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8.9
@Limited_Edition_Jonathan
Co-Founder of AI Cred. Ai Developer. Owner of Contention Media Video Production.
AI Fluency Score
8.9/10
Assessed 11/25/2025
Velocity
Co-Founder, AI Cred | AI Developer | Owner, Contention Media Video Production
Video production veteran turned AI automation architect. I run Contention Media out of Wilkes-Barre, PA, where I've spent over a decade producing commercials, corporate videos, documentaries, and political campaign content. My technical foundation in DaVinci Resolve workflows and professional camera systems led me down the rabbit hole of AI-powered automation—and I never came back out.
Now I build production-grade AI systems: automated podcast generation pipelines using ElevenLabs, multi-agent orchestration with Claude Code, content workflows in n8n, and CRM architectures that actually scale. I treat prompt engineering as a craft, developing reusable templates and testing frameworks across platforms.
I write about AI, technology criticism, and calling out panic narratives on my Substack. I host the Mega Holy Podcast, which uses AI tools to expose evangelical harm. I believe AI should be a force multiplier for independent creators and small businesses—not just enterprise tech.
My approach: systematic problem-solving, direct communication, and zero patience for unfalsifiable claims. If something's broken, I fix it. If a workflow sucks, I rebuild it. If the conventional wisdom is wrong, I'll say so.
Currently building AI-powered business automation, migrating from fragmented tools to centralized systems, and trying to convince more people that the machines aren't coming for us—they're coming with us.
Generated 12/1/2025
Jonathan Edwards is a video production veteran turned AI automation architect with over a decade of media experience and 2-3 years building production-grade AI systems. He designs infrastructure that compounds—versioned prompt databases, multi-agent orchestration, sectional architectures that cut token overhead by 80%—treating AI development as engineering discipline rather than casual experimentation.
His systematic approach to workflow design positions him to solve the problems most practitioners haven't even identified yet: how to make AI fluency transferable, how to build systems that scale beyond individual productivity, how to architect for graceful failure rather than perfect prediction.
The assessment platform you're reading this on? He built it—and it's just the beginning of what he's shipping.