How AI Mode works under the hood – Understand layered reasoning, passage-level retrieval, vector embeddings, and synthetic queries as described in Google’s patents.

The role of query fan-out – Learn how a single query triggers dozens of related searches behind the scenes and how to build content that aligns with those hidden prompts.

Why SEO tools don’t support this shift (yet) – See the gaps in today’s rank tracking, content editors, and keyword tools, and what your stack needs to stay competitive. Some SEO Tools do (like WordLift).

Using Qforia to reverse-engineer AI Mode – See how to simulate query fan-out, generate embeddings, and map your content journey from prompt to citation.

Embedding strategy and user memory – Andrea Volpini explains how Google builds persistent user context through embeddings and why your content must match the memory, not just the query.

Multimodal implications – Understand why images, video, charts, and transcripts might outrank your content even if you’re technically “number one.”

The rise of Relevance Engineering – Reframe your SEO strategy to focus on semantic fit, passage-level precision, and engineered visibility in a matrixed search environment.