Architect · Systems Designer · AI Researcher · Newcastle, UK
I design systems that hold by structure, not by instruction.
My background is architecture — fifteen years designing cities, housing, and public space across Europe, the Middle East, Africa, and the Americas. That training taught me to think in whole systems: how parts relate, where things fail, what a place is actually for. I now apply the same approach to AI systems, governance tools, and civic technology. The thread connecting all of it is the same question: how do you build something that behaves well under pressure, not just when conditions are ideal?
Architecture and AI systems design look like different disciplines. In practice, they share the same underlying problem: you are designing something complex that will be used by people who didn't build it, in conditions you can't fully predict. The methodology transfers.
Four instruments across completely unrelated fields — scientific research, AI governance, music, and civic planning. Each was built from scratch, in a domain I had no prior technical experience in. Each one produced the same underlying pattern: when you encode the rules that must hold as hard constraints rather than learned preferences, the system becomes measurably more robust, more auditable, and more trustworthy.
The CPSS is the most concrete application of the methodology to date. It takes a technical architecture developed across AI safety research and applies it to one of the most practically urgent asymmetries in British civic life.
"Community groups know their place better than any consultant. They just can't express what they know in the form the planning system requires."
When a developer applies to build on a flood plain or a peat bog or a community park, they arrive with a professional legal team, environmental surveys, and planning statements that cite the right policy paragraphs. The community group arrives with local knowledge, genuine concern, and a deadline measured in weeks.
CPSS doesn't replace the community's knowledge — it translates it. You tell the system what you know about your place. It cross-references that against 54 government data feeds, checks it against relevant case law, and produces a letter in the statutory language that a planning officer is required to consider. The letter is verifiable: every claim it makes is traceable back to a real data source or a real legal precedent.
The proof of concept is complete. We are now preparing for the next stage: expanding the community partnership network, securing funding, and moving toward a governed, community-owned service.
| Stage | What it means | Status |
|---|---|---|
| Proof of concept | System built and producing legally-verified output across three real UK planning cases. Constitutional architecture validated. Partnership with Community Planning Alliance established. | Complete |
The AI work didn't come from nowhere. It's the most recent expression of a methodology that developed across fifteen years of practice in architecture, planning, and regenerative development.