Brown builds a social-media research app that stores short-form videos, statistics and transcripts for a team. He frames ChatGPT Work as a middle ground between ordinary chat and Codex, with Sites providing a hosted application surface that can be created from a natural-language brief.
The initial prompt asks for a signed-in team interface, video storage, structured metadata and an agent-driven way to import content. After the first build, Brown uses visual annotations to request layout changes and shows that the deployed app updates without a separate manual coding workflow.
He explains that the data collection comes from a reusable agent skill connected to an external API. The skill gathers videos and metadata, while the Site gives that information a purpose-built interface. API credentials can be stored as environment variables instead of embedded in the visible application.
The finished project includes authentication, database records, storage, analytics and a custom-domain setting. Brown's broader lesson is to choose the best small interface for information a team needs, then let an agent build and maintain that focused tool instead of forcing every workflow into a generic dashboard.
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