Exploring programming, architecture, and the future of technology
Production-proven strategies to reduce LLM API costs by 60-80% without sacrificing quality. Covers token optimization, caching, model routing, and async processing with code examples.
An honest, hands-on comparison of the three dominant AI coding assistants. Real performance tests, pricing breakdown, and a decision framework to choose the right tool for your workflow.
A comprehensive guide to securing AI applications. Covers prompt injection, data leakage, model poisoning, and compliance frameworks with practical code examples.
A comprehensive guide to building and launching a SaaS business in 2026. Covers tech stack, validation, pricing, marketing, and everything between idea and first customer.
A hands-on guide to building production-ready AI agents using Claude Code. Learn agentic patterns, tool integration, and multi-step workflows that actually work.
A comprehensive guide to architecting production React applications at scale. Covers React 19 patterns, performance optimization, AI integration, and team scaling strategies.
A hands-on guide for Python developers transitioning to Go. Covers syntax differences, concurrency patterns, type system, and real-world examples with side-by-side comparisons.
A comprehensive guide to building, deploying, and scaling Model Context Protocol servers. Learn authentication, rate limiting, error handling, and production patterns.
A comprehensive guide to acing system design interviews in 2026. Covers traditional distributed systems plus AI-native architectures, LLM-powered apps, and vector databases.
An in-depth comparison of vector databases in 2026: Pinecone, Weaviate, pgvector, Chroma, Qdrant, and Milvus. Features, pricing, performance, and recommendations.
A practical guide to observability for production web applications. Covers OpenTelemetry, distributed tracing, cost optimization, and the modern observability stack.
Claude Code 不只是代码补全工具，它是新一代 AI 软件工程平台。深入探讨如何在生产环境中规模化使用 Claude Code，涵盖高级模式、团队协作、自动化集成和最佳实践。
Why does your LLM app work in testing but fail in production? Build a systematic evaluation framework that catches failures before users do.
Production LLM systems fail silently. Learn how to implement comprehensive observability: distributed tracing for agent workflows, cost attribution, prompt versioning telemetry, and debugging strategies for when AI goes wrong.
Stop guessing with prompts. Learn the systematic patterns that separate amateur prompt hacking from production-grade LLM interactions: structured outputs, chaining strategies, defensive prompting, and more.
如何用 AI 提升技术文档、博客和方案设计的写作效率？分享我实践一年的 AI 写作工作流，包括提示工程技巧、内容审查策略和保持个人风格的秘诀。
代码冲突、回滚困难、发布混乱？分享我 8 年来在多个团队中实践和迭代的 Git 工作流，包括分支策略、Commit 规范、Code Review 流程和 CI/CD 集成。
凌晨 3 点被报警叫醒？面对生产事故手足无措？分享我 5 年处理 100+ 起事故的实战经验，建立从事前预防到事后复盘的全流程体系。
担心代码泄露给云端 AI？不想每月支付 API 费用？分享我构建本地 LLM 工作流的经验：从硬件选型到模型选择，打造完全离线的 AI 编程环境。
深入解析 Model Context Protocol，Anthropic 推出的开放标准如何让 AI 应用像插 USB 一样连接数据源，并手把手教你构建第一个 MCP Server。
为什么你的 RAG 应用在生产环境表现不佳？深入解析检索增强生成的工程实践，涵盖分块策略、重排序、向量数据库选型、缓存机制和评估体系。
从 OWASP Top 10 到安全开发生命周期，如何在日常开发中构建安全防线？分享我在处理 30+ 安全事件后总结的安全工程实践，让安全成为开发流程的自然部分。
为什么我还在用终端？因为配置好的终端比任何 GUI 都快 10 倍。分享我 5 年迭代的终端工作流：从 shell 选择到现代 Rust 工具链，打造极致效率的命令行环境。
AI agents are the next evolution in LLM applications. Deep dive into agent architecture, the ReAct pattern, tool use, memory management, and building production-ready multi-agent systems.
为什么你的网站加载慢？分享系统化的性能优化方法论，从度量指标到具体优化技巧，涵盖图片、代码、网络和渲染四大维度的实战经验。
为什么你的测试总是跟不上代码变更？分享我团队 3 年迭代出的测试策略，包括测试金字塔实践、Mock 的艺术、以及如何让测试成为开发加速器而非负担。
容器化不是魔法，而是一套工程实践。分享我 5 年来使用 Docker 的经验教训，包括镜像优化、多阶段构建、安全加固和 CI/CD 集成。
为什么你的应用越来越慢？80% 的性能问题来自数据库。分享我 6 年来在 PostgreSQL 和 MySQL 上的优化经验，包括索引策略、查询优化和架构设计模式。
从 Copilot 到 Cursor，从代码补全到 Agent 模式。分享我如何用 AI 重构开发工作流，以及为什么我认为 AI Native IDE 是编程的未来。
RESTful 还是 GraphQL？版本控制怎么做？错误响应如何设计？分享我设计 50+ API 的实战经验，以及那些踩过的坑和学到的教训。
A comprehensive guide to building production-ready AI systems in 2026
Master TypeScript's type system with advanced patterns including conditional types, mapped types, template literals, and real-world architectural patterns.
Transition from JavaScript to Rust. Learn memory safety, ownership, and why companies like Discord and Cloudflare are rewriting performance-critical code in Rust.
From prompt engineering to production deployment: a comprehensive guide to building robust AI-powered applications that scale.
A practical guide to designing scalable systems. Learn real-world patterns used by companies like Netflix, Uber, and Stripe.