Director of AI at Consensus · Engineering and Applied AI leader
I work at the intersection of engineering, product, and organizational transformation—turning frontier AI capability into production systems, stronger teams, and AI-native ways of delivering software.
My background spans full-stack engineering, architecture, engineering leadership, applied machine learning, agent systems, and enterprise AI adoption. I stay close enough to the work to prototype, evaluate tradeoffs, and know where the demo ends and the operating system begins.
At Consensus, I lead applied AI across internal teams, engineering, and product. The portfolio includes machine-learning recommendations, agentic buyer experiences, MCP capabilities, and internal agents operating at millions of production traces per month.
- Production agent systems, evaluation, observability, and responsible deployment
- AI-native product delivery across Product, Design, Engineering, and Applied AI
- Developer platforms, MCP, and agent-accessible software
- Building organizational fluency and independent technical judgment
- Practical operating models for mixed human-and-agent teams
Field notes on AI fluency, agentic systems, product delivery, and the operating models companies need as software becomes increasingly capable.
The useful part of a build is rarely the technology list. I care about the problem boundary, the product decision, the architecture, the evaluation strategy, the failure modes, and what changed after reality disagreed with the original plan.
This profile is where I publish reference implementations, architecture notes, experiments, and open-source work that make those decisions inspectable.