Research

An open, graph-based knowledge system that makes regenerative design patterns — from permaculture to indigenous land management to biodiversity conservation — accessible, composable, and actionable for communities worldwide.

An interactive AI-augmented visualization platform that surfaces scenario trajectories and enables long-term strategic foresight through multi-model deliberation.

An open-source, AI-augmented knowledge architecture that preserves institutional wisdom, enables composable collaboration, and maintains contextual integrity across generations.

Building domestic AI infrastructure that leverages Canada's geographic and energy advantages to retain talent, reduce dependency on foreign compute, and prepare for a climate-shifted future.

Redesigning co-op and experiential learning for an era where AI automates entry-level roles, producing AI-native professionals who create value rather than compete with automation.

Building a labour economy based on licensing dynamic knowledge context rather than selling hours, while preserving dignity and preventing new forms of exclusion.

Structuring economics and legal frameworks around dynamic knowledge context, where individuals license their AI agents' trained patterns while avoiding static decay and catastrophic liability.

Designing knowledge systems that decouple institutional wisdom from individual tenure, ensuring knowledge survives departure and evolves with every contribution.

Designing AI education partners that accelerate learning without removing productive struggle or creating dependency on AI-mediated environments.

Designing collaboration that extends human capability without eroding our capacity for independent judgment or triggering an energy crisis.