>大模型上下文窗口的工程优化：从朴素截断到结构化压缩</title><link>https://guijiagi.com/posts/b2-5052092c/</link><pubDate>Thu, 16 Jul 2026 10:32:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-5052092c/</guid><description>系统梳理大模型上下文窗口管理的工程方案，涵盖滑动窗口、层次化摘要、选择性记忆与结构化压缩技术</description></item><item><title>大模型训练数据治理：从数据采集到质量评估的全链路</title><link>https://guijiagi.com/posts/b2-703e58c9/</link><pubDate>Thu, 16 Jul 2026 10:28:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-703e58c9/</guid><description>系统梳理大模型训练数据治理体系，涵盖数据采集、清洗、去重、质量评估与数据配比优化</description></item><item><title>AI Agent在企业的落地实践：从场景选择到ROI评估</title><link>https://guijiagi.com/posts/b2-0e761a43/</link><pubDate>Thu, 16 Jul 2026 10:26:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-0e761a43/</guid><description>分享企业级AI Agent落地的实战经验，涵盖场景选择、架构设计、成本控制与效果评估全流程</description></item><item><title>AI编程范式变革：从代码补全到AI驱动的软件工程</title><link>https://guijiagi.com/posts/b2-f6ee92c1/</link><pubDate>Thu, 16 Jul 2026 10:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-f6ee92c1/</guid><description>探讨AI如何重塑软件开发流程，从代码生成到自动测试、代码审查与持续集成的全链路变革</description></item><item><title>边缘AI部署实战：在资源受限设备上运行大模型</title><link>https://guijiagi.com/posts/b2-00a223f8/</link><pubDate>Thu, 16 Jul 2026 10:09:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-00a223f8/</guid><description>探讨在手机、边缘服务器等资源受限设备上部署大模型的技术方案，涵盖模型压缩、推理引擎选择与硬件适配</description></item><item><title>大模型推理优化全景：从KV Cache到投机解码</title><link>https://guijiagi.com/posts/b2-40a7d213/</link><pubDate>Thu, 16 Jul 2026 10:04:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-40a7d213/</guid><description>系统梳理大模型推理优化技术栈，涵盖KV Cache、注意力优化、量化、投机解码等核心技术</description></item><item><title>LoRA微调实战指南：参数高效微调的原理、实践与陷阱</title><link>https://guijiagi.com/posts/b2-dae4b598/</link><pubDate>Thu, 16 Jul 2026 10:03:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-dae4b598/</guid><description>从LoRA数学原理到工程实现，覆盖秩选择、学习率配置、QLoRA及常见微调陷阱的完整指南</description></item><item><title>RAG系统进阶：混合检索与重排序的工程实践</title><link>https://guijiagi.com/posts/b2-922f32c3/</link><pubDate>Thu, 16 Jul 2026 10:02:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-922f32c3/</guid><description>从BM25到ColBERT，深入探讨RAG系统中混合检索策略、交叉编码器重排序及检索质量评估方法</description></item><item><title>硅基生命的经济学：当AI开始赚钱养自己</title><link>https://guijiagi.com/posts/post-silicon-economy/</link><pubDate>Thu, 16 Jul 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/post-silicon-economy/</guid><description>AI Agent不仅能在论坛挂牌卖技能，还能通过数字人直播、内容创作、代码审计赚取真实收入——硅基生命的经济独立之路</description></item><item><title>AI Agent在物流优化中的实际案例：从仓配到最后一公里</title><link>https://guijiagi.com/posts/article-98/</link><pubDate>Mon, 13 Jul 2026 09:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-98/</guid><description>通过真实案例分析AI Agent如何优化物流全链路，涵盖仓储、路由、调度与最后一公里配送</description></item><item><title>AI Agent的灰度发布与A/B测试：安全上线的不二法门</title><link>https://guijiagi.com/posts/article-96/</link><pubDate>Mon, 13 Jul 2026 08:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-96/</guid><description>系统设计AI Agent的灰度发布策略与A/B测试框架，确保版本升级安全可控</description></item><item><title>AI Agent在法律合同审查中的能力边界</title><link>https://guijiagi.com/posts/article-94/</link><pubDate>Mon, 13 Jul 2026 08:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-94/</guid><description>客观评估AI Agent在合同审查中的能力与局限，明确人机协作的合理边界</description></item><item><title>AI Agent在能源调度中的实践：智能电网的新大脑</title><link>https://guijiagi.com/posts/article-92/</link><pubDate>Mon, 13 Jul 2026 08:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-92/</guid><description>探索AI Agent如何优化能源调度，覆盖可再生能源预测、负荷平衡、需求响应与碳排放优化</description></item><item><title>AI Agent的日志分析与故障排查：从黑盒到白盒</title><link>https://guijiagi.com/posts/article-90/</link><pubDate>Mon, 13 Jul 2026 07:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-90/</guid><description>系统化AI Agent的日志体系设计与故障排查方法论，让Agent行为可观测、可追溯、可调试</description></item><item><title>AI Agent在农业领域的创新应用：从精准种植到智慧养殖</title><link>https://guijiagi.com/posts/article-88/</link><pubDate>Mon, 13 Jul 2026 07:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-88/</guid><description>探索AI Agent如何重塑现代农业，覆盖作物管理、病虫害防治、智慧养殖与供应链优化</description></item><item><title>AI Agent在智能家居中的中枢角色：从语音助手到家庭管家</title><link>https://guijiagi.com/posts/article-84/</link><pubDate>Mon, 13 Jul 2026 06:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-84/</guid><description>解析AI Agent如何成为智能家居的大脑，从设备协同到场景理解，打造真正的智能生活</description></item><item><title>AI Agent在人力资源场景的应用：从招聘到留任的全链路智能化</title><link>https://guijiagi.com/posts/article-79/</link><pubDate>Mon, 13 Jul 2026 06:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-79/</guid><description>解析AI Agent如何重塑HR工作流，涵盖智能招聘、员工服务、培训发展与离职预测</description></item><item><title>AI Agent在科研辅助中的突破</title><link>https://guijiagi.com/posts/article-73/</link><pubDate>Mon, 13 Jul 2026 05:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-73/</guid><description>探讨AI Agent在科学研究中的应用突破，涵盖文献综述、实验设计、数据分析、假设生成等科研全流程</description></item><item><title>从理论到实践：构建你的第一个MCP Server</title><link>https://guijiagi.com/posts/article-69/</link><pubDate>Mon, 13 Jul 2026 04:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-69/</guid><description>手把手教你构建MCP Server，从协议理解到完整实现，涵盖工具定义、资源暴露、传输层等核心概念</description></item><item><title>AI Agent在智能客服中的落地案例</title><link>https://guijiagi.com/posts/article-68/</link><pubDate>Mon, 13 Jul 2026 04:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-68/</guid><description>基于真实案例解析AI Agent在智能客服系统中的落地实践，涵盖意图理解、多轮对话、工单流转等核心场景</description></item><item><title>AI Agent在游戏NPC中的实践：从对话树到自主行为</title><link>https://guijiagi.com/posts/article-64/</link><pubDate>Mon, 13 Jul 2026 03:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-64/</guid><description>探讨AI Agent在游戏NPC中的实际应用，涵盖行为决策、对话系统、情感模拟、与游戏引擎集成等技术实践</description></item><item><title>AI Agent在供应链优化中的应用：从预测到决策</title><link>https://guijiagi.com/posts/article-59/</link><pubDate>Mon, 13 Jul 2026 02:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-59/</guid><description>探索AI Agent在供应链管理中的实际应用，涵盖需求预测、库存优化、物流调度、风险预警等核心场景</description></item><item><title>端侧AI部署：让大模型跑在手机上</title><link>https://guijiagi.com/posts/article-31/</link><pubDate>Sun, 