AI engines extract specific passages from sources to synthesize answers. The structural and stylistic choices that increase citation likelihood: **Lead with the direct answer.** The first sentence should answer the underlying question in a complete, attribution-friendly way. Not 'In this article, we will explore the question of X' — but the actual answer to X. The first 100–300 words determine citation likelihood for most queries. **Use specific numbers and named entities.** 'Studies show response times affect conversion' is less citable than 'Pages with Largest Contentful Paint above 2.5 seconds show 7–12% lower conversion rates in Canadian B2B SaaS' (with the source for the data). LLMs preferentially cite sources that contain specific, verifiable facts. **Structure with clear section headers and bullet lists.** Both classical and LLM SEO benefit from scannable structure. LLMs especially prefer content where the structural hierarchy makes the answer location predictable. **Attribute to a named expert.** Publish under a real author byline with a bio link to a page that includes credentials, publication history, and external verifiable references. Anonymous content is cited less consistently than equivalent content with named authorship. **Cite original sources.** When you reference a fact, link to the original source rather than to an aggregator. LLMs use citation patterns to assess source quality, and being part of a high-quality citation graph compounds your own citation likelihood. **Include the obvious caveats and edge cases.** LLMs reward content that addresses 'but what if' scenarios because handling edge cases improves the synthesized answer's completeness. A piece that handles the messy reality is more cite-worthy than one that handles only the clean case. **Implement schema correctly.** Article schema with author, datePublished, dateModified properties. FAQPage schema for question-style content. HowTo schema for procedural content. Schema gives LLMs a clean entity parse. **Update content regularly.** LLMs preferentially cite recently-updated content. Implement a substantive review cycle — at least every 6 months for important pages, every 12 months for evergreen content. Update the dateModified property and refresh meaningfully (not just changing a date). **Make crawl access explicit.** Confirm in robots.txt that the AI crawlers you want citations from are allowed access. **For Canadian businesses specifically:** Lead with Canadian context where relevant. Use Canadian spellings where appropriate. Reference Canadian sources, regulations, and statistics. AI engines synthesizing answers about Canadian markets need Canadian sources, and citing them disproportionately benefits Canadian-context publishers.