An intro to LLM optimization — what comes after SEO

⏰ The 30-second version

• LLM optimization is the work of making your content easy for a language model (LLM) to use as material. It's essentially the same direction as GEO (generative engine optimization) — just a different vantage point. GEO looks at "the engine (the search surface)"; LLM optimization looks at "the model (the reader)."
• "LLM optimization" gets 30 searches a month, +29% in three months — small but growing.
• The core principle is one thing: an LLM consumes a document in pieces, not whole. Content that's complete at the piece level wins.
• Starting isn't grand — conclusion first, self-contained paragraphs, question-style subheads, FAQs. You can do it today.

Terms first: LLM optimization, GEO, AI SEO

It's a confusing moment, with similar terms arriving all at once. To sort them out —

Term	Focus	Search vol. (trend)
GEO (generative engine optimization)	Getting cited on the AI search surface (answers)	390 (+29%) / 140 (+66%)
LLM optimization (LLMO)	Content easy for a language model to read and use	30 (+29%)
AI SEO	Traditional SEO extended into the AI era	320 (0%)

The three aren't competing concepts — they're names for the same phenomenon from different angles. The work in practice mostly overlaps. In this piece, we'll frame it from the LLM angle: "how does the model read?"

The principle: an LLM reads in pieces

When a language model uses a web document, the path is roughly this — find documents relevant to the question, extract the relevant parts, and assemble an answer from those pieces. From this comes a property that matters in practice.

1. Completeness of the piece is everything. A paragraph that opens with "as mentioned above, that product…" loses its meaning the moment it's cut. Rewrite the subject (the product name) and conditions in every paragraph.
2. Direct-answer sentences get pulled. A sentence with a clear question-answer pair ("When to take a probiotic? After a meal is generally recommended") gets selected as assembly material.
3. No readability, no start. Text inside images and content behind a login don't exist to an LLM.

The deeper principle is covered in how AI decides what to quote, in three stages.

4 ways to start LLM optimization today

It's not a grand rewrite — it's a matter of habit.

These four share a root with the 5 GEO moves. Do one and GEO, LLMO, and AI SEO all improve at once — there are three names, but only one job.

How to measure your content's LLM-optimization state

If it's hard to judge by gut, start with measurement. Bulti's free audit measures your pages' coverage, structure, and readability against 30 customer questions in a minute, and prescribes fixes for the weak spots.

FAQ

Q. Does LLM optimization hurt my existing SEO rankings? No. Conclusion-first, structured, FAQ — these have long been recommended in traditional SEO too, so generally both improve.

Q. Do I have to optimize separately for each model (GPT, Claude, Gemini)? No. "Piece completeness, direct answers, readability" is a consumption pattern common to all models, so one round of work applies across every model.

Q. Do I need to make an llms.txt file too? llms.txt is a proposed spec, still under discussion, for guiding LLMs to your site's content. It doesn't hurt to have, but improving the body structure comes first — the shelf matters before the signpost.