#semantic matching
22 related articles
·2 min
RAG Recall Rate Optimization: A Full-Pipeline Funnel Engineering Breakdown from Data Ingestion to Reranking
How to fix low RAG recall? A systematic breakdown covering data ingestion, query processing, retrieval strategy, and reranking—including semantic chunking, HyDE, hybrid search, and Cross-Encoder reranking.
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·4 min
Deconstructing the Core Principles of AI Agents: A Deep Dive into the Control, Perception, and Action Modules
A systematic breakdown of the three core AI Agent modules (Control, Perception, Action), with deep analysis of AutoGPT, BabyAGI, HuggingGPT, LlamaIndex architectures and Chain-of-Thought reasoning.
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·2 min
The Complete Guide to Claude Code Skills: Write Once, Auto-Match On-Demand Knowledge Injection
Deep dive into Claude Code Skills: semantic matching, storage locations, priority rules, and advanced tips. Master on-demand knowledge injection for AI coding.
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·4 min
HAMAS Multi-Agent Framework in Practice: A Guide to Building 5 AI Personas Working in Harmony
Learn how to build a multi-Agent AI team with the HAMAS framework: 5 role configurations, Skill mechanisms, gradient model scheduling, and solutions for AI hallucination and deception.
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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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·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
Beginner's Guide to Agent Skills: Core Components and Customization Methods Explained
Deep dive into Agent Skills: their concept, four core components (skill.md, references, scripts, assets), and how to customize AI skill modules with practical examples.
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·3 min
Compile First: Using AI to Revive the Dormant Files on Your Hard Drive
Explore how the open-source LLM Wiki project uses a compile-first paradigm to turn dormant local files into a searchable AI knowledge base, compared with traditional RAG approaches.
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·3 min
Firebase's Major Upgrade: Real-Time SQL Sync, On-Device AI Inference, and Agent Skills
Firebase unveils major updates at Google I/O 2025: SQL Connect real-time sync, AI Logic on-device inference, Firestore Enterprise full-text search, phone verification GA, and more.
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·3 min
Beginner's Guide to Agent Skills: Structure Breakdown & Custom AI Skill Development
A deep dive into Agent Skill's core concepts and internal structure, covering skill.md, references, scripts, and assets with a restaurant poster Skill example.
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·3 min
Andrew Ng's New Course: A Complete Guide to Enhancing RAG with Knowledge Graphs
Deep dive into Andrew Ng's Knowledge Graphs for RAG course with Neo4j. Learn how knowledge graphs overcome traditional RAG limitations to enable cross-document relationship reasoning.
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·3 min
Xiaomi Open-Sources MiMo Code: Can an Infinite Memory Mechanism Solve AI Coding's Biggest Pain Point?
Xiaomi open-sources MiMo Code, an AI coding tool with infinite memory, multi-Agent collaboration, and Claude Code compatibility — solving context forgetting in large projects.
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·3 min
Complete Guide to MCP Protocol in Claude Code: Configuration, Management, and Context Optimization
Complete guide to MCP protocol in Claude Code: adding servers, configuring three scope levels, and optimizing context windows to efficiently connect external tools and data sources.
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Deep Dives·4 min
AI Hallucinations: Why Large Language Models Inevitably "Make Things Up" and How to Deal With It
Deep dive into AI hallucination's three root causes: training objective flaws, exposure bias, and probabilistic generation. Covers classification and practical mitigation strategies including RAG.
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Tutorials·4 min
MCP Beginner's Guide: Model Context Protocol Architecture and Three Core Primitives Explained
A deep dive into Anthropic's MCP (Model Context Protocol) covering client-server architecture, the three core primitives (Tools, Resources, Prompts), and how developers can quickly integrate with the MCP ecosystem.
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Tutorials·4 min
MCP Beginner's Guide: Model Context Protocol Architecture and Three Core Primitives Explained
A deep dive into Anthropic's MCP (Model Context Protocol) covering client-server architecture and the three core primitives — Tools, Resources, and Prompts — to help developers quickly understand and integrate with the MCP ecosystem.
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Deep Dives
CodeRAG Technical Deep Dive: Four Core…
·3 min
CodeRAG Technical Deep Dive: Four Core Components That Help AI Truly Understand Your Codebase
Deep dive into CodeRAG's four core technologies: vector similarity search, file system tools, Code Knowledge Graph (CKG), and DeepWiki — how they work together to help AI coding assistants truly understand enterprise codebases and eliminate hallucinations.
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Industry Insights
Qoder's Context Engineering in Practic…
·4 min
Qoder's Context Engineering in Practice: Four-Layer Retrieval Engine and Memory System Architecture
Deep analysis of Qoder's (Tongyi Lingma international edition) context engineering architecture, including its four-layer retrieval engine, memory engine, context caching, and core product design.
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Tutorials·2 min
Claude Code Sub-Agent: A Practical Guide to Multi-Agent Collaboration for Enhanced Development Efficiency
Deep dive into Claude Code Sub-Agent mechanism with a practical blog writing + Git commit case study, showing how multi-agent collaboration solves instruction loss and context bloat issues.
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Tutorials·3 min
Deep Agents: Enterprise-Grade Agent Engineering and Deep Research Implementation Guide
Learn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.
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