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Build Your Agents 101

Welcome to Build Your Agents 101 - a hands-on tutorial series where you'll learn to build AI agents from scratch!

What You'll Learn

This tutorial takes you through building a complete SQL query agent that converts natural language questions into database queries. Along the way, you'll master:

  • ReAct Pattern - The reasoning and acting loop that powers modern agents
  • Function Calling - How LLMs interact with external tools
  • Security - Building safe agents that can't be exploited
  • Practical Skills - Real-world agent development patterns

The Project

We'll build a Natural Language SQL Agent for a bookstore database:

User: "Who are my top 5 customers by revenue?"
Agent: Generates SQL → Executes → Returns formatted answer

Tutorial Stages

Stage 1: Database Setup

Create a SQLite database with sample data. Learn schema design and relationships.

Time: 30 minutes | Difficulty: Beginner

Stage 2: Basic Agent

Build your first agent from scratch using OpenAI's API. Understand the ReAct loop.

Time: 1-2 hours | Difficulty: Intermediate

Stage 3: LangChain Version

Rebuild using LangChain to understand what frameworks provide.

Time: 1 hour | Difficulty: Intermediate

Stage 4: Custom Tools

Extend LangChain agents with custom tools beyond built-in capabilities.

Time: 45-60 minutes | Difficulty: Intermediate-Advanced

Prerequisites

  • Python 3.8+
  • Basic SQL knowledge
  • Familiarity with APIs
  • OpenAI API key (or use Ollama for free local models)

Why Build Agents?

Agents are the future of AI applications. Unlike simple chatbots, agents can:

  • Break down complex tasks
  • Use tools to interact with external systems
  • Reason through multi-step problems
  • Make decisions autonomously

By building one from scratch, you'll understand exactly how they work - no magic, just clear patterns.

Ready to Start?

Jump into Stage 1: Database Setup and let's build something real!

Questions? Open an issue on GitHub