⭐ The State of AEO 11/27 – The Indexability Protocol [State of AEO Call Recording] [State of AEO Slide Deck] [State of AEO AEO Indexability Checklist] This session introduced the first major phase of the AEO Blueprint: Indexability. Julian moved beyond general theory to the mechanics of "Machine Access." Before an AI can rank you (Optimization) or recommend you (Answer), it must be able to retrieve and understand your data. We defined Indexability not just as being found, but as the efficiency with which an AI agent can read, categorize, and utilize your business information. 1. 🔐 Access & The "Open Door" Policy We opened with the absolute foundation: If the AI cannot enter, the quality of your content is irrelevant. - The Robots.txt Reality: Many sites unknowingly block critical crawlers (like GPTBot or OAI-SearchBot) via default settings. You must audit your robots.txt file to ensure you aren't slamming the door on the very agents you want to impress. - The Cloudflare Check: For those using Cloudflare, Julian highlighted the "AI Scrape Protection" feature. While useful for blocking bad actors, you must whitelist the "Good Bots" (Perplexity, OpenAI, Anthropic) to ensure you remain visible in the generative web. - The "Energy Efficient" Bot: AI optimizes for energy and speed. If your site blocks access or loads slowly, the retrieval mechanism will skip you to save resources. 2. 🏗️ Structure as Strategy: The "Book" Analogy Website is no longer a brochure; it is a structured database (like a book) that needs a clear index. - Hierarchy is Language: AI reads H-tags (H1, H2, H3) to understand the "plot" of your business. H1 is the title, H2s are chapters. If these are used for design (e.g., using an H1 for "Welcome") rather than structure, you confuse the machine. - The Bitrix24 Case Study: We looked at Bitrix24 as a prime example of "Deep Structure." They don't just have a "Product" page; they fracture their structure into "Solutions," "Integrations," and "Comparisons" (e.g., "Bitrix vs. Monday"). This creates specific landing zones for AI to retrieve exact answers for specific user intents. - The 3-Click Rule: Information buried more than three clicks deep is "expensive" for AI to retrieve. Keep critical entity data near the surface.

⭐ The State of AEO 12/4 – The Retrieval Architecture [State of AEO Call Recording] [State of AEO Slide Deck] [State of AEO Access and Retrieval Checklist] This session drilled down into the mechanics of Indexability, specifically focusing on how we transform our websites from human destinations into efficient data sources for silicon intelligence. Julian emphasized that before an AI can recommend you, it must be able to "afford" to retrieve your data. We explored the technical gatekeepers (Robots.txt), the future of AI documentation (LLMs.txt), and the critical concept of "Cost of Retrieval." 1. 📉 Reducing the "Cost of Retrieval" We started with a fundamental shift in how we view site performance. AI agents prioritize energy and speed. - The Inverted Pyramid: In the past, we buried conclusions to keep humans reading. For AEO, the key takeaways and data points must be at the very top. If AI has to dig through "fluff" to find the answer, the cost of retrieval is too high, and it will move to a cheaper (competitor’s) source. - Speed is Visibility: A slow site isn't just bad UX; it’s an opaque wall to a crawler. We touched on Core Web Vitals and image optimization (WebP formats) not just for loading times, but to ensure the raw HTML is served instantly to the bot. 2. 🚪 The Bouncer: Robots.txt & The Amazon Case Study Access is binary: You either let them in, or you don't. - The Amazon Experiment: Julian showcased a live example of why access matters. When asked "Who are the authors of the AEO Blueprint?" via a link to Amazon: - The Lesson: You might have the best content in the world, but if your robots.txt file is accidentally acting as a bouncer against Perplexity or GPTBot, the AI is forced to guess (and often lies) about your brand.