Applied AI for Enterprise Java Development
Leveraging Generative AI, LLMs, and Machine Learning in the Java Enterprise
Published on 30. November 2025
Book
Paperback/Softback
350 pages
978-1-0981-7450-7 (ISBN)
Description
As a Java enterprise developer or architect, you know that embracing AI isn't just optional-it's critical to keeping your competitive edge. The question is, how can you skillfully incorporate these groundbreaking AI technologies into your applications without getting mired in complexity?
Enter this clear-cut, no-nonsense guide to integrating generative AI into your Java enterprise ecosystem. With insights from authors Alex Soto Bueno, Markus Eisele, and Natale Vinto, you'll learn to marry the robustness of Java's enterprise world with the dynamism of AI. It's more than just a how-to-it's a way to elevate enterprise software with savvy AI integrations, ensuring your skills and your applications remain on the cutting edge.
Inside, you'll unlock the power to:
Demystify GenAI's role and impact on contemporary software development
Craft actionable, AI-driven applications using Java's rich ecosystem of open source frameworks
Implement field-tested AI patterns tailored for prod-ready, enterprise-strength applications
Access and integrate top-tier open source AI models with Java's Inference APIs
Navigate the Java framework landscape with AI-centric agility and confidence
Enter this clear-cut, no-nonsense guide to integrating generative AI into your Java enterprise ecosystem. With insights from authors Alex Soto Bueno, Markus Eisele, and Natale Vinto, you'll learn to marry the robustness of Java's enterprise world with the dynamism of AI. It's more than just a how-to-it's a way to elevate enterprise software with savvy AI integrations, ensuring your skills and your applications remain on the cutting edge.
Inside, you'll unlock the power to:
Demystify GenAI's role and impact on contemporary software development
Craft actionable, AI-driven applications using Java's rich ecosystem of open source frameworks
Implement field-tested AI patterns tailored for prod-ready, enterprise-strength applications
Access and integrate top-tier open source AI models with Java's Inference APIs
Navigate the Java framework landscape with AI-centric agility and confidence
More details
Language
English
Place of publication
Sebastopol
United States
Target group
Professional and scholarly
Dimensions
Height: 232 mm
Width: 179 mm
Thickness: 30 mm
Weight
736 gr
ISBN-13
978-1-0981-7450-7 (9781098174507)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Alex Soto is a Director of Developer Experience at Red Hat. He is passionate about the Java world, software automation and he believes in the open-source software model.
Alex is coauthor of several books and contributes to various open-source projects, further fostering collaboration and innovation. Recognized as a Java Champion since 2017, and awarded with the Hermano Salvador González prize for his work on Emergent Intelligence applied to Data Mining.
Alex is an esteemed international speaker, sharing his knowledge and expertise at conferences and events worldwide. He also serves as a radio collaborator at Onda Cero and imparts sessions as a teacher at Salle URL University.
For the latest updates and insights into the Kubernetes and Java world, follow Alex on Twitter (@alexsotob).