#agent development
4215 related articles
·7 min
Agentic AI Development in Practice: Evaluation and Error Analysis Are the Real Competitive Edge
Cut through the Agentic AI hype to see the real value of agentic applications. Based on Andrew Ng's course, learn why Evals and error analysis—not framework choice—separate top developers.
Read more →
·6 min
Getting Started with LangChain: Unified Interfaces and Agent Development Explained
A beginner's guide to the LangChain open-source framework: explaining how to use the init_chat_model unified interface, tips for disabling DeepSeek's thinking mode, and core essentials of Agent development.
Read more →
·2 min
MCP Protocol Deep Dive: The Unified Standard and Practical Guide for Agent Development
Deep dive into MCP (Model Context Protocol): core principles, communication mechanisms, and security design. Learn how MCP replaces Function Calling and enables remote agent-tool integration.
Read more →
·4 min
Enterprise AI Agent Development Guide: Multi-Task Recognition and Dynamic Tool Calling in Practice
A deep dive into AI Agent architecture and enterprise deployment. From LangChain and ReAct design to dynamic tool calling and multi-task recognition — build autonomous enterprise AI assistants.
Read more →
·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.
Read more →
·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.
Read more →
·3 min
Harness Architecture Explained: The Next-Generation Design Paradigm for Agent Development
A deep dive into Harness Architecture — the next-gen Agent design paradigm. Covers its evolution from prompt engineering and context engineering, multi-agent collaboration, sandbox security, feedback loops, and why it's a must-have for LLM developer interviews.
Read more →
·3 min
Benchmarking Popular Claude Skill Libraries: A 5-Step Core Pattern for AI Agent Development
A deep-dive evaluation of Addy Osmani, Matt Pocock, and Gary Tan's skill libraries, distilling a 5-step Research→Prototype→Plan→Build→Test agent dev loop and why the best skill system is always your own.
Read more →
·2 min
AIVenture: Master Agent Development and Vibe Coding Through a Dungeon Game
AIVenture is an open-source retro dungeon game by Google that teaches Vibe Coding, agentic workflows, and tool calling through playable levels. Built with Angular, Phaser.js, and Gemma.
Read more →
·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
Read more →
·7 min
Getting Started with LangGraph Multi-Agent Development: Architecture Analysis and Three Practical Case Studies
Learn LangGraph multi-agent development covering Supervisor and Collaboration architectures, with three hands-on projects: code assistant, prompt assistant, and WebRTC digital human.
Read more →
·6 min
The New Normal of AI Programming: How Autonomous Agent Development Is Reshaping Software Engineering
AI Agent autonomous programming is evolving from niche experiments to the industry default. This article analyzes the three stages of AI-assisted programming, its impact on developer skills, process restructuring, and key challenges.
Read more →
·3 min
6-Week AI Agent Development Learning Roadmap: A Complete Guide from Zero to Project Deployment
A systematic 6-week AI Agent development roadmap covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and deployment for beginners to build production-ready agents.
Read more →
·4 min
LangGraph.js Practical Guide: A Frontend Engineer's Path to AI Agent Development
A practical LangGraph.js guide for frontend engineers covering LangGraph vs LangChain comparison, workflow vs general-purpose agent types, and layered Agent architecture design.
Read more →
·4 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Plan from Zero to Production
A systematic AI Agent development learning roadmap covering LLM fundamentals, ReAct paradigm, memory & tool calling, and multi-agent collaboration across four stages with project suggestions.
Read more →
·3 min
Getting Started with AI Agent Development: Core Concepts, Architecture, and Practical Essentials
A comprehensive guide to AI Agent development covering core concepts, the Perception-Brain-Action architecture, key differences from chatbots, four essential components, and mainstream framework selection.
Read more →
·3 min
Four Core Modules of AI Agent Development: An Architecture Guide from Failure to Stable Deployment
Deep dive into four core AI Agent modules: system prompts, tool calling, RAG memory, and ReAct workflow orchestration. Solve hallucinations, loops, and build reliable agents.
Read more →
·4 min
Three Modes of AI Development: A Complete Guide from Chat to Agent to IDE
A systematic guide to three AI development modes: chat-based, Agent, and AI IDE. Covers model selection, cost comparison, and use cases for beginners.
Read more →
·3 min
AI Agent Development: A Three-Stage Learning Roadmap from Zero to One
A systematic three-stage AI Agent development roadmap: from Python basics and LLM fundamentals, through five core capabilities like planning and tool use, to hands-on RAG projects for real-world deployment.
Read more →
·3 min
Agent Skills Architecture Explained: A New Paradigm for Modular AI Agent Development
A deep dive into Agent Skills architecture: core concepts, components, and how it works. Clarifies common misconceptions about Skills vs. MCP, and compares Skills with Multi-Agent architecture.
Read more →