AI Automation + Content Systems
Ai Is Mid Autonomous Media.
Fully automated multi-platform media pipeline that transforms single RSS input into distributed content across Spotify, TikTok, YouTube, and blog. Zero manual intervention.
System architecture.
How it's built.
Engineering process.
How it was built.
- Mapped entire manual workflow (32 distinct steps identified)
- Identified automation opportunities and technical blockers
- Defined data schema for content metadata tracking
Workflow diagram, technical specification, risk assessment
- Designed multi-layer system architecture
- Created agent prompt specifications (JSON-only outputs enforced)
- Defined webhook event flows and error handling
System architecture diagram, API contracts, database schema
- Built n8n workflows for RSS monitoring and content ingestion
- Developed Flask API for content extraction and enrichment
- Implemented GPT agents with structured prompts
- Created Supabase database schema with proper indexing
Working ingestion and processing pipeline
- Integrated Google TTS for voice synthesis
- Built ffmpeg video rendering logic in Docker container
- Implemented caption overlay with frame-accurate timing
- Integrated Pexels API for visual asset sourcing
End-to-end media generation pipeline
- Integrated platform APIs (Spotify, TikTok, YouTube, WordPress)
- Implemented error handling and retry logic
- Built monitoring dashboard and Telegram alerting
- Stress-tested with 50+ episodes
Production-ready automated system
Engineering challenges.
What broke. How we fixed it.
Media Synchronization Accuracy
ffmpeg rendering required frame-accurate sync between audio, video, and captions. Timing mismatches caused captions to appear 1–3 seconds off.
Video frame rates (30fps) vs audio sampling rates (44.1kHz) vs caption timing (millisecond precision). Off-by-one errors compounded over longer videos.
Built custom timing engine converting all timestamps to frame-based indices. Added pre-render validation for caption placement accuracy. Buffer frames added for subtitle transitions.
Caption sync: 99.8% accuracy (within 100ms). Rendering failures: 23% → <2%.
AI Content Consistency
AI-generated summaries varied in length (50–500 words) and tone. Database schema required consistent field lengths.
GPT ignores length constraints in standard prompts. Temperature settings affect consistency. Each episode has different content complexity.
Strict JSON schema validation in prompts. Token counting logic to enforce max lengths. Multi-pass validation (generate → validate → fix).
Schema consistency: 94% on first pass. Manual intervention: 40% → 6%.
Docker Resource Management
ffmpeg consumed 4–8GB RAM per process. Running multiple renders simultaneously crashed the server.
VPS with 8GB RAM total. Peak: 3 concurrent renders = 24GB needed. No server upgrade possible mid-project.
Single-threaded rendering queue. Container resource limits (6GB RAM, 2 CPU cores). Off-peak scheduling (2am–6am).
Uptime: 99.9%. Render queue: 2-hour average delay. Zero crashes in production.
Platform API Rate Limiting
TikTok API limited to 100 uploads/day. Pexels API limited to 200 requests/hour. Batch processing hit both limits.
Enterprise API tier not viable at project scale. Requests needed to be distributed across available windows.
Caching layer for Pexels results in Supabase. Exponential backoff with retry. 80% threshold alerts. Requests distributed across 24-hour window.
API limit hits: zero in production. Success rate: 95% first attempt.
Measured impact.
Results. Numbers only.
Operational efficiency
Production time: 4–6 hours → 8 minutes (97% reduction)
Manual steps: 32 → 2 (quality review + approval only)
Platform distribution: 1 → 4 platforms (4x reach)
Automation coverage: 0% → 95%
Technical performance
Automation success rate: 95%
System uptime: 99.9%
Media rendering: 1080p @ 30fps standard
Processing queue: real-time, no backlog
Infrastructure footprint
Labor saved: 20–25 hours/week
Infrastructure footprint: single VPS + standard API tiers
Scalability headroom: 10x current volume, no infrastructure changes
Related.
Related systems.
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