I build and support public-sector application systems, translate operational needs into usable low-code solutions, and independently explore how governed, local-first AI can extend human capability without surrendering human authority.
I explore responsible-use frameworks, policy, human oversight, and practical controls for putting AI to work — with public-sector realities such as records, accessibility, procurement, privacy, security, and public trust kept in view.
Through my independent Frontier project, I explore local models, retrieval over personal knowledge, model-agnostic orchestration, and zero-trust architecture — with governance and human authority designed into the system.
Turning complex institutional workflows into working systems — low-code integration and portfolio/project management at city-government scale, with an emphasis on sustainable design, adoption, and governance.
A background in the arts, teaching, and libraries shapes how I work: translating complex systems into tools, documentation, and practices that people can actually understand and use.
My principal independent AI research and engineering project: a governed personal AI ecosystem exploring how local models, persistent knowledge, external intelligence, tools, and agents can extend human capability without surrendering human authority.
Frontier is local-first, model-agnostic, and built around explicit delegation, zero-trust boundaries, provenance, auditability, reversibility, and human judgment. I document selected architecture, experiments, principles, and lessons as the system evolves.
Frontier is governed by The Frontier Constitution, a public charter for sovereign, human-directed personal AI. Version 1.0 is the frozen canonical public release and is licensed under CC BY-SA 4.0.