How to Prompt for AI Video: Runway Gen-3 & Sora Movements Demystified

1. The Kinetic Language of Video Prompting

When you prompt a static image model, you describe a static state. But when prompting video systems like Runway Gen-3 Alpha, OpenAI Sora, or Luma Dream Machine, you are directing a sequence over time. You need to write in a kinetic language that defines both **subject movement** and **camera movement**.

If you don't define the camera movement, the model will often default to a lazy zoom or cause the subject to warp erratically. By taking control of the virtual lens, you establish stable frame pacing.

2. Camera Movements: Verbs that Work

Modern video models are trained on professional cinematic footage. Using real film director commands yields the highest consistency:

• Dolly-In / Dolly-Out: The camera physically moves closer to or further from the subject, changing background perspective lines.
• Tracking Shot / Trucking Shot: The camera moves horizontally alongside a moving subject, matching its speed.
• Pan and Tilt: The camera remains stationary but rotates horizontally (pan) or vertically (tilt).
• FPV Swooping Shot: For drone or high-speed kinetic movements, creating rapid depth shifts.

3. Subject Action & Pacing

Avoid ambiguous descriptions like "dancing" or "running". Instead, define the pace and transition of the action. Describe the speed using temporal terms:

• Use "slow-motion", "fluid slow pace", or "fast-paced dynamic motion" to dictate the temporal weight.
• Describe actions with clear physical bounds: e.g. "a drops of rain falling and hitting the leaf, causing it to bounce slightly" instead of just "rain on leaf".

Understanding Video Model Architecture

Before diving deeper, it helps to understand how video generation models process your prompts differently from image generators. Unlike image models that create a single static frame, video models must maintain temporal coherence — ensuring that objects, lighting, and physics remain consistent across dozens or hundreds of frames. This architectural difference has direct implications for prompt design.

Video prompts must include time-based descriptors (camera motion, action progression, pacing) that image prompts don't need. The most common mistake beginners make is writing video prompts the same way they write image prompts — describing a static scene without any motion or temporal information.

The 5-Part Video Prompt Formula

Effective video prompts follow a five-part structure that addresses both spatial and temporal dimensions:

Platform-Specific Optimization

Google Veo 3

Veo 3 excels at understanding natural language descriptions and produces highly coherent long-form video. It responds well to cinematic direction language borrowed from actual filmmaking. Key strengths: temporal consistency, physics simulation, and human motion. Use full sentences rather than comma-separated tags. The ZETRAX AI Builder's video mode is specifically optimized for Veo 3's natural language preferences.

Runway Gen-3

Runway performs best with concise, action-oriented prompts. It has strong camera motion understanding and excels at short, stylized clips. Keep prompts under 100 words for best results. Runway supports motion brush controls that let you paint motion paths directly — combine these with text prompts for maximum control.

Sora

Sora handles complex multi-subject scenes better than most competitors. It understands spatial relationships and can maintain multiple characters in frame with independent actions. However, it requires more specific physics descriptions to avoid unrealistic motion artifacts. Always specify gravity, wind, and material properties when relevant.

Common Video Prompting Mistakes

Mistake	Why It Fails	Fix
No camera motion	Produces a static image with slight jitter	Always specify camera movement
Too many subjects	Temporal incoherence and morphing	Limit to 1-2 primary subjects
Contradictory actions	Model can't resolve conflicting motion	One clear sequential action
Ignoring physics	Unrealistic fabric, water, gravity	Describe material properties

Frequently Asked Questions

How long should a video prompt be?

For Veo 3, 50-150 words works well. For Runway, keep it under 100 words. Sora handles longer prompts (up to 200 words). The key is semantic density — every word should add unique directional information.

Can I create a consistent style across multiple video clips?

Yes, by using a fixed "style prefix" across all prompts — the same camera, lens, color grade, and lighting setup. Change only the subject and action for each clip. This produces remarkably consistent results for multi-shot sequences.

What framerate should I specify?

24fps for cinematic feel, 30fps for broadcast/web content, 60fps for smooth motion. Most models default to 24fps if not specified. Higher framerates produce smoother motion but may reduce the "filmic" quality many creators prefer.

How do I handle dialogue in video prompts?

Veo 3 supports basic audio generation including speech and ambient sound. Include audio cues in your prompt: "ambient forest sounds," "distant city traffic." For lip-synced dialogue, most workflows still require separate audio production combined in post.