Status: 📋 Planned
Version: Future
Last Updated: November 15, 2025
Auto-generate case study videos by running commands with recording, editing (speed up, add captions, highlight logs), cutting unnecessary parts, and producing 1-minute demo videos automatically for showcasing MassGen capabilities.
Automate the entire video production pipeline for MassGen case studies: from running the command to publishing a polished 1-minute demo video, eliminating manual video editing work.
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Automated Recording
- Record entire MassGen execution session
- Capture terminal output, logs, and visual output
- Track important events (agent responses, tool calls, results)
- Support both terminal and browser recording
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Intelligent Editing
- Speed up boring sections (compilation, waiting, repetitive output)
- Cut unnecessary parts (errors that were recovered, redundant logs)
- Highlight key moments (final answers, important decisions, insights)
- Add captions for important commands and outputs
- Picture-in-picture for multi-agent coordination
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Content Analysis
- Video understanding to identify key frames
- Log analysis to find important events
- Automatic chapter markers
- Generate video description and keywords
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Production Quality
- Add intro/outro sequences
- Background music (optional)
- Smooth transitions between sections
- Professional color grading and effects
- Export in optimal format and resolution
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Multi-Format Output
- Full recording (for documentation)
- 1-minute highlight reel (for social media)
- 30-second teaser (for Twitter)
- GIF animations (for docs/GitHub)
- Tutorial segments (for YouTube)
Run MassGen Command
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Record Session (asciinema/OBS)
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Analyze Recording (identify key moments)
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Edit Video (speed up, cut, add effects)
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Generate Multiple Formats
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Publish (YouTube, Twitter, Docs)
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Short Task Recording (5 min execution)
- Task: Simple research query
- Test: Record, edit, produce 1-min video
- Expected: Captures key moments, smooth pacing
- Validation: Video is watchable and informative
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Long Task Recording (30 min execution)
- Task: Complex multi-agent workflow
- Test: Handle long recording, intelligent time-lapse
- Expected: Condense to 2-3 minutes without losing narrative
- Validation: All major steps visible, progression clear
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Multi-Agent Recording
- Task: Parallel agent execution with coordination
- Test: Show multiple agents working simultaneously
- Expected: Picture-in-picture or split-screen layout
- Validation: Easy to follow, coordination visible
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Error Recovery Recording
- Task: Task with failure and recovery
- Test: Show error briefly, then skip to recovery
- Expected: Error visible but not dwelled on
- Validation: Maintains flow, shows resilience
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Caption Accuracy Test
- Task: Recording with important commands/outputs
- Test: Auto-generate captions for key moments
- Expected: Captions are accurate, well-timed, readable
- Validation: Human review of caption quality
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Full Pipeline Test
- Task: Run case study, produce video automatically
- Test: End-to-end automation with no manual intervention
- Expected: Publication-ready video in <10 minutes
- Validation: Video quality suitable for public sharing
Technical Quality:
- Resolution: 1080p minimum
- Frame rate: 30fps minimum
- Audio quality: Clear, no artifacts
- Compression: Balanced quality/size
Content Quality:
- Narrative clarity: Easy to follow
- Pacing: Not too fast or slow
- Information density: Key points visible
- Engagement: Holds attention
Production Value:
- Transitions: Smooth and professional
- Captions: Readable and well-placed
- Effects: Subtle and helpful
- Branding: Consistent with MassGen identity
- ✅ Full automation: command → published video
- ✅ 10:1 compression ratio (10 min → 1 min) without losing key info
- ✅ Human evaluation: Video quality >7/10
- ✅ Caption accuracy >95%
- ✅ Processing time <10 minutes per video
- ✅ Videos suitable for public sharing (YouTube, Twitter)
Recording:
- asciinema for terminal (from v0.1.14)
- OBS Studio for screen capture
- Browser automation recording
- Event logging for synchronization
Video Understanding:
- Multimodal models (v0.1.3) for frame analysis
- Log parsing for event detection
- Importance scoring for key moments
Editing:
- FFmpeg for video manipulation
- Python libraries: moviepy, opencv
- Automated editing scripts
- Caption generation
Planning Mode:
- Break editing into phases
- Coordinate multiple tools
- Handle >10min processing time
- Progress tracking and reporting
video_production:
recording:
mode: auto
capture: screen_and_terminal
fps: 30
resolution: 1920x1080
editing:
speed_up_threshold: 5 # Speed up if no activity for 5s
max_duration: 60 # Target 1 minute
cut_errors: true
add_captions: true
highlight_key_moments: true
output_formats:
- full_recording # Complete session
- highlight_reel # 1 minute
- teaser # 30 seconds
- gif_animations # Key moments
production:
intro_outro: true
background_music: subtle
branding: massgen# Record and auto-produce video
massgen --config case_study.yaml \
--query "Research AI trends and write report" \
--record \
--auto-edit \
--output-video ./demos/ai_trends.mp4
# Batch process multiple recordings
massgen-video-edit \
--recordings ./recordings/*.cast \
--template highlight_reel \
--output ./videos/- Terminal Evaluation (v0.1.14 planned) - Session recording with asciinema
- Multimodal Video Analysis (v0.1.3) - Video understanding
- Automation Mode (v0.1.8) - Structured output for analysis
Key Value: Reduce video production time from hours to minutes, enabling rapid case study publication and increasing MassGen visibility through high-quality demo videos.
Target Output: Professional demo videos similar to existing MassGen case study videos on YouTube, but produced automatically.