AI Video Production Master

AI Video Production Master

Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, style consistency, and motion graphics generation.

DECISION POINTS

Method Selection Tree

Script Analysis:
├── Content Type = Educational/Corporate/Documentary
│   ├── Budget < $50/month → Stock Footage Assembly (InVideo-style)
│   └── Budget > $50/month → Stock + T2V Hybrid
├── Content Type = Creative/Artistic/Abstract
│   ├── Timeline < 2 days → Sora/Runway T2V
│   └── Timeline > 2 days → Custom I2V with LoRA training
└── Content Type = Brand/Character-focused
    ├── Existing assets available → I2V animation pipeline
    └── No assets → Commission artists → I2V pipeline

Quality vs. Cost Decision:
├── Professional deliverable needed
│   ├── Use Sora/Runway Gen-3 (premium T2V)
│   └── Commission custom artwork for I2V
├── Prototype/test content
│   ├── Use stock footage + free T2V models
│   └── Local ComfyUI I2V generation
└── High volume production
    ├── Cloud batch processing (Vast.ai)
    └── Automated stock footage workflows

Error Recovery Tree:
├── Quality fails at T2V generation
│   ├── Switch to stock footage + motion graphics overlay
│   └── Fallback to I2V with commissioned artwork
├── Cloud GPU timeout/failure
│   ├── Retry with different provider (Vast.ai → RunPod)
│   └── Switch to local processing with extended timeline
└── Style consistency breaks
    ├── Retrain LoRA with more reference images
    └── Use IPAdapter + consistent prompt structure

Processing Location Decision Matrix

FAILURE MODES

Blurry Motion Jitter

Symptoms: Inconsistent frame rates, stuttering motion, temporal artifacts Diagnosis: Mismatched FPS settings or insufficient motion guidance Fix: Set consistent 24fps pipeline, add motion strength controls, use higher guidance scale (7-9) Detection Rule: If temporal consistency score < 0.7 or frame delta > 0.3, apply motion stabilization

Character Consistency Drift

Symptoms: Character appearance changes between shots, style inconsistency Diagnosis: Insufficient reference conditioning or LoRA overfitting Fix: Retrain LoRA with 15-20 reference images, use IPAdapter for face consistency Detection Rule: If character similarity score < 0.8 between consecutive shots, halt and retrain

Cost Overrun Spiral

Symptoms: Cloud GPU bills exceed budget by >200%, slow iteration cycles Diagnosis: No cost monitoring or inefficient batch sizing Fix: Set hard limits in cloud scripts, optimize batch sizes, use spot instances Detection Rule: If cost-per-minute exceeds $0.50 or iteration time > 15min, switch to local processing

Audio Desync Cascade

Symptoms: Lip sync drift, audio-visual timing mismatches Diagnosis: Variable generation times affecting audio alignment Fix: Generate all video first, then align audio in post with markers Detection Rule: If audio offset > 200ms from video markers, re-align with FFmpeg

Schema Bloat Paralysis

Symptoms: Too many generation options, analysis paralysis, project stalls Diagnosis: Over-optimization without testing simple approaches first Fix: Always start with stock footage proof-of-concept, iterate to complexity Detection Rule: If project planning > 2 hours without generated content, default to stock footage

WORKED EXAMPLES

Educational Video: "Quantum Computing Explained"

Input: 3-minute script about quantum computing basics

Decision Process:

1. Content analysis: Educational → Stock footage recommended
2. Budget check: $30 budget → Use Pexels API + motion graphics
3. Shot breakdown: 12 shots needed
4. Quality target: Professional but not cinematic

Execution:

# Step 1: Generate shot list from script
python scripts/script_analyzer.py --script quantum_script.txt
# Output: 12 shots identified, 8 require stock footage, 4 need motion graphics

# Step 2: Source stock footage
python scripts/stock_video_generator.py --shots_file shots.json --style documentary
# Selected: Laboratory footage, abstract tech visuals, clean backgrounds

# Step 3: Generate motion graphics for complex concepts
python scripts/motion_graphics_generator.py --type data_viz --concept "quantum_states"
# Created: Animated diagrams for superposition, entanglement

# Step 4: Assembly and sync
python scripts/video_assembler.py --footage stock_clips/ --graphics motion/ --audio narration.wav

Expert vs. Novice:

• Expert: Checked audio levels before graphics generation, chose 16:9 format for platform compatibility
• Novice would miss: Consistent lighting in stock selection, proper motion graphic duration matching speech pace

Final output: 3:15 video, cost $0 (free stock), 45 minutes total production time

QUALITY GATES

Video production complete when ALL conditions met:

• Frame rate consistent at 24fps across all segments
• Audio levels normalized between -23dB and -18dB LUFS
• Visual style maintains consistency (color grading, aspect ratio)
• Motion graphics sync with narration within 100ms tolerance
• Character/subject consistency score >0.8 across shots
• No temporal artifacts (flicker, jitter) in any 5-second segment
• Subtitle/caption timing aligned with audio peaks
• Export renders without errors in target resolution
• File size within platform limits (YouTube: <128GB, social: <4GB)
• Backup files stored with version control

NOT-FOR BOUNDARIES

This skill should NOT be used for:

• Real-time video editing → Use DaVinci Resolve or Premiere Pro directly
• Complex video effects/compositing → Delegate to After Effects or physics-rendering-expert skill
• Audio production beyond basic sync → Use sound-engineer skill for mixing, mastering, sound design
• 3D modeling or complex animation → Use Blender/Maya or physics-rendering-expert skill
• Live streaming or broadcast → Use OBS Studio or broadcast-specific tools
• Color grading beyond basic correction → Use professional colorist workflows
• Motion tracking or match moving → Use specialized tracking software
• Multi-camera synchronization → Use dedicated sync tools like PluralEyes

Handoff triggers:

• If project requires >20 layers of compositing → physics-rendering-expert
• If audio needs custom sound design → sound-engineer
• If 3D elements need modeling → Blender specialist
• If real-time performance needed → Use native video editing software