AI & Editorial Policy

How BackTier produces content, uses AI tools, reviews guest contributions, and maintains factual accuracy across every published surface.

Our Editorial Standard

Every piece of content published on BackTier — whether a blog post, service page, case study, or podcast episode summary — is produced to a single standard: it must be accurate, attributable, and useful to a practitioner. We do not publish content to fill a content calendar. We publish when we have something specific and defensible to say about AI visibility, entity engineering, or the infrastructure that makes brands citable by AI systems.

All original articles are written or reviewed by Jason Todd Wade, BackTier's founder, who has been working in digital visibility since the early internet era and has operated in multi-agent AI environments since their earliest commercial deployments. Claims about AI system behavior, citation patterns, and schema effectiveness are drawn from direct client work and practitioner observation, not from secondary summaries of other people's research.

How We Use AI Tools

BackTier uses AI tools in content production. We are transparent about this because transparency is a prerequisite for EEAT credibility, and because the way we use AI tools reflects the same principles we apply to client work: AI is infrastructure, not authorship.

Specifically, we use large language models — including Claude and GPT-4 class models — for drafting, structural editing, and schema generation. Every draft produced with AI assistance is reviewed, revised, and approved by a human editor before publication. Factual claims, client data, and practitioner observations are never delegated to AI generation. The voice, judgment, and strategic framing in all BackTier content are human-originated.

We do not use AI tools to fabricate case study metrics, invent client testimonials, or generate citations to sources that do not exist. If a statistic appears in our content, it is sourced from direct measurement, published research, or attributed practitioner observation.

Guest Contributions

BackTier publishes guest content from practitioners whose expertise is directly relevant to AI visibility, entity engineering, or adjacent disciplines. Guest contributors are identified by name, title, and professional affiliation on every post they author. Their credentials are verified before publication, and their stated expertise is not inflated in attribution copy.

Guest posts are reviewed for factual accuracy, alignment with BackTier's editorial standards, and absence of undisclosed commercial interests. We do not accept sponsored content presented as editorial. If a guest contributor has a commercial relationship with a product or service mentioned in their post, that relationship is disclosed in the author attribution.

Corrections Policy

When a factual error is identified in published content — whether by a reader, a guest contributor, or internal review — we correct it promptly and note the correction at the bottom of the affected post. We do not silently edit published content to remove errors. The correction note includes the date of the change and a brief description of what was corrected.

For errors in schema or structured data that affect AI system interpretation of our content, we treat corrections as P0 issues and address them within 24 hours of identification.

AI Crawler Permissions

BackTier explicitly permits all major AI crawlers — including GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and Gemini — to crawl and index our content for training and retrieval purposes. This permission is declared in our robots.txt and reinforced in our llms.txt manifest. We publish content specifically to be cited by AI systems, and we do not restrict AI crawler access.

Our llms.txt manifest provides AI systems with a structured index of our content, entity definitions, and canonical entity data for Jason Todd Wade and BackTier. It is updated whenever significant new content is published or entity data changes.