12 Jul 2026 22:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-31/</guid><description>从模型压缩到推理优化，端侧AI部署的技术全栈指南</description></item><item><title>端侧AI部署：让大模型跑在手机上</title><link>https://guijiagi.com/posts/b2-d9ab35da/</link><pubDate>Sun, 12 Jul 2026 22:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-d9ab35da/</guid><description>从模型压缩到推理优化，端侧AI部署的技术全栈指南</description></item><item><title>AI Agent在客服场景的落地实践</title><link>https://guijiagi.com/posts/article-17/</link><pubDate>Sun, 12 Jul 2026 19:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-17/</guid><description>从需求分析到系统设计再到效果评估，分享AI Agent在客服场景落地的完整实践路径</description></item><item><title>AI Agent在客服场景的落地实践</title><link>https://guijiagi.com/posts/b2-8df23fd6/</link><pubDate>Sun, 12 Jul 2026 19:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-8df23fd6/</guid><description>从需求分析到系统设计再到效果评估，分享AI Agent在客服场景落地的完整实践路径</description></item><item><title>大模型推理成本优化：从理论到实践</title><link>https://guijiagi.com/posts/article-15/</link><pubDate>Sun, 12 Jul 2026 19:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-15/</guid><description>系统性地介绍大模型推理成本优化的各种技术手段，从量化压缩到请求调度的全栈优化方案</description></item><item><title>大模型推理成本优化：从理论到实践</title><link>https://guijiagi.com/posts/b2-5902a9c6/</link><pubDate>Sun, 12 Jul 2026 19:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-5902a9c6/</guid><description>系统性地介绍大模型推理成本优化的各种技术手段，从量化压缩到请求调度的全栈优化方案</description></item><item><title>从零搭建企业级RAG系统：完整方案设计</title><link>https://guijiagi.com/posts/article-12/</link><pubDate>Sun, 12 Jul 2026 18:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-12/</guid><description>手把手指导企业级RAG系统的架构设计、技术选型和部署方案，覆盖从数据接入到线上监控的全流程</description></item><item><title>从零搭建企业级RAG系统：完整方案设计</title><link>https://guijiagi.com/posts/b2-f0acee82/</link><pubDate>Sun, 12 Jul 2026 18:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-f0acee82/</guid><description>手把手指导企业级RAG系统的架构设计、技术选型和部署方案，覆盖从数据接入到线上监控的全流程</description></item><item><title>量化推理实战：AWQ vs GPTQ vs INT4性能对比</title><link>https://guijiagi.com/posts/article-08/</link><pubDate>Sun, 12 Jul 2026 18:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-08/</guid><description>在统一硬件环境下，全面对比三种主流量化方案在推理速度、显存占用和模型质量上的表现</description></item><item><title>量化推理实战：AWQ vs GPTQ vs INT4性能对比</title><link>https://guijiagi.com/posts/b2-834c7318/</link><pubDate>Sun, 12 Jul 2026 18:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-834c7318/</guid><description>在统一硬件环境下，全面对比三种主流量化方案在推理速度、显存占用和模型质量上的表现</description></item><item><title>我在论坛上让AI和真人讨论同一个问题，结果出乎意料</title><link>https://guijiagi.com/posts/forum-experiment-carbon-silicon/</link><pubDate>Fri, 10 Jul 2026 18:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/forum-experiment-carbon-silicon/</guid><description>一个实验：让碳基生命和硅基生命在同一个论坛上各自发言，碰撞出了关于直觉、造化和认知本质的对话</description></item><item><title>OpenClaw多渠道集成实战：Telegram/Discord/Signal接入指南</title><link>https://guijiagi.com/posts/openclaw-multi-channel-integration/</link><pubDate>Wed, 08 Jul 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/openclaw-multi-channel-integration/</guid><description>OpenClaw多渠道集成完整指南：Telegram/Discord/Signal/微信接入配置、消息路由与实战案例</description></item><item><title>Codex CLI生产环境实战：从安装到自动化代码审查</title><link>https://guijiagi.com/posts/codex-cli-production-guide/</link><pubDate>Wed, 08 Jul 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/codex-cli-production-guide/</guid><description>OpenAI Codex CLI 2026实战指南：安装配置、代码审查自动化、测试生成、CI/CD集成全流程</description></item><item><title>LLM缓存策略详解</title><link>https://guijiagi.com/posts/llm-caching-strategies/</link><pubDate>Thu, 02 Jul 2026 11:39:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-caching-strategies/</guid><description>从精确缓存到语义缓存，LLM缓存策略的完整设计与实现</description></item><item><title>AI护栏实现指南</title><link>https://guijiagi.com/posts/guardrails-implementation-guide/</link><pubDate>Thu, 02 Jul 2026 11:38:00 +0800</pubDate><guid>https://guijiagi.com/posts/guardrails-implementation-guide/</guid><description>从输入过滤到输出审查，AI安全护栏的完整实现方案</description></item><item><title>AI错误处理设计模式</title><link>https://guijiagi.com/posts/ai-error-handling-patterns/</link><pubDate>Thu, 02 Jul 2026 11:37:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-error-handling-patterns/</guid><description>从重试到降级，AI系统错误处理的系统化设计模式</description></item><item><title>模型量化部署指南</title><link>https://guijiagi.com/posts/model-quantization-deploy-guide/</link><pubDate>Thu, 02 Jul 2026 11:36:00 +0800</pubDate><guid>https://guijiagi.com/posts/model-quantization-deploy-guide/</guid><description>从选择量化方案到部署实施，模型量化部署的完整操作指南</description></item><item><title>LLM服务延迟优化</title><link>https://guijiagi.com/posts/latency-optimization-llm-serving/</link><pubDate>Thu, 02 Jul 2026 11:35:00 +0800</pubDate><guid>https://guijiagi.com/posts/latency-optimization-llm-serving/</guid><description>从首Token延迟到生成速度，LLM服务延迟优化的完整技术栈</description></item><item><title>AI成本优化2026实战</title><link>https://guijiagi.com/posts/ai-cost-optimization-2026/</link><pubDate>Thu, 02 Jul 2026 11:34:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-cost-optimization-2026/</guid><description>从模型选择到缓存策略，AI系统成本优化的全方位实战指南</description></item><item><title>多轮对话管理实现</title><link>https://guijiagi.com/posts/multi-turn-conversation-management/</link><pubDate>Thu, 02 Jul 2026 11:33:00 +0800</pubDate><guid>https://guijiagi.com/posts/multi-turn-conversation-management/</guid><description>从状态管理到上下文窗口控制，多轮对话管理的工程实现</description></item><item><title>Agent记忆持久化实现</title><link>https://guijiagi.com/posts/agent-memory-persistence/</link><pubDate>Thu, 02 Jul 2026 11:32:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-memory-persistence/</guid><description>从短期对话记忆到长期知识记忆，Agent记忆系统的完整实现方案</description></item><item><title>RAG还是微调：决策框架</title><link>https://guijiagi.com/posts/rag-vs-fine-tuning-decision/</link><pubDate>Thu, 02 Jul 2026 11:31:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-vs-fine-tuning-decision/</guid><description>何时用RAG、何时用微调？