Description

Coding Your First Local AI Agent (Step-by-Step Tutorial) (AI Lesson: 01)

This is the first lesson of the AI learning series.

Want to learn how AI agents actually work by building one on your own computer? In this video, we break down what makes an AI agent distinct from a standard LLM—including tool usage, autonomous execution loops, and built-in self-correction.

We’ll walk through the architecture step-by-step and run sample code locally using Python 3.13 and Google’s open-source Gemma 4 via Ollama. No expensive API keys required!

📥 Get the Starter Code & Docs:
https://github.com/humanuturn-source/AI_Lesson_01/tree/main /

⚙️ Tech Stack Used:
⚬ Engine: Ollama
⚬ LLM: Gemma 4 (Google)
⚬ Language: Python 3.13
⚬ OS: Works on macOS, Windows, and Linux

Timestamps:
⚬ 00: 00 – Introduction
⚬ 00: 35 – System Prompt and User Prompt
⚬ 01: 10 – What is AI Agent
⚬ 01: 20 – Agents demo
⚬ 02: 05 – Agent Architecture
⚬ 03: 10 – LLM vs AI Agent
⚬ 03: 30 – Tech Stack
⚬ 03: 45 – What is next

If you’re serious about mastering AI, hands-on practice is key. Grab the code from the link above, follow along, and don’t forget to Like, Comment, and Subscribe to support more free tutorials!

Hashtags:
#AIAgent #LocalAI #PythonCoding #Gemma4 #Ollama #MachineLearning #ArtificialIntelligence #SoftwareEngineering #TechTutorial