AI-Native Engineering Leader
Monetization Systems Architect
Designing revenue-critical pricing systems built for rapid experimentation and measurable economic impact.
Operating at eight-figure annual booking scale.
Selected Impact
I design systems that learn.
Modern engineering leadership operates simultaneously at three levels:
Strategy — Where does value come from?
Architecture — How does the system enable it?
Execution — How fast can we learn?
Revenue systems are feedback loops.
AI is leverage embedded into those loops.
Former ThoughtWorker. Builder at heart.
Architected pricing and experimentation platforms that compress hypothesis → deploy → measure → decide cycles.
Built high-velocity infrastructure supporting experimentation at scale within an eight-figure booking domain.
Scaled cancel-for-any-reason coverage across operators and currencies.
Integrated pricing logic, experimentation frameworks, and provider APIs to increase attach rate while maintaining regulatory and operational constraints.
Integrated AI directly into engineering practice — from architecture ideation and RFC drafting to experimentation design and code review augmentation.
Increased developer leverage in revenue-critical environments.
I write and speak about the mechanics behind high-leverage systems — where architecture, experimentation, and AI intersect in production environments.
Long-form essays exploring how pricing systems evolve, how experimentation shapes architecture, and how AI enhances engineering workflows.
View Writing70+ talks and workshops for engineering teams and communities on operating high-impact systems and increasing experimentation velocity.
Building revenue systems?
Designing AI-native engineering workflows?
Let's talk.