AI Governance · University Lecturer · RFDS AI Advisory
Writing on the intersection of artificial intelligence, government service delivery, digital policy, and what it means to build technology in the public interest.
Public sector AI strategy, agentic systems in public service, and the policy frameworks that make it safe.
Coursework, assignments, and reflections from postgraduate study in technology management and AI.
Technical work, open source, self-hosted infrastructure, and the craft of building things.
Exploring what it means when AI agents, not forms, not chatbots, deliver government services at scale. A consolidation of my personal thinking on agentic government.
An exploration of designing a website to serve two readers at once: a human and an LLM/agent. Clean per-page markdown, an llms.txt index, structured data, and a deliberate crawler posture.
A small, reusable, privacy-first widget that lets readers anonymously rate how much any piece of writing smells of AI slop. A slider from human craft to pure slop, with a live crowd verdict.
I built a little widget that lets readers anonymously rate how much any post smells of AI slop: a slider from human craft to pure slop. Here's the design, the privacy tricks, and the small mistakes I made along the way.
Read more →When government acts on your behalf, what record do you get? The accountability frameworks for agentic government build the supply side of the audit trail without specifying the citizen-facing output. The case for an Agentic Transparency Standard.
Read more →We are approaching a point where government services can be delivered not just digitally, but autonomously. This is what that means for public accountability, trust, and the future of public service work.
Read more →Evasion attacks, data poisoning, and model stealing are not theoretical concerns — they're active threats to AI systems in high-stakes environments. A practical overview for technical leaders who aren't researchers.
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