ai-agents-the-definitive-guide README

The project's README from github.com/Nicolepcx/ai-agents-the-definitive-guide. As one markdown file: README.md.

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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

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 Open In Colab

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

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

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

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

Chapter 4 — Models Behind the Agents: Capabilities and Optimization

Notebook Colab
Supervisor Agent Team Open In Colab

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

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

Chapter 6 — Secure Execution and Tool Governance

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

Chapter 7 — Deploying Agents in Real Products

Notebook Colab
Hardening Backbone Open In Colab
Inference Backends Open In Colab
Model Fallback Open In Colab

Chapter 8 — Foundational Evaluation and Operational Observation of Agentic Systems

Notebook Colab
OWASP ASI 2026 Open In Colab
Evaluation Harness Open In Colab

Chapter 9 — Customized and Advanced Evaluation of Agentic Systems

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

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

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

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

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

Chapter 12 — Threat Modeling for AI Agents

Notebook Colab
LlamaFirewall Open In Colab

ai-agents-the-definitive-guide (Nicolepcx/ai-agents-the-definitive-guide)

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Ai-agents-the-definitive-guide
What is this?It is the companion code repository for the book 'AI Agents - The Definitive Guide': a set of runnable Jupyter notebooks that walk through every chapter, from basic agent patterns to production deployment and threat modeling.
Is this a library I install into a project, or something else?Neither — it is a collection of Jupyter notebooks, one folder per book chapter (CH01-CH12), with names like ch01attentionmechanismvariations.ipynb. You run them, you do not install them.
How do I actually run one of these notebooks?Every notebook in the README has an 'Open In Colab' badge — click it and the notebook opens and runs directly on Google Colab, so no local setup is required.
Do I need to already be building agents to follow along?The material starts from foundations — Chapter 1 goes from LLMs to agents — and advances to production deployment, evaluation and threat modeling, so it targets developers taking agents from prototypes to real systems.
Does the book come with anything besides the code?Yes. The book has an accompanying website with quizzes and additional material, as well as a Discord channel for readers.
Which frameworks and tools do the notebooks use?LangChain and LangGraph appear throughout, and the notebooks also touch Pydantic, MCP, Composio, E2B sandboxes, Monty programmatic tool calling, Langfuse, LangSmith and LlamaFirewall.
Where should someone completely new to agents start?At Chapter 1, 'From LLMs to Agents: The Foundational Blueprint', then the Chapter 2 notebooks (CoT, ToT, ReAct, HITL, agent teams, swarms) — the chapters build in reading order.
What are similar projects?ai-system-design, agents-towards-production, adk-python, GenAI_Agents, spring-ai-alibaba, PocketFlow, Agentlas-OS, all-agentic-architectures
Which topics is it in?benchmarks, production, evaluation-framework, pydantic, cost-optimization, owasp, a2a, tracing, langgraph, llm-evaluation, ai-security, reasoning
Creator
Nicolepcx
Size
1.8 MB
Stars
2.8K
Updated
CommitAug 01
Age
1y
Commits · 90 Days