editorial-forge

To make AI-generated text copyrightable, you apply structured editorial judgment, voice extraction, and narrative framing to transform the output. This process logs your human selection and arrangement decisions, creating an authorship provenance record that establishes ownership.

Voice extraction in book writing builds a personalized voice profile through an interview process before drafting begins. This ensures later prose reflects your authentic voice rather than a generic AI style, capturing your specific tone and narrative preferences.

Structuring a book with Sorkin DOB narrative framing applies Desire–Obstacle–Battle at the chapter level and an optional book-level throughline. This produces coherent long-form structure and persuasive argument arcs throughout your writing.

Yes, you can maintain authorship provenance records using Google Drive. The workflow requires phased intent-to-structure-to-voice-to-draft execution with Google Drive state persistence, manifest updates, and continuous authorship decision logging.

The best way to take over an existing project folder is through a phased execution approach that reads the current manifest and provenance logs. It maintains your authorship decision logging while applying structured editorial judgment to continue the draft.

Yes, you need to complete an interview process before drafting to extract your voice profile. This prerequisite ensures the editorial transformation reflects your authentic voice rather than generic AI style, and supports delegated validation if needed.