Mastering Agentic AI with OpenAI: Build Production-Ready AI Agents with OpenAI, Tool Calling, Multi-Agent Orchestration, RAG, Memory, and Enterprise Deployment (English Edition)

Don't Just Build AI Agents. Engineer Them to Operate.

Key Features
● Get a free one-month digital subscription to http://www.avaskillshelf.com.
● Production-grade agentic AI engineering using the OpenAI Responses API, AgentKit, and Reasoning Effort controls.
● Multi-agent orchestration with tool integration, state management, memory, and agentic RAG pipelines.
● Enterprise-ready deployment covering security, observability, evaluation, governance, and responsible AI operation.

Book Description
Building an AI Agent Is Easy. Building One You Can Trust in Production Is Engineering.

Agentic AI systems are moving fast from research papers and demos into production software. Mastering Agentic AI with OpenAIis a practical, authoritative guide for engineers, architects, and technology leaders designing and operating production-ready Agentic systems on the OpenAI platform — covering everything from multi-turn interactions to autonomous AI operation at enterprise scale.

The book progresses from agent foundations and tool integration through multi-agent orchestration, state management, memory, agentic RAG, and reasoning effort controls for balancing cost, latency, and capability. Each section addresses how agentic systems integrate with the existing applications and services, while remaining reliable, controllable, and observable under production conditions.

The final section moves from prototype to production, covering scaling, security, evaluation, testing, monitoring, and autonomous AI systems. By the end of the book, you will design, deploy, and govern agentic AI systems with the architectural discipline and operational confidence that production environments demand.

What you will learn
● Design and build production-ready agentic AI systems using OpenAI Responses API and AgentKit.
● Develop multi-agent workflows with tool integration, memory, retrieval, and orchestration patterns.
● Integrate OpenAI APIs into secure, scalable Python and JavaScript production applications.
● Evaluate performance, reliability, cost, and governance across autonomous AI system deployments.
● Implement responsible AI practices covering security, monitoring, observability, and human oversight.
● Deploy and manage agentic AI solutions across modern cloud environments at production scale.

Who is this book for?
This book is tailored for software developers, AI engineers, solution architects, technical leaders, and advanced students who want to design and deploy production-ready Agentic AI systems using OpenAI technologies. Readers should have a working knowledge of Python or JavaScript, REST APIs, and general software development concepts.

Table of Contents
1. Foundations of Agentic AI Systems
2. OpenAI Platform Overview and Capabilities
3. Architecting Agentic Workflows with the Responses API
4. Multi-Agent Orchestration Using AgentKit
5. State, Memory, and Tool Use in Agentic Systems
6. Implementing Agentic RAG for Knowledge Systems
7. Managing Reasoning Effort, Cost, and Latency Trade-offs
8. Scaling OpenAI Workloads
9. Securing Agentic AI Systems and Protecting Data
10. Governance, Compliance, and Ethical AI Design
11. Monitoring, Evaluation, and Observability for Agentic AI
12. Operating Models for Agentic AI Systems
13. The Roadmap to Autonomous Enterprises
       Index

About the Author
Dr. Edward D Lavieri Jr.is a software engineer, university dean, and campus chief academic officer with nearly four decades of technology experience. A generative AI leader and author of Higher Education: The AI Imperative, he has written about 19 technical books and founded BlueCert® and BlueCert® Institute.