about me

i have a background in mechanical engineering and data science. for the last five years i've been helping organizations figure out how to deploy ai so it actually helps them — which in practice means understanding messy workflows, running workshops, sorting through which use cases are real and which ones only look good in a deck, then building the delivery systems that carry a first prototype into something people actually use. the gap between proof-of-concept and adopted workflow is where most of the interesting problems live.

that gap is about to get a lot harder to close. agi is probably 18 months away, and i think a lot about what that means — how organizations get restructured around it, how it diffuses through society, and what humans actually do on the other side of that. no good answers yet.