Full Description
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.
Contents
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 Audience
Chapter 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.
