I’m a product leader and developer with deep experience in enterprise software, innovation platforms, and healthcare. Over the past several years, I’ve worked across the full lifecycle of AI products, from research and prototyping, to workflow design, to evaluation frameworks, to production rollout inside large organizations. My work combines product strategy, UX, and systems thinking with a strong belief that AI should make work feel lighter, not more complicated.

I’m especially interested in the gap between AI capability and real-world adoption. Most organizations have no shortage of demos, experiments, or excitement. What they struggle with is turning those ingredients into dependable tools that improve throughput, reduce errors, and transform how teams operate. I like building what sits in that space: structured workflows, guardrails, prompts, evaluations, data flows, and user interfaces that make AI feel predictable and trustworthy.

Outside of work, I’m always exploring new ways to bring clarity to complex systems. I write, build small tools and prototypes, analyze vector databases, experiment with clustering and visualization, and document what I’m learning along the way. I like sharing the process, not just the polished end result. Because I think the path is often more useful than the output.