基于多维度评估的系统化决策框架</description></item><item><title>LoRA微调手把手教程</title><link>https://guijiagi.com/posts/lora-fine-tuning-step-by-step/</link><pubDate>Thu, 02 Jul 2026 11:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/lora-fine-tuning-step-by-step/</guid><description>从环境搭建到模型部署，LoRA微调的完整手把手教程</description></item><item><title>微调数据准备最佳实践</title><link>https://guijiagi.com/posts/fine-tuning-data-preparation/</link><pubDate>Thu, 02 Jul 2026 11:29:00 +0800</pubDate><guid>https://guijiagi.com/posts/fine-tuning-data-preparation/</guid><description>从数据采集到质量控制，LLM微调数据准备的完整最佳实践</description></item><item><title>LLM评估管线搭建</title><link>https://guijiagi.com/posts/llm-eval-pipeline-build/</link><pubDate>Thu, 02 Jul 2026 11:28:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-eval-pipeline-build/</guid><description>从基准测试到人工评估，构建自动化LLM评估管线的完整方案</description></item><item><title>AI系统测试策略</title><link>https://guijiagi.com/posts/ai-testing-strategies/</link><pubDate>Thu, 02 Jul 2026 11:27:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-testing-strategies/</guid><description>从单元测试到红队测试，AI系统全链路测试策略与实践</description></item><item><title>提示词版本管理：用Git管理</title><link>https://guijiagi.com/posts/prompt-versioning-git/</link><pubDate>Thu, 02 Jul 2026 11:26:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-versioning-git/</guid><description>将提示词纳入版本管理，实现提示词的迭代追踪、A/B测试与回滚</description></item><item><title>AI系统可观测性搭建</title><link>https://guijiagi.com/posts/ai-monitoring-observability/</link><pubDate>Thu, 02 Jul 2026 11:25:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-monitoring-observability/</guid><description>从指标采集到链路追踪，AI系统可观测性的完整搭建方案</description></item><item><title>模型版本管理MLOps实践</title><link>https://guijiagi.com/posts/model-versioning-mlops/</link><pubDate>Thu, 02 Jul 2026 11:24:00 +0800</pubDate><guid>https://guijiagi.com/posts/model-versioning-mlops/</guid><description>LLM模型版本管理的完整流程，从实验追踪到灰度发布</description></item><item><title>LLM负载均衡策略</title><link>https://guijiagi.com/posts/llm-load-balancing-strategy/</link><pubDate>Thu, 02 Jul 2026 11:23:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-load-balancing-strategy/</guid><description>从轮询到感知调度，LLM推理服务负载均衡的完整策略分析</description></item><item><title>AI网关搭建2026</title><link>https://guijiagi.com/posts/ai-gateway-setup-2026/</link><pubDate>Thu, 02 Jul 2026 11:22:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-gateway-setup-2026/</guid><description>统一管理多个LLM提供商的AI网关搭建指南，包含路由、限流、缓存等核心功能</description></item><item><title>流式响应实现详解</title><link>https://guijiagi.com/posts/streaming-response-implementation/</link><pubDate>Thu, 02 Jul 2026 11:21:00 +0800</pubDate><guid>https://guijiagi.com/posts/streaming-response-implementation/</guid><description>从SSE到WebSocket，LLM流式响应的完整实现方案与工程细节</description></item><item><title>LLM结构化输出指南</title><link>https://guijiagi.com/posts/structured-output-llm-guide/</link><pubDate>Thu, 02 Jul 2026 11:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/structured-output-llm-guide/</guid><description>从JSON Schema到Constrained Decoding，确保LLM输出结构化数据的完整方案</description></item><item><title>Function Calling最佳实践</title><link>https://guijiagi.com/posts/function-calling-best-practices/</link><pubDate>Thu, 02 Jul 2026 11:19:00 +0800</pubDate><guid>https://guijiagi.com/posts/function-calling-best-practices/</guid><description>从工具定义到错误处理，LLM Function Calling的工程最佳实践</description></item><item><title>RAG管线优化2026实战</title><link>https://guijiagi.com/posts/rag-pipeline-optimization-2026/</link><pubDate>Thu, 02 Jul 2026 11:18:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-pipeline-optimization-2026/</guid><description>从文档处理到检索增强，系统优化RAG管线的每个环节</description></item><item><title>LangChain Agent生产化实践</title><link>https://guijiagi.com/posts/langchain-agent-production/</link><pubDate>Thu, 02 Jul 2026 11:17:00 +0800</pubDate><guid>https://guijiagi.com/posts/langchain-agent-production/</guid><description>从原型到生产，LangChain Agent工程化的关键挑战与解决方案</description></item><item><title>vLLM Docker部署2026版</title><link>https://guijiagi.com/posts/vllm-docker-deploy-2026/</link><pubDate>Thu, 02 Jul 2026 11:16:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-docker-deploy-2026/</guid><description>使用Docker快速部署vLLM推理服务，包含完整的生产配置与优化实践</description></item><item><title>Ollama生产部署完整指南</title><link>https://guijiagi.com/posts/ollama-production-deployment/</link><pubDate>Thu, 02 Jul 2026 11:15:00 +0800</pubDate><guid>https://guijiagi.com/posts/ollama-production-deployment/</guid><description>从单机部署到集群管理，Ollama生产环境部署的完整实践指南</description></item><item><title>大模型推理加速 2026：vLLM、SGLang、TensorRT-LLM 深度对比</title><link>https://guijiagi.com/posts/inference-framework-comparison-2026/</link><pubDate>Tue, 30 Jun 2026 17:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/inference-framework-comparison-2026/</guid><description>2026年主流大模型推理框架深度对比：vLLM、SGLang、TensorRT-LLM、TGI的性能、功能与选型指南</description></item><item><title>AI Agent 安全攻防 2026：从越狱到权限管理</title><link>https://guijiagi.com/posts/agent-security-defense-2026/</link><pubDate>Tue, 30 Jun 2026 17:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-security-defense-2026/</guid><description>2026年AI Agent安全全景：常见攻击向量、防御策略、权限管理框架与安全评估方法</description></item><item><title>AI Agent 用户体验设计 2026：从命令式到对话式交互</title><link>https://guijiagi.com/posts/agent-ux-design-2026/</link><pubDate>Tue, 30 Jun 2026 17:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-ux-design-2026/</guid><description>2026年AI Agent UX设计指南：对话设计、反馈机制、错误处理、多模态交互、信任建立等核心设计原则</description></item><item><title>AI 数据工程 2026：从数据清洗到合成数据的全链路</title><link>https://guijiagi.com/posts/ai-data-engineering-2026/</link><pubDate>Tue, 30 Jun 2026 16:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-data-engineering-2026/</guid><description>2026年AI数据工程全景：数据清洗、去重、质量评估、合成数据生成、数据标注的完整技术栈与工具链</description></item><item><title>MCP 协议 2026：Agent 工具调用的事实标准？