AI Power calls model vendors and drops the response back into WordPress as a post, an image attachment or a chatbot log entry. The conversation lives in the vendor's logs. The artifact lives in WordPress: rows in wp_posts, postmeta tagging the model, and (for chatbot use) rows in AI Power's own logging tables.

That artifact is what an editorial or chatbot owner can govern. SleekView reads those rows directly and renders them as a real table. Title, status, author and date sit alongside model meta and prompt category as sortable columns. Filter to drafts on a single model, scope to a single bot, or pull every generation tied to a specific run, all without opening each post.

Edits run through standard WordPress CRUD, so post-save hooks still fire, taxonomies still update, and any AI Power meta the plugin reads on update stays consistent.

AI Power covers writing, images and chatbots in one plugin, and that breadth means the volume sneaks up on a team fast. The default Posts screen shows fixed columns and the chatbot logs tab is a row screen with limited filters. SleekView reads the same wp_posts rows, attachments and log tables and renders them as a workspace with model and prompt category as real columns.

Editorial leads stop opening every draft to check the model. Chatbot owners triage in seconds. Finance argues about defaults with a real model mix rather than impressions.

Same data, same plugin, very different working posture.