Our site's AEO Rank is 87. Here are the 4 checks we still fail

The last points of an AEO Rank of 87 sit in work like this: captions, author proof and first sentences, done by hand.

I sell AEO for a living, and my own site still fails four checks. aeocontent.ai sits at an AEO Rank of 87, high enough to look finished and low enough to sting. The points it is missing hide in image context, internationalization signals, creator transparency and the answer capsule pattern. Each one names something a reader can see on the page.

The stakes are not small. At Google I/O 2026, Sundar Pichai put AI Overviews at more than 2.5 billion monthly active users, with AI Mode past 1 billion. Google's own guidance says those features carry "no additional technical requirements" beyond being indexed and eligible for a snippet. Read that twice. The research section below walks through what Google actually asks for.

Practitioner forums still point at the usual suspects: robots.txt errors, a missing llms.txt, Bing indexing gaps. Those matter on the way up. At 87, check whether your audit still flags any of them before you spend a dollar there.

What is left is slower work. Captions. Author proof. First sentences that answer the question cold. A rank in the high 80s hangs on that kind of labor, and the rest of this piece walks through each failure, what it means and what closing it takes, starting with the one that cost the most.

What does an AEO Rank of 87 already prove about a site?

An 87 proves the machinery works: engines can reach, read and lift answers from the pages. What stays broken is editorial, and our own pilot showed rules change that.

Before you chase the last points, check what the rank is already telling you:

• Confirm the failing criteria are content criteria, not crawl or index errors.
• Read the first sentence under every H2 by itself and ask whether it answers the heading.
• Look at who is named on each page and what proof of expertise stands beside that name.
• Check whether your images carry captions and prose that explain them.

Answer engine optimization (AEO) is the practice of making a page easy for an AI engine to extract, not just easy to rank. A practitioner on r/DigitalMarketing drew that line hard in April 2026. SEO chases ranking signals like backlinks and authority. AEO asks whether an engine can pull "a clean, self-contained answer out of your page without needing the surrounding context." The same commenter offered a blunt test: "if I extract just this section, does it still make complete sense as a standalone answer?"

That test is cold. It does not care how pretty your site is.

The common assumption is that more markup closes whatever gap is left. It does not. Google has stated more than once that generative AI search requires no special schema.org markup. There is no AI page type to add and no secret property to switch on. So ask a narrower question of your own audit: which failing checks name something a reader can see on the page?

In 2025, Simplilearn's AEO explainer told marketers to structure content with schema markups, FAQs and conversational formats so AI systems could extract it. That advice is right at the bottom of the climb. At the top, it is already done, and doing more of it buys you nothing.

Our repo-based knowledge base pilot showed where the real lever sits. We wrote the same two knowledge base questions twice. With web research allowed, 30 to 38 web sources entered each article and each one carried 15 to 18 first-person opinions. Under a code-only rule, both counts fell to zero, and every product claim checked line by line against the code was correct. The difference came from the rule the writer followed, nothing else.

Read across 4 sources, one practical step follows: set every failing check beside the person who would have to fix it. The research section below walks through these findings. They are lost there too.

That is why we build on research-driven content built on evidence instead of another round of tag tweaks. And it is why, when I opened our own scorecard, the four checks still bleeding points were not the ones a developer could fix by Friday. The first one was the images.

Why do the last AEO Rank points depend on editorial and asset work, not code?

Every check we still fail asks for something to be written, photographed or verified. Our own pilot showed why: reading the product end to end caught an admin page describing sign-in wrongly.

Here is the ground we stand on. aeocontent.ai holds an AEO Rank of 87. The four criteria dragging on it are these:

• Image context: 2 of 10. Pictures sit on the page without the words that tell an engine what they show.
• Internationalization signals: 3 of 10. The pages do not declare clearly who they are written for.
• Creator transparency: 4 of 10. Names appear, but the proof behind them is thin.
• Answer capsule pattern: 4 of 10. Too many sections warm up before they answer.

Look at that list hard. None of it is a broken tag. None of it is a crawler locked out at the door.

