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 loop fails.

We will cover the following:

• The Big Picture
• What is the AI Agent Loop
• Why an AI Agent Needs a Loop
• The Think-Act-Observe Cycle
• The Loop Step by Step
• The Loop in Real Code
• Parallel Tool Calls in One Turn
• How the Loop Knows When to Stop
• Common Loop Failures
• Quick Summary

Let's get started: AI Agent Loop

ReAct Agent

In this blog, we will learn about the ReAct Agent - what it is, how it is built, its anatomy, how it thinks and acts, and how to handle its common failure modes.

When we hear ReAct Agent, it sounds complex. But do not worry. If we break it down into its individual parts, every single piece is simple.

We will cover the following:

• What is a ReAct Agent
• ReAct Agent vs AI Agent
• Anatomy of a ReAct Agent
• The ReAct Prompt Template
• How a ReAct Agent Thinks and Acts
• A Full Trace Example
• Implementing a ReAct Agent
• Common Failure Modes and How to Fix Them
• Quick Summary

Let's get started: ReAct Agent

Reflection Agent

In this blog, we will learn about the Reflection Agent - what it is, how it is built, its anatomy, how it generates, critiques, and revises its own work, and how to handle its common failure modes.

We will cover the following:

• What is a Reflection Agent
• Reflection Agent vs AI Agent
• Anatomy of a Reflection Agent
• How a Reflection Agent Works
• A Full Trace Example
• Reflection Agent vs ReAct Agent
• Common Failure Modes and How to Fix Them
• Quick Summary

Let's get started: Reflection Agent

Plan-and-Execute Agent

In this blog, we will learn about the Plan-and-Execute Agent - what it is, its anatomy, how it plans and runs the steps, how it differs from a ReAct Agent, and how to handle its common failure modes.

We will cover the following:

• What is a Plan-and-Execute Agent
• Plan-and-Execute Agent vs AI Agent
• Anatomy of a Plan-and-Execute Agent
• How a Plan-and-Execute Agent Works
• A Full Trace Example
• Plan-and-Execute Agent vs ReAct Agent
• Common Failure Modes and How to Fix Them
• Quick Summary

Let's get started: Plan-and-Execute Agent

AI Agent Memory

In this blog, we will learn about AI Agent Memory - why agents need it, the memory stack, the four core operations (write, read, update, forget), how memory flows at runtime, and the common mistakes.

We will cover the following:

• The Big Picture
• Why AI Agents Need Memory
• The Memory Stack
• The Four Core Operations
• How Memory Flows at Runtime
• What to Store and What Not to Store
• Common Mistakes and How to Fix Them
• Quick Summary

Let's get started: AI Agent Memory

Context Engineering

In this blog, we will learn about Context Engineering - what it is, why it has become the most important skill for building reliable AI applications, how it differs from Prompt Engineering, the components that make up the context, common patterns like RAG, few-shot examples, tools, and memory, and the best practices and common mistakes to keep in mind.

We will cover the following:

• What is Context Engineering?
• The Big Picture
• Why Context Engineering matters
• Prompt Engineering vs Context Engineering
• The components of the context
• Common patterns in Context Engineering
• Common mistakes to avoid
• Best practices
• Quick Summary

Let's get started: Context Engineering

Agentic RAG

In this blog, we will learn about Agentic RAG - what it is, why standard RAG falls short, the agentic RAG loop, the three building blocks, the common patterns, when to use it, and the limitations to keep in mind.

A hard question often needs more than one search. Some of those searches need different sources. Some depend on what the previous search found. Standard RAG cannot do any of this. Agentic RAG can.

Agentic RAG = Agentic + RAG

We will cover the following in this blog:

• The Big Picture
• A Quick Recap of RAG
• A Quick Recap of AI Agent
• Why Standard RAG Falls Short
• What is Agentic RAG
• The Agentic RAG Loop
• The Three Building Blocks
• A Walkthrough with a Real Example
• Common Patterns of Agentic RAG
• Standard RAG vs Agentic RAG
• When to Use Agentic RAG
• Limitations of Agentic RAG
• Quick Summary

Let's get started: Agentic RAG

GraphRAG

In this blog, we will learn about GraphRAG and how it improves retrieval by using a knowledge graph along with vector search.

We will cover the following:

• What is GraphRAG?
• Why normal RAG is not enough
• The big picture of GraphRAG
• How GraphRAG builds the knowledge graph
• How GraphRAG answers a question
• Local search vs Global search
• When to use GraphRAG
• Trade-offs of GraphRAG
• Quick Summary

Let's get started: GraphRAG

Multi-Agent Systems

In this blog, we will learn about Multi-Agent Systems - what they are, the three pillars that hold them together, the common agent roles, how agents communicate and coordinate, the trade-offs, and when to use them.

We will cover the following:

• The Big Picture
• What is a Multi-Agent System
• The Three Pillars
• Common Agent Roles
• How Agents Communicate
• How Agents Coordinate
• Multi-Agent vs Single Agent - The Trade-offs
• Common Mistakes
• When to Use a Multi-Agent System
• Quick Summary

Let's get started: Multi-Agent Systems

AI SubAgents

In this blog, we will learn about AI SubAgents. We will understand what they are, why we need them, how they work, and how to use them to build AI systems that can handle big and complex tasks.

We will cover the following:

• What is an AI Agent?
• What are AI SubAgents?
• Why do we need SubAgents?
• How do SubAgents work?
• Example use case
• Benefits of using SubAgents
• Challenges with SubAgents
• Best practices

Let's get started: AI SubAgents

AI Orchestration

In this blog, we will learn about AI Orchestration. We will understand what it is, why we need it, how it is different from AI Agents, and the common patterns we use to coordinate multiple LLMs, tools, and steps together to build real AI products.

We will cover the following:

• What is AI Orchestration?
• Why do we need AI Orchestration?
• AI Orchestration vs AI Agents
• Components of AI Orchestration
• How AI Orchestration works
• Patterns of AI Orchestration
• Sequential Pattern
• Parallel Pattern
• Conditional Pattern
• Loop Pattern
• Orchestrator-Worker Pattern
• Tools for AI Orchestration
• Challenges in AI Orchestration
• Best Practices

Let's get started: AI Orchestration

How AI Agents Communicate

In this blog, we will learn about how AI agents communicate. We will understand why agents need to communicate, the main ways they talk to each other, the message format, and the protocols that make agents work together to finish complex tasks.

We will cover the following:

• What is agent communication?
• Why do agents need to communicate?
• What agents need in order to commun