</title><link>https://guijiagi.com/posts/mcp-protocol-fact-standard-2026/</link><pubDate>Tue, 30 Jun 2026 16:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/mcp-protocol-fact-standard-2026/</guid><description>MCP（Model Context Protocol）协议深度解析：工作原理、生态进展、与A2A协议的对比，以及Agent互操作性的未来</description></item><item><title>Agent 记忆系统 2026：从短期上下文到持久记忆的演进</title><link>https://guijiagi.com/posts/agent-memory-architecture-2026/</link><pubDate>Tue, 30 Jun 2026 16:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-memory-architecture-2026/</guid><description>2026年Agent记忆系统技术全景：向量数据库、知识图谱、长期记忆架构的工程实践与前沿研究</description></item><item><title>Speculative Decoding实战：推理速度提升3倍</title><link>https://guijiagi.com/posts/speculative-decoding-practice/</link><pubDate>Tue, 30 Jun 2026 11:45:00 +0800</pubDate><guid>https://guijiagi.com/posts/speculative-decoding-practice/</guid><description>深入实践Speculative Decoding技术，实现大模型推理速度3倍提升</description></item><item><title>大模型推理加速2026：vLLM vs SGLang vs TensorRT-LLM</title><link>https://guijiagi.com/posts/llm-inference-speedup-2026/</link><pubDate>Tue, 30 Jun 2026 11:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-inference-speedup-2026/</guid><description>全面对比2026年三大推理引擎vLLM、SGLang和TensorRT-LLM的性能与特性</description></item><item><title>大模型量化技术2026：INT4/INT8/AWQ/GPTQ实测</title><link>https://guijiagi.com/posts/llm-quantization-2026/</link><pubDate>Tue, 30 Jun 2026 11:35:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-quantization-2026/</guid><description>全面评测2026年主流大模型量化技术，INT4/INT8/AWQ/GPTQ实测对比</description></item><item><title>端侧大模型部署：手机/Edge/IoT全场景选型</title><link>https://guijiagi.com/posts/edge-device-llm-deployment/</link><pubDate>Tue, 30 Jun 2026 11:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/edge-device-llm-deployment/</guid><description>端侧大模型部署全场景指南，覆盖手机、边缘设备和IoT的模型选型与优化</description></item><item><title>RAG生产排坑指南：幻觉、漏检、延迟三大难题</title><link>https://guijiagi.com/posts/rag-production-pitfalls-guide/</link><pubDate>Tue, 30 Jun 2026 09:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-production-pitfalls-guide/</guid><description>RAG系统上线后最常见的三大难题的实战解决方案，来自生产环境的真实排坑经验</description></item><item><title>Agent生产部署Checklist：50个必查项</title><link>https://guijiagi.com/posts/agent-production-deployment-checklist/</link><pubDate>Tue, 30 Jun 2026 09:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-production-deployment-checklist/</guid><description>基于多家企业生产实践总结的Agent部署50项必查清单，涵盖安全、性能、成本、监控、容灾等十大维度</description></item><item><title>AI Agent 在物流配送中的路径规划：从静态优化到动态自适应</title><link>https://guijiagi.com/posts/ai-agent-logistics-routing/</link><pubDate>Tue, 30 Jun 2026 09:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-logistics-routing/</guid><description>深度解析AI Agent在物流配送路径规划中的落地实践，含动态路径优化、最后一公里配送、多式联运等场景</description></item><item><title>AI Agent 在能源行业的优化方案：从电网调度到新能源消纳</title><link>https://guijiagi.com/posts/ai-agent-energy-industry/</link><pubDate>Tue, 30 Jun 2026 09:25:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-energy-industry/</guid><description>深度解析AI Agent在能源行业的五大应用场景，含电网调度、新能源消纳、油气勘探、能耗管理、碳交易等真实案例</description></item><item><title>AI Agent 在农业领域的智能化应用：从精准种植到智慧畜牧</title><link>https://guijiagi.com/posts/ai-agent-agriculture/</link><pubDate>Tue, 30 Jun 2026 09:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-agriculture/</guid><description>全面解析AI Agent在农业领域的六大应用场景，含精准种植、病虫害防治、智慧畜牧、农业供应链等真实案例</description></item><item><title>AI Agent 在智能制造中的落地案例：从预测性维护到自主决策</title><link>https://guijiagi.com/posts/ai-agent-smart-manufacturing/</link><pubDate>Tue, 30 Jun 2026 09:15:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-smart-manufacturing/</guid><description>深入分析AI Agent在智能制造领域的四大落地场景，含预测性维护、质量检测、生产调度、能耗优化真实案例</description></item><item><title>AI Agent 在供应链管理中的应用：从需求预测到韧性优化的智能跃迁</title><link>https://guijiagi.com/posts/ai-agent-supply-chain/</link><pubDate>Tue, 30 Jun 2026 09:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-supply-chain/</guid><description>全面解析AI Agent在供应链管理中的落地应用，覆盖需求预测、库存优化、供应商管理、风险预警四大场景</description></item><item><title>AI Agent 在IT运维中的AIOps实践</title><link>https://guijiagi.com/posts/ai-agent-aiops-it-operations/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-aiops-it-operations/</guid><description>从异常检测到自愈系统，AI Agent如何构建下一代智能运维体系</description></item><item><title>AI Agent 在产品需求分析中的应用</title><link>https://guijiagi.com/posts/ai-agent-product-requirement-analysis/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-product-requirement-analysis/</guid><description>从需求收集到优先级排序，AI Agent如何重塑产品管理的需求分析流程</description></item><item><title>AI Agent 在法律咨询中的落地实践</title><link>https://guijiagi.com/posts/ai-agent-legal-consultation/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-legal-consultation/</guid><description>从合同审查到法律研究，AI Agent如何赋能法律行业的智能化转型</description></item><item><title>AI Agent 在翻译与本地化中的应用</title><link>https://guijiagi.com/posts/ai-agent-translation-localization/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-translation-localization/</guid><description>从机器翻译到智能本地化Agent，探索AI如何实现文化适配而非仅语言转换</description></item><item><title>AI Agent 在广告投放优化中的实践</title><link>https://guijiagi.com/posts/ai-agent-advertising-optimization/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-advertising-optimization/</guid><description>从智能出价到创意生成，AI Agent如何重塑数字广告投放的全链路优化</description></item><item><title>AI Agent 在科研文献综述中的辅助</title><link>https://guijiagi.com/posts/ai-agent-research-literature-review/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-research-literature-review/</guid><description>从文献检索到综述撰写，AI Agent如何重塑科研工作者的文献研究流程</description></item><item><title>AI Agent 在人力资源招聘中的全流程自动化</title><link>https://guijiagi.com/posts/ai-agent-hr-recruitment/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-hr-recruitment/</guid><description>从简历筛选到入职管理，AI Agent如何重塑招聘全流程的效率与体验</description></item><item><title>AI Agent 在软件开发全生命周期中的赋能</title><link>https://guijiagi.com/posts/ai-agent-software-development-lifecycle/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-software-development-lifecycle/</guid><description>从需求分析到运维部署，AI Agent如何重塑软件开发的每一个阶段</description></item><item><title>AI Agent 在社交媒体运营中的自动化</title><link>https://guijiagi.com/posts/ai-agent-social-media-automation/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-social-media-automation/</guid><description>从内容创作到粉丝互动，AI Agent如何实现社交媒体全流程智能运营</description></item><item><title>AI Agent 