#MetaGPT
77 related articles
Product Reviews·3 min
Manus Review: A Deep Dive Comparing It to MetaGPT to Reveal the True Capabilities of This AI Agent
A deep review of Manus AI Agent across technology, product, and marketing dimensions, compared with MetaGPT. Core capabilities overlap by 90%+. Is it innovation or packaging?
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·5 min
Loop Engineering Explained: The New Programming Paradigm Where AI Prompts Itself
Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·3 min
From Frontend to Agent Development: A Complete 6-Week Systematic Learning Path
A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy That Makes Everything Click
LLMs aren't search engines — they're more like super compressors. This article explains how large models compress corpora to learn semantic patterns, and explores the principles and limitations of emergent intelligence.
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·3 min
Coze Agent Development in Practice: From Beginner to Multi-Agent Collaboration
Coze is ByteDance's homegrown agent-building platform. This article covers getting started with Coze, its comparison with Dify, skill system, workflow orchestration, and multi-agent collaboration.
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·3 min
Building AI Agents with Coze: From Beginner to Multi-Agent Collaboration
Coze is ByteDance's homegrown agent-building platform. This article explains getting started with Coze, comparison with Dify, its skill system, workflow orchestration, and multi-agent collaboration.
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·4 min
Burning Through 80 Billion Tokens: Why Vibe Coding Is Doomed to Fail
A creator spent 40 days and 80 billion tokens testing the real limits of Vibe Coding. This article dissects why AI programming crashes in production: complexity, context limits, and compression loss.
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·6 min
30-Minute Hands-On: Building a Working AI Agent from Scratch
Skip the dry theory and get hands-on! This article demonstrates step by step how to build a working AI Agent from scratch in 30 minutes using AI coding tools—covering the agent skeleton, tool system, memory mechanism, Flask web UI, and DeepSeek API integration.
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·2 min
AI-Native Development in Practice: Building an Enterprise Management System in 30 Minutes Without Writing a Single Line of Code
Can a non-coder build an enterprise management system in 30 minutes? We tested XDevelop, an AI-native dev tool, to see how natural language turns into a fully running app.
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PlanWright: A Control Plane and Multi-…
·2 min
PlanWright: A Control Plane and Multi-Agent Orchestration Layer for AI Coding Agents
PlanWright is a control plane for AI coding agents, drawing on Kubernetes orchestration principles to tackle multi-agent task assignment, state tracking, and collaboration conflicts.
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·2 min
The Complete AI Agent Development Roadmap: A Four-Stage Guide from Zero to Production
A complete four-stage AI Agent development roadmap: from LLM fundamentals and core modules, to ReAct/CoT paradigms, multi-agent collaboration, and real-world projects.
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·2 min
AI Agent Learning Path: Mastering Intelligent Agent Development from 0 to 1
Many people learn tons of fragmented content yet remain confused. This article maps out the complete AI Agent knowledge landscape—from LLM and prompt basics, tool calling, and RAG to LangChain and multi-agent collaboration—with a clear learning order.
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·3 min
The Four-Stage Learning Path for AI Agent Development: A Complete Guide from Beginner to Practitioner
A systematic guide to the four-stage AI Agent development path: core concepts, principle paradigms like ReAct, RL and multi-agent optimization, and real-world projects. Mastering Agent development is the true hardcore edge in today's LLM field.
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·4 min
Four Major LangChain Updates: OpenWiki, Voice Agents, and Sub-Agent Orchestration Explained
LangChain releases four major updates: OpenWiki for auto-generating codebase docs, voice agent tutorials, Harbor evaluation integration, and deepagents programmable sub-agents.
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·2 min
Why Is Learning AI Agents So Hard? A Smarter Approach to Beginner Tutorials
Why do beginners struggle with AI Agent development? This article breaks down a concise tutorial approach: real-world examples, core logic focus, and practical mindset-building to help you get started fast.
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·6 min
The Complete Beginner's Guide to Claude Code: From Installation to Advanced Usage
Claude Code is one of the most powerful AI coding agents, running in the terminal to write code, batch operations, build web projects, and more. This guide covers installation, connecting local models via CC Switch, permission modes, CLAUDE.md, Skills, MCP, Subagents, and more.
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·6 min
Using Skills to Let AI Automatically Manage LLM API Gateway Stations
An in-depth look at the Skills paradigm in AI programming: through intent routing and script encapsulation, let AI agents auto-manage multi-channel LLM APIs on a One API gateway for one-click distribution, health checks, and auto-degradation.
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·4 min
Career Switch to LLM Development: A Four-Level Skill Progression Roadmap
Want to switch careers into LLM development but don't know where to start? This guide breaks down a four-level skill roadmap — from basics and API calls to RAG, fine-tuning, Agent development, and multimodal — to help you build real AI career value.
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·4 min
The AI Story Bubble: Cutting Through the Hype to Find Real Value
When "AI-powered" becomes a magic phrase for valuation premiums, are companies paying for technology or for a story? A deep analysis of AI hype cycles, the gap between narrative and reality, and how to identify genuine AI value.
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