This book examines the structural limitations of modern AI video generation systems and explains why consistent results often fail despite detailed prompting.
Rather than treating AI as a black box or a simple tool, it analyzes internal constraints such as token limits, memory resets, and narrative fragmentation, and introduces the Sink Seeding Method as a practical framework to work within those limits.
Through real production analysis and controlled comparisons, the book demonstrates how structured intent, thematic continuity, and dialogue-based design allow AI systems to behave as if they possess memory and purpose.
This is not a catalog of tools or shortcuts. It is a system-level explanation for creators who want to understand how AI actually processes intent, time, and structure in long-form video generation.
