The Long Game for SEO Is Still About Durable Signals

Introduction

SEO sits at an interesting crossroads. One camp insists on optimizing for large language models (LLMs) and AI engines, and the other insists on doing SEO the same way we've always done it. But there's another way to approach it: combining the fundamentals of SEO with an understanding of how LLMs operate and why. With this approach, you can keep what's always worked - like on-page SEO and backlinks from reputable sources. Yet...

How the Red Queen theory applies to AI search

The Red Queen evolutionary model says that for everything to stay the same over time, everything must change . But as you adapt to the changing environment, so does the competition. As a result, you and your competitors remain the same distance apart. In your attempt to become the predator, your prey adapts in equal measure, leaving the status quo firmly in place. Essentially, if you don't adapt, you'll get eaten.

How to apply the Red Queen principle to your AI SEO strategy

Along the same lines, AI search is a natural progression of what has existed for at least a decade. A hybrid search model has been in place since 2015, with the introduction of RankBrain . That's why many of the same SEO tactics still work now. Instead of a fundamental change, a series of big and small shifts has taken place over time. LLMs still use retrieval-based search engines. Content quality and freshness still matter....

Why RAG is essential to understanding AI search

The most effective approach is focusing on where LLMs fall short: their limited databases. Their systems rely on retrieval-augmented generation (RAG) to address gaps in their databases without requiring constant retraining. AI assistants like Google AI Mode and Gemini need RAG to prevent hallucinations and to continue surfacing relevant answers for consumers. Here, I gave Google AI Mode and ChatGPT the same prompt: "I am...

How to optimize for AI search vs. traditional search

For SEO, you need to understand how your content aligns with the limitations of AI engines. They do the searching for themselves and then generate a response for the user, only showing external sources some of the time. It's a subtle shift in thinking. Optimizing for search is less about crafting SEO content and more about becoming a trusted supplier for these LLMs - so when people enter a prompt, your brand shows up in the...

Short-term SEO tactics rely on topical authority

A short-term SEO strategy can work now, in the overlap between traditional and AI search. It uses topical authority to deliver results immediately, shortening clients' time to success. Here's the short-term plan.

Use internal links to build entity relationships

"Today, internal links aren't just distributing authority. They're defining the semantic structure of your site." Internal links help search engines understand your site's overall structure. AI Mode, for example, is built with vector search models, and entities are crucial to their operation. Vector search puts your website's information into a 3D model, allowing algorithms to go beyond keywords and determine the intent...

Think in terms of topical coverage versus keyword research

Plan your topical authority through these four lenses: Topical coverage: Develop pages that cover the overall topic and its subtopics in a relevant, useful way. Query fan-out: Study the query fan-out behavior for your most valuable search terms to identify gaps in your website content. Intent: Be ruthless in determining intent by breaking down the categories in your niche that do or don't have AI visibility potential. Content...

Optimize and maintain your site's technical health

Technical health is rooted in what works for search now: site speed, schema markup, and optimized titles and descriptions. After all, LLMs are expensive to maintain and run. It's in their best interest to use resources that are fast and easy to extract information from. Consider recent site speed findings from Mike King, who notes, "Slow responses can trigger 499 errors, where the AI stops waiting." These three short-term...

The long-term future of SEO relies on human behavior

Long-term SEO strategies should focus on the intent and actions of human behavior surrounding AI.

Identify search intent

The four traditional search intents (informational, navigational, commercial, and transactional) are still relevant. But AI search has added a few more. According to MIT , examples include zero-shot, instructional, and contextual prompts. Grammarly considers other intents, including educational, opinion-based, and problem-solving. I tend to break down intent into multiple categories of SEO opportunity based on the clients I'm...

Consider query fan-out

Once you identify the most relevant search intents, you can hypothesize what people are looking for the generative engine to do. From there, you can do one of two things: Rule a subset of topics out of your strategy. For example, if you don't have a local business but the results have local intent, you don't need to focus on those topics. Create web pages optimized for LLMs. For example, you can break down a topical category,...

Prepare for the future of AI search

Prompting may not even be a concern in the future if AI assistants become more sophisticated at solving problems rather than responding to prompts. Instead, AI engines may be able to anticipate searchers' needs and intentions, according to Harvard Business Review . That means it may be increasingly helpful to focus less on prompts and more on problems. In the absence of keyword research, it will be more important than ever to...

SEO's role in the future of search

SEO will have a future as long as there are search engines with AI experiences. While it might look like SEO has become the prey, it's evolved just as much as the predator has. Everything's changed. Yet everything's the same...

Practical next steps

The useful part is not only the idea itself, but the operating habit behind it. Use it as a checklist for decisions: what deserves attention now, what should be monitored, what needs a stronger evidence base, and what can wait until the system has more scale.