Developer shares prompt engineering lessons from building AI text-to-video tool

A developer building CineGen, an AI text-to-video generator, discovered that prompting for video requires a fundamentally different approach than image prompting. Unlike static image prompts, effective video prompts must specify what is in the frame, what is moving, and how the shot evolves over time. The developer found that using cinematography vocabulary — such as shot types, camera movements, and lens descriptions — significantly improved output quality and reduced visual artifacts. Structuring prompts around a three-beat arc of establish, action, and resolve also helped eliminate the disjointed, slideshow-like effect common in AI-generated clips. The key takeaway is to use motion-focused, verb-driven language and direct the camera explicitly, rather than relying on descriptive adjectives alone.