I work at the point where emerging technical capability becomes operational reality. Research, enterprise systems, open source, teaching, and now AI — the recurring pattern is the same: identify, build, help adapt.
Teaching
Teaching courses in data science, data and software engineering, with substantial GenAI integration, at Boston University.
Working on
Exploring where institutional capacity meets agentic systems.
Operating the AI-Native Stack
Essays & Writing
Most talk about AI agents treats 'the agent' as one worker. In practice it's two roles, and keeping them apart, with a written contract between them, is most of why the setup works.
Agentic coding reintroduced the dead time long compiles used to have. The part that reorganized my day isn't that the agents write code, it's that I turned into the scheduler.
When an agent writes the code and you direct and approve it, 'who's the author' feels like a deep question. Operationally it isn't a question about authorship at all. It's a logging problem.
Three of many
A four-level taxonomy for describing how AI was involved in a piece of work — built for journalism, academia, and professional practice, and positioned as an open standard.
Methodology and program design at the intersection of journalism, computation, and institutional practice — including TRACE, open tools, and curricular experimentation.
Systematic protocols for integrating generative AI across data science coursework — balancing productivity with educational integrity and professional responsibility.
Semantic Trails
Trails are author-curated paths through the body of work — linking essays, older projects, and material that wouldn't surface in a feed. Start anywhere and follow the connections.
A trail on ambient presence, consulting infrastructure, and the things remote work tooling keeps getting wrong — and what that reveals about what presence actually requires.
2 stops