@xiaojianjian567: Introduction to the Excellent GitHub Project with 45k Stars: hello-agents. Produced by Datawhale, it gained 1,200+ stars in 7 days and is surging. What does this project do? One-sentence description: Teaches you from scratch how to build real AI Agents—not just by calling APIs, but by understanding core principles, system design, and…

Introduction to the Excellent GitHub Project with 45k Stars: hello-agents Produced by Datawhale, it gained 1,200+ stars in 7 days and is surging. What does this project do? One-sentence description: It teaches you from scratch how to build real AI Agents. It’s not about calling APIs; it’s about understanding core principles, system design, and multi-agent collaboration. It breaks down Agent systems into 16 chapters, progressing layer by layer from basic concepts to practical projects. After studying it, you will transition from someone who uses GPT to write copy to someone capable of designing Agent systems. Core Technical Features * **First-Principles Teaching**: It doesn’t teach you how to call APIs; it teaches you how to build the mental model of an Agent from scratch—covering memory modules, tool calling, autonomous planning, and protocol communication. * **Multi-Agent Collaboration**: Advances from single Agents to system design involving multi-Agent division of labor, collaboration, and debate. * **Covers All Mainstream Frameworks**: AutoGen, AgentScope, LangGraph, Coze, Dify—all mainstream frameworks are covered. This is not API calling tutorial, but design thinking tutorial. * **Classic Paradigms Hand-Implemented**: Paradigms such as ReAct, Plan-and-Solve, and Reflection are all implemented from principle to code by hand. Supported Features * **16 Chapters, 5 Stages**: Basics → Single Agent → Advanced → Practical Application → Graduation Project. * **Complete Code Repository**: Combines theory with practice; every knowledge point has runnable code. * **Comprehensive Practical Projects**: Intelligent Travel Assistant (Multi-Agent Collaboration), Cyber Town (Agent Simulated Society), and Reproduction of DeepResearch Agent. * **Continuous Updates with Extra Chapters**: Agent interview questions, step-by-step Dify tutorials, GUI Agent practice, environment configuration, and Skill writing. Who Is This For? 1. **Developers who want to upgrade from AI users to AI system designers**: This isn’t about learning how to use ChatGPT; it’s about learning how to build Agents that can work autonomously. 2. **Researchers or engineers interested in multi-agent systems**: The book thoroughly explains how multiple Agents communicate, collaborate, and are evaluated. 3. **Friends looking to switch careers to AI or preparing for AI-related job interviews**: It includes a dedicated summary of Agent interview questions and answers. Learning Path: Basics → Single Agent → Advanced → Practical Application → Graduation Project. Each stage includes code and runnable projects. Project Link: https://github.com/datawhalechina/hello-agents Polo’s Perspective: The people most likely to be replaced in 2025 are those still chasing the release of new models. The people truly hard to replace are those who can design Agent systems and enable multiple AIs to collaborate on complex tasks. Large models will become cheaper and more open-source. However, the ability to use these models to build reliable systems will not become oversaturated. The strength of this hello-agents book lies in the fact that it doesn’t teach you to chase trends; it teaches you to build systems.