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
| Shot Count | Complexity | Budget | Recommendation |
|---|
| 1-5 | Simple | Any | Local M4 Max |
| 6-20 | Medium | <$10 | Stock footage |
| 6-20 | High | >$10 | Cloud GPU batch |
| 20+ | Any | Any | Cloud GPU required |
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:
- Content analysis: Educational → Stock footage recommended
- Budget check: $30 budget → Use Pexels API + motion graphics
- Shot breakdown: 12 shots needed
- 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:
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