Context Architecture
Map the knowledge, language, and decision rules that let AI operate inside the business without flattening what makes it valuable.
Consulting
Build the context layer first.
For companies that want AI systems with judgment, boundaries, and a point of view grounded in how the business actually works.
Approach
Good AI work starts before the model.
It starts with structure: what the organization knows, how it speaks, what it protects, and which decisions should never be left to guesswork. That is the layer most teams skip, and the reason so many AI efforts feel impressive in theory and fragile in practice.
Services
What I help with
This is operator-led AI strategy for teams that need useful systems, not demo theater.
Trusted AI Systems
Design internal AI tools and workflows people can rely on. Clear boundaries. Better retrieval. More useful answers. Less theater.
Editorial AI Strategy
Shape a point of view around AI that sounds like your brand, not the market.
Engagement model
How engagements work
Diagnose the context problem
We identify where knowledge lives, which sources matter, what needs to be preserved, and where the current system breaks down.
Define the operating layer
We translate that knowledge into standards, rules, and structures that AI systems can actually use.
Shape the experience
We turn the layer into something the team can work with: clear workflows, usable tools, and a system that fits the business instead of fighting it.
Best for
Who this is for
- Founders who want AI to help the company think more clearly.
- Operators and GTM leaders who need internal systems that reflect reality.
- Teams that are done with AI theater and want something durable.