Beyond the Model
Production Architectures for Enterprise Generative AI in AWS
Building a successful AI prototype has never been easier.
Building an enterprise-grade AI platform that is secure, observable, scalable, governed, and economically sustainable is an entirely different challenge.
Beyond the Model explores what happens after the demo.
Instead of focusing on prompt engineering or model capabilities, this book examines the engineering decisions required to operate Generative AI successfully in production on AWS.
Across 24 in-depth chapters, you'll learn how to design production platforms using Amazon Bedrock, SageMaker AI, multi-provider gateways, GenAIOps, evaluation pipelines, AI observability, FinOps, multi-tenancy, agentic architectures, and the latest AWS Well-Architected guidance-including the Generative AI Lens and the new Agentic AI Lens.
Inside you'll discover how to:
• Design production-ready enterprise AI platforms
• Build secure multi-tenant GenAI architectures
• Operate LLMs with observability, evaluation and governance
• Apply GenAIOps and FinOps practices at scale
• Design AI Gateways and multi-provider strategies
• Architect enterprise RAG and Agentic AI systems
• Perform AWS Well-Architected reviews for GenAI workloads
• Avoid the production failure patterns that most AI teams discover too late
Every chapter combines official AWS guidance with independent engineering analysis, highlighting not only recommended architectures, but also where they break, their operational trade-offs, and how experienced architects make production decisions.
The model is only one component.
Production architecture is everything around it.
For AI Engineers, ML Engineers, Data Engineers, Platform Engineers and Solutions Architects building enterprise Generative AI on AWS.
