Mastering Agentic AI with OpenAI

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

Key Features
● Get a free one-month digital subscription to 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 OpenAI is 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.

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

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.

About the Technical Reviewer
Vasu Raj Jain has over 10 years of experience in designing and engineering large-scale distributed systems, AI-powered applications, and advertising technology infrastructure. His passion for innovation has taken him across AI, computer vision, and agentic systems, including building computer vision tools for content classification at Prime Video. His interest in emerging technology dates back to his time at the University of Florida, where he developed CPR.VR, a healthcare VR application designed to teach CPR techniques.

Currently, Vasu works as a Lead Software Engineer at Amazon Ads, where he builds AI-powered ad serving systems responsible for generating billions of dollars in revenue for Amazon Ads. His systems deliver ads at massive scale - serving live events with over 20 million concurrent viewers - across Amazon's owned-media supply platforms. His work includes implementing IAB specifications, developing revenue-critical capabilities such as programmatic guaranteed deals, share of voice, and real-time bidding, as well as building the core platform infrastructure that supports these features.

Saurabh Sarode is a Software Architect with over 20 years of experience designing innovative, scalable solutions in software development. Proficient in leveraging technologies like C#, Python, Snowflake, AWS, and GenAI, he has focused on creating efficient architectures for risk management, compliance, and business automation since his early career in computer science.

Saurabh has worked across industries including finance, healthcare, mining, and Governance, Risk, and Compliance (GRC), delivering projects for Fiserv, Infosys, and Approva Systems (currently known as Infor).