Press & Media

About the Book

• Q.What inspired you to write Sovereign AI?
• Q.Who is this book for?
• Q.What misconceptions about AI do you hope to challenge?
• Q.What surprised you most while writing the book?

AI Infrastructure

• Q.Why are local models becoming increasingly important?
• Q.How should developers think about AI ownership?
• Q.What role does RAG play in production systems?
• Q.Are knowledge graphs making a comeback?
• Q.How do you approach long-term AI memory?

Industry

• Q.Where do you think AI is heading over the next five years?
• Q.Which open-source AI projects excite you the most?
• Q.What advice would you give developers entering AI today?

Personal

• Q.How did you become interested in AI?
• Q.What does your development workflow look like?
• Q.What are you building next?

Short Bio (50 Words)

Daniel Kliewer is a software engineer, AI researcher, and author of Sovereign AI. His work focuses on local AI, Retrieval-Augmented Generation (RAG), AI agents, knowledge graphs, and open-source AI systems designed around ownership rather than dependence.

Medium Bio (100 Words)

Daniel Kliewer is a software engineer, AI researcher, and author specializing in local-first artificial intelligence. His work explores open-source LLMs, Retrieval-Augmented Generation (RAG), knowledge graphs, AI agents, and long-term memory architectures. Through his writing and software projects, he advocates for building AI systems that users own, understand, and control. His book, Sovereign AI, examines the technologies and architectural principles that enable developers to create resilient, privacy-conscious AI applications independent of proprietary cloud services.

Long Bio (250 Words)

Daniel Kliewer is a software engineer, AI researcher, open-source contributor, and author focused on the emerging field of sovereign artificial intelligence. His work centers on the belief that the future of AI should be defined not only by increasingly capable models but also by the ability of individuals and organizations to own, understand, and control the intelligent systems they build.

His research and development span local large language models, Retrieval-Augmented Generation (RAG), knowledge graphs, semantic search, AI agents, long-term memory systems, and local-first architectures. By combining these technologies, he explores practical approaches to creating AI systems that remain resilient in the face of changing APIs, evolving cloud services, and rapidly shifting commercial ecosystems.

As the author of Sovereign AI, Daniel presents a technical and philosophical framework for designing AI infrastructure around ownership, transparency, and sustainability. His work encourages developers to think beyond prompt engineering and consider the broader architecture that supports intelligent software over the long term.

In addition to writing, Daniel develops open-source software, publishes technical articles, and shares practical insights into building modern AI systems. His mission is to help developers move from simply consuming AI services to creating intelligent systems they truly own.