Building Distributed Systems in the Age of AI

Designing Intelligent, Resilient Architectures

Häftad, Engelska, 2026

769 kr

Kommande

This book provides a forward-looking guide to building distributed systems in the era of AI. It examines how foundational software architecture must collaborate and adapt to a world increasingly influenced by machine agents, real-time data streams, and autonomous behavior. As AI becomes a runtime component, rather than just a feature, traditional architectural patterns such as microservices, event-driven flows, and reactive design must be reinterpreted.This book explores emerging strategies like agent-based architectures, streaming-first systems, and privacy-preserving AI infrastructure. It demonstrates how to create intelligent, resilient systems that remain observable and interoperable even as their behavior becomes more opaque and autonomous.Beyond the technology, this book also addresses the evolving role of the software engineer. Code is no longer written solely for humans; it must now communicate clearly with large language models that read, generate, and reason about it.Finally, the book assesses the machine-centric shift of the Internet. As AI agents increasingly consume content, activate APIs, and make decisions online, the design of interfaces, protocols, and privacy safeguards must evolve. Systems must now cater to two audiences: humans and machines with very different expectations. This book is aimed at software engineers, architects, and technical leaders navigating the next generation of distributed system design. It assists them in rethinking priorities, adapting skills, and designing systems that remain relevant, scalable, and safe in an AI-shaped world. You Will:• Learn how to serve modern complex use cases in the progressing environment by combining different architectures• Discover how the responsibilities and skill sets of software engineers evolve in the context of AI-centric development• Learn to shape systems for the new audience and demands This book is for: Software engineers, architects, and technical leaders.

Produktinformation

Utgivningsdatum2026-12-13
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
FörlagAPress
ISBN9798868823930

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Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Max Hopei is a software engineer, architect, and engineering leader with over 15 years of experience building distributed systems at scale. Throughout his career, he has navigated the complexity of modern software architecture, from high-throughput messaging platforms to resilient microservices and AI-integrated systems. His work spans startups and enterprise environments, where he has led cross-functional teams, established engineering best practices, and guided organizations through complex technical transformations. Max has deep expertise in software architecture, cloud infrastructure, and developer experience, and brings a pragmatic, use-case-oriented mindset to everything he builds. He believes great engineering isn't just about technology—it's about designing systems that are understandable, evolvable, and aligned with the human context in which they operate. As a Principal Engineer at Regiondo, he led the re-platforming of one of the biggest B2B booking systems in Europe, migrating it from a monolithic to a microservices architecture. He learned to be pragmatic and to focus on market needs and systems adaptability. At the Celonis Strategy & Innovation department, he investigates emerging technologies, identifies upcoming trends, and drives the design and development of new business models to build the future of Process Intelligence.

Part 1. The Modern Technology.- Chapter 1. Setting the focus on the right things.- Chapter 2. Revising microservices architecture.- Chapter 3. Message-driven architecture.- Chapter 4. Streaming architecture.- Chapter 5. Agentic architecture.- Chapter 6. A real-world system example.- Chapter 7. Private information retrieval.- Chapter 8. Making your system approachable.- Chapter 9. Observability in unpredictable systems.- Chapter 10. Using AI in your systems.- Part 2. The New Engineer.- Chapter 11. Using AI to build systems.- Chapter 12. From “Code for people” to “Code for AI”.- Chapter 13. A programming language for LLM (by LLM).- Chapter 14. LLM-based compiler and the natural language code.- Chapter 15. A full-stack team for distributed systems.- Part 3. The New AudienceChapter 16. Machine-generated traffic.- Chapter 17. Machine-friendly content.- Chapter 18. Machine-friendly protocols.- Chapter 19. Changing expectations towards interfaces.- Chapter 20. Growing complexity of use cases.- Chapter 21. Growing data privacy pressure.- Summary.