Blog
Daily insights on how large language models are changing search, content strategy, and web visibility.
A look at how large language models reshaped search over the past year and what most SEO teams still get wrong about AI-driven discovery.
Schema markup isn't just for rich snippets anymore. Here's why structured data is becoming the backbone of AI-driven content discovery.
LLM hallucinations aren't just a curiosity. When models make up facts about your business, it can damage trust and revenue.
AI-powered answer engines are eating into organic traffic. Here's how to maintain visibility when users never click through.
LLMs handle content recency differently than traditional search. Understanding their approach changes how you should update your content.
AI crawlers have different behaviors and needs compared to traditional search bots. Your technical SEO needs to account for both.
Not all content is equally likely to be cited by AI models. Understanding citability factors can reshape your content strategy.
Building a strong entity presence is becoming more important than keyword optimization. Here's how to think about entity-first SEO.
There's a lot of noise about AI content penalties. Here's what actually matters and what's just fear-mongering.
Traditional SEO metrics don't capture AI visibility. Here's a practical framework for measuring how well your content performs in LLM contexts.