AI SEO is the new SEO — here's what that actually means.

A year ago, "AI SEO" sounded like a rebrand. Today it's the whole category. The shift is not cosmetic — the ranking surface changed, the signals changed, and most of the tactics that won Google in 2022 now also need to win ChatGPT, Perplexity, Claude, and Google's own AI overviews.

The buyer journey moved

Watch how your own ICP searches now. A technical founder evaluating a new vector database doesn't type "pinecone vs qdrant" into Google anymore. They ask ChatGPT to summarize the differences, then ask a follow-up about enterprise pricing, then ask which one their peer companies are using. Three queries happen inside one LLM session. Google sees none of them.

Search didn't disappear. It fragmented. Google still wins navigational and local. Reddit and YouTube still win community-of-use. But the consideration loop — the part where a buyer builds a mental model of your category — now happens inside an AI product more often than not.

What "AEO" actually is

Answer Engine Optimization gets misread as "optimize for Perplexity" — a ninth channel to bolt onto the marketing plan. It's not. AEO is the acknowledgment that four different products now compete to answer your buyer's question, and they all lean on roughly the same inputs.

Those inputs are boringly familiar: entity clarity (the LLM can tell what your page is about), structured data (it can parse specifics without hallucinating), quotable passages (it can lift a sentence and cite the source confidently), and signal of authority (other sites it already trusts link to you). The same work that made you a Google authority in 2022 is the foundation of LLM citation in 2026.

What actually changed

Three things are genuinely new, and none of them are the ones the loud voices on LinkedIn harp on.

One: measurement is harder. Google Search Console tells you which queries you ranked for. ChatGPT tells you nothing. To know whether you're getting cited, you have to run prompts in every AI product every week, log the results, and track trend lines over time. Nobody does this yet, which means doing it is a moat.

Two: the content ceiling moved up. A passable blog post won't get cited — it needs to be the clearest, most specific, most quotable version of the answer in the LLM's training window. The bar is now "the LLM prefers your source to everyone else's," which is a much higher bar than "you rank on page one."

Three: entities matter more than keywords. LLMs reason over concepts, not strings. The site that ranks for "vector database" in 2026 is the one whose pages make the clearest claims about the things vector databases do, connect to, compete with, and cost.

Why the old playbook still matters

The dirty secret is that the moves that make you AI-SEO-strong are the same moves that make you Google-SEO-strong. Core Web Vitals. Schema. Entity architecture. Original data. Expert authorship. These were all ranking signals before; they're still ranking signals now, and they're the primary citation signals LLMs use to decide whose content to lift.

If anyone tells you they have a "totally different" playbook for AEO, they're selling you something. The playbook is the same — it's just that the measurement surface and the content ceiling both shifted up.

What to do in the next ninety days

Run the free checklist on your own site. Score honestly. The technical foundation and entity architecture sections will identify most of the misses. Then run twenty ICP queries in ChatGPT, Perplexity, and Claude, and note which competitors are getting cited. That's your gap to close.

If the gap is large and you'd rather ship product than spend a quarter doing SEO triage, that's the job we take.