SEO is Not Dead. But GEO Changes the Playbook. Here’s the Data.

Reading time: 6 min

The panic is misplaced

I’ve been watching the SEO death proclamations cycle for twenty-five years. Every time something new arrives — social media, voice search, AI — someone writes the obituary. Let me show you the data.

In June 2026, Google still handles roughly 15 times more queries than ChatGPT. That gap isn’t shrinking quickly. Transactional searches, in particular, remain firmly in Google’s territory. Here’s what actually happened: LLMs are a new channel, not a replacement.

If you’re a search practitioner, you need to understand how Generative Engine Optimization (GEO) works alongside traditional SEO. The book SEO + GEO: Dominate Search in the Age of Generative AI, co-authored by Maxime Doki-Thonon (CEO, RocketLinks) and Sylvain Peyronnet (CEO, Babbar), is the most practical playbook I’ve seen on this.

How LLMs actually process searches

Let’s talk about the mechanics. LLMs don’t crawl the web like Googlebot. They work in layers: prompt processing, internal knowledge retrieval, then — if configured — real-time web search via a fan-out mechanism. That fan-out sends parallel requests to multiple sources and aggregates results.

This matters because the ranking algorithms inside these engines are different. Two I see most often: Reciprocal Rank Fusion (RRF) and Maximal Marginal Relevance (MMR). RRF gives weight to how many sources mention the same result — not how high it ranks in any single one. MMR prioritizes content diversity, penalizing duplicates.

Nobody talks about this part; consistency across sources beats top position in one source. Your content needs to appear in multiple authoritative locations for LLMs to pick it up reliably.

The anatomy of the ideal mention

For LLMs, a good mention isn’t just a backlink. It’s a clear, structured reference. Three components dominate: explicit mentions (your brand or core concept named directly), Strategic Text Sequencing (STS) (how your content orders information to align with LLM training patterns), and EEAT signals that are parsed directly from your content’s authority indicators.

This isn’t a take — it’s a pattern I’ve verified across multiple tests. The book walks through each, with examples from real campaigns.

Netlinking: the bridge between SEO and GEO

Here’s where the traditionalists win. Networking — acquiring links and mentions from authority sites — is the single highest-leverage activity for both search and generative models. The same links that drive your Google rankings also increase the probability an LLM will cite your domain as a source.

Slow down. Think. If you’re already running a link acquisition campaign, you’re already doing GEO. You just didn’t know it. The difference is in how you frame the content — mentions need to be structured for citation, not just click-through.

I’ve seen campaigns that optimized for GEO alone fail, because they neglected traditional search volume. I’ve also seen pure SEO campaigns miss LLM traffic entirely. The playbook changed. Again. The winners now build for both.

What’s actually new here

The book’s contribution is in making these mechanisms explicit. It covers: the internal anatomy of LLM prompt processing, RRF and MMR in practice, the design of LLM-friendly content, and how netlink campaigns feed both systems. No hype. Just the technical and operational details needed to act.

If you’re looking for a one-index-future-rule-all argument, this won’t satisfy you. If you want to understand how to adjust your SEO approach for the present reality — where Google dominates but LLMs grow — the full report is here: Download the white paper for free.

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Matt S. Riley

Building websites since before Google existed. I’ve run SEO, growth, and content for startups across California — and I’ve watched every ‘revolutionary’ tactic eventually expire. What doesn’t expire: understanding systems, compounding effort, and thinking slower than everyone else.

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