Building AI Agents from Scratch with Python

A practical, from-first-principles guide to building AI agents in Python — the agent loop, tool calling, memory, and production guardrails, with real code at every step.

3 chapters · 9 sections · 11 min read · Updated Sep 12, 2026

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What you'll learn

What actually makes something an agent, versus a chatbot or a fixed workflow
The perceive-think-act loop that every agent framework is built on top of
How to implement tool calling from scratch, with no framework in between
How to give an agent working and short-term memory
The production guardrails — bounded loops, retries, timeouts — real agents need

Chapters

1. Foundations
This chapter builds the mental model before any code. An "agent" is a specific, narrow idea — not a marketing word — and getting that idea…
3 sections
2. Building the Core Loop
Theory is done — this chapter writes the actual agent loop in Python, from an empty file to something that can hold a conversation, call a…
3 sections
3. Tools and Real-World Robustness
An agent that can only talk isn't useful — the point is letting it do things: query a database, call an API, run code. This chapter adds to…
3 sections