Text-to-Video Fundamentals

Text-to-video AI is one of the most exciting developments in content creation. You describe what you want to see, and the AI generates video footage. Let's understand how it works and how to get the best results.

How Text-to-Video Works

Modern text-to-video models use a process called diffusion:

1. Start with noise: The model begins with random visual noise
2. Denoise guided by text: Step by step, it removes noise while being guided by your text prompt
3. Maintain temporal coherence: Unlike images, video must be consistent across frames
4. Output video: The result is a short clip, usually around 5 to 15 seconds. Many models now generate matching sound at the same time

Think of it as the AI "imagining" what your description would look like as video, then gradually bringing that vision into focus.

Current Capabilities and Limitations

What AI Video Does Well

• Cinematic establishing shots: Landscapes, cityscapes, aerial views
• Abstract and artistic visuals: Dream-like sequences, creative effects
• Simple motion: Camera movements, basic object motion
• Atmospheric footage: Weather, lighting effects, ambiance
• Style consistency: Maintaining a visual style throughout
• Sound: The leading models (like Veo and Kling) add dialogue, sound effects, and background audio that match the picture

What AI Video Struggles With

• Complex human motion: Walking, dancing, hand movements
• Text in video: Words often become garbled
• Physics accuracy: Objects interacting realistically
• Long duration: One clip is still short. Longer scenes are made by extending clips or joining several shots
• Specific details: Exact compositions are hard to achieve

The Anatomy of a Video Prompt

A good video prompt has these components:

1. Subject

What is the main focus of the video?

A golden retriever puppy

2. Action/Motion

What is happening? What moves?

A golden retriever puppy running through a meadow

3. Setting/Environment

Where does this take place?

A golden retriever puppy running through a sunlit meadow with wildflowers

4. Camera Motion

How does the camera move?

A golden retriever puppy running through a sunlit meadow with wildflowers, tracking shot following the dog

5. Style/Quality

What's the visual style and quality?

A golden retriever puppy running through a sunlit meadow with wildflowers, tracking shot following the dog, cinematic, 4K, warm golden hour lighting

6. Sound (for models that generate audio)

What should we hear?

A golden retriever puppy running through a sunlit meadow with wildflowers, tracking shot following the dog, cinematic, warm golden hour lighting. Sound: happy barking, rustling grass, birdsong

Try It: Build a Prompt

Improve the prompt below. The checker shows which of the six parts you've covered, and what to add next. It runs in your browser and doesn't send anything to an AI.

Camera Motion Terms

Camera motion is crucial for video. Here are terms AI video tools understand:

Term	Effect
Static shot	Camera doesn't move
Pan left/right	Camera rotates horizontally
Tilt up/down	Camera rotates vertically
Tracking shot	Camera follows subject
Dolly in/out	Camera moves toward/away
Zoom in/out	Lens zooms (different from dolly)
Crane shot	Camera rises or descends
Orbit/arc	Camera circles subject
Handheld	Slight natural shake
Steadicam	Smooth following motion

Video Style Keywords

These terms help establish the visual style:

Cinematic Qualities:

• Cinematic, film grain, anamorphic
• 35mm film, IMAX, documentary style
• High contrast, moody lighting

Quality Terms:

• 4K, 8K, high definition
• Sharp, detailed, crisp
• Professional, broadcast quality

Lighting:

• Golden hour, blue hour, magic hour
• Dramatic lighting, soft light
• Backlit, rim lighting, silhouette

Color:

• Warm tones, cool tones, muted colors
• Vibrant, saturated, desaturated
• Sepia, black and white, teal and orange

Common Prompt Patterns

The Establishing Shot

Aerial view of [location], slowly descending,
cinematic, golden hour lighting, 4K

The Product Shot

[Product] rotating slowly on a white surface,
studio lighting, commercial quality, shallow depth of field

The Nature Scene

[Animal/plant] in [environment], gentle movement,
nature documentary style, soft natural lighting

The Abstract/Artistic

Abstract flowing [material/color], morphing and transforming,
dreamlike, surreal, smooth motion, ethereal lighting

The Urban Scene

[City/street] at [time of day], [people/vehicles] in motion,
cinematic, [camera motion], atmospheric

Iterating on Prompts

Your first generation rarely matches your vision. Here's how to iterate:

If the motion is wrong: Add or change camera terms, specify "slow motion" or "fast motion"

If the style is wrong: Add more style keywords, reference specific film looks

If the subject is wrong: Be more specific about the subject, add details

If it's too chaotic: Add "stable," "steady," "minimal motion," "subtle movement"

If it's too static: Add "dynamic," "energetic," specify what should move

Prompt vs. Image-to-Video

You have two main approaches:

Text-to-Video:

• Start from scratch with a text description
• Best for: Abstract concepts, when you don't have reference images
• Less control over exact composition

Image-to-Video:

• Start with a still image and animate it
• Best for: Specific compositions, consistent characters
• More control over the starting point

Many workflows combine both: generate images first, then animate them. Newer tools also let you add reference images, so the same character or product looks the same across several clips.

Key Takeaway

Effective video prompting requires understanding both what AI can do well and how to communicate your vision through specific terminology. Start with clear subject-action-setting descriptions, add camera motion, and refine with style keywords. In the next lessons, we'll apply these fundamentals to specific tools.