AI Agents Tutorial

Learn AI Agents step by step, from scratch - from function calling to agent loops to multi-agent systems, orchestration, and evaluation.

Prepared and maintained by the Founder of Outcome School: Amit Shekhar

Note: This series will continue to grow as I write more blogs and create more videos on new topics. Keep learning.

AI Engineering (LLM, RAG, MCP, Agent)

Before diving into AI Agents, it's a good idea to first understand the foundations that agents are built on.

In this video, we will cover the following:

• LLM
• RAG
• MCP
• Agent
• Fine-tuning
• Quantization

Let's get started: AI Engineering Explained: LLM, RAG, MCP, Agent, Fine-Tuning, Quantization

AI Agent Explained

In this blog, we will learn about the AI Agent - what it is, how it is different from a plain LLM, its five core parts, how it works end to end, the main types, and when to use one.

We will cover the following:

• The Big Picture
• What is an AI Agent
• AI Agent vs Plain LLM vs Chatbot
• The Five Core Parts
• How an AI Agent Works End to End
• A Concrete Example: Research Agent
• Types of AI Agents
• What AI Agents Can Do Today
• When to Use an AI Agent
• Common Failure Modes
• Quick Summary

Let's get started: AI Agent Explained

How does Function Calling work in LLMs?

In this blog, we will learn about how Function Calling works in LLMs. We will see what it is, why we need it, the key insight behind it, and how it powers AI agents and assistants step by step.

We will cover the following:

• What is Function Calling
• Why We Need Function Calling
• The Key Insight: The Model Does Not Run the Function
• How Function Calling Works Step by Step
• A Concrete Example: get_weather(city)
• The Conversation Loop
• Multi-Step and Parallel Function Calling
• Relation to Structured Outputs and JSON Mode
• Real-World Use: The Backbone of AI Agents
• Quick Summary

Let's get started: How does Function Calling work in LLMs?

AI Agent Loop

In this blog, we will learn about the AI Agent Loop - what it is, why an AI Agent needs it, the think-act-observe cycle that powers it, how the loop knows when to stop, and the common ways the l