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From “Building AI Agents in Pure Python - Beginner Course” by Tech With Tim

Building an AI agent in pure Python

Three simple parts become a working coding agent.

Open the interactive page →Make a page from any YouTube video

Stages of the build

Intro: what an agent is — The presenter introduces the video and the idea that an agent is a model, tools and a loop. 0:21
An agent is three things — Slides explain that a model, tools and a loop make up what Claude Code, Codex and Cursor run on. 2:31
First script: calling the model — The code in step1.py calls an OpenAI model, then adds a system rule and assistant message to shape its answer. 3:51
Memory is just a list — Slides and step2.py show that the conversation is kept as a list of messages resent with each request. 12:01
Step 3: tool calling — The model asks for a read_file tool call, a schema describes the tool, and Python runs it and returns the result. 17:51
Looping until no tool calls remain — The loop runs repeatedly until the model stops requesting tools, and the guardrails and context are built up. 27:51
Full coding agent with a snake game — agent.py adds list, read, write and run-command tools and a system prompt, then builds a snake game in the terminal. 32:51

Things on screen worth a look

What the model doesn't do — A card reads 'It doesn't call a tool' under the heading 'What the model doesn't do'.
read_file tool schema — The schema lists the name read_file, a path parameter of type string, and a required field.
list_files schema in agent.py — A highlighted schema for list_files describes listing a directory with a path parameter.

Words the build depends on

Term: Agent · What the video says: A model, some tools and a loop working together, as shown on the slide.
Term: Context window · What the video says: The conversation list resent with every request; when it grows large, agents summarise it (compaction).
Term: Schema · What the video says: A breakdown of how a tool works, its parameters and what it returns.

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