That stings, because we are not short on engineering. Our team includes a full-stack engineer and content infrastructure architect with 20 years of building enterprise systems. I built a company onto the INC 5000 at #84 across 2015-2018. Neither fact wrote a single image caption. Ask of each failing check one plain question: who on the team would have to sit down and write something to fix it?

The pilot made the point in a way I could not argue with. When the writer read the product from the admin setting through to the screen a user sees, the admin page said two-factor sign-in used an authenticator app. The real sign-in screen sent a one-time code by text and email. A page written from documentation would have repeated the wrong wording. Only someone checking, line by line, caught it.

The research backs the same instinct. A 2023 paper on generative engine optimization, presented at KDD 2024, found that adding quotations, statistics and cited sources raised visibility in generative answers by up to roughly 40%. Keyword stuffing, the old reflex, performed worse than doing nothing at all. Those three levers are editorial. You cannot ship a quotation from a config file.

Plan the staffing before you plan the sprint. Code fixes are fast and finite. Editorial fixes are slow and they never quite end, because every new page arrives carrying the same old habits in its blood. For readers who want the definitions behind each criterion, our AEO FAQ on AI search optimization lays them out plainly. What it cannot do is write the captions for you.

That work starts with the worst number on the board: a 2 out of 10, sitting on images nobody bothered to explain.

Which editorial and asset work should you do first to get named in AI answers?

Start with answer capsules and author proof, then images, then language signals. Speed is real: one client site went from quiet to 10 booked calls in 3 weeks.

Here is the order I would put a B2B SaaS team or a startup through, cheapest and widest first:

1. Rewrite the first sentence under every H2 so it answers the heading cold, with no warm-up. This touches every page and costs only an editor's afternoon per batch.
2. Put a real person behind every page. A name, a role, credentials a reader can check, and a profile page that ties it together.
3. Give every image its words. A caption, alt text that describes what is shown, and a sentence in the body that explains why the picture is there.
4. Declare who the pages are for. Language and region signals come last because they are quick and rarely move citations alone.

That order follows the money. Capsules and authors shape whether an engine trusts and lifts a passage. Images and language tags shape whether it understands the page around the passage.

Then step off your own site. On Lenny's Podcast, Graphite CEO Ethan Smith named three tactics that work: landing pages, YouTube videos and Reddit comments. He also argued that help-center content can become a company's highest-return investment, and that early-stage startups can win at AEO right away, unlike SEO, which takes years. He was just as clear that AI-generated content does not work. None of those moves is a code change. Every one of them is a thing somebody has to make with their hands.

One AI education vendor goes further and pitches AEO as mostly about a brand's presence across the whole web rather than its own site. I would not go that far. Your pages still carry the answer. But the off-site assets are what make an engine believe it.

Watch the questions buyers actually type. They ask which companies specialize in answer engine optimization. They ask who the top companies are for ranking in ChatGPT and AI search. Those are questions about being named, not about being crawled. Some teams buy their way into that conversation with sponsored listings that AI engines cite, and that can sit beside the editorial work, not replace it.

We put our own name on the outcome: named in AI answers in 90 days, or we work free until you are. A promise like that depends on exactly this list getting done, page by page, with nobody cutting corners on the dull parts.

The dullest part, it turns out, is the one with the worst number. Images.

What will close the last 13 points on a site like ours?

Editors, not engineers, will close them: captions written, authors proven, first sentences rewritten. No re-audit is on record yet, so the next scorecard will tell the truth.

I expect the gap between cited sites and ignored ones to keep moving off the server and onto the page. Graphite's Ethan Smith framed it plainly on Lenny's Podcast: avoid "hyper-SEOed content," and remember "the importance of originality." Originality is not a plugin.

Our own pilot is the reason I trust that bet. Once the writer worked only from the product itself, every product claim checked line by line came back correct. That is what an engine is hunting for. Proof it can lift without flinching.

So the work ahead of us is plain and slow. Caption the images first, the ones scoring worst, then put a real name and real credentials on every page that still has neither.