Trust Before Publish™
Build a repeatable human-led quality-control system for AI-assisted content so you can verify claims, catch hallucinations, protect your brand, handle disclosure and provenance decisions, and publish with confidence.
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Publish faster without outsourcing your judgment.
Turn AI-assisted drafts into publish-ready work through risk tiers, source verification, originality checks, disclosure decisions, and clear human accountability before anything carries your name.
Catch unsupported claims before they go public.
Classify claims by risk, use stronger source hierarchies, challenge AI output, and escalate sensitive statements before publication.
Protect voice, originality, rights, and audience confidence.
Review authorship, disclosure, provenance, brand voice, and originality so faster production does not create avoidable trust debt.
Build a repeatable pre-publish system that scales.
Use practical boards, checklists, correction workflows, and automation boundaries that keep final judgment in human hands.
A practical operating system for AI-assisted publishing quality.
Verify what matters
Learn claim classification, source hierarchy, source logging, hallucination challenge passes, and higher scrutiny for sensitive or consequential claims.
Protect the brand
Work through disclosure choices, human authorship and rights tracking, content provenance concepts, brand-voice protection, and originality review.
Operationalize quality
Build cross-platform QA, correction and incident response, repeatable boards and checklists, sensible automation boundaries, and a 30-day implementation sprint.
AI can accelerate production. It cannot own your reputation.
No checklist can guarantee zero mistakes, and platform rules continue to evolve. This guide focuses on durable controls that improve verification, transparency, originality, and accountability while keeping final publication responsibility with the human publisher.
Classify. Verify. Challenge. Disclose. Review. Publish.
Start by identifying the claims and risks in the work, verify the important ones against strong sources, challenge AI-assisted output for unsupported details, make any required disclosure or provenance decisions, complete the human review, then publish with a correction path already defined.
