#HyDE
36 related articles
·7 min
The Agent Engineer Transition Roadmap: A Deep Dive into Three Core Skill Systems
Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.
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·6 min
Complete Guide to Deploying Dify Locally: Docker + Ollama + RAG Setup Tutorial
A detailed guide to deploying the Dify agent platform locally: from Docker setup and integrating Ollama + DeepSeek local LLMs to workflow orchestration and RAG knowledge base construction.
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·7 min
6 Core Standards of a High-Value Agent Project That Impress Interviewers
Most Agent projects lack competitiveness in interviews due to missing business value and engineering depth. This article breaks down the 6 core standards of high-value Agent projects.
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·4 min
Career Switch to LLM Development: A Four-Level Skill Progression Roadmap
Want to switch careers into LLM development but don't know where to start? This guide breaks down a four-level skill roadmap — from basics and API calls to RAG, fine-tuning, Agent development, and multimodal — to help you build real AI career value.
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·6 min
A Beginner's Guide to AI Agents: How Large Models Are Driving a New Computing Revolution
What is an AI Agent? This article systematically explains the core architecture of AI agents (LLM + Planning + Memory + Tools), how they differ from ChatGPT, their combination with robots, and why developers must master Agent development skills.
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·6 min
Coze from Scratch: A Complete Guide to Building Multi-Agent Collaboration
A detailed guide to Coze's core features: cross-platform interoperability, the Skills system, multi-agent collaboration, and workflow building. Compare Coze and Dify to build practical AI apps with zero coding.
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·6 min
Getting Started with Vibe Coding: Building Software with Natural Language from Scratch
Vibe Coding lets you build software with no coding background—just talk to AI in natural language. Learn its core ideas, learning path, and practical tools.
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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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·6 min
LangChain 1.0 Comprehensive Guide: Three Core Frameworks and Hands-On AI Application Development
Deep dive into LangChain 1.0's architecture: LangChain framework, LangGraph multi-Agent orchestration, and LangSmith observability platform, with hands-on RAG and intelligent customer service projects.
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·6 min
Java Developer's Guide to AI Application Development: Building an Airline Intelligent Customer Service System
A practical guide for Java developers to build AI apps without switching to Python. Learn LangChain4j, RAG, Function Calling, and MCP through an airline customer service project.
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Three Role Shifts for Engineers in the…
·4 min
Three Role Shifts for Engineers in the AI Agent Era: From Coders to System Designers
As AI Agents handle long-horizon autonomous tasks, engineers are shifting from writing code to setting direction, reviewing output, and designing systems around models.
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Keurig Pod Coffee Machines: Quality Co…
·2 min
Keurig Pod Coffee Machines: Quality Compromises and Environmental Costs Behind the Convenience Revolution
Keurig redefined American coffee habits with a tiny pod — but sparked debates over quality and environmental impact. A deep dive into convenience vs. sustainability.
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·2 min
Why Banks and Hospitals Must Use Local AI: A Complete Guide to Private Large Model Deployment
Why do banks and hospitals build Local AI instead of using cloud services? This guide covers the full tech stack — Ollama, RAG, vector databases — and real-world enterprise deployment use cases.
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·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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Tutorials·3 min
Enterprise RAG Project in Practice: A Complete Guide from Principles to Deployment
Complete guide to enterprise RAG projects covering principles, LangChain implementation, data processing, retrieval optimization, evaluation, and cloud deployment for AI knowledge base applications.
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Tutorials·3 min
Can You Really Transition to AI/LLM in Three Months? A Deep Dive into the Learning Roadmap
Deep dive into a popular 3-month AI/LLM transition roadmap: from Python basics and Prompt engineering to LangChain, RAG, Agents, and hands-on projects, with realistic time estimates and pitfall warnings.
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