AI Optimization Is Mostly Just Good Marketing
Why optimizing for LLMs can feel like pressure-washing a spoon — and what to do instead.
We’re at a funny stage of AI optimization where it feels like we’re using an enormous amount of computing power just to help us make basic editorial decisions. I keep thinking of a particular Robin Williams joke about Michael Jackson but it’s too crass to type out here, so I’ll offer my own version: a lot of AI optimization advice feels like using a pressure washer to rinse a spoon. Does it work? Well, yeah. Is it overkill? YES. STOP WASTING WATER.
This is the argument behind today’s episode of the Zero Click Marketing podcast: GEO/AEO is real, but it is not magic. The work is part technical, part editorial, part credibility-building, and very much a zero-click problem. Listen here (or watch on YouTube if that’s your thing).
I heard someone recently ask:
“What’s the ideal H2 header length so that it’s optimized for LLMs?”
I get it. We’re all trying to understand how AI systems retrieve, parse, summarize, and cite information. There is a real technical layer here.
But also… shouldn’t a heading be as long as it needs to be while still being concise? Weren’t we supposed to be doing that anyway?
Then I saw someone else say, “LLMs have started to discover video. And it might not be that people are watching these videos — the LLMs are. Now it’s more important than ever to do video.”
Yes, AI systems may increasingly use video transcripts, captions, and metadata as part of the information they retrieve.
But weren’t people already making videos? Weren’t captions already useful? Weren’t transcripts already good for accessibility, search, repurposing, and plain ol’ human comprehension?
This is the part of the GEO/AEO conversation that makes me feel like I’m the one who’s losing my mind here.
Before we go further, a quick terminology caveat — partly for you, partly for me. I’m aware this is a fast-changing topic, and so people often use terms like AEO, GEO, and even AI and LLMs interchangeably. (Present company included.) I think of Answer Engine Optimization (AEO) as one piece of the larger Generative Engine Optimization (GEO) umbrella.
AEO is about making content easy to surface as an answer in chatbots and search. GEO, more broadly, is about making your content, brand, and public evidence easier for generative systems to synthesize, cite, or mention, in an AI-generated response.
Next, I acknowledge that AI search changes things.
Ahrefs’ February 2026 update found that the presence of an AI Overview correlated with a 58% lower average click-through rate for the top-ranking page. So sure, when clicks are dramatically lower, it feels like what you have left is the chance at visibility.
Meanwhile, Cyrus Shepard recently analyzed 54 AI citation experiments, patents, and case studies, then ranked the factors most associated with AI citations. His TL;DR was refreshingly sane: most of the critical factors still align with traditional SEO practices. Or, in his words: “win SEO, win AI citations,” most of the time, with extra steps.
The visibility stakes are changing. The mechanics are changing. But a lot of the “new” advice keeps arriving at suspiciously familiar destinations: clear structure, specific answers, credible evidence, useful formats, and content people can actually understand.
Great. Love this for us.
I just refuse to pretend the pressure washer is groundbreaking when all we had to do was rinse the spoon in the sink.
“AkShUaLLy, There’s a Technical Side Too.”
1/ Retrievability
I know. I don’t disagree with that. In GEO, AEO, LLMO, or whatever acronym we are arguing about this week, of course there is a technical side: crawling, rendering, retrieval, indexing, sitemaps, structured information — all of that matters. In fact, Cyrus’s top-ranked factor was URL accessibility: whether a page is available and crawlable during training or grounding. He notes that this has become more complex as AI companies use different crawlers and as more sites deploy AI-scraper-blocking protections.
In the Zero Click Marketing podcast episode I recorded this week, I refer to this retrievability: can AI-mediated systems access the thing in the first place?
But retrievability is only the first layer.
2/ Extractability
The second layer is extractability: once the system finds your content, can it easily understand and reuse the useful parts? Here’s where GEO starts to look suspiciously like good writing.
Clear definitions. Structured information. Useful headings. Concrete examples. Evidence close to the claim. Comparison language. Original frameworks. Standalone statements. Video when video helps people better understand the thing.
Cyrus also calls out factors like AI-ready structure, factually specific content, explicit phrasing, cited sources, and self-contained passages as characteristics associated with AI citations. In other words: structure the page clearly, make specific claims, show your work, and write important points so they can stand on their own.
