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INSTRUCTOR-LED TRAINING SCRIPT - COURSE 3,
MODULE 2: AI SEARCH DEEP DIVE Let's go deeper into how AI systems process and deliver information.

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AI SEARCH ARCHITECTURE: 1.

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CRAWLING: AI bots index web content •
GPTBot (OpenAI) • Anthropic-AI • Google-Extended 2.

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PROCESSING: Content analyzed for entities,
facts, relationships 3.

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INDEXING: Information stored in knowledge
bases 4.

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RETRIEVAL: User queries matched to stored
knowledge 5.

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GENERATION: AI synthesizes response from
sources WHAT AI SYSTEMS PRIORITIZE: • Entity clarity: Clear identification of who/what you are • Factual content: Verifiable, specific information • Structured data: Machine-readable formats • Authority signals: Multiple sources confirming info • Freshness: Up-to-date content Your team needs to know how to manage AI crawler access.

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KNOWN AI CRAWLERS: • GPTBot (OpenAI) •
Anthropic-AI (Anthropic) • Google-Extended (Google AI features) • CCBot (Common Crawl) ROBOTS.TXT CONFIGURATION: # Allow all AI crawlers User-agent: GPTBot Allow: / # Or block specific content User-agent: GPTBot Disallow: /private-content/ STRATEGIC DECISION: Most businesses benefit from allowing access to public content.

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Block only truly proprietary material.

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For organizations with multiple locations,
services, or brands: ENTITY HIERARCHY: • Parent Organization └─ Subsidiary/Division └─ Location └─ Services └─ People (providers) Use schema to show these relationships: • parentOrganization • department • member • makesOffer MULTI-LOCATION CHALLENGES: • Unique content per location • Consistent NAP format • Location-specific reviews • Individual GBP profiles In Module 3, we'll tackle managing local SEO at scale across all your locations.