AI leadership and hands-on delivery

I lead AI, automation and data work from strategy through delivery.

I stay close to the work itself: understanding the problem, getting the data in order, building a solution around the customer's goals and making sure people can run it.

Enterprise experience

My experience spans strategy, delivery, operations, analytics and governance.

Hands-on lab

I use my home lab to build and test local AI, agents and workflow automation.

Writing and projects

Articles and project notes on what I am building, testing and learning.

Strategy into working systemsAutomation with clear ownershipData for better decisions

Current focus

Making AI useful in day-to-day work.

The point is not to decorate a process with AI or automate one step in isolation. I look at the work end to end—the people, decisions, data and constraints—then decide where AI or automation will actually help. Whatever we build needs a clear owner and has to work in practice.

Enterprise AI strategy and delivery

Helping organisations move from early trials to services with clear ownership, sensible governance and results that can be measured.

Agentic systems and workflow automation

Building agents and automated workflows for work that is repetitive, fragmented or difficult to coordinate.

Data and portfolio insight

Bringing finance, delivery and operational data together so leaders can see what is happening and decide what to do next.

Projects

What I’m building and testing.

A selection of current projects from my home lab.

Protected

Token Gen

Protected local model serving, monitoring, chat, and search tooling.

Local AIMonitoringProtected
Current

Frontier CMS

Tenant-aware content operations and publication workflow tooling.

Content OpsWorkflowGovernance
Lab

Flow Studio

Workflow authoring and orchestration experiments.

WorkflowsControl PlaneSystems

Writing

Articles on AI, architecture and delivery.

Notes from building agentic systems, automation and the platforms around them.