How to Optimize for AI Mode Using Query Fan-Outs and User Context

Google’s AI Mode is live. Search behavior is changing fast, and your strategy needs to catch up.

Michael King, Andrea Volpini, and Garrett Sussman broke down how AI Mode actually works, what query fan-out means for your visibility, and how to rebuild your SEO playbook around context, embeddings, and machine reasoning.

• What’s Under the Hood of AI Mode: From passage-level retrieval to synthetic queries, understand the mechanics behind how AI Mode rewrites and expands a search query into dozens of invisible prompts.

• The Impact of User Context: Google’s embedding-based personalization means every result is shaped by memory, not just the words someone types. Learn how to optimize for the memory.

• Why Your SEO Tools Are Failing You: Today’s rank trackers, content editors, and keyword tools don’t account for AI Mode. We showed where they fall short—and how tools like Qforia and WordLift pick up the slack.

New SEO Tactics for an AI-First Search Experience
We covered the shift from keyword targeting to Relevance Engineering. That includes building semantic fit, passage-level precision, and visual content designed for multimodal search.

You’ll walk away with tactical ways to:

• Simulate query fan-out and reverse-engineer prompt clusters

• Map content relevance to embeddings and citations

• Align with Google’s reasoning and retrieval processes

• Engineer content for inclusion in personalized, multimodal responses

This one’s for the SEOs, content strategists, and technical marketers who want to stop guessing—and start optimizing for how search actually works now.