#agent development
4241 related articles
·3 min
NVIDIA XR AI Platform Explained: Full-Stack AI Agent Development for AR Glasses
Deep dive into how NVIDIA's XR AI platform enables AI Agent development for AR glasses through cloud-edge architecture, covering visual perception, voice interaction, and multimodal reasoning.
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·4 min
Loop Engineering Explained: Agent Loop Mechanisms and the New Paradigm of AI Agent Development
Deep dive into Loop Engineering: from Agent Loop principles and While loops to Graph structures, covering loop efficiency optimization and termination strategies for AI agent development.
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·4 min
AI Agent Development: A Complete Six-Week Systematic Learning Roadmap
A systematic six-week learning roadmap for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, deployment, and hands-on projects.
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·4 min
Deep Dive into Six AI Development Tools: Loop Recipe Library, Vercel Agent Framework, and More
Deep analysis of Loop workflow recipes, Vercel's open-source Agent framework, Pyker AI-native project management, Arrow P2P tool, DBX database client, and NVIDIA's Skill Spectre security tool.
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·3 min
TraeHarness Open-Sourced: 18 AI Agents Form a Virtual Development Team
TraeHarness is an open-source multi-agent framework with 18 specialized AI Agents simulating a real software team, covering requirements, architecture, development, testing, and deployment.
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·4 min
Loop Engineering from Beginner to Expert: A Complete Guide to Agent Loop Development
A deep dive into Loop Engineering covering Agent Loop workflows, code implementation (While loops and Graph patterns), and how it differs from Prompt Engineering.
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·2 min
LangChain + MCP Agent Development: A Practical Guide to LLM Selection and Common Pitfalls
A deep dive into LLM selection for LangChain and MCP agent development, comparing DeepSeek V3/R1 vs Qwen3 on Function Calling and MCP support with practical tips.
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·3 min
Building a DeepSeek Agent from Scratch: Principles, Token Optimization, and Bootstrapped Development
Learn how to build a DeepSeek V3 AI Agent from scratch with zero dependencies, covering Agent loop mechanics, token optimization, cache hit strategies, and bootstrapped development.
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·3 min
AI Agent Hands-On Learning Path: A Complete Guide from Beginner to Enterprise-Level Development
A systematic AI Agent development learning roadmap covering prompt engineering, RAG, multi-Agent collaboration, tool calling, and more—with phased learning advice and 28 hands-on project references.
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·3 min
Loopcraft Explained: Loop-Stacking Architecture Design in AI Agent Development
Deep dive into Loopcraft loop-stacking architecture for AI Agent development, covering retry, self-validation, and meta-learning loops to boost reliability.
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·3 min
Beginner's Guide to Agent Skills: Structure Breakdown & Custom AI Skill Development
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.
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·4 min
Complete Guide to Commercial AI Agent Development: From Requirements Analysis to Production Deployment
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.
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·4 min
AI Agent Systematic Learning Path: From Zero to Independent Development
A systematic AI Agent learning path covering core principles, Prompt engineering, RAG, multi-Agent collaboration, and hands-on projects for beginners.
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·4 min
AI Agent Development: A Complete 6-Week Systematic Learning Roadmap
A 6-week systematic learning roadmap for AI Agent development, covering core architecture, ReAct principles, multi-agent collaboration, RAG integration, and deployment.
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·3 min
Four Core Advantages Frontend Developers Have When Transitioning to AI Agent Development
Frontend developers have key advantages for AI Agent development: TypeScript ecosystem fit, low-barrier full-stack bridging, and state management isomorphism. Learn the transition path here.
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·3 min
AI Agent Core Architecture Breakdown: From Concept to Enterprise-Grade Intelligent Agent Development
Deep dive into AI Agent architecture: perception, brain, and action modules. Covers RAG memory systems, tool calling mechanisms, Chain of Thought reasoning, and enterprise agent development roadmap.
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·3 min
Hands-On with Tencent Cloud ADP 4.0: How an Enterprise-Grade Agent Development Platform Tackles the Agent Commercialization Challenge
Hands-on review of Tencent Cloud ADP 4.0: testing its full-lifecycle Agent management — from rapid creation and enterprise integration to automated evaluation and Skill governance for real-world deployment.
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·2 min
AI Agent Development Learning Path: A Practical Guide from Zero to Commercial Deployment
A complete AI Agent development learning path covering theory, frameworks, tool integration, and commercial deployment with real enterprise use cases.
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·3 min
Getting Started with AI Agent Development: A Detailed Three-Stage Learning Roadmap
A complete roadmap for learning AI Agent development from scratch, covering Python & LLM basics, five core skills, and hands-on RAG projects in 1-2 months.
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·4 min
Learning Path for AI Agent Development: A Complete Guide from Core Architecture to Production Deployment
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.
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