Ask-the-Book Companion
Answers reader questions from an approved public knowledge set, explains terminology, and directs people to the right book or public resource without reproducing protected chapters.
The core principle
A public book companion should not be a reconstructed manuscript. It should be a deliberately designed interface built from approved concepts, public metadata, FAQs, selected excerpts, exercises, and source-linked resources.
Answers reader questions from an approved public knowledge set, explains terminology, and directs people to the right book or public resource without reproducing protected chapters.
Lets a reader choose a role — owner, board member, marketer, educator, operator — and turns approved concepts into role-specific questions, meeting prompts, and decision checklists.
Supports listening with public definitions, reflection questions, timestamps, resource links, and note prompts rather than chapter transcripts or full summaries.
Provides bibliographic information, acquisition language, approved discussion prompts, course-use ideas, and links to source materials for educators.
A private assistant for the author or publishing team that can help maintain FAQs, talks, newsletters, updates, metadata, source records, and future editions from approved files.
For a multi-book series, helps readers identify which volume, audio resource, or public tool best matches the decision they are trying to make.
Turns approved public concepts into a 7-, 30-, or 90-day practice plan, with the author deciding which exercises can be exposed outside the book.
Keeps source-linked public updates, corrections, new research, and post-publication commentary separate from the static book edition.
IP guardrails
The companion architecture can separate public knowledge from private source material and keep the book itself as the authoritative paid work.
Existing examples
These examples show how a publication, course, or future book can become interactive without treating the AI tool as the publication itself.
An interactive companion for evaluating cybersecurity vendors and asking clearer buying questions without reproducing the book itself.
Before Buying CybersecurityOpen example →A practical bridge from AI capability to workflow, ownership, risk, evidence, and implementation decisions.
AI Implementation Blind SpotsOpen example →Guided practice for stronger prompts, clearer constraints, prompt debugging, and applying prompting skills to real work.
The 19 Laws of AI Prompting IntelligenceOpen example →Adaptive reasoning practice that demonstrates how a book concept can become an ongoing learning experience.
IQ + Logic + Tutor™Open example →A visual prompt and image-quality assistant for composition, hierarchy, lighting, intent, and artifact control.
AI Visual ArchitectOpen example →Custom build
The platform should follow the audience and access model. The publishing work begins with the use case, source boundary, permissions, update owner, and what the tool must refuse to reveal.