💡 The Power of Prompts

Expert creators dedicate 70% of their effort to crafting precise prompts, leaving only 30% for video generation. Perfecting prompts is the cornerstone of exceptional AI video production.

The VISION Prompt Framework

The VISION Framework:

Visual Description + Image Quality + Style Keywords + Instruction Clarity + Output Parameters + Negative Prompts

Understanding the VISION Components

1. Visual Description (30% of prompt)

This defines the core visuals of your scene, specifying exactly what the AI should render. For example, you might describe a '30-year-old man with short black hair, wearing a black suit, standing in a futuristic cityscape, with a determined expression.'

"30-year-old man with short black hair, wearing black suit, standing in futuristic cityscape, determined expression"

2. Image Quality (20% of prompt)

This section ensures high-quality output by including technical details like '4K resolution, cinematic lighting, high detail, professional-grade visuals, sharp focus.'

"4K resolution, cinematic lighting, high detail, professional-grade visuals, sharp focus"

3. Style Keywords (20% of prompt)

These keywords shape the artistic tone, such as 'futuristic aesthetic, cyberpunk vibe, neon lighting, dynamic atmosphere,' to align the video with your creative vision.

"futuristic aesthetic, cyberpunk vibe, neon lighting, dynamic atmosphere"

Advanced Prompt Strategies

Strategy 1: Prompt Chaining for Continuity

Prompt chaining ensures seamless transitions by linking scenes through consistent references to previous prompts, maintaining visual and narrative coherence.

Scene 1 → Scene 2 Example:

Scene 1:

"James, 30-year-old man in black suit, entering futuristic city building, neon-lit night"

Scene 2:

"Same man from previous scene, James in black suit, now inside high-tech office, continuing from entrance, neon lighting"

Strategy 2: Negative Prompting

Negative prompts help eliminate unwanted elements, ensuring cleaner outputs by specifying elements to avoid, such as 'blurry images, distorted features, extra objects, unrealistic lighting.'

Common Negative Prompts:

• "blurry images, distorted features, extra objects"
• "inconsistent lighting, crowded scenes, multiple characters"
• "cartoonish style, exaggerated proportions, unrealistic visuals"
• "text overlays, watermarks, logos, signatures"

Optimizing for AI Video Platforms

Runway ML Tips:

• Keep prompts concise, under 500 characters
• Specify camera angles and movements
• Include detailed lighting instructions
• Simplify complex scene descriptions

Pika Labs Tips:

• Use detailed, longer prompts for better results
• Describe motion and dynamic elements
• Define frame composition clearly
• Reference specific artistic styles

Avoiding Common Prompt Pitfalls

❌ Pitfall: Overly General Prompts

Bad: "Man in city"

✅ Better: "30-year-old businessman in a tailored suit, walking through a neon-lit cyberpunk city at night, confident demeanor"

❌ Pitfall: Inconsistent Details

Bad: Scene 1: "dark-haired man" → Scene 2: "man"

✅ Better: Consistent: "Liam, short dark hair, green eyes, black jacket" across all scenes

🚀 PromptyScript's Automation Advantage

While manual prompt engineering is a valuable skill, PromptyScript simplifies the process by automating key tasks. It maintains character consistency, creates optimized prompt sequences, adapts prompts for various platforms, and includes effective negative prompts and quality settings for superior results.

Automate Your Prompts →

Your Prompt Engineering Toolkit

🛠️ Essential Prompt Templates:

Character Introduction:

"[Name], [age] year old [gender], [physical description], [clothing], [location], [lighting], [mood], cinematic quality, 4K"

Scene Transition:

"Same character from previous scene, [character name with key features], now [new location/action], maintaining [consistent elements]"

Action Scene:

"[Character], [specific action], [camera movement], [lighting change], dynamic composition, [emotional state]"

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