Start with the useful problem.
Technology follows the operating outcome, not the other way around.
About / The through-line
Software engineer first.
AI multiplied.
I have spent more than 20 years turning awkward requirements, platform constraints and operational risks into software people can actually use.
01 / Career arc
The technology changed. The job did not.
My foundation is hands-on product engineering: C#, .NET, mobile applications, cloud APIs, integrations, authentication, offline workflows, automated testing and release systems. I have worked across government, transport, healthcare, finance, mining, agriculture, manufacturing, accessibility and consumer software.
Over the last several years, AI has radically increased what one experienced operator can research, design and deliver. I use that leverage across agents, MCP, grounded knowledge, local inference, browser tools, workflow automation and day-to-day software delivery.
The core value is not access to a model. It is knowing what to build, where a model belongs, what must remain deterministic, how failure should be handled and how the result improves the organisation rather than merely producing a demo.
02 / How I work
Make the hard parts visible.
Permissions, failure, ownership and recovery belong in the architecture early.
Build the smallest honest proof.
State, evidence and limitations are labelled precisely so decisions can be trusted.
Leave capability behind.
Documentation, tests and team understanding matter as much as the first release.
Current professional development
Claude architecture pathway
Through Dark Ice, I have access to Anthropic Partner Academy via the Claude Partner Network. I am preparing for the Claude Certified Architect – Professional pathway, targeting completion by the end of August 2026. This is in progress—not an awarded credential.