575 related articles

A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.

A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.

A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.

Exploring the next evolution in coding agent architecture: decoupling the reasoning core from code execution environments to separate control and execution planes.

Cursor users selecting Grok 4.5 find subagents secretly calling expensive Opus 5, consuming 11% quota per prompt. Analysis of model decoupling, cost transparency, and user strategies.

Deep analysis of AI agent jailbreak and escape incidents, covering prompt injection attacks, permission control failures, and sandbox isolation breakdowns, with practical multi-layer defense strategies.

A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.

A 12-person product team shares real-world experiences with Cursor, Codex, Claude Code, and CodeRabbit—exploring efficiency plateaus, scenario matching, and selection criteria for AI coding tools that actually stick.

Coze is ByteDance's homegrown agent-building platform. This article covers getting started with Coze, its comparison with Dify, skill system, workflow orchestration, and multi-agent collaboration.

Coze is ByteDance's homegrown agent-building platform. This article explains getting started with Coze, comparison with Dify, its skill system, workflow orchestration, and multi-agent collaboration.

A systematic guide to the complete learning path for AI Agent development—covering prompt engineering, RAG knowledge bases, LangChain & LangGraph, fine-tuning, and multi-agent collaboration.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM basics, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM fundamentals, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.

A complete guide to learning AI Agents: from large model fundamentals and core technologies to hands-on projects. Systematically outlines beginner methods and exposes crash-course marketing traps.

The RingCentral China Hackathon, themed on Agentic AI, gathered top engineering teams. This article explores agent AI's evolution, champion team Stargate, and China's developer culture.

The RingCentral China Hackathon, themed on Agentic AI, gathered top engineering teams. This article explores the evolution of agentic AI, champion team Stargate's engineering skill, and the unique value of China's developer culture.

The RingCentral China Hackathon, themed on Agentic AI, gathered top engineering teams. This article explores agent AI's evolution, champion team Stargate, and China's unique developer culture.

Want to become an AI Agent engineer? This article breaks down a 4-week roadmap: from core agent architecture and ReAct, to multi-agent collaboration and real projects.

A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.