
Engineering Generative AI-Based Software
- 1st Edition - May 1, 2026
- Latest edition
- Author: Miroslaw Staroń
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 7 6 0 6 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 7 6 0 7 - 1
Software Engineering professionals now face challenges in incorporating GAI into the products and programs they are developing. At this point, the knowledge about developing… Read more
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Software Engineering professionals now face challenges in incorporating GAI into the products and programs they are developing. At this point, the knowledge about developing AI-based software is mostly based on classical AI, i.e., non-generative ML systems. Developers know how to use machine learning and, to some extent, how to include it in production systems. Engineering Generative-AI Based Software takes software development to the next level by using generative AI instead. Readers learn how to use text, image and audio models as part of larger software systems. The book discusses both the process of developing such software and the architectures for this kind of software, combining theory with practice. Generative AI software is gaining popularity thanks to such models as GPT-4 or Llama. More and more products use them as part of their feature portfolio, but this software is often limited to web applications or recommendation systems. Author Miroslav Staron shows readers how to tackle the challenges of professionally engineering generative AI-based systems. The book starts by reviewing the most relevant models and technologies in this area, both theoretically and practically. Once readers know the technologies, the book goes into details of software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, various architectural styles and tactics for such systems, and different programming platforms. The book also shows how to create robust licensing models and the technology to support them. Finally, readers learn how to manage data, both during the training and also when generating new data, as well as how to use the generated data and user feedback to constantly evolve generative AI-based software.
- Emphasizes holistic software engineering approach to constructing generative AI software
- Shows use of modern models to create long-term products that can bring value
- Presents a combination of process, product, and business models for generative AI-based software engineering
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.
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
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
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
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