The SEO Checklist

Allow AI systems to reach the pages, files, and content blocks you want surfaced. Review your robots.txt, page-level directives, login gates, rendering setup, and media/file access to make sure important content is not accidentally blocked. Treat this as a distinct access review for AI visibility, not just a generic SEO crawlability check. This matters because content cannot be summarized, cited, or reused if the systems that power LLM experiences cannot reliably access it.

Creating Markdown-formatted summaries of your site’s most critical information. This gives AI agents a lightweight, high-density roadmap to your content without requiring them to parse complex HTML or navigate deep directory structures, which significantly reduces the “noise” the model has to filter and ensures your core value proposition is ingested accurately.

Make every section understandable even when lifted out of the full page. Use headings that name the exact topic, and write paragraphs that repeat the subject instead of relying on pronouns like “it,” “this,” or “they.” Build pages as a series of independently useful answer blocks rather than one continuous narrative. This matters because LLMs often work at the passage level, not the full-page level.

Starting your text with a single, jargon-free sentence that provides a definitive answer to a specific “Who, What, or How” question. Front-load the most important fact of the paragraph so the LLM can easily identify the “claim” of the section, which increases the chances of your text being synthesized into a concise AI-generated summary or featured citation.

Utilizing clear H2 and H3 headers that mirror natural language questions and keeping associated text blocks between 100 and 150 words. You should treat every subheading as a retrieval hook so that when an LLM performs a vector search, it can pull a self-contained, logical “chunk” of information that doesn’t rely on context from three paragraphs prior, increasing the likelihood of your site being used as a primary source.

Increase the “Information Gain” score of your pages compared to the rest of the web. You must publish insights that cannot be found elsewhere—such as original survey results or “lessons learned” from a specific project—because LLMs are designed to summarize the consensus; if you only repeat the consensus, you are redundant, but if you provide new data, you become a necessary citation.

Linking to primary sources, academic papers, or raw datasets used to build your content. Show your work by clearly attributing facts to their origins, as modern AI models are increasingly trained to prioritize “grounded” content that demonstrates a high level of factual integrity, thereby reducing the risk of the model hallucinating while using your site as a reference.

Predict the user’s “next logical question” and addressing it in the subsequent paragraph. You must design your content flow to mimic a natural dialogue because LLMs are fundamentally next-token predictors that favor text which aligns with a conversational trajectory. By providing the “Step 2” answer before the user even asks it, you position your content as the most helpful path for the model to follow, increasing your visibility in multi-turn AI interactions.

Map out the most common natural language questions associated with your topic and nesting them in JSON-LD format. You must go beyond using this for “rich results” in Google and treat it as a direct API for AI models to understand the specific problem-solution pairs your content addresses. This structured approach allows an LLM to quickly parse and retrieve your answers during a RAG (Retrieval-Augmented Generation) process, making your site the definitive source for conversational queries.

Identify 2–3 key sentences in your content that provide a concise, high-value summary of the page’s intent. You should implement this markup to explicitly tell AI systems which parts of your text are most suitable for “text-to-speech” or “concise summary” playback, which is a signal largely ignored by traditional SEO but highly valued by AI agents. This increases the likelihood that a model will select your specific phrasing when it needs to deliver a verbal or summarized response to a user.

Ensure that your article, section, and aside tags reflect the actual importance of the text rather than using nested div tags for styling. Test your site by viewing it in a text-only “reader mode” to ensure the information hierarchy remains perfectly logical, as many AI crawlers ignore styling entirely and rely on the underlying DOM structure to determine what is a primary fact versus a sidebar or footer.

Utilizing server-side rendering (SSR) or static site generation so that your “source of truth” is present in the initial HTML payload. While Googlebot is proficient at rendering complex client-side applications, many independent AI training crawlers are less sophisticated; providing raw HTML ensures your data is indexed by the widest possible variety of models without being “invisible” to non-rendering bots.

Explicitly link your domain to your official social profiles and professional database entries. Add these specific URLs to your organization’s structured data so the LLM can “stitch” your fragmented digital footprint into a single, cohesive entity, preventing the model from confusing your business with others that have similar names.

Ensure your brand’s core facts are identical across websites like Wikipedia, Wikidata, LinkedIn, and Crunchbase. You must audit these third-party platforms for consistency because LLMs use these datasets as “ground truth” to verify facts; any discrepancy in founding dates, key personnel, or service offerings will lower the model’s “confidence score” in your brand.

Writing About pages that lead with “Brand X is a [Category] specializing in [Niche]” rather than using metaphorical or creative marketing copy. Replace vague adjectives with concrete nouns to help the LLM categorize your business within its latent space, ensuring that when a user asks for a specific type of provider, the model recognizes you as a perfect categorical match.

Create objective, data-heavy tables and sections that outline how you differ from competitors or industry standards. You should focus on being the primary source of comparison data for your own brand—rather than leaving it to third-party review sites—because LLMs frequently synthesize “X vs. Y” answers by looking for direct comparisons in their training data. Providing this clear, comparative framework ensures that when a user asks an AI for the “difference between X and Y,” the model uses your preferred definitions and feature sets.

Participating in niche forums, Reddit discussions, and industry-specific community boards. You should focus on being mentioned in the same context as established industry leaders because LLMs learn through “co-occurrence”—if your name frequently appears alongside top-tier competitors in training data, the model will infer that you belong in that same “prestige” cluster even without a traditional backlink.

Regularly querying AI tools like Perplexity, ChatGPT, and Claude about your specific brand or niche. If you find the model is misattributing facts or failing to mention you, you should rewrite the source content on your site using more “un-misinterpretable” and declarative language to force a correction in the model’s next fine-tuning or RAG retrieval cycle.

Verifying your entity through Google Search Console and suggesting edits to any inaccurate attributes or missing social connections. You should meticulously curate the data points that appear in this box—such as your official logo, founding date, and key leadership—because LLMs are heavily trained on these structured knowledge graphs to establish “ground truth.” By refining this panel, you ensure the model has a high-confidence, verified anchor for your brand’s identity, which prevents it from hallucinating or conflating your business with a competitor.

Raw text mentions — not links — are what matter. Prioritize coverage in Reddit threads, Wikipedia, G2/Capterra, industry forums, and earned media placements. Target inclusion in “best of” and comparison articles, since LLMs pull heavily from aggregator content when answering recommendation queries. Anchor text is irrelevant; the words surrounding your brand name are everything.