Thesis

NRLC recommendation SEO did not end. The unit of competition expanded from “rank a URL” to “be the passage an answer engine can trust and name.”

Teams that only chase blue links will misread traffic declines. Teams that only chase “GEO hacks” will ignore crawl, index, and relevance foundations that Google still documents as the floor for AI features.

What changed

Officially documented Google AI Overviews and AI Mode synthesize multi-source answers with query fan-out. Eligibility starts with ordinary Search requirements. (Google AI features)

Officially documented ChatGPT Search returns answers with linked web sources. (OpenAI)

Independent observational study Pew Research found lower click-through when AI summaries appeared (~8% vs ~15%). That is click compression evidence, not proof that every vertical is doomed. (Pew)

SEO · GEO · AEO

  • SEO — crawl, index, relevance, links, UX; still the eligibility layer
  • GEO — generative-engine visibility; experimental methods in Aggarwal et al. (GEO paper)
  • AEO — industry umbrella for answer-surface optimization across Google, ChatGPT, Perplexity, Copilot, and others
  • Ontological SEO — NRLC's practice layer: govern entities, relationships, and truth claims so those surfaces resolve to the correct brand

NRLC treats these as stacked control surfaces, not competing religions.

Operating model

  1. Keep classic technical SEO healthy (robots, canonicals, index hygiene, unique intent)
  2. Write citation-ready passages with local evidence
  3. Structure pages to lower retrieval waste
  4. Measure rankings and answer attributions
  5. Label claims honestly: documented vs experimental vs observational

FAQ

Is traditional SEO dead?

No. Crawlability, indexability, and relevance remain prerequisites for most answer-engine eligibility. What changed is that ranking alone no longer maps cleanly to clicks when answers are synthesized on the results page.

What is GEO vs AEO?

GEO (Generative Engine Optimization) focuses on visibility inside generative answers. AEO (Answer Engine Optimization) is a broader industry label for optimizing for answer surfaces. Both sit on top of classic technical SEO rather than replacing it.

Do AI Overviews reduce clicks?

Pew Research reported that users were less likely to click through when an AI summary appeared (about 8% vs 15% in their study window). Treat that as observational evidence of click compression, not a universal law for every query class.

What should teams measure now?

Track classic rankings and organic clicks, plus citation presence, branded mentions in AI answers, referral from answer engines where available, and whether your passages are actually retrievable.