MMT Media Response Accelerator
Software Specification: MMT Media Response Accelerator
Executive Summary
The MMT Media Response Accelerator is an AI-powered web application that transforms recorded media appearances by MMT economists into publication-ready social media content within one hour of broadcast. When MMT advocates appear on news shows, podcasts, or other media, the narrow amplification window often closes before manual content creation can occur. This tool automatically processes video content to identify quotable moments, generate branded quote cards, and draft platform-specific social media posts, enabling rapid response to capitalize on media opportunities.
The system uses AI transcription and natural language processing to analyze uploaded video content, extracting the most impactful MMT messaging moments and transforming them into shareable assets. A streamlined review dashboard allows communication teams to quickly approve and distribute content across Twitter/X and LinkedIn, turning what was previously a multi-hour manual process into a sub-60-minute automated workflow with minimal human oversight.
Tool Overview
Type: Web application with AI processing pipeline
Description: An automated content processing system that ingests video of MMT economist media appearances and generates publication-ready social media assets including quote cards and platform-specific post copy through AI analysis of transcripts and automated graphic generation.
Primary Users: MMT communication teams, social media managers, and advocacy coordinators responsible for amplifying economist media appearances
Problem Solved: Eliminates the manual content creation bottleneck that causes missed opportunities to amplify MMT messaging during the critical 1-hour post-broadcast window
Key Features
[MVP] Video Input Processing
Accept video files via upload or URL input from major platforms (YouTube, news sites) with automatic download and format standardization
User Story: As a communication coordinator, I want to quickly input a video URL or upload a file so that I can start processing content immediately after a media appearance
Complexity: medium
[MVP] AI Transcript Generation
Automated speech-to-text conversion with timestamp synchronization and speaker identification to distinguish between host and MMT economist
User Story: As a content creator, I want accurate timestamped transcripts so that I can locate specific quotes without manually transcribing
Complexity: medium
[MVP] Quotable Moment Detection
AI analysis of transcript to identify 5-10 most impactful, complete, and shareable MMT concepts using NLP trained on MMT terminology and messaging patterns
User Story: As a social media manager, I want the system to automatically identify the best quotes so that I don't have to watch entire videos to find shareable moments
Complexity: complex
[MVP] Quote Card Generator
Automated creation of branded visual quote cards with MMT styling, featuring extracted quotes, speaker attribution, and customizable background templates
User Story: As a communication team member, I want professional-looking quote cards generated automatically so that I can focus on distribution rather than design
Complexity: medium
[MVP] Platform-Specific Copy Generation
AI-generated social media post text optimized for Twitter/X character limits and LinkedIn professional tone, including relevant hashtags and call-to-action suggestions
User Story: As a social media coordinator, I want platform-optimized post copy so that content performs well on each social network without manual adaptation
Complexity: simple
[MVP] Content Review Dashboard
Single-page interface displaying all generated content options with preview capabilities, edit functions, and one-click approval workflow
User Story: As a team reviewer, I want to see all content options in one place so that I can quickly approve the best materials for publication
Complexity: simple
[MVP] Clipboard Export System
One-click copying of approved content (text and images) to clipboard for easy pasting into social media platforms
User Story: As a content publisher, I want to instantly copy approved content so that I can paste directly into social platforms without additional formatting
Complexity: simple
[POST-MVP] Video Clip Extraction
Automated video segment extraction around identified quotable moments with proper lead-in/lead-out timing for social media sharing
User Story: As a multimedia content creator, I want short video clips of the best moments so that I can share video content alongside quote cards
Complexity: complex
[POST-MVP] Direct Social Platform Publishing
API integration with Twitter/X, LinkedIn, and Bluesky for direct posting with scheduling capabilities
User Story: As a social media manager, I want to post directly from the dashboard so that I can streamline the entire publication workflow
Complexity: medium
[FUTURE] Performance Analytics
Tracking system to monitor which types of quotes and content formats perform best across platforms for continuous optimization
User Story: As a communication strategist, I want to see which content performs best so that I can improve future content selection
Complexity: medium
User Workflows
Rapid Content Generation Flow
Steps:
- User pastes video URL or uploads file on main dashboard
- System processes video and generates transcript with progress indicator
- AI analyzes transcript and identifies top quotable moments
- System generates quote cards and social copy for each moment
- User reviews all generated content in unified dashboard view
- User selects preferred content pieces and makes minor edits if needed
- User copies approved content to clipboard for social platform posting
Screens: Upload Interface, Processing Status, Content Review Dashboard, Edit Modal
Data Requirements
Media Appearance
Fields: video_file_path, source_url, appearance_date, economist_name, show_name, processing_status, transcript_text, created_at
Relationships: Has many QuotableMotents and GeneratedContent
Storage Notes: Video files stored in cloud storage with database references, large transcript texts may need text field optimization
Quotable Moment
Fields: transcript_text, start_timestamp, end_timestamp, confidence_score, mmt_concepts, selected_for_content
Relationships: Belongs to MediaAppearance, has many GeneratedContent
Storage Notes: Timestamps stored as seconds for easy video synchronization
Generated Content
Fields: content_type, content_text, image_url, platform, approval_status, published_at, performance_metrics
Relationships: Belongs to QuotableMoment
Storage Notes: Generated images stored separately with URL references, JSON field for performance metrics
Integrations with MMT Ecosystem
No direct integrations with existing MMT projects in MVP
Type: Future API integration potential
Future versions could integrate with MMT educational content systems to tag and categorize concepts, or connect with broader MMT advocacy coordination platforms
Data Exchanged: Content tagging, concept categorization, and coordinated messaging data
Technical Considerations
Suggested Stack: Next.js frontend with Node.js backend, PostgreSQL database, OpenAI/Whisper for transcription, cloud storage (AWS S3/CloudFlare), Redis for job queue management
Hosting: Cloud platform (Vercel for frontend, Railway/Heroku for backend) with auto-scaling for processing jobs
Authentication: Simple username/password for MVP, can expand to OAuth for team management later
Key Challenges:
- Video processing time optimization
- AI accuracy for MMT-specific terminology
- Concurrent job processing during high-volume periods
- Quote card design template system scalability
MVP Scope
Included in MVP:
- Video upload/URL input
- AI transcription
- Quotable moment detection
- Quote card generation
- Platform-specific copy
- Review dashboard
- Clipboard export
Excluded from MVP (Future):
- Video clip extraction
- Direct social posting
- Multi-user team features
- Performance analytics
- Advanced editing tools
Success Criteria: Process a 30-minute video appearance and generate 5+ publication-ready social media assets in under 15 minutes with 90%+ user satisfaction on content quality
Development Phases
Phase 1: Core Processing Pipeline
Deliverables:
- Video upload system
- AI transcription integration
- Basic quotable moment detection
- Simple content review interface
Phase 2: Content Generation System
Deliverables:
- Quote card template engine
- Platform-specific copy generator
- Clipboard export functionality
Phase 3: Enhanced Features
Deliverables:
- Video clip extraction
- Direct social platform APIs
- Performance tracking
Next Steps
- Set up development environment with video processing libraries and AI service integrations
- Create database schema and basic video upload/storage infrastructure
- Implement AI transcription service integration with timestamp synchronization
- Build quotable moment detection algorithm using NLP libraries and MMT terminology training
- Design and implement quote card template system with MMT branding