[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_28":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNzc1ODU","title","Architecting Production-Ready Gen AI and Agentic AI Systems","state","published","contactAuthorMethod","email","aboutText","

Architecting Production-Ready Gen AI and Agentic AI Systems is a practical playbook for architects and technology leaders who need to move AI systems from impressive prototypes to reliable production platforms.

Most Gen AI projects do not fail because teams cannot call a model API. They fail because the system around the model is incomplete. Retrieval is not governed. Prompts are not versioned. Tool use is not bounded. Evaluation is treated as a one-time test. Observability arrives too late. Governance becomes documentation rather than architecture.

This book takes a systems view of Gen AI and Agentic AI. It explains how to classify AI-added, AI-first, generative, agentic, and hybrid systems; how to assess architecture readiness; how to design a canonical AI architecture; and how to build the controls needed for retrieval, agents, prompts, evaluation, security, cost, observability, and governance.

Inside, you will learn how to architect:

Production-ready RAG and knowledge systems
Agentic architectures with bounded autonomy
Multi-agent orchestration patterns
Prompt registries and prompt engineering discipline
Evaluation and quality gates for LLM-based systems
Security and threat models for Gen AI and agents
Cost and FinOps controls for LLM systems
Observability and LLMOps practices
Governance evidence trails for regulated environments
Engagement checklists for architecture reviews

The book uses NovaCred, a fictional financial-technology company, as a recurring case study to show how architecture decisions change when AI touches credit decisioning, policy interpretation, customer communication, collections workflows, audit evidence, and human review.

This is not a book about chasing tools or frameworks. It is about the architecture responsibilities that remain stable even as models, vendors, and orchestration libraries change.

If you are an enterprise architect, solution architect, AI architect, engineering leader, platform owner, product leader, or governance practitioner, this book will help you design Gen AI and Agentic AI systems that can survive production, regulation, operational stress, and real human use.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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