Now
What I am working on and thinking about now.
Most of my day-to-day work is enterprise data and AI at Insight Partners. Around the edges, I still follow public data, Syracuse, libraries, and small tools that make messy information easier to use.
Current focus
Enterprise data and AI, close to the work.
At Insight Partners, I work across investment, HR, compliance, finance, and operations on data foundations, AI workflow design, governance, and tools people actually use.
I am most interested in the practical middle: where good data, usable systems, judgment, and organizational habits meet.
Recurring questions
- What would make this decision easier to understand?
- Where is the workflow actually breaking down?
- What data needs to be trusted before AI is useful here?
- What can be made public, reusable, or easier for the next person?
Still in the background
Public data, place, and practical institutions.
I am not doing public-sector data work day to day anymore, but the Syracuse work still matters to how I think. Systems should be understandable. Data should help people make better choices. Public institutions deserve practical tools, not just dashboards.