Includes a FREE GitHub companion project with complete source code.
GitHub Companion Project:
https: //github.com/masud-dot/production-ready-ai-agent
AI agents are moving beyond simple chatbots. Modern production systems need to work with real tools, retrieve reliable information, maintain state, enforce security, handle failures, and operate under real-world constraints.
Building Production-Ready AI Agents with Python takes you from the fundamentals of AI agents to designing, testing, securing, deploying, and scaling practical agentic AI systems.
Instead of focusing only on prompts and prototypes, this book teaches the engineering practices required to build reliable AI applications using Python, LLMs, tools, RAG, memory, LangGraph, MCP, evaluation, guardrails, observability, APIs, Docker, and CI/CD.
- Understand AI agent architecture and the agent loop
- Build LLM-powered applications with Python
- Implement tools and function calling
- Build production-oriented RAG systems
- Add memory and state management
- Orchestrate complex workflows with LangGraph
- Integrate MCP for tool and context interoperability
- Design guardrails, permissions, and security controls
- Test and evaluate AI agent behavior
- Add observability and production monitoring
- Build APIs with FastAPI
- Containerize applications with Docker
- Create CI/CD workflows with GitHub Actions
- Prepare AI agents for production deployment
Throughout the book, you progressively build a production-oriented AI Support Agent that brings the concepts together into a practical system.
The companion GitHub project provides the source code so you can study the implementation, run the tests, experiment with the architecture, and extend the application beyond the examples in the book.
GitHub: https: //github.com/masud-dot/production-ready-ai-agent
This book is designed for Python developers, software engineers, AI engineers, backend developers, automation engineers, data engineers, and technical professionals who want to move from AI prototypes to production-ready agentic systems.
You do not need to be an AI research expert. The book focuses on practical engineering concepts and progressively introduces the technologies needed to build reliable AI agents.
From Prototype to ProductionBy the end of the book, you will have a practical understanding of how modern AI agents are architected, implemented, tested, secured, observed, and deployed-and how the individual components work together as a production system.
Build the agent. Understand the architecture. Engineer it for production.