#agent development
138 related articles
Tutorials
LangGraph 0.5.3 + MCP Agent Developmen…
·2 min
LangGraph 0.5.3 + MCP Agent Development in Practice: Security Authentication & Deployment Guide
LangGraph 0.5.3 introduces MCP server security authentication and agent deployment solutions. Combined with Qwen3 models, it provides a complete production-grade AI agent development stack.
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Tutorials
AI Agent Practical Development: A Comp…
·3 min
AI Agent Practical Development: A Complete Guide from Concept to Building Production-Grade Intelligent Agents
A deep dive into AI Agent core principles and practical development paths, covering perception-decision-execution capabilities, MCP protocol tool integration, and analysis of Manus and AutoGLM.
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Tutorials
CrewAI Multi-Agent Collaboration in Pr…
·2 min
CrewAI Multi-Agent Collaboration in Practice: Core Concepts, Model Comparison & API Deployment
A deep dive into CrewAI's four core concepts for multi-agent collaboration, with hands-on FastAPI deployment and a comparison of GPT-4o-mini, Qwen MAX, and Llama 3.1.
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Tutorials
Practical Guide to Building Multi-Agen…
·3 min
Practical Guide to Building Multi-Agent Collaborative Applications with CrewAI + FastAPI
Learn how to build a multi-Agent collaborative system with CrewAI and FastAPI. Covers Agent, Task, Crew concepts, GPT/Tongyi Qianwen/Ollama integration, with complete code examples and model comparisons.
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Tutorials
Getting Started with LangChain: Core C…
·3 min
Getting Started with LangChain: Core Concepts and Hands-On Guide for LLM and Agent Development
A systematic guide to LangChain's core features, covering LLM vs. Agent concepts, unified interface design, multi-provider support, environment setup, and hands-on code examples for AI app development.
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Deep Dives
Hermes Self-Evolution Framework: An Op…
·3 min
Hermes Self-Evolution Framework: An Open-Source Solution for Automated AI Agent Prompt Optimization
Deep dive into NousResearch's open-source Hermes Agent self-evolution framework, using DSPy and GEPA for automated prompt optimization with five-layer safety mechanisms.
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Tutorials
Why Qwen3 Is the Best Open-Source Mode…
·2 min
Why Qwen3 Is the Best Open-Source Model for MCP Agent Development
Analysis of Qwen3's advantages for MCP agent development, comparing DeepSeek R1's lack of Function Calling, covering MoE architecture and thinking mode switching.
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Tutorials
AI Agent Learning Roadmap: From Beginn…
·3 min
AI Agent Learning Roadmap: From Beginner to Enterprise-Level Development in Three Months
A detailed three-month AI Agent learning roadmap covering LLM basics, ReAct paradigm, LangChain, memory mechanisms, tool calling, and multi-agent collaboration with practical project suggestions.
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Research·2 min
How GitHub Is Building a General-Purpose Accessibility AI Agent: Lessons Learned and Technical Challenges
GitHub is building a general-purpose accessibility AI Agent to automatically detect and fix software accessibility issues. Explore the technical challenges, human-AI collaboration, and industry impact.
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Product Reviews
Warp 2.0 Deep Dive: An AI Development …
·3 min
Warp 2.0 Deep Dive: An AI Development Environment with Multi-Agent Parallelism
Deep dive into Warp 2.0's Agent Development Environment (ADE): multi-agent parallel orchestration, terminal editor, AI coding platform, hands-on SaaS app building, and comparison with Cursor and Claude Code.
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Tutorials·3 min
Building a Financial Report Analysis AI Agent with Cursor + Skills: A Step-by-Step Tutorial from Scratch
A hands-on tutorial for building a financial report analysis AI Agent from scratch using Cursor editor, Skills definitions, and MiniMax M2.1. Covers setup, architecture, Skills methodology, and multi-language programming.
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Tutorials·3 min
Complete Vibe Coding Tutorial: 15 Key Steps to Building an AI Agent from Scratch
A systematic breakdown of 15 key steps for building AI Agents with Vibe Coding, covering environment setup, product docs, frontend UI, backend APIs, databases, and deployment.
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Tutorials·3 min
Claude Agent SDK + LiteLLM + Local LLMs: Building a Zero-Cost AI Agent Platform
Learn how to redirect Claude Agent SDK API requests to local LLMs via LiteLLM Proxy, achieving zero-cost inference while retaining full agent framework capabilities.
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Tutorials·2 min
Career Progression in AI/LLM Application Development: Four Stages from Beginner to 40K Monthly Salary
A systematic four-stage career path for AI/LLM application development: from RAG and Agent fundamentals to architecture design, helping developers transition to AI roles targeting 40K+ monthly salary.
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Deep Dives·2 min
AI Agent Development Methodology: A Complete Guide from ReAct to Enterprise-Grade Tech Stack
A deep dive into AI Agent development methodology, from the ReAct theoretical framework to a four-layer enterprise tech stack covering model services, Agent types, LangChain, and production deployment.
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Tutorials·2 min
Coze Beginner's Guide: A Complete Tutorial for Building AI Agents with Zero Code
A detailed guide to Coze AI development platform's core features including agent building, workflow orchestration, knowledge base setup, and plugins — build custom AI apps with zero code.
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Tutorials·2 min
npcpy: An Open-Source Framework That Rethinks AI Agent Development with Software Engineering Principles
Deep dive into npcpy's four-layer architecture, multi-agent collaboration, knowledge graph lifecycle management, and deployment strategies for building stable, controllable AI Agent systems.
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Tutorials·3 min
MCP Protocol Explained: The New Agent Communication Standard Replacing Function Calling
Deep dive into MCP (Model Context Protocol): its core concepts, three communication mechanisms, and ecosystem. Learn how MCP replaces Function Calling with Streamable HTTP and SDK 2.0.
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Tutorials·2 min
LangGraph vs LangChain: How to Choose Your Agent Development Framework
In-depth comparison of LangGraph vs LangChain: controllability, extensibility, and FastAPI-powered performance. Covers storage, enterprise private deployment, and migration guidance for agent developers.
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Tutorials·3 min
From Programmer to Agent Developer: A Detailed Four-Stage Learning Roadmap
A systematic four-stage learning roadmap for programmers transitioning to AI Agent development, covering core theory, ReAct and classic paradigms, Prompt engineering, and hands-on projects.
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