I started building websites in the GeoCities era, so I’ve watched a lot of SEO advice come and go. Keyword stuffing. Hidden text. Exact-match everything. Now everyone wants to know how to write content for AI search. One of the buzzwords of the moment is token efficiency, and it arrives with a brand new alphabet: AEO, GEO and friends.
Here’s my honest take. There’s something real underneath the buzzword, and it isn’t a trick. It’s good writing, seen through the way AI answer engines actually read.
Short answer: To write content for AI search, put the answer first and get the most meaning into the fewest words, so any passage on your page can be lifted out and still answer a question clearly. That’s token efficiency, and it matters for AI SEO because answer engines pull specific passages from pages and quote the ones that answer cleanly. It isn’t a secret ranking factor: Google says its AI features run on the same SEO fundamentals, so lean, clear, original writing helps people and machines at once.
What is token efficiency, exactly?
A token is the chunk of text a language model reads, usually a whole word or a piece of one. Token efficiency is the ratio of meaning to tokens: how much a passage actually says for its length.
In AI SEO, it means writing so each section makes its point quickly, without filler, while keeping the depth and nuance. Lean, not thin. A 2,000-word guide can be token efficient. A 300-word post can be bloated.
How do AI answer engines choose which passages to quote?
They search, retrieve pages, then pull the specific pieces that answer the question and link to the pages those pieces came from. Google describes two techniques behind AI Overviews and AI Mode in its guide to generative AI search:
- Query fan-out. The model turns one question into several related searches. Google’s own example: a question about fixing a weedy lawn fans out into searches about herbicides, weeding without chemicals and preventing weeds.
- Retrieval-augmented generation, or grounding. The system retrieves relevant pages from its search index, reviews specific information on those pages, and writes an answer with links to the pages that support it.
Answer engines that show their sources, like ChatGPT search and Perplexity, also search the web and cite the pages behind their answers. Nobody outside these companies knows exactly how passages get weighed. But the shape of the process tells you what helps.
You’re competing passage by passage, not just page by page. That’s where token efficiency earns its keep: one clear paragraph can answer one of those fan-out questions, even when someone else’s page wins the main search.
If I write efficient content, will it rank in AI search?
Not directly, and anyone promising otherwise is guessing. Google says there are no additional requirements or special optimizations for AI Overviews or AI Mode, and that SEO fundamentals still apply.
It even lists things you can ignore. You don’t need an llms.txt file or special markup for Google Search. You don’t need to chop your content into tiny chunks, and you don’t need to rewrite everything just for AI.
So why care? Because token efficiency isn’t a hack. It describes writing that’s easy to understand, and that’s what people and retrieval systems both reward. Google’s guide asks for a unique point of view, organized with clear headings and sections. Efficient passages are what that looks like at the paragraph level.
You are allowed to question the hype. Clear beats clever, every time.
Token efficiency vs. keyword density
Keyword density asked how many times you repeated a phrase. Token efficiency asks how much each sentence says.
Google notes that its AI systems understand synonyms and general meaning, so you don’t need to cram in every variation of your keyword. Repeating “best vegan protein powder” ten times adds tokens and no meaning. Answering ten real questions about vegan protein adds both.
The Lift-Out Test: is this passage worth quoting?
Picture an answer engine lifting one paragraph off your page and dropping it into an answer, with no context around it. Would it still make sense, stay accurate and sound like you? Run each important passage through five checks.
| Check | The question | The fix |
|---|---|---|
| 1. Answer first | Does the first sentence answer the heading’s question? | Move the answer up and put the context after it |
| 2. Name it | Does it make sense with no surrounding text? | Swap “this,” “it” and “as mentioned above” for the actual noun |
| 3. One job | Does the paragraph make one point? | Split it, or cut the second point |
| 4. Only you | Is there something here only you could say? | Add your number, example, process or opinion |
| 5. No throat-clearing | Could the first sentence go without losing anything? | Delete it |
Check four matters most over time. Google’s guide says unique, non-commodity content will likely influence your presence in generative AI search more than any other suggestion it makes. A summary of what’s already out there is exactly what an AI can write without you. Trimming fat is half the job. The other half is making sure there’s muscle left.
A worked example: how to write content for AI search, before and after
Let’s say you’re a brand photographer, and your FAQ page answers “How long does a brand photo session take?” (A hypothetical page, written to show the difference.)
