Skip to main content
AI Visibility Engineering
System track

SEO optimizes for rank. Answer engines optimize for citation-worthiness.

This track is the engineering playbook for the second game: entity coherence, schema specificity, originality signals, and the measurement loops that show whether ChatGPT, Perplexity, and Google AI Overviews are actually citing you.

Guided track Machine-readable 16 foundational, tactical, and case-study notes

Why this cluster exists

SEO optimizes for rank. Answer engines optimize for citation-worthiness. This cluster is the engineering playbook for the second game, sized for operators, not enterprise SEO teams.

System object

retrieval lattice

Best for

content engineers and sub-DR-20 operators engineering for AI citations

16 foundational, tactical, and case-study notes

Start here

The best first read in this track.

Open the guide

Core journey

Read these in order if you want the strongest mental model.

Supporting angle

Not every important idea belongs in the main reading path.

Use the supporting pieces to deepen the model, test tradeoffs, and connect adjacent ideas without losing the main narrative.

Recommended next

How to Get Perplexity and ChatGPT to Cite Your Website

How to optimize your website for ChatGPT and Perplexity: robots.txt, llms.txt, schema, and answer-first structure so AI search crawls and cites you.

Related tools and products

Audit your citability

Run the citability.dev scorer on any page to see what AI engines actually extract, cite, and miss.

Open
AI Visibility Engineering newsletter

Subscribe to the AI Visibility Engineering track

This is not a general-purpose digest. It follows the same cluster as this page, so the emails continue the reading path instead of resetting the context.

  • Priority posts from this topic hub
  • New supporting notes and adjacent experiments
  • Distribution-ready summaries instead of noisy roundups

Segment: ai-visibility-engineering