Established leadership
Operating scale across people, platforms, and the business.
- 20+years in technology leadership
- 50+person organization and $4.3M budget at PrePass
- $300M+recurring-revenue business supported
Technology ExecutiveArtificial Intelligence TransformationProduct & Engineering Leadership
I build technology organizations that turn strategy into measurable results.
For more than 20 years, I have built and scaled product and engineering organizations, transformed established platforms, and connected technology decisions to customer and business outcomes. My current focus is helping companies redesign how technology is built and operated for the AI era.
Hands-on AI practice
Direct evidence from sustained operation—not isolated experiments.
Five months operating an independent, single-operator engineering environment, including a 30-day study of 4,419 prompts and 240 manually reviewed samples.
Hands-on research—not an enterprise deployment or proof of commercial impact.
Examine the case studiesExecutive record
Built from zero. Transformed at scale.
Corporate operating experience leads this portfolio. The hands-on AI engineering work adds firsthand evidence about what technology leadership must reconsider next.
PrePass
Enterprise transformation
Led a 50+ person organization and $4.3M budget while modernizing platforms supporting a $300M+ recurring-revenue business.
- Restructured technical silos into product value streams, helping comparable roadmap initiatives reach production about 20% sooner.
- Championed Copilot adoption, AI upskilling, and Responsible AI guardrails.
Uproad
Building and scaling
Scaled Engineering, Product, and Support from zero to 50+, then directed a global organization of more than 100.
- Held company-wide product, technology, operations, go-to-market, and profit-and-loss responsibility.
- Launched a nationwide tolling product with a 67 Net Promoter Score.
AI executive point of view
AI adoption is an operating-model transformation.
Organizations are beginning to coordinate people, conventional software, and AI systems that can reason and take action. That changes architecture, security, economics, software delivery, organizational design, governance, and the role of the technology executive.
Read my leadership point of view01Start with customer and business outcomes.
02Scale verification alongside generation.
03Allocate autonomy by consequence and reversibility.
04Measure successful outcomes and human attention, not raw activity.
Featured case studies
Operating evidence, including what failed.
Three studies from an independent, single-operator engineering environment. They demonstrate practical fluency and informed judgment—not enterprise-scale deployment.
01
Designing an AI-native engineering operating modelWhy human coordination—not agent activity—became the central measure.
02
Governing autonomous work without eliminating autonomyHow controls became a problem, were removed too quickly, and were rebuilt proportionally.
03
Making AI-generated work trustworthyWhy AI review requires measurable machinery and accountable ownership.
The work ahead
Technology leadership where AI changes how organizations operate.
I am interested in executive roles with the authority to build or transform product and engineering organizations—and connect that work to business value.