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Engineering Generative AI-Based Software

  • 1st Edition - January 5, 2026
  • Latest edition
  • Author: Miroslaw Staroń
  • Language: English

Engineering Generative-AI Based Software discusses both the process of developing this kind of AI-based software and its architectures, combining theory with practice. Sectio… Read more

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Description

Engineering Generative-AI Based Software discusses both the process of developing this kind of AI-based software and its architectures, combining theory with practice. Sections review the most relevant models and technologies, detail software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, explore various architectural styles and tactics for such systems, including different programming platforms, and show how to create robust licensing models. Finally, readers learn how to manage data, both during training and when generating new data, and how to use generated data and user feedback to constantly evolve generative AI-based software.

As generative AI software is gaining popularity thanks to such models as GPT-4 or Llama, this is a welcomed resource on the topics explored. With these systems becoming increasingly important, Software Engineering Professionals will need to know how to overcome challenges in incorporating GAI into the products and programs they develop.

Key features

  • Provides a holistic software engineering approach to constructing generative AI software
  • Shows how to use modern models to create long-term products that bring value
  • Presents a combination of process, product, and business models for generative AI-based software engineering

Readership

Computer Science researchers, software engineers, programmers, and software researchers in academia and industry, including software engineers, software developers, and architects who are interested in developing software that includes GAI in their product/programming. The book will also cater to developers, researchers, or professionals working with artificial intelligence, machine learning, and natural language processing who are looking to learn more about GAI integration in Software Engineering.

Table of contents

1. Introduction

2. Generative AI basics

3. Constructing Generative AI software

4. Functional and Non-Functional Requirements for Generative AI Software

5. Architecting Generative AI Software

6. Implementation and Quality Assurance of Generative AI Software

7. Handling Data for Generative AI Systems

8. Deployment of Generative AI Software

9. Generative AI Ecosystems

10. Summary and Current Trends

Product details

  • Edition: 1
  • Latest edition
  • Published: January 5, 2026
  • Language: English

About the author

MS

Miroslaw Staroń

Miroslaw Staron is a professor of software engineering at the Department of Computer Science and Engineering at the University of Gothenburg, Sweden. Dr. Staron has been active in national bodies such as AI Sweden, AI Competence for Sweden, and Swedsoft. His research work focuses on software design, metrics, machine learning, and software quality.

Affiliations and expertise
Department of Computer Science and Engineering, Chalmers University of Technology, Sweden

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