@RyanJones Them: Why read the literal source code when I can just spend four hours debating if a meta description should be 155 or 160 characters? Don't take my 2005 security blanket away from me, Ryan.
@SEOKeval I'm guessing it was extremely low? That’s the beauty of high-ticket SEO,.. search volume becomes a vanity metric when the intent is that specific. One $55k sale proves that quality beats quantity every single time.
@DavidGQuaid The real problem is that simplicity doesn't sell as well as complexity does. It’s the SEO paradox technology evolves but we realize the fundamentals never change
@RayMartinezSEO It's almost a symbiotic relationship at this point - Microsoft gets AI credibility, OpenAI gets infrastructure and grounding capabilities. Though it does raise questions about how truly "independent" the search results are when there's such a tight integration between the two.
@levelsio The sad part is it actually works - people assume big numbers = credibility and influence follows. The whole thing is a feedback loop that rewards fakery.
@levelsio Doesn't surprise me at all. Vanity metrics are the new status symbol, and when you have that kind of money, a few thousand dollars to inflate your follower count is basically rounding error.
@glenngabe@rustybrick If Meta builds its own, we're potentially looking at a world where your content's visibility depends on which AI ecosystem a user is in.
@harpreetchatha_ Beyond just making noise, I think consistency across press releases, Wikipedia updates, and authoritative third-party mentions is key LLMs learn trust signals from corroborating sources. The more aligned your narrative is across the web, the faster models pick up the rebrand.
@Charles_SEO The pattern is pretty clear at this point - deny everything until it becomes undeniable. The leaked docs just confirm what experienced SEOs have observed in practice for years. At some point you have to trust your own data and experiments over the official line.
@DavidGQuaid The double-edged sword of AI knowing "everything" is that it learns from our flawed information ecosystem. A model trained on propaganda still outputs propaganda-influenced answers, just with more confidence. The real challenge isn't the LLM's knowledge capacity,