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AI Agents - The definitive Guide

This is the corresponding code for the book AI Agents - The Definitive Guide the book can be found here and on Amazon. The book has an accompanying website with quizzes and additional material, as well as a Discord channel.

TOC

• Chapter 1 From LLMs to Agents: The Foundational Blueprint
• Chapter 2 Architectures and Patterns: Planning, Reactivity, and Multi-Agent-Systems
• Chapter 3 Advanced Planning, Reasoning, and Scalable Execution in Agents
• Chapter 4 Models Behind the Agents: Capabilities and Optimization
• Chapter 5 From Prototypes to Production: Contracts, Tools, and Reliable Execution
• Chapter 6 Secure Execution and Tool Governance
• Chapter 7 Deploying Agents in Real Products
• Chapter 8 Foundational Evaluation and Operational Observation of Agentic Systems
• Chapter 9 Customized and Advanced Evaluation of Agentic Systems
• Chapter 10 Agent Memory: How Persistence Turns Agents Into Evolving Systems
• Chapter 11 From Compute to Cost: Designing Efficient Agentic Systems
• Chapter 12 Threat Modeling for AI Agents

Instructions and Navigation

All of the code is organized into folders. Each folder starts with CH followed by the chapter number. For example, CH01. The notebooks are then organized as follows: ch01_attention_mechanism_variations.ipynb, where ch01 indicates the chapter and attention_mechanism_variations what is done in the notebook.

Repo structure

├── LICENSE
├── README.md             <- The top-level README for developers using this project.
├── CH01                  <- Per chapter folder with Jupyter notebooks.
    ├── [name].ipynb      <- Jupyter notebooks with naming as mentioned above.
├── CH02                  <- Per chapter folder with Jupyter notebooks.
...                       <- Same structure for all chapters.
├── utils                 <- Custom classes and functions and utility functions.
├── resources             <- Some miscellaneous resources.

Running the Notebooks

Every notebook can be opened and run on Google Colab directly from the links below. Just click the Open In Colab badge next to the notebook you want to run.

Chapter 1 — From LLMs to Agents: The Foundational Blueprint

Notebook	Colab
Code Examples

Chapter 2 — Architectures and Patterns: Planning, Reactivity, and Multi-Agent-Systems

Notebook	Colab
Chain-of-Thought (CoT)
Tree-of-Thought (ToT)
ReAct
Human-in-the-Loop (HITL)
Hierarchical Agent Teams
Swarms

Chapter 3 — Advanced Planning, Reasoning, and Scalable Execution in Agents

Notebook	Colab
ART + RULER
RULER Cat Poems
TreeQuest (AB-MCTS)

Chapter 4 — Models Behind the Agents: Capabilities and Optimization

Notebook	Colab
Supervisor Agent Team

Chapter 5 — From Prototypes to Production: Contracts, Tools, and Reliable Execution

Notebook	Colab
Deep Agents
MCP with LangGraph
Product Reliability Rule
Pydantic Agent Consistency

Chapter 6 — Secure Execution and Tool Governance

Notebook	Colab
A2A + MCP Governed
MCP Server with Composio
LangGraph + E2B Sandbox
Programmatic Tool Calling (Monty)

Chapter 7 — Deploying Agents in Real Products

Notebook	Colab
Hardening Backbone
Inference Backends
Model Fallback

Chapter 8 — Foundational Evaluation and Operational Observation of Agentic Systems

Notebook	Colab
OWASP ASI 2026
Evaluation Harness

Chapter 9 — Customized and Advanced Evaluation of Agentic Systems

Notebook	Colab
AgentVista
External Evaluation Pipelines (Langfuse)
External Evaluation Pipelines (LangSmith)
RULER Trace Answer Ranking (LangSmith)

Chapter 10 — Agent Memory: How Persistence Turns Agents Into Evolving Systems

Notebook	Colab
Agent Memory with LangGraph
Memory vs. No Memory
Memory Topologies

Chapter 11 — From Compute to Cost: Designing Efficient Agentic Systems

Notebook	Colab
Agent Cost Estimator by Topology
Memoizing Swarm Research Engine
Memory Footprint, Throughput & GPU Requirements

Chapter 12 — Threat Modeling for AI Agents

Notebook	Colab
LlamaFirewall