Learn how to structure, scale, and extend GenAI applications using 20+ software design patterns in a modular, production-ready architecture
Key Features
- Apply 20+ classic design patterns to GenAI systems with real code examples
- Build a modular, extensible GenAI platform using proven software architecture principles
- Master pattern-driven approaches to prompt design, memory, model management, and APIs
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Build modern GenAI applications that go beyond simple prompt and response loops. This book shows you how to apply proven software design patterns to build modular, testable, production-ready generative AI systems. You will explore more than 20 classic patterns including Facade, State, Interpreter, Factory, Proxy, and Strategy, mapped to real GenAI challenges such as prompt construction, session memory, tool execution, model API abstraction, and extensibility. Each pattern is introduced with context, explained through code, and connected to components in a reference GenAI system called Metis. Learn to build prompts with Builder and Template Method, manage conversations with State and Memento, control model lifecycles with Factory, Singleton, and Proxy, and abstract model APIs using Adapter and Bridge. You will also work through advanced topics like plugin architectures, instrumentation, and caching strategies for scale. Written by an experienced engineer and system architect, this book provides a practical blueprint for designing robust GenAI platforms. Whether you are building internal AI tools or commercial LLM products, you will gain the architectural thinking needed to scale confidently. By the end, you will be able to architect GenAI systems that are modular, composable, extensible, and ready for real-world complexity.
What you will learn
- Apply classic design patterns to GenAI system components
- Implement modular orchestration using Facade and Mediator
- Manage conversational state and memory with Memento and State
- Build dynamic prompts with Builder and Template Method
- Integrate multiple model APIs using Adapter and Bridge
- Add tool execution workflows using Command and CoR
- Customize system behavior with Strategy and Plugin patterns
- Design extensible, scalable LLM platforms for production use
Who this book is for
This book is for software engineers, system architects, and GenAI developers building real-world large language model (LLM) systems. It assumes you're comfortable writing Python and familiar with the basics of LLMs or APIs like OpenAI or Claude. Readers should have experience developing backend systems or platforms and want to elevate their approach to GenAI design using formal software architecture principles.
