Description
Artificial intelligence is the driving force behind the next generation of software, transforming how we build, deploy, and manage cloud-native applications. This book explores the powerful convergence of artificial intelligence, machine learning, and cloud-native software engineering, offering readers a practical understanding of how modern technologies are transforming software development. It highlights how AI-driven approaches are enhancing productivity, improving decision-making, and enabling smarter, scalable systems.
Readers will gain insights into how artificial intelligence empowers software engineering practices, including intelligent automation, predictive analytics, and improved software quality. The book also covers emerging areas such as generative AI for source code creation and advanced AI tools that assist developers in writing, optimizing, and maintaining code efficiently.
By the end of this book, readers will possess a comprehensive roadmap for upgrading their technical skills and adapting to the rapid evolution of industry demands. Readers will be equipped to enhance their professional impact by strategically leveraging AI-enabled tools, accelerating development lifecycles, and building innovative, cloud-native applications with confidence.
? Explore generative AI techniques for automated source code creation.
? Learn popular AI tools for efficient software development processes.
? Apply machine learning models to improve software quality assurance.
? Design scalable applications using cloud-native architecture principles.
? Enhance productivity with intelligent automation in coding practices. Who this book is for
This book is for students, software developers, data scientists, cloud engineers, and IT professionals who want to integrate AI and ML into modern software development practices. It is also valuable for tech leads, researchers, and architects aiming to build scalable, intelligent, and cloud-native applications in evolving industry environments. Table of Contents
1. Technical Perspective of AI for Ensuring Knowledge Era
2. Empowering Software Engineering with Artificial Intelligence
3. Artificial Intelligence for Application Modernization and Migration
4. Generative and Agentic AI Principles and Practices for Accelerated Software Engineering
5. Study on AI Tools That Can Generate Software Source Code
6. AI-powered Tools to Enhance the Stages of Software Development
7. AI for IT Infrastructure Resource Optimization
8. AI and Workload Infrastructure Optimization
9. Challenges of Using AI in Software Development
10. Next-generation Developer Experience Enabled by AI
11. Coding to Prompting an Agentic AI Revolution