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Hello Agents

A free, build-first course for people who want to understand and ship AI agents.

Hello Agents is a hands-on learning experience for building AI-native agents from first principles. It moves from the mechanics of a single tool-using loop to memory, retrieval, multi-agent systems, evaluation, and real-world capstone projects.

The project includes a bilingual English / 中文 web experience, a living curriculum, practical builder notes, community context, and a clear path from first prompt to production-minded agent systems.

Why this exists

AI agent content is everywhere, but a clear path from curiosity to working software is still hard to find. Hello Agents focuses on the parts that compound:

  • Build over talk — every idea should become code you can run, break, and repair.
  • Explain the why — understand the mechanics underneath frameworks and patterns.
  • Measure honestly — use logs, benchmarks, and evaluation instead of demos alone.
  • Open and free — learn in public and make the work easier for the next builder.

What you can explore

  • Agent foundations, tool use, loops, and orchestration
  • Context engineering, memory, retrieval, and RAG
  • Multi-agent communication and emerging agent protocols
  • Evaluation, metrics, benchmarks, and agentic reinforcement learning
  • A practical roadmap that ends with projects you can run and share
  • Responsive pages for the home, about, roadmap, legal, and login experiences

Tech stack

  • React 19 + TypeScript
  • Vite
  • Tailwind CSS 4
  • Framer Motion
  • Responsive, client-side routing
  • English / 中文 content support

Getting started

Prerequisites

  • Node.js 20+
  • npm 10+ (or another compatible package manager)

Install and run

npm install
npm run dev

Then open the local URL printed by Vite.

Production build

npm run build
npm run preview

Project structure

src/
├── components/   Reusable page and interaction components
├── pages/        Route-level screens
├── content.ts    Curriculum and editorial content
├── data.ts       Shared content types and data
├── i18n.tsx       Language provider and translation helpers
├── router.tsx     Lightweight client-side routing
└── index.css      Global styles and design tokens
public/            Favicon, manifest, and social preview assets

Contributing

Contributions that make the learning path clearer, more practical, or more welcoming are encouraged. Before opening a pull request:

  1. Keep examples runnable and explain the reasoning behind meaningful changes.
  2. Preserve the English / 中文 experience when editing user-facing content.
  3. Run npm run build locally.
  4. Describe what a learner can now understand or build after the change.

For substantial changes, open an issue first so the direction can be discussed openly.

Roadmap

The curriculum is intentionally iterative. Future improvements may include more runnable examples, deeper evaluation walkthroughs, community-submitted projects, and additional translations.

License

The project is shared for learning and community use. A formal license will be added when the project maintainer selects the appropriate terms.


Built for curious people who learn by making.

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A build-first course for understanding and shipping AI agents.

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