What I build.
Creative operating systems. AI governance frameworks. Intake-to-delivery architecture.
Creative Operating System Architecture
Most creative teams run on improvisation. Requests come in through Slack. Priorities shift in meetings. Assets pile up in shared drives with names that stopped making sense two months ago. The work gets done, but nobody knows why some projects take two days and others take two weeks.
I design the infrastructure that makes creative production predictable: intake systems with structured brief requirements, sprint-based prioritization models, single-source-of-truth delivery pipelines, and capacity frameworks that match workload to team bandwidth before deadlines do. Built in Monday.com, Asana, Workfront or the tools your team already uses.
AI Governance & Workflow Integration
AI adoption in creative organizations follows a pattern. Someone discovers a tool. Three other people start using three different tools. Nobody agrees on what AI can approve, what it should flag, and what requires a human decision. The tools multiply. The chaos compounds.
I build the governance layer that keeps AI useful and accountable: guardrail-based system instruction frameworks, human-in-the-loop approval gates, confidence-scoring models, and audit trails that give stakeholders in Legal, Brand, and IT the visibility they need to say yes. The goal is not limiting what AI can do. It is making sure the right humans stay in the right decisions.
Intake, Prioritization & Capacity Planning
The intake problem is almost always a communication problem. Requestors submit incomplete briefs. Creative teams make assumptions. Revision cycles run long because the work was built on the wrong foundation. Speed-to-market targets get missed because nobody caught the mismatch at the front door.
I design intake systems that create accountability on both sides of the request: structured brief templates that surface missing information before work begins, intake scoring that flags high-risk or underdefined requests, and capacity models that connect incoming volume to actual team bandwidth. The result is a creative team that can say yes to the right work, no to the wrong work, and always explain why.
Performance-Connected Creative Operations
Creative teams produce assets. Media teams run campaigns. Performance data lives in a dashboard that the creative team checks once a quarter, if at all. The gap between creative output and business outcome is where brand equity and budget both disappear.
I build the feedback loop that closes that gap: KPI frameworks that connect creative decisions to performance signals, campaign sunset and iteration criteria, and reporting pipelines that trigger creative review when assets underperform rather than waiting for a quarterly debrief. Creative teams that operate with performance data make better briefs, faster iterations, and more defensible decisions in front of leadership.
Recent work
At AAA Auto Club Enterprises (2021–2026): Built Creative Services from one to nine. Increased delivery speed by 50%. Achieved 95% on-time asset delivery. Designed and deployed a centralized Monday.com intake and sprint system. Led AI platform evaluation and established governance frameworks across Google Vertex AI Studio and generative production tools.
At ProCom Products / SWAGTRON (2016–2021): Built a project management system for high-volume ecommerce content production from scratch. Scaled TikTok to 264K followers in under six months. Directed concurrent content programs across Amazon, Amazon Live, Instagram, and Facebook.
Production background: Eleven years directing and shooting commercial photo and video for Verizon Wireless, Morgan Stanley, Ralph Lauren, TD Ameritrade, Travel Channel, and Gilt Groupe across New York and Los Angeles markets. That experience is why I understand where creative production breaks down — and how to design systems that prevent it.