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126 related articles
·6 min
Reverse-Engineering ChatGPT's Source Selection: What Network Traffic Analysis Reveals About AI Citations
By capturing and analyzing ChatGPT's real network traffic during web retrieval, this article reveals the underlying logic of AI source selection—covering the layered mechanisms of retrieval recall and content filtering, domain preference patterns, and practical insights for content creators and SEO professionals.
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·4 min
Ternlight: A 7MB Browser-Side Embedding Model for Server-Free Semantic Search
Ternlight is a 7MB WebAssembly-based browser-side text embedding model requiring no server or GPU. Explore its tech, use cases, and tradeoffs for private, offline semantic search.
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·4 min
ctx: An Open-Source Tool for Searching Your Local AI Coding Assistant History
ctx is a local-first open-source tool that lets developers search and reuse conversation history from Claude Code, Cursor, and GitHub Copilot without uploading data to the cloud.
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·3 min
Agentic AI in Practice: Core Principles, Engineering Challenges, and Practical Recommendations
A deep dive into Agentic AI: core components (planning, tool calling, memory), engineering challenges (reliability, cost, safety), and practical development recommendations for production deployment.
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·7 min
Spring AI 2.0 in Practice: A Beginner's Guide for Java Developers Building AI Agents
A complete Spring AI 2.0 guide for Java developers covering unified API abstraction, RAG, tool calling, MCP protocol, and enterprise projects to build AI Agents.
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·7 min
Andrew Ng Teams Up with LangChain: Core Principles of LangGraph Agent Development
Andrew Ng and LangChain CEO Harrison Chase present AI Agents in LangGraph, covering five core agent design patterns and LangGraph's graph-based framework for building cyclical agentic workflows.
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·7 min
Andrew Ng Teams Up with LangChain: Core Concepts of LangGraph Agent Development
Andrew Ng and LangChain CEO Harrison Chase's AI Agents in LangGraph course covers five agent design patterns and LangGraph's graph-based framework for building cyclical AI workflows.
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·6 min
5 Critical Engineering Pitfalls in Enterprise RAG Knowledge Base Deployment: The Real Barriers from Demo to Production
Why do enterprise RAG knowledge bases dazzle in demos but fail in production? This article dissects five critical engineering pitfalls with real-world case studies from million-doc platforms and ops agents.
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·5 min
Building RAG from Scratch: Creating a Domain Expert System with Local Small Models
Step-by-step guide to building a complete RAG pipeline with Ollama + LangChain + FAISS + Qwen 1.5B. Run document retrieval and intelligent Q&A locally without a GPU.
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·4 min
12 Open-Source AI Agent Projects Worth Exploring: Frameworks, Skill Packs, and Toolchains
A roundup of 12 trending open-source AI agent projects on GitHub, covering video generation, agent frameworks, skill packs, code engines, security scanning, and voice processing.
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·3 min
Building a RAG Q&A Workflow with Dify: A 4-Step Guide to Enterprise Knowledge Base Chatbots
Learn RAG fundamentals and build an enterprise knowledge base chatbot with Dify in 4 steps: data prep, model config, knowledge base import, and workflow orchestration.
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·2 min
Dify Getting Started Guide: Build Enterprise-Grade AI Apps with Zero Code
Dify is a Chinese open-source AI app platform supporting chatbots, Agents, and workflows. This guide covers Dify 1.8.0 Docker deployment, enterprise use cases, and how to build your first AI app.
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·7 min
Agent Loop Explained: The Core Runtime Mechanism and Think-Act Cycle of AI Agents
Deep dive into Agent Loop mechanics: the think-act cycle, how agents differ from LLMs, termination conditions, and design principles for building autonomous AI Agent systems.
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·6 min
Dify Self-Hosted Deployment in Practice: Building an Enterprise-Grade AI Application Platform from Scratch
A complete guide to self-hosting Dify, the open-source AI platform: environment setup, Docker Compose deployment, LLM integration, and app building. Runs on just 2 cores and 4GB RAM.
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·7 min
AI Agent Memory Layer Comparison: Mem0, Zep, Letta, and Cloudflare — Four Major Solutions Evaluated
In-depth comparison of four AI agent memory layer solutions: Mem0's extract-retrieve approach, Zep's temporal knowledge graphs, Letta's self-editing memory, and Cloudflare Durable Objects as infrastructure primitives.
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·3 min
Dify Comprehensive Guide: The Open-Source Platform for Building AI Apps Without Code
Deep dive into Dify, the open-source LLM app development platform featuring visual workflow engine, RAG knowledge base, Agent capabilities, hundreds of model integrations, Docker deployment, and comparisons with LangChain, Coze, and FastGPT.
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·3 min
The Complete Guide to Building Dify Workflows: A Hands-On Guide to No-Code AI Applications
Complete guide to Dify's five app types, Docker deployment for v1.8.0, and workflow building. Compare Dify vs Coze and learn to build enterprise AI apps with no code.
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·4 min
Dify Local Deployment Tutorial: Build Your AI Application Development Platform from Scratch
Step-by-step guide to deploying Dify locally using BT Panel, covering VM setup, Ubuntu configuration, and Docker deployment for a private AI dev platform.
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·3 min
The Complete Guide to n8n: An Open-Source Automation Platform with 400+ Integrations That Combines Code and Visual Workflows
Deep dive into n8n, the open-source workflow automation platform: 400+ integrations, native AI capabilities, and dual code/visual modes. Covers deployment, AI Agents, community templates, and more.
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·4 min
Building an Enterprise Knowledge Base with RAG: A Complete Guide from Principles to Optimization
A comprehensive guide to building enterprise knowledge bases with RAG, covering vector database selection, text chunking, Embedding models, multi-strategy retrieval, re-ranking, and Agent integration for high-accuracy AI Q&A systems.
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