Building AI agents ยท Brisbane, Australia

I build AI agents that do the boring, valuable work.

I lead AI engineering at OFX, where I build production agents that take on real operational work with humans still in the loop. Outside that, I build small agents for everyday problems and put them online. Here are a few of them.

What I'm building

Live & open source

๐Ÿฆ† DuckFleet

โ— Live Open source MCP connector Multi-agent

An agent fleet that hunts loyalty points while you sleep. Tell it your programs once. It hunts overnight and sends a ranked morning brief of what is worth doing, and what it skipped, with reasons. Governed by design: it refuses, asks, and logs before it acts.

Inktrace

Open source Python

An AI agent security platform: intelligent monitoring for agents that take real actions.

WattsMyBill

Open source Python Multi-agent

A multi-agent system that works out exactly what is going on with your energy bill.

Compliance Advisor

Open source TypeScript

An agent-driven advisor for navigating compliance questions.

How I build

I am drawn to agents that do the useful, time-costly work people never get around to. The harder and more interesting part is doing it responsibly: knowing when to act, when to ask, and when to stay out of the way.

  • Governance is a feature, not a report. An agent that takes real actions has to earn being left running. Mine refuse, ask, and log.
  • The model finds, code computes. LLMs are good at finding and reasoning. Anything a person acts on, deterministic code does, so the numbers are right.
  • Build in the open. The wins and the failure modes both go public. That is most of the credibility.