72 related articles

What is an AI Agent? This guide explains the key differences between LLMs and Agents, breaks down the Agent formula (LLM + Workflow + Knowledge Base), and compares tools like Dify, Coze, LangChain, and LlamaIndex.

A systematic guide to the full DeepSeek Agent development process: covering prompt engineering, the ReAct framework, workflow orchestration, local deployment, and business requirement breakdown for commercial-ready AI Agents.

A complete guide to Dify's core features and 1.8.0 deployment. Covers 5 app types, Docker setup, Workflow vs Chatflow differences, and RAG knowledge bases for beginners.

A complete AI Agent learning roadmap covering agent principles, prompt engineering, RAG, multi-agent systems, and hands-on projects — from zero to real-world deployment.

Prompt engineering and RAG are just the basics. Real enterprise AI runs on Agents. Explore the 4 stages of LLM deployment, Agent core capabilities, and industry trends.

Want to break into AI application development? This guide covers the full learning path — from Agents and RAG to Prompt Engineering — helping you master LLM engineering skills and land the job.

A deep dive into Agent Skills: from basic prompts to fully encapsulated AI capability units. Five levels of human-AI interaction evolution, with clear distinctions between Skills, MCP, and Workflow.

A systematic guide to Coze's core positioning, its differences from Dify/n8n, and its full capability system covering agents, workflows, and multi-agent modes—helping beginners get started fast.

An in-depth walkthrough of deploying Dify 1.8.0 and building applications: three-step Docker deployment, five app types compared, and Workflow vs Chatflow use cases—build enterprise AI apps with zero code.

A hands-on guide to building an enterprise-grade AI Agent workflow orchestration app with Electron Forge and LangGraph, covering local LLM deployment (Qwen3-0.6B), node-based visual canvas design, and full Function Calling integration.

A hands-on guide to Coze 3.0 multi-user, multi-Agent projects: create projects, add members, toggle Agents, and use @ mentions to dispatch tasks efficiently.

A practical LangGraph.js guide for frontend engineers covering LangGraph vs LangChain comparison, workflow vs general-purpose agent types, and layered Agent architecture design.

A systematic guide to three AI development modes: chat-based, Agent, and AI IDE. Covers model selection, cost comparison, and use cases for beginners.

Learn how to build 6 testing agents using AI Skills for test case generation, Xmind mind maps, performance reports, JMeter scripts, and more — saving 3-4 hours daily with no coding required.

Complete guide to Coze workflow development covering Agent building, node orchestration, plugin systems, API integration, and a Coze vs Dify comparison.

Microsoft Build 2026 unveils MAI Thinking-E, its first in-house reasoning model with 1T MoE architecture, plus 6 vertical AI models. Deep dive into performance, strategy, and industry trends.

Complete guide to commercial AI agent development from scratch, covering requirements analysis, architecture design (ReAct framework, deep search, intent recognition), hands-on Coze platform implementation, workflow creation, and production deployment.

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.

A systematic AI Agent learning path covering core principles, Prompt engineering, RAG, multi-Agent collaboration, and hands-on projects for beginners.

A 6-week systematic learning roadmap for AI Agent development, covering core architecture, ReAct principles, multi-agent collaboration, RAG integration, and deployment.