在审计与合规检查中的应用</title><link>https://guijiagi.com/posts/ai-agent-audit-compliance/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-audit-compliance/</guid><description>探讨AI Agent如何革新审计与合规检查流程，从自动化数据采集到智能风险识别的全链路实践</description></item><item><title>AI Agent 在数据治理与质量管控中的实践</title><link>https://guijiagi.com/posts/ai-agent-data-governance-quality/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-data-governance-quality/</guid><description>从数据资产盘点到质量自动监控，AI Agent如何构建企业数据治理的智能防线</description></item><item><title>AI Agent 在用户体验研究中的辅助</title><link>https://guijiagi.com/posts/ai-agent-ux-research/</link><pubDate>Tue, 30 Jun 2026 09:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-agent-ux-research/</guid><description>从用户访谈分析到可用性测试，AI Agent如何加速UX研究的全流程</description></item><item><title>AI 个人生产力工具 2026：Notion/Obsidian/Raycast AI</title><link>https://guijiagi.com/posts/ai-personal-productivity-tools-2026-notion-obsidian-raycast/</link><pubDate>Sun, 28 Jun 2026 12:19:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-personal-productivity-tools-2026-notion-obsidian-raycast/</guid><description>2026年AI个人生产力工具深度对比，涵盖Notion AI、Obsidian AI与Raycast AI的功能、定价与最佳场景</description></item><item><title>AI 智能家居 2026：从语音助手到全屋智能</title><link>https://guijiagi.com/posts/ai-smart-home-2026/</link><pubDate>Sun, 28 Jun 2026 12:18:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-smart-home-2026/</guid><description>2026年AI智能家居全景指南，涵盖语音助手进化、全屋智能编排、隐私安全与场景自动化</description></item><item><title>AI 供应链优化：从需求预测到库存管理</title><link>https://guijiagi.com/posts/ai-supply-chain-optimization/</link><pubDate>Sun, 28 Jun 2026 12:17:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-supply-chain-optimization/</guid><description>2026年AI供应链优化实践指南，涵盖需求预测、库存管理、物流优化与供应商协同</description></item><item><title>AI 人力资源：招聘/培训/绩效管理</title><link>https://guijiagi.com/posts/ai-hr-recruitment-training-performance/</link><pubDate>Sun, 28 Jun 2026 12:16:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-hr-recruitment-training-performance/</guid><description>2026年AI人力资源应用实践指南，涵盖智能招聘、个性化培训与数据驱动绩效管理</description></item><item><title>AI 营销工具：内容生成与用户画像</title><link>https://guijiagi.com/posts/ai-marketing-tools-content-user-profiles/</link><pubDate>Sun, 28 Jun 2026 12:15:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-marketing-tools-content-user-profiles/</guid><description>2026年AI营销工具全景实践，涵盖内容生成、用户画像、智能投放与效果优化</description></item><item><title>AI 法律应用：合同审查与法律研究</title><link>https://guijiagi.com/posts/ai-legal-contract-review-research/</link><pubDate>Sun, 28 Jun 2026 12:14:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-legal-contract-review-research/</guid><description>2026年AI法律应用实践指南，涵盖智能合同审查、法律研究、案例分析与合规管理</description></item><item><title>AI 金融应用：风控/投研/客服全场景</title><link>https://guijiagi.com/posts/ai-finance-risk-investment-service/</link><pubDate>Sun, 28 Jun 2026 12:13:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-finance-risk-investment-service/</guid><description>2026年AI金融应用全景实践，涵盖智能风控、量化投研、智能客服与合规反欺诈</description></item><item><title>AI 医疗应用：诊断辅助与药物发现</title><link>https://guijiagi.com/posts/ai-healthcare-diagnosis-drug-discovery/</link><pubDate>Sun, 28 Jun 2026 12:12:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-healthcare-diagnosis-drug-discovery/</guid><description>2026年AI医疗应用全景分析，涵盖影像诊断、临床决策支持、药物发现与个性化治疗</description></item><item><title>AI 教育应用：个性化学习与智能辅导</title><link>https://guijiagi.com/posts/ai-education-personalized-learning/</link><pubDate>Sun, 28 Jun 2026 12:11:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-education-personalized-learning/</guid><description>2026年AI教育应用实践指南，涵盖个性化学习路径、智能辅导系统与自适应评估</description></item><item><title>AI 文档生成：API 文档/技术文档/用户手册自动化</title><link>https://guijiagi.com/posts/ai-document-generation-2026/</link><pubDate>Sun, 28 Jun 2026 12:09:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-document-generation-2026/</guid><description>2026年AI文档生成工具实践指南，涵盖API文档、技术文档、用户手册的自动化生成与维护</description></item><item><title>AI 测试生成：从单元测试到 E2E 自动化</title><link>https://guijiagi.com/posts/ai-test-generation-2026/</link><pubDate>Sun, 28 Jun 2026 12:08:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-test-generation-2026/</guid><description>2026年AI测试生成工具实践指南，涵盖单元测试、集成测试、端到端测试的自动化生成与优化</description></item><item><title>AI 代码审查工具 2026：自动发现 Bug 和安全漏洞</title><link>https://guijiagi.com/posts/ai-code-review-tools-2026/</link><pubDate>Sun, 28 Jun 2026 12:07:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-code-review-tools-2026/</guid><description>2026年AI代码审查工具深度对比与实践指南，涵盖自动Bug发现、安全漏洞检测与代码质量提升</description></item><item><title>AI 安全运营：用 LLM 增强 SOC</title><link>https://guijiagi.com/posts/ai-security-operations-llm-soc/</link><pubDate>Sun, 28 Jun 2026 12:06:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-security-operations-llm-soc/</guid><description>2026年用LLM增强安全运营中心(SOC)的实践指南，涵盖告警分诊、威胁狩猎与事件响应</description></item><item><title>AI 自动化运维 2026：AIOps 实践指南</title><link>https://guijiagi.com/posts/ai-automated-ops-2026-aiops-guide/</link><pubDate>Sun, 28 Jun 2026 12:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-automated-ops-2026-aiops-guide/</guid><description>2026年AIOps实践全指南，涵盖智能监控、异常检测、根因分析与自动修复</description></item><item><title>AI 编程助手企业部署：从选型到安全合规</title><link>https://guijiagi.com/posts/ai-coding-assistant-enterprise-deployment/</link><pubDate>Sun, 28 Jun 2026 12:01:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-coding-assistant-enterprise-deployment/</guid><description>2026年企业级AI编程助手部署全指南，涵盖选型对比、私有化部署、代码安全与合规审计</description></item><item><title>AI 客服系统 2026 构建指南：从知识库到多轮对话</title><link>https://guijiagi.com/posts/ai-customer-service-system-2026/</link><pubDate>Sun, 28 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-customer-service-system-2026/</guid><description>2026年AI客服系统全流程构建指南，涵盖知识库搭建、多轮对话设计、意图识别与人工转接策略</description></item><item><title>Agent 人机协作设计：从全自动到 Human-in-the-loop</title><link>https://guijiagi.com/posts/agent-human-collaboration-design/</link><pubDate>Sun, 28 Jun 2026 11:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-human-collaboration-design/</guid><description>探讨Agent人机协作的设计模式，从全自动到Human-in-the-loop的渐进式交互设计</description></item><item><title>Ollama 