112 related articles

Skill and MCP are two easily confused core concepts in AI Agent development. This article uses a kitchen analogy to explain how Skill (recipe/methodology) and MCP (kitchen assistant/tool connection) differ and work together.

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

Deep dive into Harness Engineering: using the open-source Hermes Agent framework's four-layer memory system and Skill evolution to build controllable, evolvable AI agents.

A developer built a self-designed AI Agent collaboration system that turns a one-sentence idea into a complete playable Web game, auto-generating GDD docs and code.

Testing Claude Code, Codex, DeepSeek & MiniMax simultaneously, all four AI models wrote files to the same path. A real-world lesson in multi-model isolation.

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.

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.

A detailed AI LLM learning roadmap covering Transformer architecture, Prompt Engineering, RAG, Agent development, model fine-tuning & deployment, with enterprise project guides.

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.

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

Learn how to configure Open Cloud for multi-Agent communication, including session_visibility, agent_to_agent toggle, and whitelist setup, plus Feishu group chat orchestration for AI team collaboration.

A complete learning path for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and lightweight deployment to guide developers from basics to production.

A systematic AI Agent development roadmap covering core concepts, ReAct paradigm principles, multi-agent collaboration, and hands-on projects across four stages to master agent development in 2-3 months.

Open-source AI Agent tutorial project with 2600+ GitHub Stars covering multi-agent systems, memory, planning, and reasoning loops via Jupyter Notebooks for hands-on learning.

Deep dive into OpenAgent, an open-source AI assistant featuring Computer Use, Browser Use, and Coding Agent capabilities, built on LLM + RAG + Agent Loops.

A deep dive into AI Agent principles, core architecture, and practical applications. Learn how Agents differ from LLMs and how to leverage Agent Skills to boost productivity.

A comprehensive guide to Vibe Coding's three tool categories: Agent frameworks, CLI Coding, and IDE tools, with practical examples including Snake game and data analysis workbench.

A junior student uses Cursor and Vibe Coding to build a multi-agent system with 51 AI officials modeled on China's Three Departments and Six Ministries, featuring task distribution, approval workflows, and Token cost visualization.

A systematic four-stage learning roadmap for AI Agent development, covering core concepts, classic paradigms like ReAct, multi-agent collaboration frameworks, and hands-on projects to master Agent development skills in 2-3 months.

Step-by-step guide to configuring CreateNow agents with DeepSeek, Kimi, and Xiaomi LLMs. Covers one-click setup, custom model integration, and API Key acquisition for building AI digital employees.