Prompts for Video Generation
Learn how to direct AI video models by mastering cinematic language, temporal reasoning, and motion control for high-fidelity narrative generation.
Video generation represents the most complex form of multimodal prompting. While image generation requires spatial control and audio generation requires temporal control, video generation demands both simultaneously. We are no longer specifying a static frame or a single waveform; we are defining a sequence of frames that evolve coherently over time.
Video prompting can be defined as the structured specification of subject, environment, motion, camera behavior, and temporal progression to guide a generative model in producing a coherent moving sequence. Unlike static media, video includes dynamics such as motion continuity, pacing, transitions, and narrative flow.
When prompting for video, we must reason across four primary dimensions:
Space: Refers to what appears within the frame and how visual elements are arranged.
Time: Describes how the scene evolves or unfolds over a duration.
Motion: Defines how subjects and the camera move within the sequence.
Style: Specifies how the sequence is rendered visually.
The central challenge is coordination. A well-written video prompt must ensure that subject movement aligns with camera motion, lighting remains consistent across frames, and environmental details remain stable. Small ambiguities can compound over time, leading to drift, inconsistency, or visual artifacts.
In this lesson, we aim to establish a structured framework for designing production-grade video prompts. We will adopt a cinematic vocabulary, define controllable components, and examine how to maintain continuity and realism across time.