Start with delivery
Start with one task in the team’s normal work. Define the problem before choosing a tool.
Engineering leadership and applied AI
How AI can improve the way teams work.
I lead cross-functional engineering work. I focus on where AI improves the way work gets done, and on the leadership needed to make those changes stick.
Direction
Give teams more room to do their best work.
Every organisation has work that takes attention without moving the work forward: finding information, preparing routine material, following up decisions and moving data between systems. AI can reduce some of that drag.
I am interested in what teams can do with the space that creates. The opportunity reaches beyond engineering: people operations, business analysis, planning and other functions where better information and less repetition can improve the way work gets done.
Working principles
What I look for in AI adoption.
Make practice shared
If a prompt, workflow or specification helps, document it. One person’s shortcut is not a team practice.
Measure the result
Ask what changed: time, quality, rework or decision-making. If the value is unclear, do not scale it.
Current work
Where I am putting time now.
I am learning and building in three areas: agent design and evaluation, workflow automation, and AI-enabled engineering leadership.
I want to understand where these approaches help in real delivery work and where they add unnecessary complexity.
I will publish case studies when there is work worth showing. They will cover the decisions made, the limitations and the results.
What I am working on