Tutorials
598 articles
Tutorials·2 min
LangGraph vs LangChain: How to Choose Your Agent Development Framework
In-depth comparison of LangGraph vs LangChain: controllability, extensibility, and FastAPI-powered performance. Covers storage, enterprise private deployment, and migration guidance for agent developers.
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Tutorials
Codex Desktop App Hands-On Tutorial: 1…
·3 min
Codex Desktop App Hands-On Tutorial: 15 Use Cases from Beginner to Advanced
A detailed guide to 15 core use cases for OpenAI's Codex desktop app, covering file management, website development & deployment, browser control, Computer Use, Skills, MCP services, and automation.
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Tutorials·2 min
Gemini 3.0 Pro + Claude Opus 4.5: A Practical Guide to Dual-Model Programming Workflows
Compare Gemini 3.0 Pro and Claude 4.5 Opus in programming tasks, build a dual-model workflow with KiloCode for architecture planning and code execution.
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Tutorials·3 min
Getting Started with Spring AI: How Java Developers Can Integrate Large Language Models
Spring 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.
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Tutorials·3 min
Claude Code Beginner's Guide: Installation, Cost-Saving Solutions & Source Code Architecture Analysis
Claude Code beginner tutorial covering installation, common issues, low-cost alternatives for budget users, and deep analysis of 8 Agent design patterns revealed by the 510K-line source code leak.
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Tutorials·3 min
From Programmer to Agent Developer: A Detailed Four-Stage Learning Roadmap
A 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.
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Tutorials·3 min
The Complete Guide to Claude Code: From Personal Assistant to AI Agent Development
A systematic breakdown of the Complete Guide to Claude Code course, covering context engineering, MCP protocol, claude.md configuration, multi-Agent architecture, and three progressive projects.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep 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.
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Tutorials·2 min
Five Core Differences Between Claude Code and Traditional AI Chat Tools
Compare Claude Code vs traditional AI chat tools like ChatGPT across 5 dimensions: interaction, context, execution, memory, and tool invocation to decide if this AI coding assistant is right for you.
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Tutorials·3 min
From Traditional RAG to Agentic RAG: Principles Compared and Enterprise-Grade Implementation Guide
Deep 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.
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Tutorials·3 min
Complete Installation & Configuration Guide for VectCut AI Editing Agent: Windows & Mac
Complete guide to installing and configuring VectCut AI Editing Agent on Windows and Mac, covering client download, CapCut draft path setup, and Git Bash installation.
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Tutorials·3 min
Agent Skills Decision Trees: Enabling Autonomous Decision-Making for AI Coding Assistants
Learn how to embed decision tree logic in Agent Skills to give AI coding assistants like Antigravity and Claude Code autonomous decision-making. Includes a Code Review Router case study with complexity scoring and failover.
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Tutorials·3 min
Complete Guide to Connecting Claude Code with DeepSeek-V4
Complete guide on connecting DeepSeek-V4 to Claude Code, covering Node.js installation, environment variable configuration, model mapping, and real-world coding tests for a near-premium AI programming experience with open-source models.
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Tutorials·3 min
Frontend Engineers Leveling Up to AI Agents: LangGraph.js Architecture Design & Practical Guide
How 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.
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Tutorials·2 min
The Three-Layer Pyramid Model for Agent Development: From Beginner to Industrial-Grade Deployment
Deep 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.
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Tutorials·3 min
Getting Started with AI Full-Stack Development: A Knowledge Framework from Machine Learning to Large Language Models
A systematic guide to the relationships between AI, machine learning, deep learning, and large language models, helping developers build a clear knowledge framework and find an efficient learning path.
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Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-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.
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Tutorials·3 min
LangChain Core Concepts Explained: A Complete Guide to Components, Chains, and Agents
Deep 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.
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Tutorials·3 min
RAG Technology Full-Stack Analysis: Core Principles, Enterprise Implementation & Learning Path
Deep analysis of RAG technology's core principles, three key values, enterprise implementation cases, common pitfalls, and a systematic learning roadmap covering vector databases, retrieval optimization, and Knowledge Graph fusion.
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Tutorials·2 min
Huawei Hermes Agent Manual Explained: Five-Layer Memory Architecture and Multi-Agent Collaboration in Practice
Deep dive into Huawei's 100-page Hermes Agent manual: five-layer memory architecture solving AI amnesia, self-evolution loops for continuous optimization, and multi-agent collaboration engineering.
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