7 Technical Checks Your Site Will Fail (And How to Fix Them)

The 2026 AEO Audit Technical Checkslists

In traditional SEO, if you rank on page 1 of Google, you win. In Answer Engine Optimization (AEO), you can rank #1 in organic search and still be completely invisible to the AI.

Why? Because "ranking" and "reading" are different.

An LLM (Large Language Model) doesn't just look for keywords; it ingests, chunks, and synthesizes your content. If your site has technical barriers that prevent this RAG (Retrieval-Augmented Generation) process, you simply don't exist in the answer.

Recent data is alarming: A 2025 study found that 68% of enterprise SaaS websites were inadvertently blocking at least one major AI crawler. Another 17% of sites explicitly block GPTBot, often without realizing the downstream impact on their brand visibility.​

We’ve audited hundreds of sites at Lantern. Here are the 7 most common technical failures we see—and the specific fixes you need to implement right now.

1. The "Robots.txt" Suicide Pact

The Failure: You are accidentally blocking the very bots you want to impress.
Many security teams, fearing data scraping, apply a blanket "Block All Bots" policy. Or, they use outdated User-agent strings that don't account for the nuances of 2025 crawlers.

The Data:

• 17% of sites block GPTBot (OpenAI), and 12% block ClaudeBot (Anthropic).​
• Blocking these bots doesn't just stop them from training; it stops them from retrieving live data for current answers.​

The Check:
Open your robots.txt file. Do you see this?

1textUser-agent: * Disallow: /

Or specifically:

1textUser-agent: GPTBot Disallow: /

If so, you have voluntarily removed your brand from ChatGPT Search.

The Fix:
You must move to a Selective Permission model. Allow the specific agents that power the search engines you care about, while blocking generic scrapers.

• Allow: GPTBot (ChatGPT), OAI-SearchBot (ChatGPT Search), ClaudeBot (Claude), PerplexityBot (Perplexity).
• Nuance: Be careful with Google-Extended. Blocking it stops Gemini from using your data for training, but may also limit your visibility in AI Overviews.​

2. The PDF Black Hole

The Failure: Your highest-value research is locked in an unreadable PDF.
Marketing teams love PDFs for whitepapers. RAG systems hate them.

The Data:
Standard RAG pipelines convert PDFs to text before processing. Without "tagging," this conversion fails. Headers merge with body text, and multi-column layouts turn into gibberish.

• Hallucination Risk: Unstructured PDF extraction has a high error rate, leading AI to hallucinate facts about your reports.​

The Check:
Copy-paste a section of your PDF into a plain text editor. Does it retain its structure, or does it look like a jumbled mess? That is exactly what the AI sees.

The Fix:

• Tag Your PDFs: Use Adobe Acrobat to add accessibility tags (headings, paragraphs, lists).
• The HTML Companion: Always publish a purely HTML version of the executive summary. Give the AI an easy "cheat sheet" to cite.​

3. The "Table" Test

The Failure: Using <div> or images for data tables.
Designers love CSS grids. Developers love <div> soups. But LLMs love semantic <table> tags.

The Data:
LLMs show a 40% performance improvement in data extraction when reading semantic HTML tables compared to unstructured text or non-semantic grids. If your pricing is in a screenshot, you are invisible.​

The Check:
Inspect your pricing page source code. Do you see <table>, <tr>, and <th>? Or do you see endless nested <div>s?

The Fix:
Refactor critical data (pricing, feature comparisons, specs) into standard HTML tables. Add a <caption> tag to tell the AI exactly what the table represents.

4. The Hallucination Risk Score

The Failure: You aren't tracking what the AI is inventing about you.
Visibility is vanity; accuracy is sanity. If the AI cites you but claims your enterprise plan costs $10/month (when it’s $1,000), you are losing revenue.

The Data:
Current benchmarks show hallucination rates for specific brand facts can range from 26% (OpenAI) to 43% (Mistral) depending on the query complexity.​

The Check:
Manually prompt ChatGPT: "What are the pricing tiers for [My Brand]?" If it's wrong, you have a Hallucination Risk.

The Fix:
There is no single code fix for this. You need a Defensive AEO Strategy (documented in our Defensive AEO Guide). This involves creating "Ground Truth" pages with high-authority schema to correct the record.

5. Schema Gaps: The "SameAs" Problem

The Failure: You have Organization schema, but it’s incomplete.
Most brands have basic schema. But they miss the critical sameAs property, which connects your website to your Knowledge Graph entity.

The Data:
Schema markup is used by over 45 million domains, but deeper implementation (like nesting entities) is rare. Products with comprehensive schema appear in AI recommendations 3-5x more frequently.​

The Check:
Run your homepage through the Schema Validator. Does your Organization schema list your LinkedIn, Crunchbase, Wikipedia, and Twitter profiles under sameAs?

The Fix:
Update your JSON-LD to include every authoritative profile you own. This helps the AI "triangulate" your brand identity and reduces hallucinations.

6. The "Context Window" Overflow

The Failure: Your content is too long and unstructured.
RAG systems "chunk" content into small pieces (e.g., 512 tokens). If your key answer spans 3,000 words of fluff without clear headers, the AI loses the context.

The Data:
LLMs have limited "attention." Information buried in the middle of long, unstructured documents is frequently lost—a phenomenon known as "Lost in the Middle."

The Check:
Look at your top-performing blog post. specific Is the answer to the main question ("What is X?") buried in paragraph 45?

The Fix:
Adopt BLUF (Bottom Line Up Front) writing. Put the direct answer immediately after the H2. Use clear, descriptive H2s and H3s to act as "anchors" for the chunks.

7. The "Zero-Click" Blind Spot

The Failure: You are measuring success with the wrong metric.
You are looking at Google Analytics and seeing traffic drop. You think you’re failing. In reality, you might be winning in the AI answer, but the user isn't clicking.

The Data:
Traditional analytics cannot track "Zero-Click" citations. You are flying blind.

The Check:
Do you have a way to measure your "Share of Voice" in AI answers? If not, you can't manage what you can't measure.

The Fix:
This is the only one you can't fix with code. You need a dedicated AEO analytics platform.

Stop Guessing. Start Auditing.

Manual checks are a good start, but they don't scale. A single "Disallow" line in a subplot of your robots.txt can wipe out your visibility on Perplexity overnight.

Don't leave your AI visibility to chance.

Get started today for Free Lantern on Lantern to prep your site for all 7 of these failures and get a prioritized fix list in minutes.