Search engines can sometimes work around heavy JS or blocked crawlers. AI systems often do not.
Step 1: Schema “Hyper-Definition”
Basic schema is no longer enough. AI systems rely on structured data to disambiguate entities. Without it, your brand is just another name in a sea of text.
Organization Schema
Defines who you are. Key fields: Legal name, Website, Logo, SameAs links (LinkedIn, Crunchbase, Twitter, Wikipedia).
FAQPage Schema
Critical for AI answers. FAQs are treated as direct answer candidates. Well-written FAQs frequently appear verbatim.
Speakable Schema
Signals which parts of your content are best suited for voice and AI playback. Helps systems like Google Assistant and Gemini.
Schema is not about gaming rankings. It is about reducing ambiguity.
Step 2: Token Efficiency & Text-to-HTML Ratio
AI models have context limits. If your page is overloaded with code, tracking scripts, and design elements, the AI may truncate the content before it reaches the meaningful parts.
A practical benchmark:
- Aim for a text-to-HTML ratio above 15%
- Minify CSS and JavaScript
- Avoid excessive client-side rendering for core content
If 90% of your page is code and 10% is text, the AI sees noise. Lean pages win.
Step 3: Robots.txt & AI Crawlers
This is one of the most common and costly mistakes. Many sites block AI crawlers without realizing it.
Allow: /
User-agent: Google-Extended
Allow: /
User-agent: ClaudeBot
Allow: /
If you block these bots, your content cannot be retrieved. No retrieval means no citation.
Step 4: Performance & Accessibility
AI systems inherit many of Google’s quality expectations: HTTPS, Fast load times, Mobile optimization, Clean HTML structure.
The Storefront Metaphor
Think of your site as a storefront. If the door sticks, the lights flicker, and the shelves are messy, no one trusts what’s inside. Machines are no different.