Build Claude Code in ~5,000 lines of Python.

20 chapters · the entire agent loop in 6 lines · 3 providers · 42 tests pass without an API key · $0.50 speedrun · zero frameworks.

📺 75-second narrated walkthrough: assets/explainer.mp4 (click the GIF or open directly).

⚡ Run it in 30 seconds (no API key)

git clone https://github.com/KeWang0622/agent-zero-to-hero.git
cd agent-zero-to-hero && pip install -e .
pytest tests/                                          # 42 passed in 0.6s

To run the actual agent:

export ANTHROPIC_API_KEY=sk-ant-...
python -m chapters.ch00_welcome "what is 17 * 23?"     # your first agent
python agent.py "build me Tetris in one HTML file"     # the climax
python microsite/build_site.py "Brooklyn ramen shop"   # the capstone

🎯 The entire agent loop is 6 lines

while True:
    r = client.messages.create(model=M, messages=msgs, tools=TOOLS)
    msgs.append({"role": "assistant", "content": r.content})
    if r.stop_reason != "tool_use":
        return r
    msgs.append({"role": "user", "content": run_all_tools(r.content)})

That's Claude Code. That's Cursor. That's Devin. Every coding agent on Earth wraps these six lines. By the end of chapter 5 you'll write this from memory.

flowchart LR
    User([👤 user prompt]) --> Msgs[/messages array<br/><i>ch02 · the only memory</i>/]
    Msgs --> Model[the model<br/><i>claude · openai · gemini<br/>ch01 · ch17</i>]
    Tools[🔧 tools<br/><i>ch04-06</i>] -.-> Model
    Skills[📜 skills<br/><i>ch12</i>] -.-> Model
    MCP[🔌 MCP servers<br/><i>ch13-14</i>] -.-> Model
    Model --> Stop{stop_reason?<br/><i>ch03</i>}
    Stop -- end_turn --> Answer([💬 final answer<br/><i>saved to session.jsonl · ch09</i>])
    Stop -- tool_use --> Run[run all tools<br/>append tool_results]
    Run --> Msgs
    style Msgs fill:#1e1e2e,stroke:#89b4fa,color:#89b4fa
    style Model fill:#1e1e2e,stroke:#cba6f7,color:#cba6f7
    style Stop fill:#1e1e2e,stroke:#f9e2af,color:#f9e2af
    style Answer fill:#1e1e2e,stroke:#94e2d5,color:#94e2d5
    style Run fill:#1e1e2e,stroke:#f9e2af,color:#f9e2af
    style Tools fill:#1e1e2e,stroke:#a6e3a1,color:#a6e3a1
    style Skills fill:#1e1e2e,stroke:#fab387,color:#fab387
    style MCP fill:#1e1e2e,stroke:#f5c2e7,color:#f5c2e7
    style User fill:#313244,stroke:#cdd6f4,color:#cdd6f4

The model is stateless. The messages array is the only memory. Tools, skills, sessions, MCP — they're how the harness extends the model. They're not the agent. The loop is.

👀 Who this is for

You'll get the most out of it if you:

• Can write basic Python (loops, dicts, functions). No advanced async, types, or web frameworks needed.
• Have used a coding agent (Claude Code, Cursor, Devin) and wonder what's actually happening inside.
• Want to read the source of a real agent harness and recognize every primitive by name.

Not for you if you want a plug-and-play framework. Use LangGraph or smolagents.

📑 The 20 chapters

Each chapter is one Python file + a matching learning page (chapters/chNN_topic.py + .md). Read the .md, run the .py, do the homework.

Every chapter ends with Summary, Homework, and References (papers + docs + reference repos).

🗺️ The 7-week journey

Bold chapters are load-bearing concepts — read them twice. Full schedule with problem sets, labs, and the final exam: SYLLABUS.md.

📅 How to take it

API spend: about $0.50 for the speedrun, $5–$10 for the full course (the capstone is the most expensive turn). You can verify the install without an API key — pytest tests/ runs against mocked LLMs and a real MCP subprocess.

🐢 Quotable mottos

Hi! I'm GuiGui 🐢 — the mascot for this course

The chapters are written in plain prose; I show up in the illustrations to keep the energy up. If you spot me with a graduation cap, you've reached week 7.

📂 Repo layout

chapters/        20 numbered Python files + matching .md walkthroughs
agent.py         the climax — Claude-Code-shaped CLI built from chapter primitives
microsite/       capstone — build a website from one prompt
skills/          example SKILL.md files (haiku-master, landing-page)
mcp_servers/     example MCP servers (calculator)
tests/           verify your install, no API key required
docs/            ADAPTING.md (port to OpenAI/Gemini), FAQ.md
SYLLABUS.md      7-week schedule with problem sets and exam
AGENT.md         project context auto-loaded by agent.py

🎓 For instructors

This course is MIT-licensed and built to be adopted. All chapters are runnable in 30 seconds. 25 students × 7 weeks ≈ $50 in total API spend. See SYLLABUS.md for problem sets, labs, and final exam. Open an issue if you adopt this for a class — we'll add your school here.

📤 Share-ready images

If you want to tweet about this course, assets/share/ has 8 PNGs designed for screenshot-friendly sharing — the 6-line loop poster, a side-by-side comparison vs LangChain / LangGraph / CrewAI / smolagents, and 6 motto cards in tweet-card aspect ratio. MIT-licensed; attribution appreciated, not required.

📈 Star history

🙏 Acknowledgements

• @karpathy for the literary genre of educational repos (nanoGPT, nanochat, micrograd).
• Anthropic for shipping the cleanest tool-use protocol of any major LLM provider.
• Simon Willison — "Claude Skills are maybe a bigger deal than MCP" inspired chapter 12.

Written by Ke Wang — agent identity & memory at Pika. Previously: Samsung, Adobe (Marc Levoy's team). PhD in computational imaging.

License

MIT. See LICENSE.