Say the thing, explain the thing, and prove the thing. I’ll say… it’s nice (I guess?) that more people are caring about all this. But it’s writing for humans’ comprehension. It’s not really writing for the robots.
3/ Credibility
Once the system finds and understands your content, does it have a reason to trust it?
You know those listicles called like, “Top 20 Marketing Experts to Follow?” and it’s the same 20 people except for the addition of one rando who — surprise! — is the author of the shitty listicle? Or those 2,000-word articles called, “What is Customer Research? A Complete Guide,” and it’s written by someone who has never spoken to a customer, never conducted research, and appears to have learned about the topic by reading eight other articles called — surprise! — “What Is Customer Research? A Complete Guide”?
AI search sees this human slop (we can’t blame AI for this particular sin) and makes the problem weirder. Sometimes it summarizes the lukewarm consensus. Sometimes it pulls in the thing that stands out. And sometimes the thing that stands out is not the thing you wish it had found.
So no, credibility doesn’t mean you can force AI to cite your “complete guide.”
It actually means you need a stronger public record than generic content, stale claims, and whatever random artifact happens to be most distinctive.
Credibility means your content gives people — and search systems — a reason to trust this answer from you and you specifically.
That can mean original research. First-party data. Expert quotes. Clear methodology. Customer examples. Specific experience. Screenshots. Named sources. Author expertise. Transparent limitations.
And — surprise! — this is not just an AI thing. It’s a trust thing.
4/ Public evidence
And finally, public evidence. This is the most zero-click part of GEO.
Because AI systems and buyers do not only learn from your website. They learn from Reddit threads, YouTube videos, LinkedIn posts, reviews, comparison pages, third-party mentions, communities, and many more discovery surfaces.
Unfortunately, those are all the places you don’t own… which is largely what makes them more credible to your audience.
So if the public record around your brand is thin, confusing, outdated, or nonexistent, you have a problem.
What does the internet seem to know about you?
What do customers say?
What comparisons exist?
What questions come up repeatedly?
What misconceptions go uncorrected?
What phrases are associated with your brand?
What proof exists outside your own website?
Your website matters, yes. But so does your audience’s language, the trail of proof, the conversation around your brand, and whether you and your category are visible enough in credible places that both humans and machines can connect the dots.
The goal is not to follow every hack to trick the robots. It’s to become more trustworthy. First, by people. Then, by robots.
So… now what?
Say it with me, fellow marketers who love nuance: “It depends.”
Because it’s not all about “just good writing,” fretting over your robots.txt or focusing on PR. The answer — surprise! — is somewhere in the middle.
GEO is technical enough that marketers need to understand retrievability. Can the system access the page?
It’s editorial enough that we need to care about extractability. Can your page be understood, summarized, and cited?
It’s evidentiary enough that we need credibility. Can this answer be trusted?
And it’s zero-click enough that we need public evidence. Does proof exist beyond your own website?
Because when search becomes an answer engine, your content has to do more than attract traffic. It has to earn its place in the answer. Achieving this is not that different from what good marketing has always been.
Be findable. Be useful. Be credible. Be memorable. Show up where your audience learns. Say something worth repeating. Create evidence that outlives the click.
And for the love of God, stop washing your spoons with the pressure washer. Just turn on the faucet.
🧁 Petits Fours
Four delicious considerations because this newsletter is, after all, called the “Menu.”
💰 Join this webinar on CRO, hosted by me, led by Talia Wolf: Most CRO advice is tactical noise: tweak the button, rewrite the CTA, move the form, repeat until everyone loses the will to live. Talia Wolf has a smarter take. She’s the author of Emotional Targeting and CEO of GetUplift, and at SparkToro Office Hours, we’ll talk about how to optimize across the full customer journey — not just the website. Save your seat or get the replay here.
🎁 Content Marketing in a Post-SEO World: I’m joining my friend Matt Lerner for a live session on what content marketing looks like when organic traffic is harder to win, social platforms penalize links, and AI answers questions before people reach your site. We’ll talk Zero Click Marketing, measurement, and what founders should do when they have limited time and no content team. Register here.
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