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TutorialsA hands-on tutorial for building a financial report analysis AI Agent from scratch using Cursor editor, Skills definitions, and MiniMax M2.1. Covers setup, architecture, Skills methodology, and multi-language programming.
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Product ReviewsDeep comparison of Qoder, Cursor, Windsurf, and Devin across autonomy, reliability, and context capabilities to help developers choose the right AI coding assistant.
TutorialsLearn how to redirect Claude Agent SDK API requests to local LLMs via LiteLLM Proxy, achieving zero-cost inference while retaining full agent framework capabilities.
TutorialsA systematic four-stage career path for AI/LLM application development: from RAG and Agent fundamentals to architecture design, helping developers transition to AI roles targeting 40K+ monthly salary.
Deep DivesA deep dive into AI Agent development methodology, from the ReAct theoretical framework to a four-layer enterprise tech stack covering model services, Agent types, LangChain, and production deployment.
TutorialsDeep dive into Andrew Ng and Harrison Chase's LangChain course, covering the five core components—Models, Prompts, Indexes, Chains, and Agents—to help developers master LLM app development.
TutorialsA detailed guide to Coze AI development platform's core features including agent building, workflow orchestration, knowledge base setup, and plugins — build custom AI apps with zero code.
TutorialsLearn how to build a ChatBI data analysis Agent from scratch using LangGraph + multi-MCP architecture, covering centralized-to-decentralized evolution, NL2SQL, agent orchestration, and enterprise deployment.
Deep DivesA systematic breakdown of AI's four-stage evolution from Chat Mode to Agentic AI, covering multi-agent architectures, ReAct framework, and MCP protocol.
TutorialsDeep dive into MCP (Model Context Protocol): its core concepts, three communication mechanisms, and ecosystem. Learn how MCP replaces Function Calling with Streamable HTTP and SDK 2.0.
TutorialsIn-depth comparison of LangGraph vs LangChain: controllability, extensibility, and FastAPI-powered performance. Covers storage, enterprise private deployment, and migration guidance for agent developers.
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.
TutorialsA systematic four-stage learning roadmap for programmers transitioning to AI Agent development, covering core theory, ReAct and classic paradigms, Prompt engineering, and hands-on projects.
TutorialsDeep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
TutorialsDeep dive into traditional RAG limitations and Agentic RAG upgrades, with ChatBox source code analysis covering core tool design, intelligent decision flows, and LangGraph implementation for enterprise deployment.
TutorialsHow can frontend engineers advance into AI Agent development? This guide covers LangGraph.js core architecture (state, nodes, edges), LangChain comparison, and workflow agent design with practical examples.
TutorialsDeep dive into the Three-Layer Pyramid Model for Agent development, covering autonomous agents, collaborative multi-agent systems, and universal orchestration agents with a complete learning path from beginner to industrial-grade deployment.