## **3 Steps to Getting Cited by AI** %%Principles for Long-term AI Discoverability%% %%Stop optimizing for algorithms and start optimizing for answers. AI systems are fundamentally trying to provide the best possible response to user queries. success requires content that is: - **Discoverable** (traditional SEO + new AI considerations) - **Relevant** (addresses all sub-topics with current information) - **Authoritative** (provides expertise that reconciles conflicts AI can't handle alone) Build monitoring systems to detect changes I think these need to move to be inserted into the whole paper as quotes or something. Perhaps replaced by an explaination of the pyramid. Reorganize around principles that will remain true regardless of algorithm changes: - **Information Quality**: Superior content wins (with current examples as evidence) - **Multi-format Presence**: Being discoverable in multiple ways - **Conflict Resolution**: Addressing contradictions AI can't reconcile - **Continuous Adaptation**: Building systems to track and respond to changes %%To holistically improve AI Visibility across all system architectures and platforms over time, with an emphasis on AIO in B2B contexts: %%I feel like this whole section falls apart with the recent nerfing of GEO stats, actually. It also doesn't account for the new "dimensions" framing, nor owned vs earned content. This needs to go. Put it throughout the paper.%% 1. **Pass Google's Discoverability Filter:** - **SEO** → on-page, off-page, & technical, adapting to AI crawlers - **SERP features** → Featured Snippets, Knowledge Panels, People Also Ask (PAA) - **Knowledge sources** → Wikipedia, Google's Knowledge Graph (by proxy), Google's Shopping Graph - **Video content** → Build a YouTube presence, especially for product comparisons - **Create content pairs** → Develop video + text versions of your most important content - **Target temporal knowledge gaps** where AI has maximum uncertainty: breaking news, product launches after training cutoffs, regulatory changes - **Create reconciliation content** that explicitly addresses conflicting information: "While Source A claims X, Source B reports Y. Our analysis of the underlying data shows..." - **Build information density** through multiple complementary pieces: reinforce key facts across blog posts, videos, and technical documentation to leverage majority rule dynamics 2. **Pass the LLM's Relevance, Quality, & Recency Filters:** - **Content creation** → focus on decision-making, proprietary data, comparative analysis, & implementing statistics, quotes, and sources from inception%%consider moving to "Discoverability"%% - **Content retrofitting** → statistics, quotes, and sources integration into existing, high-performing assets - **Content maintenance** → systematic updates to maintain freshness ("living documents") 3. **Scale AI Visibility:** Earn authoritative 3rd party mentions (prioritize industry-trusted blogs and news sites) that simultaneously: - **Shape future LLMs** by being included in training data (like Common Crawl) - **Boost organic search rankings** through high-quality backlinks - **Provide credible sources** for generative engines, regardless of linking