Professional case study · Complete
Making AI-generated content reviewable inside an enterprise workflow
An early proof of concept where marketing teams could review and use language-model output inside their existing systems, not just stare at a demo chat box.
Context
An enterprise marketing team wanted to see if a language model could help with content creation inside tools they already used. The tech was new to the group, and the UI had to fit enterprise constraints.
Challenge
People needed to understand generated output, catch bad results, and edit before anything went live. The flow had to match how they already reviewed content.
Role
I led the frontend for the proof of concept in React, wired to a language-model API, and worked with backend and product on what the UI owned vs. what the API owned.
Approach
- Built the UI around clear states: idle, generating, review, edit, and error.
- Put review at the center so people could inspect and change output before committing it.
- Kept the model call behind a clear API boundary so the UI could handle loading, failure, and retry on its own.
- Worked with product and backend to keep the pilot scoped to what we could show safely.
Result
The pilot showed the idea could work in that environment and led to more exploration. It was an early proof of concept, not a full production launch.
What this shows
React leadership, shipping through ambiguity, AI feature UI work, and collaborating inside a large company.
Technologies
- React
- TypeScript
- Language-model API integration
- Enterprise workflow UX
Need something like this?
I help teams turn an existing AI capability into a reviewable product feature.