One owner across AI strategy, architecture, design, and product. Four ways to start, chosen by what creates value — not by what sells easiest.
I read the workflow, talk to the people who live with it, and come back with a map — where AI should act on its own, where humans stay, and why each line sits where it does. Grounded in Information Systems research on cost, efficiency, and adoption.
When the problem is messy and there's no clean spec yet.
I own architecture and implementation end to end — the agents and pipelines where automation pays, the interfaces where human judgment does, and the joints between them. The person who understood the problem is the one writing the code.
When the target is defined and you need it shipped, not re-scoped.
I stay with the system past the demo. I measure adoption, fix the joints that don't hold under real load, and evaluate against the goals we set — so the system still earns its place six months in.
When your last AI pilot didn't survive contact with real users.
I bring the research to your team. Half-day to multi-day formats on user-centered AI, knowledge graphs, and how to decide what to automate and what to keep close to human judgment. Written for product, research, and operations people who want the lens, not just the deliverable.
When you want to invest in your own judgment.
Not sure which fits? Describe the problem and I'll tell you where to start.
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