Applied AI. Early and all-in.
Every one of these systems follows the same principle: AI handles the labor so the human can focus on the meaning.
Credential
Produced broadcast-quality deliverables across radically compressed timelines and budgets. Delivered across independent clients and as part of the SGWX production team.
Companies need video content that competes. Traditional production timelines are long and expensive.
AI-native video production, from storyboard to final cut. A fundamentally different workflow that delivers broadcast-quality work at a fraction of the cost and timeline.
Project briefs that took days to build now take minutes. Errors eliminated. The team got their time back.
Major international sporting event. Dozens of stakeholders. Staff spent days every year pulling data from old spreadsheets, rebuilding documents from scratch.
Built an automated system that pulls historical data and generates ready-to-use briefing documents.
Analytics that took hours of manual pulls now run automatically, and surface insights the manual process missed entirely. Designed to scale.
Performance data lived on multiple platforms. Formats were inconsistent. It took hours every week to manually pull and reconcile numbers.
Built an automated system that pulls data from all platforms, merges inconsistent formats, and generates performance insights automatically.
Used the analytics pipeline to go deeper: 2+ years of performance data analyzed in hours, not weeks. Uncovered the real problem, reframed the strategy from recovery to first-time growth.
Downloads were in decline. Leadership needed a recovery plan.
Used AI to analyze 2+ years of performance data. Analysis that would have taken a team weeks. Discovered the real problem: the content had never built an organic audience. Reframed the entire strategy from recovery to first-time growth.
Automated hours of production grunt work: transcript searching, tagging, paper edits, music sourcing. Got that time back for the creative work.
55 transcripts to search. 120+ quotes to cut, shape, and structure into a 5-act story. Multiple tracks of music to source. One-person team.
Built AI tools that handled the tedious parts: transcript searching, organizing quotes into a paper edit, writing music prompts, building meta tags. What remained was the creative work: culling 120+ quotes into 26, shaping the narrative, editing the episode.
The final chapter takes that principle to its furthest conclusion yet.
Next: Experiential Knowledge Design →