Design the context
before the interface.
I help teams turn institutional knowledge into trusted AI systems — with the clarity, restraint, and judgment real work requires. Most companies do not have an AI problem. They have a context problem.
What I do
Context Architecture
Map the knowledge, language, and decision rules that let AI work inside the business without flattening what makes it valuable.
Trusted AI Systems
Design internal AI tools and workflows people can rely on — with clear boundaries, better retrieval, and less theater.
Editorial AI Strategy
Shape a point of view around AI that sounds like your brand, not the market.
How I think about it
Trust does not come from sounding smart. Plenty of systems already sound smart. Trust comes from context — from a system that knows what matters here, with these people, under these conditions.
The work is not choosing a model. It is deciding what a system should know, what it should ignore, what it should remember, what should decay, and what it should never decide on its own. Those questions are not secondary. They are the work.
Architecture, at least in this case, is just a serious word for judgment made durable. Build that layer well and you are not just automating work — you are building the conditions under which the business can think.
Build the context layer first.
If you want AI that people actually trust, start with the context — not the interface. Let's map it together.