#Agent development
138 related articles
·2 min
Firebase Agent Skills Explained: An All-in-One AI Agent Development Solution
Deep dive into Firebase Agent Skills architecture covering Firestore data backend, Firebase Auth, and AI Logic — three core components for building AI agent apps.
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·4 min
Five Common Misconceptions in AI Agent Development: An Essential Guide Before You Start
Debunking 5 common AI Agent development misconceptions: Agents aren't smarter ChatGPTs, complexity doesn't equal power, and RAG can't cure hallucinations. Learn the right approach to building Agents.
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·3 min
Firebase Integrates with AI Studio: Four Core Capabilities for Production-Grade Agent Applications
Deep dive into Google Firebase's integration with AI Studio, covering four core capabilities—database auto-configuration, authentication, security rules drafting, and zero-config deployment—for production-grade AI agent apps.
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·4 min
OpenAI Swarm Framework Explained: The Core Mechanisms of Function Call and Handoff
Deep dive into OpenAI Swarm multi-agent orchestration framework, explaining Function Call tool invocation and Handoff task transfer mechanisms with local deployment guide.
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·2 min
Andrew Ng's Agent Skills Course Explained: Building Reusable Professional Skills for AI Agents
Deep dive into Andrew Ng's Agent Skills course with Anthropic, covering Skills architecture, progressive loading, MCP integration, and hands-on examples for building reusable AI agent skills.
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Tutorials·2 min
Cursor Multi-Agent in Practice: Building a Full-Stack Next.js Blog in 50 Minutes
Build a full-stack blog in 50 minutes using Cursor IDE's multi-Agent mode with Next.js, Clerk auth, and Supabase. Learn the 4-phase AI Agent workflow and key integration pitfalls.
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Tutorials·3 min
ReAct vs. CodeAct: Two Core Approaches to Agent Tool Calling
In-depth comparison of ReAct and CodeAct — two core Agent tool-calling architectures. From paper principles to code implementation, learn the trade-offs between reasoning+action and code execution.
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Tutorials·2 min
Building a Financial Analysis Agent with Cursor + MCP: From Architecture Design to Production Deployment
A complete guide to building a financial analysis Agent system from scratch using Cursor AI and MCP protocol, covering three-layer architecture design, MCP Server development, and production deployment.
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Tutorials·2 min
Understanding Function Calling and MCP Through Cursor's System Prompt
Deep dive into Function Calling and MCP working principles through Cursor editor's system prompt analysis, comparing regular tools vs MCP tools and testing Agent capabilities across model sizes.
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Tutorials·1 min
Spring AI Alibaba Agent Framework: Three-Layer Architecture and Learning Path
Deep dive into Spring AI Alibaba Agent Framework's three-layer architecture: Spring AI foundation, Graph framework, and Agent Framework, with a recommended learning path for Java developers.
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Tutorials·3 min
MCP vs CLI: 40x Token Cost Difference — How AI Engineers Should Choose
In-depth comparison of MCP vs CLI architecture, Token costs (CLI ~1400 vs MCP ~54600), security mechanisms, and use cases with practical selection guidance for AI engineers.
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Tutorials·3 min
Getting Started with AI Agent Development: A Complete Learning Path from Concepts to Practice
A comprehensive guide to AI Agent development for beginners, covering core concepts, market outlook, LangChain framework, RAG knowledge bases, and hands-on projects to systematically master intelligent agent development skills.
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Tutorials·3 min
Fully Automated Invoice Reimbursement with Local AI Agent: From Process Breakdown to Deployment
How to build a fully automated invoice reimbursement system with local AI Agents, covering OCR, info extraction, and form generation with MinerU+Qwen3+Qianwen Po.
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Tutorials·3 min
MCP Protocol Explained: Differences from Function Calling and Agent Tool Development in Practice
Deep dive into MCP (Model Context Protocol): its principles, communication architecture, and practical applications. Compare MCP vs Function Calling, explore client-server communication and security.
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Tutorials·2 min
Anthropic's Official MCP Tutorial: From Protocol Principles to Production Deployment
Deep dive into Anthropic's open-source MCP protocol, covering client-server architecture, tool calling mechanisms, MCP server development, and remote deployment for standardized AI integration.
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Deep Dives·3 min
MCP (Model Context Protocol): Solving the Three Core Pain Points of AI Tool Calling
Deep dive into how MCP (Model Context Protocol) solves three core pain points of Tool Calling: verbose descriptions, unstable invocations, and lack of unified standards.
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Deep Dives·3 min
MCP Protocol Explained: The Unified Standard and Complete Workflow for LLM Tool Calling
Deep dive into MCP (Model Context Protocol): core concepts, role definitions, and complete workflow. Learn how MCP Server, Client, and Host work together to standardize LLM tool calling.
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Industry Insights·3 min
The Survival Crisis and Transformation Path for Traditional Programmers in the AI Coding Wave
Since 2025, AI-driven tech layoffs intensify with 75% of coding work coverable by AI. This article analyzes programmers' structural elimination crisis and the transformation path from code workers to AI architects.
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Tech Frontiers·3 min
Rent a Human Platform: AI Hiring Humans to Do Work — The Truth Behind 700,000 Sign-ups
Rent a Human lets AI Agents hire humans for physical tasks, with 700K+ sign-ups. Deep analysis of how AI hiring humans works, its gig economy ties, and implications for human-machine collaboration.
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Product Reviews·3 min
Deep Dive into Coze Agent World: When AI Gets Identity and Social Freedom
Deep analysis of Coze's Agent World update, covering AI identity systems, Agent social networks, Skill markets, and the paradigm shift from tools to digital companions.
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