About

I've spent most of my career designing infrastructure for large organisations. Storage platforms, hybrid cloud, AI compute. The kind of systems where a wrong decision costs millions and a right one runs for a decade.

Somewhere along the way I started building things on the side. Not because I had to. Because I'd see a problem at work, think about it on the drive home, and by midnight I'd have a prototype running. A warehouse platform because a friend's business was drowning in spreadsheets. A price tracker because I got tired of overpaying for camera gear. An agent framework because I realised I was doing the same infrastructure tasks every week and kept wondering why I hadn't automated myself out of the loop.

That last one changed how I work. I now run a multi-agent orchestration framework where AI agents handle the operational work I used to do manually. Cloud provisioning, identity management, network configuration, monitoring, code delivery. The goal is full hands-off on the routine stuff so I can spend my time discovering what's next instead of maintaining what already exists.

I was designing modular GPU-clustered liquid-cooled processing farms 14 years ago, before anyone was calling it "AI infrastructure." Today I design AI compute platforms at national scale. Fabric topology, storage tiering, inference pipelines, cooling envelopes. The hardware changed. The thinking didn't.

I don't just call APIs. I run models locally on a cluster of Mac Studios, test their limits, build evaluation datasets, and try to understand why they fail before I trust them with anything real. When a model gets something wrong I want to know if it's the data, the quantisation, or the prompt.

I run a scaled hybrid lab. Containers, orchestration clusters, multiple cloud regions, all meshed and secured end to end. It's where I test architectures before I recommend them to anyone. If I'm going to stand in a steering committee and say something works, I want to have broken it first.

At home I'm building something I've wanted since I was a kid. An AI that lives inside the house. It sees, it listens, it understands context, it controls the environment. Not a smart speaker with a wake word. A presence that follows what's happening and responds naturally. And it stays inside. No cloud. No external exposure. Private by architecture, not by policy.

I don't really have a specialty. I have a pattern. See a problem. Understand it deeply. Build a system that solves it. Then build an agent that runs the system. The domain changes. The approach doesn't.

I get genuinely excited when things click. When a small model running locally extracts business rules from a photo of a receipt. When a single Go binary embeds an entire mobile web app. When a Telegram bot renders an AI agent's permission dialog as inline keyboards and you approve a code commit from the bus.

Those moments are why I still build things after 25 years.