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Engineering Software Systems in the AI Era
Architecture, Design, Quality, Scale & Intelligent Development
The Future of Software Engineering Has Arrived.
AI can now write code, generate tests, analyze requirements, explain systems, assist with debugging, and automate increasingly complex engineering tasks.
But building great software has never been just about writing code.
How do you design the right architecture?
How do you build systems that remain secure and reliable at scale?
How do you integrate AI without sacrificing quality, privacy, or control?
How do you use AI to make engineers more effective without replacing engineering judgment?
Engineering Software Systems in the AI Era explores these questions and provides a practical framework for designing, building, testing, securing, deploying, operating, and evolving modern software systems.
Inside, you will explore:
- Modern software architecture and system design
- Cloud-native and scalable systems
- Data architecture and intelligent data systems
- AI engineering and AI-native applications
- Cybersecurity and privacy by design
- Software quality and reliability
- DevOps, DevSecOps, and continuous delivery
- Observability and production engineering
- AI-augmented software development
- AI agents and intelligent engineering workflows
- Platform engineering
- Technical debt and engineering strategy
- AI governance and risk management
- Technical leadership in the AI era
- The future of software engineering
The central message is simple:
AI may make software development faster. Engineering makes software better.
Learn how to combine the power of artificial intelligence with the discipline of software engineering to build systems that are secure, scalable, reliable, intelligent, maintainable, and ready for the future.
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About
About the Book
Engineering Software Systems in the AI Era is a practical guide to designing, building, securing, testing, scaling, deploying, and evolving modern software systems in an increasingly AI-driven world.
The book takes a system-level approach to software engineering rather than focusing exclusively on programming.
It brings together the major disciplines required to build production-grade software:
- Software architecture
- System design
- Requirements engineering
- Data architecture
- AI engineering
- Cybersecurity
- Privacy
- Software quality
- Reliability engineering
- Cloud-native systems
- DevOps and DevSecOps
- Observability
- Platform engineering
- AI-augmented development
- Technical debt management
- Engineering strategy
- Technical leadership
- AI governance
- Intelligent software systems
A central theme throughout the book is the changing role of the software engineer.
As AI makes coding increasingly automated, engineers must become better at understanding problems, designing systems, evaluating trade-offs, verifying results, managing risk, and making architectural decisions.
This book provides a practical blueprint for doing exactly that.
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Author
About the Author
Mohammad Kamrul Hassan
Mohammad Kamrul Hassan is an IT engineer, tech consultant, and writer specializing in global politics, information technology, and travel. A former student of Voronezh State University, Russia, he currently works as an IT engineer for a UK-based international organization and collaborates with several global technology firms. Driven by a lifelong passion for international socio-political realities and long-distance travel, his writing seamlessly blends technical depth with rich, analytical global storytelling.
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