GEO + AEO, in 2026.

The session

GEO + AEO, in 2026.

Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) are not the same thing, even though they get used interchangeably. GEO is the discipline of making your content rank in AI-generated search summaries — Google AI Overviews, Bing Copilot, Perplexity, ChatGPT search. AEO is the discipline of making your content the cited source inside those summaries. The two overlap. They are not identical. You can rank in a summary without being cited. You can be cited without ranking. The right metric is citation, not ranking.

The reason citation matters more than ranking in 2026 is that the answer engines do the ranking for the user. The user does not see a ranked list — they see a paragraph, sometimes a single sentence, that summarizes the answer. The user clicks through only if the summary names a source or a domain they trust. If your content is in the corpus the answer engine pulled from but not in the citation, you get no traffic. If your content is cited, you get all the traffic for that query.

The five schema types that matter for AEO in 2026 are: FAQPage (for Q&A content), HowTo (for step-by-step content), Article (for editorial content), Product (for product pages), and Organization (for company information). Every page on vzu.ca has at least one of these. Pages with structured process content (the "how this works" pages) carry HowTo. Pages with Q&A content carry FAQPage. Pages with product detail carry Product. The schema is not magic — it has to match the visible content on the page, or the answer engines will learn to ignore your schema over time.

The llms.txt is a new file (early 2026) that lives at the root of your site and tells language models what your site is, what the canonical pages are, and how the content is organized. It is the LLM equivalent of robots.txt. It does not change what gets crawled, but it does change what gets surfaced. A well-built llms.txt is the difference between an answer engine knowing your site is the canonical source for "what is MCP" and an answer engine treating your site as one of a thousand results. The file is at /llms.txt on vzu.ca.

The Direct Answer Block is the single highest-impact AEO pattern. A 2-3 sentence direct answer to the question the page is about, placed before any marketing language, in the first 150 words of the page. No hedging, no promotion. Just the answer. This is what the answer engines pull from. The rest of the page is the long-form evidence and the persuasion. The Direct Answer Block is the citation surface. The long-form is the trust surface.

The internal linking hub is the second-highest-impact pattern. Programmatic pages (comparison, glossary, calculator) must link to the canonical brand pages and to each other by topic cluster. Orphaned programmatic pages get crawled slowly and cited rarely. A page that is three clicks from a high-authority page on the same topic gets cited. The internal linking is the network that gives the answer engines a reason to trust the content.

The third high-impact pattern is original data. Pages that contain data the answer engines cannot get anywhere else (a benchmark, a survey result, a measured outcome, a worked example) get cited preferentially over pages that summarize other pages. The AEO research is consistent on this point. Original data is the citation moat. Synthesis of public sources is not.

The session walks through the GEO vs AEO distinction, the five schema types, the llms.txt specification, the Direct Answer Block pattern, the internal linking hub, and a live audit of three real answer-engine citations (one good, two bad) with a fix playbook for the bad ones. The recording and the audit templates are sent to all registrants.