Before: “When it comes to the question of how long a brand photography session takes, the answer is that it really depends on a lot of different factors. Every client is unique, and as mentioned above, we always want to make sure we take the time needed to capture your brand. Generally speaking, sessions can vary quite a bit, but we will discuss this together.”
After: “A brand photo session takes two to four hours. Two hours covers one location and two outfits. Four hours covers two locations, a team photo and product shots. Not sure which you need? We’ll plan your shot list together on a free call first.”
That’s token efficiency in action: the after version is shorter, and it says far more. It answers in the first sentence, drops “as mentioned above,” keeps to one job, and adds specifics only this photographer could offer. Ask an answer engine how long a brand shoot takes, and it can quote that whole paragraph without changing a word.
How do I write content for AI search without sounding like a robot?
Keep the personality and cut the padding. They aren’t the same thing, and token efficiency only asks you to lose one of them. A witty aside, a real story or a strong opinion is meaning. “In today’s fast-paced digital landscape” is padding.
- Answer first, then be yourself. Put the answer in the first sentence of each section and let your voice live in what follows.
- Use real questions as headings. Write them the way your readers would type them.
- Use lists for actual lists. Steps and options, yes. A story chopped into bullets, no.
- Define a term once, then move on. Over-explaining basics wastes everyone’s time.
Your firsthand experience is the part no model can fake. It’s also what makes your content actually reflect you.
How do I check the content I write for AI search?
You don’t need to be an engineer. Try these:
- Count takeaways. Pick a 200-word stretch and ask, “How many useful points did that deliver?”
- Run the Lift-Out Test on the first paragraph under each heading.
- Ask an AI assistant to summarize your page. If it misses or mangles your main points, they’re buried.
- Peek at the tokens. Paste a paragraph into a free tokenizer (OpenAI has one) to see how text gets split.
- Check Search Console. Google points site owners to its Generative AI performance report to see how content does in its AI features.
Try this today (15 minutes)
- Open your most important page: your services page or your most-visited post.
- List its headings, and rewrite any vague one as the question a reader would type.
- Read the first sentence under each heading. If it doesn’t answer, rewrite it so it does.
- Add one “only you” detail: a number from your own work, a step in your process or an opinion.
- Delete one throat-clearing sentence per section.
That’s token efficiency in fifteen minutes: a page that’s easier to read for humans and easier to quote for machines.
If you’d like a second set of eyes
It’s hard to see your own content clearly, because you already know what you meant. If your content is solid but nobody finds it, or you’re not sure what to rewrite first, that’s what consulting with me is for. An outside perspective spots the friction insiders no longer notice, and then we build a practical path forward. If you’re still laying the groundwork, start with a strong online foundation.
Quick answers
What is token efficiency in AI SEO?
Token efficiency in AI SEO means getting the most meaning into the fewest words, so each passage on a page can stand alone and answer a question clearly. Tokens are the chunks of text language models read. Efficient writing puts the answer first, names its subject, sticks to one point per paragraph and skips the filler.
Does token efficiency affect Google rankings?
Token efficiency isn’t an official ranking factor. Google says AI Overviews and AI Mode have no special requirements beyond normal SEO fundamentals. Clear, efficient passages still help, because they’re easier for people to read and easier for answer engines to match to a question and quote accurately. Treat it as good writing, not a trick.
Do I need an llms.txt file for AI search?
Not for Google. Google says Google Search doesn’t use llms.txt files or other special AI markup, so creating one won’t help or hurt your visibility there. Some other services may use these files, so it’s fine to have one. Clear, original, well-organized content matters far more for AI search than any special file.
Should I write shorter content for AI search?
Not necessarily. Google says there’s no ideal page length and no need to break content into tiny chunks. What matters is that each section answers its question clearly and early. A long, well-organized guide can be very token efficient, while a short post full of filler isn’t. Write for your readers first.
How do AI Overviews choose which pages to link?
AI Overviews draw on Google’s search index. Google’s systems retrieve relevant pages, review specific information on them, and link the pages that support the answer, sometimes after fanning one question out into several related searches. Your page must be indexed and eligible to show a snippet, and clear, original passages help.
Every word gets to have a job. Give your best ideas a clear first sentence, keep the parts only you could write, and let the machines quote you accurately.