Create music with AI—using songs that have stood the test of time. The AI Public Domain Songbook is a practical, hands-on collection of 50 carefully selected public-domain songs, curated and formatted to help you explore how modern AI music tools—such as Suno—interpret lyrics, structure, repetition, and musical intent. Rather than treating these songs as historical artifacts, this book presents them as working material. Each selection is offered in clean, structured text, lightly marked up to reflect verses, choruses, and form—making it easy to copy, adapt, and experiment with AI music generation. The focus is not on rigid prompts or prescriptive styles, but on learning by doing: running variations, iterating creatively, and discovering what AI music systems do well—and where they surprise you. The songs span folk music, parlor ballads, spirituals, and early popular standards, providing a rich and legally free foundation for experimentation. Because all material is drawn from the public domain, readers are free to adapt, remix, and reinvent without restriction. This book is ideal for: Musicians curious about AI-assisted composition Writers, filmmakers, and creators seeking original music workflows Educators and students exploring AI and creativity Technologists and hobbyists experimenting with generative tools Anyone interested in public-domain music and modern reinterpretation Designed as a text-first, instruction-forward songbook, this volume avoids screenshots and interface diagrams in favor of principles that will remain useful as AI tools evolve. For readers who want deeper instruction on workflows, prompting strategies, and advanced techniques, this book pairs with A Creative Guide to Making Music with Suno. The AI Public Domain Songbook is not a replacement for musicianship. It is a companion to it—an invitation to explore a new creative niche where historical music and modern artificial intelligence meet. Edited by Jesse Shanks Aquitaine Publishing