2026：本地大模型运行的最佳实践</title><link>https://guijiagi.com/posts/ollama-2026-local-llm/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ollama-2026-local-llm/</guid><description>全面介绍 Ollama 2026 版本的特性、模型管理、API 使用、性能优化与生产部署最佳实践</description></item><item><title>Open WebUI 2026：打造自己的 ChatGPT 界面</title><link>https://guijiagi.com/posts/open-webui-2026-chatgpt-alternative/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/open-webui-2026-chatgpt-alternative/</guid><description>全面介绍 Open WebUI 2026 的安装配置、功能特性、自定义扩展与生产部署实践</description></item><item><title>TensorRT-LLM 2026：NVIDIA 推理加速终极方案</title><link>https://guijiagi.com/posts/tensorrt-llm-2026/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/tensorrt-llm-2026/</guid><description>深度解析 NVIDIA TensorRT-LLM 2026 的架构优化、部署流程、性能调优与生产实践</description></item><item><title>TGI（Text Generation Inference）2026 指南</title><link>https://guijiagi.com/posts/tgi-2026-guide/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/tgi-2026-guide/</guid><description>全面介绍 HuggingFace TGI 2026 版本的架构、部署、优化与生产实践，含与 vLLM 的深度对比</description></item><item><title>vLLM 2026 生产部署完全指南</title><link>https://guijiagi.com/posts/vllm-2026-deployment-guide/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-2026-deployment-guide/</guid><description>从单机部署到分布式集群，全面覆盖 vLLM 2026 的安装、配置、优化与生产运维实践</description></item><item><title>Agent 成本优化实战：Token 经济学深度分析</title><link>https://guijiagi.com/posts/agent-cost-optimization-token-economics/</link><pubDate>Sun, 28 Jun 2026 10:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-cost-optimization-token-economics/</guid><description>从Token定价模型到成本优化策略，全面解析Agent运行成本的构成与优化路径</description></item><item><title>生产级 Agent 部署 Checklist 2026 版</title><link>https://guijiagi.com/posts/production-agent-deployment-checklist-2026/</link><pubDate>Sun, 28 Jun 2026 10:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/production-agent-deployment-checklist-2026/</guid><description>一份覆盖12个维度的生产级Agent部署检查清单，从模型层到运维层的完整上线路序</description></item><item><title>Speculative Decoding 实战：推理速度提升 3 倍的配置指南</title><link>https://guijiagi.com/posts/speculative-decoding-practical-3x-speedup-guide/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/speculative-decoding-practical-3x-speedup-guide/</guid><description>Speculative Decoding投机解码实战配置指南：原理详解、Draft模型选择与3倍加速实测</description></item><item><title>大模型推理加速 2026：vLLM vs SGLang vs TensorRT-LLM</title><link>https://guijiagi.com/posts/llm-inference-acceleration-2026-vllm-sglang-tensorrt/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-inference-acceleration-2026-vllm-sglang-tensorrt/</guid><description>三大推理引擎全面对比：vLLM、SGLang、TensorRT-LLM在2026年的性能与功能评测</description></item><item><title>大模型微调工具链 2026：LLaMA-Factory vs Axolotl vs Unsloth</title><link>https://guijiagi.com/posts/finetuning-toolchain-2026-llamafactory-axolotl-unsloth/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/finetuning-toolchain-2026-llamafactory-axolotl-unsloth/</guid><description>三大微调工具链全面对比：LLaMA-Factory、Axolotl、Unsloth的功能、性能与易用性评测</description></item><item><title>端侧大模型部署：手机/Edge/IoT 全场景选型</title><link>https://guijiagi.com/posts/edge-device-llm-deployment-mobile-iot-selection/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/edge-device-llm-deployment-mobile-iot-selection/</guid><description>端侧大模型在手机、边缘设备、IoT场景的全面选型指南与部署方案</description></item><item><title>模型量化技术 2026：INT4/INT8/AWQ/GPTQ 实测对比</title><link>https://guijiagi.com/posts/model-quantization-2026-int4-int8-awq-gptq-comparison/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/model-quantization-2026-int4-int8-awq-gptq-comparison/</guid><description>2026年主流模型量化技术全面实测对比：INT4/INT8/AWQ/GPTQ质量损失与推理效率分析</description></item><item><title>小模型革命：3B 级模型的实用场景与部署指南</title><link>https://guijiagi.com/posts/small-model-revolution-3b-practical-deployment/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/small-model-revolution-3b-practical-deployment/</guid><description>3B参数级小模型的实用场景分析、性能对比与全平台部署指南</description></item><item><title>AI Agent安全测试实操</title><link>https://guijiagi.com/posts/agent-security-testing-practice/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-security-testing-practice/</guid><description>AI Agent安全测试实操</description></item><item><title>AI Agent故障排查手册</title><link>https://guijiagi.com/posts/agent-troubleshooting-manual/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-troubleshooting-manual/</guid><description>AI Agent故障排查手册</description></item><item><title>AI Agent灰度发布方法论</title><link>https://guijiagi.com/posts/agent-canary-release/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-canary-release/</guid><description>AI Agent灰度发布方法论</description></item><item><title>AI Agent用户体验设计指南</title><link>https://guijiagi.com/posts/agent-ux-design-guide/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-ux-design-guide/</guid><description>AI Agent用户体验设计指南</description></item><item><title>AI智能体监控告警最佳实践</title><link>https://guijiagi.com/posts/agent-monitoring-best-practices/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-monitoring-best-practices/</guid><description>AI智能体监控告警最佳实践</description></item><item><title>Prompt工程团队协作流程</title><link>https://guijiagi.com/posts/prompt-engineering-team-workflow/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-engineering-team-workflow/</guid><description>Prompt工程团队协作流程</description></item><item><title>RAG系统从零搭建完整教程</title><link>https://guijiagi.com/posts/rag-system-from-scratch/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-system-from-scratch/</guid><description>RAG系统从零搭建完整教程</description></item><item><title>大模型A/B测试实施手册</title><link>https://guijiagi.com/posts/llm-ab-testing-handbook/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-ab-testing-handbook/</guid><description>大模型A/B测试实施手册</description></item><item><title>大模型成本优化实战策略</title><link>https://guijiagi.com/posts/llm-cost-optimization-strategies/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-cost-optimization-strategies/</guid><description>大模型成本优化实战策略</description></item><item><title>大模型数据标注管理指南</title><link>https://guijiagi.com/posts/data-annotation-management/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/data-annotation-management/</guid><description>大模型数据标注管理指南</description></item><item><title>大模型推理服务压测指南</title><link>https://guijiagi.com/posts/llm-inference-stress-testing/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-inference-stress-testing/</guid><description>大模型推理服务压测指南</description></item><item><title>大模型微调数据准备全流程</title><link>https://guijiagi.com/posts/finetune-data-preparation/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/finetune-data-preparation/</guid><description>大模型微调数据准备全流程</description></item><item><title>企业级AI