For two decades, “search” meant retrieval.
You typed a query, the engine fetched indexed pages, and ranking decided which ones mattered.

That era is over.

LLM-powered search systems — from Gemini to Perplexity to Grok Answers — don’t retrieve.
They interpret.

The atomic unit is no longer a webpage.
It’s meaning.

A modern search model builds a semantic profile of the query, matches it to learned conceptual structures, and only then checks whether external content can support or refine the answer.

In other words, search became a thought process, not an index lookup.

This changes SEO at the root.

Content must be not just findable, but interpretable.
It must provide enough semantic density for the model to integrate it into the right conceptual clusters.

If you’re still optimizing for keywords, you’re optimizing for a search engine that no longer exists.