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System Design for the LLM Era: Patterns and principles for production-grade AI architecture - Brossura
Sinossi
STOP building fragile AI wrappers; START designing resilient AI systems.
Key Features
- From LLM fundamentals to real-world practicalities
- Patterns and principles for architecting LLM-based systems
- Learn from in-depth case studies
- Decouple from premium models using tiered fallback
- Event-driven architectures for decoupling high-latency agentic workflows
- Cost management approaches
- Security strategies for LLM systems
- Glossary of LLM and AI systems design terminology included
Book Description
Many companies are trying to turn their small AI experiments into big products, but they lack a good plan.
Engineers need a practical guide to building these new AI systems the right way, so that they can handle scale, won't cost too much to build or operate, and perform reliably.
This book is that guide, combining technical depth with breadth and practicality. Starting from LLM fundamentals, the book details the architectural patterns and design principles needed to build production-grade AI systems. In-depth case studies then show you how to apply them to a range of real-world application scenarios, including AI-native IDEs, adaptive learning platforms, and intelligent search solutions.
The book provides a deep, practical look at the real-world challenges and solutions for building systems with LLMs at their core.
What you will learn
- Architect a complete, production-grade AI-powered system from scratch
- Design and mitigate the unique challenges of LLM APIs, like high latency and cost
- Implement key software engineering patterns like circuit breakers and rate limiting for AI systems
- Choose the right databases and data models for AI applications, including vector search engines
- Build a scalable and resilient system that can handle high load and ensure user privacy
Who this book is for
This book will be an invaluable learning resource for engineers, architects and leads working with LLMs or looking to integrate LLMs into their existing systems.
Table of Contents
- Atomic Units of LLM Systems
- Core Architectural Patterns for LLM System Design
- Case Study: Designing AI-Native IDEs
- Case Study: Adaptive Learning Platform
- Case Study: AI-Powered Search for E-Commerce Platforms
- Case Study: AI-Powered Customer Support Agent
- Glossary
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull'autore
Sampriti Mitra is a software engineering lead and an alumna of IIT BHU, with over six years of experience designing and building scalable distributed systems. She understands the practical challenges of integrating large language models (LLMs) into production-grade systems. Her professional background includes roles at industry-leading companies like Sumologic and Razorpay. She also runs a newsletter, Architecturally Speaking, which is dedicated to breaking down system design principles.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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System Design for the LLM Era: Patterns and principles for production-grade AI architecture (Paperback or Softback)
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Packt Publishing 6/29/2026, 2026
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ISBN 13: 9781807789930
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Paperback. Condizione: new. Paperback. STOP building fragile AI wrappers; START designing resilient AI systems.Key FeaturesFrom LLM fundamentals to real-world practicalitiesPatterns and principles for architecting LLM-based systemsLearn from in-depth case studiesDecouple from premium models using tiered fallbackEvent-driven architectures for decoupling high-latency agentic workflowsCost management approachesSecurity strategies for LLM systemsGlossary of LLM and AI systems design terminology includedBook DescriptionMany companies are trying to turn their small AI experiments into big products, but they lack a good plan.Engineers need a practical guide to building these new AI systems the right way, so that they can handle scale, won't cost too much to build or operate, and perform reliably.This book is that guide, combining technical depth with breadth and practicality. Starting from LLM fundamentals, the book details the architectural patterns and design principles needed to build production-grade AI systems. In-depth case studies then show you how to apply them to a range of real-world application scenarios, including AI-native IDEs, adaptive learning platforms, and intelligent search solutions.The book provides a deep, practical look at the real-world challenges and solutions for building systems with LLMs at their core.What you will learnArchitect a complete, production-grade AI-powered system from scratchDesign and mitigate the unique challenges of LLM APIs, like high latency and costImplement key software engineering patterns like circuit breakers and rate limiting for AI systemsChoose the right databases and data models for AI applications, including vector search enginesBuild a scalable and resilient system that can handle high load and ensure user privacyWho this book is forThis book will be an invaluable learning resource for engineers, architects and leads working with LLMs or looking to integrate LLMs into their existing systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781807789930
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System Design for the LLM Era (Paperback)
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ISBN 10: 1807789934
ISBN 13: 9781807789930
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Paperback. Condizione: new. Paperback. STOP building fragile AI wrappers; START designing resilient AI systems.Key FeaturesFrom LLM fundamentals to real-world practicalitiesPatterns and principles for architecting LLM-based systemsLearn from in-depth case studiesDecouple from premium models using tiered fallbackEvent-driven architectures for decoupling high-latency agentic workflowsCost management approachesSecurity strategies for LLM systemsGlossary of LLM and AI systems design terminology includedBook DescriptionMany companies are trying to turn their small AI experiments into big products, but they lack a good plan.Engineers need a practical guide to building these new AI systems the right way, so that they can handle scale, won't cost too much to build or operate, and perform reliably.This book is that guide, combining technical depth with breadth and practicality. Starting from LLM fundamentals, the book details the architectural patterns and design principles needed to build production-grade AI systems. In-depth case studies then show you how to apply them to a range of real-world application scenarios, including AI-native IDEs, adaptive learning platforms, and intelligent search solutions.The book provides a deep, practical look at the real-world challenges and solutions for building systems with LLMs at their core.What you will learnArchitect a complete, production-grade AI-powered system from scratchDesign and mitigate the unique challenges of LLM APIs, like high latency and costImplement key software engineering patterns like circuit breakers and rate limiting for AI systemsChoose the right databases and data models for AI applications, including vector search enginesBuild a scalable and resilient system that can handle high load and ensure user privacyWho this book is forThis book will be an invaluable learning resource for engineers, architects and leads working with LLMs or looking to integrate LLMs into their existing systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781807789930
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System Design for the LLM Era (Paperback)
Editore:
Packt Publishing Limited, Birmingham, 2026
ISBN 10: 1807789934
ISBN 13: 9781807789930
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Paperback. Condizione: new. Paperback. STOP building fragile AI wrappers; START designing resilient AI systems.Key FeaturesFrom LLM fundamentals to real-world practicalitiesPatterns and principles for architecting LLM-based systemsLearn from in-depth case studiesDecouple from premium models using tiered fallbackEvent-driven architectures for decoupling high-latency agentic workflowsCost management approachesSecurity strategies for LLM systemsGlossary of LLM and AI systems design terminology includedBook DescriptionMany companies are trying to turn their small AI experiments into big products, but they lack a good plan.Engineers need a practical guide to building these new AI systems the right way, so that they can handle scale, won't cost too much to build or operate, and perform reliably.This book is that guide, combining technical depth with breadth and practicality. Starting from LLM fundamentals, the book details the architectural patterns and design principles needed to build production-grade AI systems. In-depth case studies then show you how to apply them to a range of real-world application scenarios, including AI-native IDEs, adaptive learning platforms, and intelligent search solutions.The book provides a deep, practical look at the real-world challenges and solutions for building systems with LLMs at their core.What you will learnArchitect a complete, production-grade AI-powered system from scratchDesign and mitigate the unique challenges of LLM APIs, like high latency and costImplement key software engineering patterns like circuit breakers and rate limiting for AI systemsChoose the right databases and data models for AI applications, including vector search enginesBuild a scalable and resilient system that can handle high load and ensure user privacyWho this book is forThis book will be an invaluable learning resource for engineers, architects and leads working with LLMs or looking to integrate LLMs into their existing systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781807789930
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