AEO Footnotes is an open publication focused on AI visibility, covering answer engine optimisation (AEO), generative engine optimisation (GEO), LLM visibility, AI search, and AI discovery. Every article ends with a list of the sources it cites, providing a transparent reference base for its claims. The publication addresses topics such as how AI crawlers from companies like OpenAI, Perplexity, Anthropic, Apple, Google, and Common Crawl behave, what robots.txt rules control them, and what official documentation from search providers states about appearing in AI-generated results. The publication includes research from the Footnotes Lab, which fetches robots.txt and llms.txt files from domains in its directory to observe real-world crawler interactions. Articles analyse case studies, academic papers, and first-party data from tools such as Search Console and Bing AI Performance. Typical use cases include professionals tracking changes in AI crawler behaviour, evaluating the limitations of visibility studies, and learning about protocols and specifications relevant to AI discovery. AEO Footnotes also operates as an earned publication, meaning interested readers can contribute by taking part, with an editor reviewing submissions before publication. The site offers topic feeds and a newsletter to support discovery, and structures its articles so answer engines can cite the content and credit the authors. Its intended audience is people working on AI visibility who require sourced, factual writing on how search and discovery systems operate.