264 related articles
TutorialsHow Hooks+Skills+Commands+Agents work together in Claude Code to boost AI skill activation from 25% to 90%, with core config files and deployment guide.
TutorialsDeep dive into Claude Code Hooks' five trigger points (PreToolUse, PostToolUse, OnToolError, Notification, OnPrompt) with a practical file deletion protection example to build efficient automated dev workflows.
Product ReviewsTwo-week in-depth review of Warp AI coding tool, comparing it with Cursor on Agent mode, MCP support, free credits, and Claude Opus 4.5 to help developers choose the right AI coding tool.
TutorialsDeep dive into Spring AI and MCP protocol integration, covering tool calling, OAuth security, horizontal scaling, and context optimization for enterprise AI Agent services.
TutorialsLearn how to auto-generate high-quality CRUD code using Claude Code with MCP and Skill files. Covers MySQL MCP setup, Skill file writing, TDD patterns, and pagination optimization.
Deep DivesDeep dive into Cursor Skills' underlying principles, from Function Call and MCP protocol to Workflow Agent, with Spring AI Alibaba practical demo for any LLM.
TutorialsFix Claude Code's amnesia problem. Use 3 documents and 4 slash commands to transform AI from a stateless code assistant into a project manager with memory, boosting efficiency 13x.
TutorialsLearn how Java developers can build MCP Server and Client using Spring AI Alibaba, define tools with @Tool annotations, and integrate with AI clients like Trae for LLM-powered business data access.
TutorialsDeep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
TutorialsDeep dive into MCP (Model Context Protocol) principles and practical applications. Learn how LLMs connect to external tools via MCP to become agents, covering Java tech stacks, MCP Server ecosystem, Cherry Studio demos, and A2A protocol comparison.
TutorialsA comprehensive guide to Spring AI covering LLM integration, prompt engineering, RAG knowledge bases, and five AI Agent patterns, with three enterprise projects for Java engineers.
Product ReviewsAn indie game developer shares practical experience using AI tools for game development, including generating cutscenes in 5 minutes with AI, implementing AAA-level character animations, and building a complete AI music, voice, and animation workflow.
TutorialsDeep dive into LangGraph's core graph structure design, single and multi-agent collaboration patterns, MCP protocol integration, and Time Travel fault-tolerance, with enterprise-level hybrid multi-agent architecture implementation.
TutorialsDeep dive into LangGraph multi-agent architecture covering Graph structure principles, MCP service integration, Time Travel debugging, and supervised multi-agent enterprise implementation patterns.
Tech FrontiersThis week's tech roundup analyzes OpenAI's Swarm Agent framework, Anthropic's Claude data visualization app, Kali Linux, Unikraft lightweight OS, and Go Blueprint — covering AI, security, and cloud computing.
TutorialsSpring AI is the LangChain for Java, helping Java developers integrate LLMs using Spring Boot conventions. This guide covers its 6 core features, setup requirements, and enterprise positioning including RAG, Tool Calling, and Chat Memory.
Tech FrontiersGLM5 code leak reveals 745B-parameter MoE architecture replicating DeepSeek V3. DeepSeek V4 may launch a 200B quantized model first, with flagship exceeding 1T parameters.
TutorialsIn-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
TutorialsDeep dive into LangChain's three core concepts—Components, Chains, and Agents. Learn how this open-source framework connects LLMs to the external world and helps developers build enterprise AI apps.
TutorialsA complete skill tree for frontend developers transitioning to AI full-stack engineers, covering TypeScript, NestJS, LangChain JS, RAG, vector databases, and Tauri 2 with a clear learning roadmap.