#MetaGPT
80 related articles
·7 min
DryFox v0.3.3: AI Agent Team Collaboration + Composable UI Panels Explained
In-depth look at DryFox v0.3.3's three core features: multi-role agent team collaboration, one-click reusable team templates, and block-style composable UI panels. With Stop Hook, file mailbox comms, and hot-reload plugins.
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·5 min
A Programmer's Guide to Large Language Models: The Complete Path from Prompts to Agents
A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.
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·2 min
Coze 3.0 Multi-Agent Collaboration: A Complete Guide to Building Your AI Team
A hands-on guide to Coze 3.0 multi-user, multi-Agent projects: create projects, add members, toggle Agents, and use @ mentions to dispatch tasks efficiently.
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·2 min
Flock: Building an AI Development Squad with Claude Code to Reshape Team Programming Workflows
Flock is a multi-agent development tool built on Claude Code. With roles like Planner, Coder, Tester, and Reviewer, it turns AI coding into a traceable development pipeline.
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·2 min
WorkBuddy Open-Source Project: 16 Functions for Fully Automated AI-Powered Lead Generation on Douyin
Deep dive into WorkBuddy, an open-source project using 16 functions and AI Agent tech to fully automate Douyin lead generation with human-like browser control.
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·4 min
Deep Dive into Alibaba's AgentScope 2.0: Six Core Upgrades and Agent Design Patterns Explained
Deep analysis of Alibaba's AgentScope 2.0 multi-agent framework: six core upgrades including event systems, security interception, HITL, and workspace systems, plus ReAct vs Plan-and-Execute agent design patterns.
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·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.
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·4 min
AI Agent Learning Roadmap for Beginners: A Three-Stage Journey from Fundamentals to Hands-On Practice
A systematic AI Agent learning roadmap for beginners covering core theory, the ReAct paradigm, and multi-agent collaboration, with hands-on project suggestions.
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·3 min
Breaking Into AI as an Ordinary Person: No Model Training Required — You Can Still Earn $10K+ Monthly by Finding the Right Niche
How can ordinary people break into AI and earn money? This guide covers three entry strategies: zero-barrier data annotation and prompt engineering, career changers becoming AI app engineers, and degree holders diving into algorithms.
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·3 min
LangGraph Beginner's Guide: Core Advantages, Deployment Options, and Complete Learning Path
A comprehensive guide to LangGraph's core advantages, storage mechanisms, differences from LangChain, and private deployment options for building production-ready AI agents.
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·3 min
AI Agent Beginner's Guide: A Complete Four-Stage Learning Path
A complete learning path for AI Agent development from scratch, covering core theory, ReAct paradigm, multi-agent collaboration, Prompt optimization, and hands-on projects across four stages.
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·4 min
AI Large Language Model Career Transition Roadmap: A Three-Phase Learning Guide from Zero to Enterprise-Ready
A systematic three-phase AI LLM career transition roadmap: from Transformer fundamentals to RAG, Agent & LangChain development, to LoRA fine-tuning. Build enterprise-ready skills in two months.
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·3 min
748-Episode AI Large Language Model Development Tutorial: Seven Core Modules from Zero to Project Deployment
Analysis of a 748-episode, 198-hour AI LLM development tutorial covering API integration, prompt engineering, RAG, AI Agents, fine-tuning, multimodal development, and deployment.
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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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·3 min
The Complete Skill Map for AI Application Engineers: A Progressive Roadmap from Fundamentals to Production
A systematic breakdown of the complete skill structure for AI application engineers, covering Python & deep learning fundamentals, small model engineering, LLM fine-tuning, Agent development, and enterprise projects.
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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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·2 min
The Essential Difference Between Skill and MCP: A Kitchen Analogy That Makes It Crystal Clear
Skill and MCP are two easily confused core concepts in AI Agent development. This article uses a kitchen analogy to explain how Skill (recipe/methodology) and MCP (kitchen assistant/tool connection) differ and work together.
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·3 min
Coze Workflow Development Tutorial: A Complete Guide to Building AI Apps with Zero Code
Complete guide to Coze workflow development covering Agent building, node orchestration, plugin systems, API integration, and a Coze vs Dify comparison.
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·4 min
Harness Engineering in Practice: Taming AI Agents with Hermes Agent
Deep dive into Harness Engineering: using the open-source Hermes Agent framework's four-layer memory system and Skill evolution to build controllable, evolvable AI agents.
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·3 min
One Person + AI Agent Team: Building a Web Game from Idea to Finished Product
A developer built a self-designed AI Agent collaboration system that turns a one-sentence idea into a complete playable Web game, auto-generating GDD docs and code.
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