Selected AI system
AI content operations
Operationalizing AI for content, grounded in real enterprise context.
In production inside a Fortune 100
The problem
Generic AI writing is easy to spot and easy to ignore. An enterprise cannot ship copy that sounds like every other prompt output, and it cannot afford a separate manual process for every surface that needs content.
The idea
Ground the AI in the company's own context and voice, then wire it into the applications where content is actually used — so generation is not a side tool but part of the operational flow.
What I built
I operationalized AI for content creation and integrated it within customer-experience applications, so the same grounded system produces consistent, on-brand output across the surfaces that need it.
How it works
The system draws on enterprise context rather than a blank prompt, which keeps output consistent and on-brand. It is embedded in the applications that consume the content, so it fits the workflow instead of sitting beside it.
The outcome
It runs in production inside a Fortune 100 as part of the broader set of AI applications I have built there. These systems are interconnected and share context across the stack.
What I learned
The value is in the grounding and the integration, not the model. Content that reads as generic never gets used; content wired into the workflow, grounded in real context, becomes part of how the organization operates.
The thinking behind it