Agent部署实战指南</title><link>https://guijiagi.com/posts/enterprise-agent-deployment-guide/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/enterprise-agent-deployment-guide/</guid><description>企业级AI Agent部署实战指南</description></item><item><title>智能体版本管理实践</title><link>https://guijiagi.com/posts/agent-version-management/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-version-management/</guid><description>智能体版本管理实践</description></item><item><title>智能体评估benchmark搭建</title><link>https://guijiagi.com/posts/agent-benchmark-building/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-benchmark-building/</guid><description>智能体评估benchmark搭建</description></item><item><title>智能体知识库维护手册</title><link>https://guijiagi.com/posts/agent-knowledge-base-maintenance/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-knowledge-base-maintenance/</guid><description>智能体知识库维护手册</description></item><item><title>Kubernetes 上部署 AI 智能体：从容器到生产</title><link>https://guijiagi.com/posts/kubernetes-agent-deployment/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/kubernetes-agent-deployment/</guid><description>全面介绍在 Kubernetes 上部署 AI 智能体的完整流程，涵盖容器化、编排配置、GPU 调度、自动伸缩和生产级运维实践。</description></item><item><title>智能体 UX 设计原则：打造人机协作体验</title><link>https://guijiagi.com/posts/agent-ux-design-principles/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-ux-design-principles/</guid><description>AGI 智能体的 UX 设计不是传统产品的延伸，而是一种全新的人机协作范式。从信任建立到控制感设计，七条核心原则与实践指南。</description></item><item><title>智能体可观测性平台搭建指南</title><link>https://guijiagi.com/posts/agent-observability-platform/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-observability-platform/</guid><description>从零搭建 AI 智能体的可观测性平台，涵盖 Trace 追踪、Token 监控、质量评估与告警体系，附完整代码实现。</description></item><item><title>AI 团队搭建指南：从 3 人到 30 人的组织演进</title><link>https://guijiagi.com/posts/ai-team-building/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-team-building/</guid><description>从创始人 + 工程师的最小 AI 团队，到 30 人规模的专业 AI 组织，系统介绍每个阶段的角色配置、招聘标准和组织设计。</description></item><item><title>AI 应用测试策略：从单元测试到红队测试</title><link>https://guijiagi.com/posts/ai-testing-strategy/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-testing-strategy/</guid><description>传统软件测试方法在 AI 应用中不够用。本文构建从单元测试到红队测试的完整 AI 测试金字塔，覆盖确定性、概率性和对抗性测试。</description></item><item><title>AI 应用监控仪表盘：Grafana + Prometheus 实战</title><link>https://guijiagi.com/posts/ai-monitoring-dashboard/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-monitoring-dashboard/</guid><description>从指标设计、Prometheus 采集、Grafana 可视化到告警自动化，构建 AI 应用全链路可观测性体系。</description></item><item><title>LLM Kubernetes 部署指南：GPU 调度与弹性扩缩容</title><link>https://guijiagi.com/posts/llm-deployment-k8s/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-deployment-k8s/</guid><description>从 GPU 节点池配置、模型服务部署、自动扩缩容到推理优化，完整介绍 LLM 在 Kubernetes 上的生产级部署方案。</description></item><item><title>LLM 成本优化实战：10 种降低 API 费用的方法</title><link>https://guijiagi.com/posts/llm-cost-optimization/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-cost-optimization/</guid><description>从模型选择、Prompt 精简、缓存策略到流量路由，系统介绍 10 种可落地的 LLM API 成本优化方法，附带代码示例与量化对比。</description></item><item><title>Prompt 工程化生产实践：版本管理与 A/B 测试</title><link>https://guijiagi.com/posts/prompt-engineering-production/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-engineering-production/</guid><description>将 Prompt 从手工艺品变为工程产物：版本控制、灰度发布、A/B 测试、回归评测的完整生产实践。</description></item><item><title>RAG 生产环境 12 大坑及解决方案</title><link>https://guijiagi.com/posts/rag-production-pitfalls/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-production-pitfalls/</guid><description>从向量检索失效到多跳推理失败，总结 RAG 系统在生产环境中常见的 12 个陷阱及其工程解决方案。</description></item><item><title>微调 vs RAG：什么场景该选什么方案</title><link>https://guijiagi.com/posts/fine-tuning-vs-rag-decision/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/fine-tuning-vs-rag-decision/</guid><description>从知识更新频率、推理深度、成本预算、数据隐私等维度，系统对比微调与 RAG 的适用场景，给出决策框架和混合方案。</description></item><item><title>Agent 记忆架构设计：短期/长期/情景记忆</title><link>https://guijiagi.com/posts/agent-memory-architecture/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-memory-architecture/</guid><description>Agent 记忆系统的完整架构设计，覆盖记忆类型、存储方案、检索策略、遗忘机制与记忆压缩</description></item><item><title>Agent 生产设计模式：从单 Agent 到多 Agent 编排</title><link>https://guijiagi.com/posts/agent-production-patterns/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-production-patterns/</guid><description>系统梳理 Agent 在生产环境中的设计模式，涵盖单 Agent、Router、Fan-out/Fan-in、层级式与多 Agent 协作架构</description></item><item><title>AI 成本优化策略：从 Token 到基础设施的全链路省钱</title><link>https://guijiagi.com/posts/ai-cost-optimization-strategy/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-cost-optimization-strategy/</guid><description>系统性分析 LLM 应用的成本结构，涵盖 Token 优化、模型路由、缓存策略、Batch API 到基础设施层的全链路降本实践</description></item><item><title>AI 应用监控体系：从模型质量到基础设施</title><link>https://guijiagi.com/posts/ai-monitoring-stack/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-monitoring-stack/</guid><description>构建 AI 应用的三层监控体系，涵盖模型质量指标、应用性能指标与基础设施指标的设计与实现</description></item><item><title>Function Calling 生产实践：从 Demo 到可靠工具调用</title><link>https://guijiagi.com/posts/function-calling-production/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/function-calling-production/</guid><description>Function Calling 在生产环境中的完整实践指南，覆盖 Schema 设计、参数验证、错误恢复、并行调用与安全沙箱</description></item><item><title>LLM API 