SEO, AEO and GEO are most useful when treated as layers of one search operating system rather than three unrelated channels.
Shared foundation
All three depend on a page being technically reachable, indexable where appropriate, understandable, internally connected and useful to a real audience. Canonical URLs, robots directives, descriptive titles, structured page hierarchy, stable entities and evidence determine whether a system can reliably discover and interpret the page before any answer-engine or generative layer becomes relevant.
For D2, this shared layer is managed as an expected-state contract: every released URL has one canonical, an explicit indexing state, a locale relationship where one exists, and an internal path from the rest of the site. This prevents GEO work from becoming a collection of AI-specific tricks that bypass ordinary Search quality.
SEO: discovery and relevance
SEO is the broadest layer. It covers technical discoverability, indexation, information architecture, query-to-page fit, content quality, internal linking, structured data where appropriate and the feedback loop from Search Console and analytics. The operating question is whether a search engine can discover the page, understand what problem it solves, and consider it useful for a relevant query.
SEO therefore remains the baseline for the other two layers. AEO and GEO do not remove the need for canonical consistency, crawl access, useful text, sound information architecture or measurement.
AEO: explicit answers
AEO focuses on whether a page exposes a clear answer to a concrete question. Direct-answer passages, unambiguous definitions, useful comparison structures, FAQ content where genuinely helpful, and enough context for an answer to remain correct when extracted are controllable elements.
AEO is not equivalent to adding FAQ schema everywhere. The visible answer must still be accurate, current and supported. Structured data can describe content, but it does not replace the content itself.
GEO: retrieval and evidence
GEO focuses on how a brand, page, claim and supporting source can be retrieved and represented in generative search or answer experiences. The controllable work includes entity consistency, evidence architecture, first-party information, clear claim boundaries, citation-friendly passages, crawl access and measurement of downstream visibility. The uncontrollable part is whether a particular external model chooses to cite or quote a page for a particular prompt.
D2 therefore treats citation readiness as an engineering and editorial property; it does not describe external citation as a guaranteed result.
One operating model
Use SEO to govern discoverability and organic demand. Use AEO to improve explicit answer quality. Use GEO to strengthen entities, evidence and retrieval readiness for generative systems. They share one URL inventory, one entity graph, one evidence layer and one measurement model.
The practical test is simple: if an AEO or GEO tactic requires duplicate thin pages, unsupported facts, hidden user content or weaker canonical clarity, it conflicts with the shared Search foundation and should be rejected.
Measurement
Observable milestones are discovery and crawl, then impressions and ranking signals, then visits and engagement, and finally business outcomes such as qualified leads. AI citation observations are stored separately because they are not equivalent to Search Console impressions or organic sessions. Keeping these states separate makes the system auditable instead of turning a few prompt screenshots into a visibility claim.