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Yao Jingang's GEO public class has ended, providing links to resources such as the course summary article, GitHub project, example site, course materials, datasets, and paper repository.
The author creates a satirical standard called cats.txt to critique the weak evidence supporting llms.txt in GEO, showing it passes flawed tests similar to current practices.
AIO.GEO Protocol is listed on Product Hunt, focusing on auditing AI search structures and dry run fixes.
An analysis based on 9,509 AI citations, pointing out that Google AI Overview does not simply copy the top ten results. Instead, it prefers videos, lists, and official product sites, and small and medium-sized sites also have a chance to get cited. GEO is essentially the same as SEO.
A user used the Claude Fable 5 model to automatically optimize the website's SEO and GEO. The model independently researched, applied for CDN whitelisting, wrote tickets, communicated with engineers, and fixed security vulnerabilities, demonstrating astonishing autonomy and intelligence.
A detailed tutorial on GEO (Generative Engine Optimization), from concepts and principles to practical methods, explaining how to make AI recommend your product when answering questions, suitable for AI product entrepreneurs to learn.
This paper studies brand dynamics in LLM product recommendations, finding a conditional monopoly for well-known brands that can be broken by small rating advantages or authority-style marketing language, and highlighting a social dilemma in multi-brand GEO competition.
This is a preview of a livestream sharing about GEO (Generative Engine Optimization), also introducing the open-source GEOFlow system and its related materials and toolkits.
The author collected and read 41 papers related to GEO, AEO, and AI search, pushed the collection to GitHub, and shared 10 key insights, including the relationship between GEO and SEO, AI search citation mechanisms, the importance of content structuring, and practical optimization directions.
GEOFlow 2.0 is officially launched, with a systematic refactoring, adding multi-site distribution, AI knowledge base enhancement, data analysis, and other features, aiming to become the infrastructure for GEO content engineering.
Dageno AI offers a platform to help brands become highly recommended across 7+ major large language models, focusing on generative engine optimization (GEO).