[P] Interactive course showing the full AI agent stack in 60 lines of Python

Reddit r/MachineLearning / 3/19/2026

📰 NewsDeveloper Stack & InfrastructureTools & Practical Usage

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Key Points

A new interactive course explains the AI agent stack by reconstructing core concepts from scratch across 9 lessons, covering tool dispatch, agent loop, conversation management, state, memory, policy gates, and self-scheduling in roughly 60 lines of Python.
The course runs in the browser via Pyodide and offers both a mock mode and a live inference option via a Groq API key, helping engineers understand what happens under abstractions to debug and extend frameworks like LangChain, CrewAI, and AutoGen.
The project is open source with a GitHub repository and a live demo at tinyagents.dev, providing an accessible resource for learning how agent architectures work.
Rather than promoting any single framework, the course emphasizes building a mental model to improve debugging, extension, and decision-making around AI agents.

Built an interactive course that walks through the architecture behind agent frameworks (LangChain, CrewAI, AutoGen) by rebuilding the core from scratch.

9 lessons covering: tool dispatch, agent loop, conversation management, state, memory, policy gates, and self-scheduling. ~60 lines of Python by the end.

The goal isn't "frameworks are bad" — it's giving engineers a mental model of what's happening under the abstractions so they can debug and extend them. Runs in the browser via Pyodide.

Mock mode included, or plug in a Groq API key for live inference.

https://tinyagents.dev

Open source:
https://github.com/ahumblenerd/tour-of-agents

submitted by /u/Glittering-Judge8541
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