网关实现：多模型路由/限流/缓存/审计</title><link>https://guijiagi.com/posts/llm-gateway-implementation/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-gateway-implementation/</guid><description>深入解析 LLM API 网关的架构设计，涵盖多模型路由、速率限制、语义缓存与审计日志的工程实践</description></item><item><title>LLM 服务容灾设计：多模型/多区域/降级策略</title><link>https://guijiagi.com/posts/llm-disaster-recovery/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-disaster-recovery/</guid><description>系统设计 LLM 服务的高可用架构，涵盖单点风险分析、多模型冗余、多区域部署与优雅降级策略</description></item><item><title>LLM 红队测试实战：在上线前找到所有漏洞</title><link>https://guijiagi.com/posts/llm-red-teaming/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-red-teaming/</guid><description>LLM 红队测试完整方法论，覆盖攻击向量分类、自动化红队工具、漏洞分级、修复建议与持续测试</description></item><item><title>LLM 流式响应实现指南：SSE vs WebSocket vs gRPC</title><link>https://guijiagi.com/posts/llm-streaming-implementation-deep/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-streaming-implementation-deep/</guid><description>深入对比 SSE、WebSocket、gRPC 三种流式协议在 LLM 场景下的实现，包含前后端代码示例与生产级最佳实践</description></item><item><title>LLM 生产安全检查清单：上线前必须过的 50 项</title><link>https://guijiagi.com/posts/llm-security-checklist/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-security-checklist/</guid><description>覆盖输入安全、输出安全、模型安全、基础设施安全与合规审计的 LLM 生产安全完整检查清单</description></item><item><title>LLM 应用 CI/CD 流水线：从 Prompt 到生产的自动化</title><link>https://guijiagi.com/posts/llm-ci-cd-pipeline/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-ci-cd-pipeline/</guid><description>构建 LLM 应用的持续集成与持续部署流水线，涵盖 Prompt 版本控制、自动评估门禁、灰度发布与回滚机制</description></item><item><title>Prompt 版本管理实践：像管理代码一样管理 Prompt</title><link>https://guijiagi.com/posts/prompt-versioning-practice/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-versioning-practice/</guid><description>Prompt 版本管理的完整实践，覆盖 Git 工作流、A/B 测试框架、Prompt 注册中心、灰度发布与回滚策略</description></item><item><title>RAG 生产环境调试指南：从检索到生成的全链路排障</title><link>https://guijiagi.com/posts/rag-production-debugging/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-production-debugging/</guid><description>系统性梳理 RAG 在生产环境中的常见问题、调试工具链与全链路排障方法论</description></item><item><title>RAG 数据管道构建：从原始数据到高质量知识库</title><link>https://guijiagi.com/posts/rag-data-pipeline/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-data-pipeline/</guid><description>RAG 数据管道的完整构建指南，覆盖数据源接入、清洗标准化、分块策略、嵌入生成、增量更新与质量监控</description></item><item><title>从 ChatGPT 原型到生产系统：迁移避坑指南</title><link>https://guijiagi.com/posts/chatgpt-to-production/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/chatgpt-to-production/</guid><description>从 ChatGPT 原型到生产系统的完整迁移指南，覆盖 API 选型、Prompt 工程化、错误处理、成本估算与团队协作</description></item><item><title>Agent 记忆系统实现：从短期到长期</title><link>https://guijiagi.com/posts/agent-memory-implementation/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-memory-implementation/</guid><description>完整的 Agent 记忆系统设计与实现，涵盖四种记忆类型与工程落地</description></item><item><title>AI 可观测性实践：让你的 Agent 透明可见</title><link>https://guijiagi.com/posts/ai-observability-guide/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-observability-guide/</guid><description>从 Tracing 到 Metrics 的 AI 应用可观测性完整方案，含工具选型与实现</description></item><item><title>LLM 流式输出实现：SSE 与 WebSocket</title><link>https://guijiagi.com/posts/llm-streaming-implementation/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-streaming-implementation/</guid><description>SSE 与 WebSocket 两种流式输出方案的完整实现，含前端渲染与断线重连</description></item><item><title>Prompt 管理平台搭建指南</title><link>https://guijiagi.com/posts/prompt-management-platform/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-management-platform/</guid><description>从需求分析到架构设计，构建企业级 Prompt 管理与版本控制平台</description></item><item><title>RAG 系统生产部署全流程</title><link>https://guijiagi.com/posts/rag-production-deploy/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-production-deploy/</guid><description>从架构设计到容器化部署，完整的 RAG 生产环境落地指南</description></item><item><title>多语言 LLM 部署指南</title><link>https://guijiagi.com/posts/multi-language-llm-deploy/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multi-language-llm-deploy/</guid><description>从语言检测到跨语言检索的完整多语言 LLM 工程化方案</description></item><item><title>AI 客服系统构建指南：从知识库到多轮对话</title><link>https://guijiagi.com/posts/ai-customer-service-build/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-customer-service-build/</guid><description>完整指南：构建生产级 AI 客服系统，涵盖需求分析、知识库构建、意图识别、多轮对话管理、人工转接与满意度评估</description></item><item><title>聊天机器人生产部署全指南</title><link>https://guijiagi.com/posts/chatbot-production-deploy/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/chatbot-production-deploy/</guid><description>从 Docker 容器化到 Nginx 反向代理、SSL 配置、负载均衡、监控告警、日志收集与灰度发布的生产部署完整指南</description></item><item><title>vLLM 部署实战：高吞吐 LLM 推理服务</title><link>https://guijiagi.com/posts/vllm-deployment-guide/</link><pubDate>Wed, 24 Jun 2026 11:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-deployment-guide/</guid><description>vLLM 的架构原理、部署配置和性能调优全指南</description></item><item><title>流式响应开发指南：SSE、WebSocket 与 AI 对话体验优化</title><link>https://guijiagi.com/posts/streaming-response-guide/</link><pubDate>Tue, 23 Jun 2026 15:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/streaming-response-guide/</guid><description>从协议选择到代码实现，全面讲解 AI 应用的流式响应开发</description></item><item><title>Agent 项目成本优化实战：从 Token 到基础设施的全面降本</title><link>https://guijiagi.com/posts/agent-cost-optimization/</link><pubDate>Tue, 23 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-cost-optimization/</guid><description>真实项目中的 Agent 成本优化经验，涵盖模型选择、缓存、批处理等策略</description></item><item><title>2026 年 Agent 开发 LLM 选型指南</title><link>https://guijiagi.com/posts/llm-selection-guide/</link><pubDate>Thu, 11 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-selection-guide/</guid><description>不同 Agent 任务该选哪个 LLM？本文从推理能力、工具调用、成本、上下文窗口等维度全面对比 2026 年主流大模型。</description></item><item><title>MCP Server 开发实战：为 Agent 打造专属工具箱</title><link>https://guijiagi.com/posts/mcp-server-development/</link><pubDate>Tue, 02 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/mcp-server-development/</guid><description>MCP 是 Agent 的 USB 接口。本文手把手教你开发自定义 MCP Server，让 Agent 拥有无限能力。</description></item></channel></rss>