TutorialSeptember 28, 2024 • 10 min read

10 Best Practices for Using Sora 2 AI Video Generator

Master Sora 2 with these expert tips and techniques. Learn how to craft perfect prompts, optimize your workflow, and create professional-quality AI videos.

1. Master Prompt Engineering

The quality of your output depends heavily on prompt quality. Follow these principles:

✅ Good Prompt Structure

[Subject] + [Action] + [Setting] + [Style] + [Camera movement] + [Lighting]

Example: "A majestic lion walking through tall savanna grass at golden hour, cinematic wide shot with slow zoom, warm sunset lighting, photorealistic"

❌ Poor Prompt

"Lion video" - Too vague, lacks detail

2. Use Specific Camera Terminology

Sora 2 understands professional camera language. Leverage this for better control:

  • Shot types: Close-up, medium shot, wide shot, extreme wide
  • Camera movements: Pan left/right, tilt up/down, dolly in/out, crane shot
  • Angles: Low angle, high angle, bird's eye view, Dutch angle
  • Lens effects: Shallow depth of field, bokeh, lens flare

3. Optimize Video Length

Sweet spot: 15-30 seconds
While Sora 2 can generate up to 60 seconds, quality tends to be highest in the 15-30 second range. For longer content:

  • Break into multiple clips and stitch together
  • Use video-to-video for transitions
  • Focus on key moments rather than continuous action

4. Leverage Style References

Mention specific visual styles for consistent results:

🎬 Cinematic Styles

  • • Film noir
  • • Cyberpunk
  • • Wes Anderson aesthetic
  • • Studio Ghibli style

🎨 Art Styles

  • • Watercolor painting
  • • Oil painting texture
  • • Pixel art
  • • Minimalist design

5. Perfect Your Lighting Descriptions

Lighting dramatically affects mood and realism:

  • Golden hour: Warm, soft morning/evening light
  • Blue hour: Cool twilight tones
  • Volumetric lighting: God rays, dust particles
  • Neon lighting: Urban night scenes
  • Studio lighting: Three-point lighting setup

6. Use Negative Prompts Effectively

Specify what you don't want to avoid common issues:

Negative prompt: "blurry, distorted faces, unnatural motion, flickering, watermark, text overlay, compression artifacts"

7. Batch Generate for Variations

Don't settle for the first result. Generate 3-5 variations of each prompt to:

  • Compare different interpretations
  • Select the best physics and motion
  • Find unexpected creative solutions
  • Build a library of options for editing

8. Optimize for Your Export Format

Use CaseRecommended Settings
Social Media1080p, 30fps, 9:16 vertical
YouTube4K, 60fps, 16:9 landscape
Presentations1080p, 30fps, 16:9
Web Banner720p, 24fps, custom aspect

9. Maintain Temporal Consistency

For best results across frames:

Avoid: Complex multi-character interactions in one shot
Instead: Focus on single subject or simple interactions

Prefer: Continuous motion over sudden changes
Instead: Smooth camera movements and gradual transitions

10. Build a Prompt Library

Save successful prompts for reuse and iteration. Organize by:

  • Subject type (people, animals, objects, landscapes)
  • Style category (realistic, artistic, animated)
  • Scene complexity (simple, moderate, complex)
  • Performance metrics (generation time, quality score)

Pro Tip: The 80/20 Rule

80% of your result quality comes from 20% of your effort. Focus on:

  1. Clear subject definition (what)
  2. Specific action/motion (how)
  3. Detailed environment (where)
  4. Visual style reference (style)

Common Mistakes to Avoid

❌ Overly Complex Prompts

Keep prompts under 200 words. Too much detail can confuse the model.

❌ Ignoring Aspect Ratios

Always specify your target aspect ratio in the prompt or settings.

❌ Not Using Seed Values

Save seed values for successful generations to recreate similar results.

Conclusion

Mastering Sora 2 is an iterative process. Start with these best practices, experiment extensively, and refine your approach based on results. The key is understanding that AI video generation is part art, part science - combine technical precision with creative experimentation.

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