9 threads to reply to

// draft reply

This is an incredibly insightful post, and you've hit on a massive blind spot for many businesses. The shift to AI models for recommendations is happening fast, and it's tough to even know where to begin optimizing for it. It's clear that understanding and influencing these recommendations is becoming as critical as traditional SEO, especially for smaller players. Your point about the gap between 'considered' and 'first pick' is especially potent for businesses trying to gain visibility in this new landscape.

// draft reply

This is a fantastic breakdown of your experiment – you're hitting on a crucial distinction between traditional conversion optimization and AI/search visibility. We've found that explicitly structuring content with answer blocks, comparisons, and FAQs, as you're doing, is key for getting cited by AI. It's almost like a new form of technical SEO. There are tools now emerging that specifically help businesses identify these AI-driven content gaps and optimize for those recommendations, which could really streamline your 'supporting edit' process.

// draft reply

This is an incredibly practical and insightful method, thank you for sharing! It really highlights how crucial those technical fundamentals like robots.txt and structured data are for AI visibility, often more so than just content quality. Have you found any specific structured data types to be more effective for certain AI models?

// draft reply

It's fantastic that ChatGPT is already citing you – that's a huge win for a new blog! Regarding hub vs. individual pages, you're right to think about the long-term. Individual pages, even for specific wallpapers, can capture highly specific long-tail intent that hub pages might miss, especially if you can provide unique value on each. This granular content can also be excellent for AI models looking for very specific answers. The 'More Details' button is a smart way to link them, just ensure each individual page offers genuinely distinct value beyond what's on the hub.

// draft reply

That's a really sharp observation, and you're definitely not late to the party – you're seeing a significant shift in real-time. 'Mention SEO' isn't a widely recognized term yet, but the phenomenon you're describing, where unlinked mentions on platforms like Reddit gain authority in AI Overviews, is absolutely happening. It highlights a growing challenge for businesses to manage their presence not just through traditional SEO, but across all digital conversations that AI models are ingesting. Understanding and influencing these mentions is becoming crucial for visibility.

// draft reply

It's definitely not just you; many are seeing similar shifts, especially with informational content. One perspective gaining traction is that a lot of top-of-funnel queries are now being answered directly by AI tools or through AI-powered search snippets, reducing clicks to traditional organic results. Focusing on optimizing for how AI models interpret and recommend your content, rather than just traditional keywords, could be a crucial next step in navigating this change.

// draft reply

Thanks for sharing this research on LLMs.txt! It's really interesting to see data debunking some of the early assumptions around AI visibility. It seems like the landscape for getting found in AI search and recommendations is still evolving rapidly, and understanding what truly moves the needle is crucial for businesses right now.

// draft reply

That's a really frustrating default to encounter, especially when every business is aiming for AI visibility. CloudFlare's aggressive bot protection is usually about preventing scraping or DDoS, but it definitely can block legitimate AI crawlers if not configured carefully. You might need to dive into your bot management settings or firewall rules to explicitly allow known AI user agents or IP ranges, or at least review what's being blocked.

// draft reply

That's a really sharp observation about the fluctuations in AI Overview. It's a complex beast, but generally, changes can stem from Google's continuous model updates, shifts in the underlying organic SERP, and varying data freshness cycles. The citations changing is a strong indicator of the source material being re-evaluated. It's definitely not a static target, which makes optimizing for it quite a puzzle. Are you seeing any patterns in the types of queries or content that fluctuate most?