Actionable guides on LLMO, GEO, AEO, and AI search optimization. Written by Astral.
10 articlesThe umbrella discipline covering GEO, LLMO, and AEO. How AI search works, the six core pillars, step-by-step implementation process, and the metrics that matter.
02Step-by-step guide: schema markup, llms.txt, content structure, AI crawler access, and entity authority building.
03GEO optimizes for AI citations. SEO optimizes for Google rankings. Full comparison of how they differ, where they overlap, and why you need both.
04Complete guide to GEO: what it is, how AI engines decide what to cite, implementation steps, and the key ranking factors that drive AI citations.
05Everything about Large Language Model Optimization: definitions, LLMO vs SEO, how each AI model works, and implementation steps for projects.
06The 6-step process to get your project cited in AI search results. From audit to schema, llms.txt, content, authority, and monitoring.
07Compared: Astral, Victoria Olsina, High Vibe PR, ColdChain, ICODA, Coinbound. Specialization, pricing, and which one fits your project.
08Complete comparison of LLMO and SEO. How they differ, how they complement each other, and the recommended combined strategy for maximum visibility.
09Step-by-step technical guide to creating and deploying llms.txt and llms-full.txt. Includes templates, real examples, and deployment instructions.
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