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388 related articles
·4 min
AI Agent Development: A Complete Six-Week Systematic Learning Roadmap
A systematic six-week learning roadmap for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, deployment, and hands-on projects.
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·3 min
The Complete Skill Map for AI Application Engineers: A Progressive Roadmap from Fundamentals to Production
A systematic breakdown of the complete skill structure for AI application engineers, covering Python & deep learning fundamentals, small model engineering, LLM fine-tuning, Agent development, and enterprise projects.
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·4 min
Is the 748-Episode AI Large Language Model Tutorial on Bilibili Worth Watching? A Full Breakdown of Content Structure and Study Tips
In-depth analysis of Bilibili's 748-episode AI LLM tutorial covering RAG, Agent, and fine-tuning. Includes content structure breakdown and practical study tips for beginners.
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·2 min
Career Switch to AI Software Testing from Scratch: A Complete 3-Month Learning Roadmap
A complete 3-month learning roadmap for switching to AI software testing from scratch, covering fundamentals, Python automation, AI-powered testing, and career guidance.
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·3 min
GitHub AI Weekly Rankings: Agent Infrastructure Projects Dominate, Toolchain Ecosystem Taking Shape
June 2026 Week 1 GitHub AI trends: Agent infrastructure projects like Hedron and MarkItDown dominate, as context compression, document parsing, memory systems, and aesthetic toolchains rapidly mature.
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·3 min
The Complete Guide to OpenAI Codex CLI: From Installation and Configuration to Enterprise-Level Practice
In-depth guide to OpenAI Codex CLI: covering installation, agents.md design, multi-agent collaboration, MCP protocol integration, and a RAG customer service project.
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·3 min
The Complete Evolution of RAG: A Six-Generation Journey from Naive Retrieval to Multimodal
A complete guide to RAG evolution from Naive RAG through Advanced, Agentic, Graph, and Multimodal RAG — covering core techniques, pain points solved, and real-world use cases.
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·4 min
Spring AI vs LangChain4j: How to Choose a Java AI Framework
In-depth comparison of Spring AI and LangChain4j — two major Java AI frameworks — covering core features, completeness, ecosystem support, and usability to help Java developers make the right choice.
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·3 min
Enterprise-Grade RAG Full-Pipeline Optimization: Multi-Turn Conversations, Retrieval Tuning, and Production Engineering in Practice
A deep dive into full-pipeline optimization for enterprise RAG systems, covering multi-turn query rewriting, retrieval tuning, and quality evaluation to take RAG from demo to production.
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·3 min
Andrew Ng and Anthropic's Definitive Claude Code Tutorial: A Deep Dive
Andrew Ng and Anthropic launch a Claude Code course covering context management, parallel sessions, MCP server integration, and hands-on projects in RAG, data analysis, and Figma-to-code conversion.
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·4 min
AI + Java Backend Learning Roadmap: Four Stages from CRUD to Senior AI Engineer
A complete AI + Java backend learning roadmap based on Spring AI Alibaba: from prompt engineering and LLM API integration to RAG knowledge bases and Agent systems across four stages.
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·3 min
Complete Guide to the Coze Platform: Build AI Agents with Zero Code
A deep dive into ByteDance's Coze platform: zero-code AI agent development, China vs. international editions, use cases, and how non-technical users can quickly build AI applications.
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·3 min
AI Agent Hands-On Learning Path: A Complete Guide from Beginner to Enterprise-Level Development
A systematic AI Agent development learning roadmap covering prompt engineering, RAG, multi-Agent collaboration, tool calling, and more—with phased learning advice and 28 hands-on project references.
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·3 min
Harness Engineering in Practice: Building an Enterprise E-Commerce System with Claude Code — A Complete Walkthrough
A deep dive into Harness Engineering for AI programming, from concept to implementation. Build an enterprise Java e-commerce system using Claude Code with Skill-driven AI development pipelines.
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·4 min
AI Full-Stack Development Architecture: A Three-Layer Progressive Path from Prototype to Production
A detailed guide to AI full-stack development architecture covering Node.js+TypeScript+Monorepo engineering, Docker CI/CD deployment, and AI engine design with interview tips.
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·3 min
A Three-Month Roadmap to LLM Development: A Deep Dive into the Learning Path from Zero to Freelancing
A deep dive into the three-step LLM development learning path: from prompt engineering and RAG knowledge bases to AI Agent development, with realistic timelines for beginners and experienced developers.
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·3 min
AI Large Language Model Learning Roadmap: A Systematic Path from Zero to Project Implementation
A detailed AI LLM learning roadmap covering Transformer architecture, Prompt Engineering, RAG, Agent development, model fine-tuning & deployment, with enterprise project guides.
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·4 min
AI Agent Systematic Learning Path: From Zero to Independent Development
A systematic AI Agent learning path covering core principles, Prompt engineering, RAG, multi-Agent collaboration, and hands-on projects for beginners.
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·3 min
AI Large Model Learning Roadmap Breakdown: Three Stages from Application Development to Model Fine-Tuning
Deep breakdown of a popular AI large model learning roadmap covering LangChain, RAG, Agent, and LoRA fine-tuning across three stages, with analysis of its strengths and limitations for career changers.
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·4 min
AI Agent Development: A Complete 6-Week Systematic Learning Roadmap
A 6-week systematic learning roadmap for AI Agent development, covering core architecture, ReAct principles, multi-agent collaboration, RAG integration, and deployment.
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