Alex Yarosh Get Free Snapshot

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@tjrobertson52 TikTok profile avatar

@tjrobertson52

2026-02-01

"AI will eventually be too smart for this to work." No it won't. Here's the flaw in AI search that's not going away. #GEO #SEO #aimarketingtips #MarketingTips

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I think it's pretty clear at this point that AI is about to replace traditional search engines, not because people are going to stop using Google, Google use will continue to rise, but because Google themselves are trying to replace their own search results with an AI response as quickly as possible.

So why is it that most people who are doing SEO are still primarily if not entirely focused on ranking in traditional search results?

I think there are two reasons.

One is that they've convinced themselves so there's no difference between SEO and G E O or AI optimization.

I've already made a few videos talking about why that's nonsense.

In this video, I'd like to talk about the other reason people are ignoring AI optimization.

They don't think it'll work long term.

I keep hearing from this group who will admit that yes, sure, you can do things to influence the recommendations of large language models, but that's just temporary, it's not gonna keep working and actually it's gonna backfire.

So I'd like to dissect this few point cause I think the closer we look, the more we'll realise it doesn't hold any water.

First of all, let me clarify what I'm not talking about because I'm sure there are things that people are doing right now that will backfire.

If you're trying to do something overtly tricky or egregiously spammy, if you're hiding your website from AI and trying to Show them a different version of your website if you're putting prompt injections into your content.

Sure, that stuff might backfire.

In the end, I think it's likely that ChatGPT and Google will have to start giving out manual penalties for this kind of stuff.

And honestly, I've got to see any of that tricky stuff be very effective.

What I'm talking about is what actually works right now.

It's paying attention to the types of pages that these large language models site before giving their response and then placing recommendations for your brand on those types of pages, primarily by creating content.

So why am I so confident this will continue working for the foreseeable future and is very unlikely to backfire?

There's this idea some people have that eventually AI will be so smart, it'll be immune to this kind of manipulation.

It will just have so much knowledge and understanding of the world that it can tell you exactly which business is best for you.

But how?

How would it do that?

The only information available to the AI is the content on the internet.

All it can do is scrape pages on the internet, decide which of those pages it trusts, and then synthesize the content on those trusted pages.

But as long as the content on those trusted pages recommend your brand, the AI has no tools available to it to discern whether or not it's true.

The only lever available, To OpenAI and Google right now is which websites they trust.

And recently we have seen Google get more and more picky as to which websites it'll trust that G b t on the other hand will trust any website.

But it really doesn't matter how picky Google gets.

They will always have to rely on websites that can be manipulated.

For example, large language models love review websites.

Sites like Yelp or niche sites like Justia. Com are cited very often by large language models and it's hard to imagine them ever not citing review sites.

However, you can just pay these review sites to be put at the top of all their lists and immediately the larger influencers will start recommending you more.

Now at first you might think eventually these AI will be smart enough to just ignore the sponsored results.

But if they ignore the sponsored results, then you'd actually get penalized for paying for placement.

Even if they ignored the order of the businesses and only looked at the reviews, you're just rewarding the businesses that are best at getting reviews and that's typically going to be larger businesses.

And that is one option available to Google.

They could just avoid recommending all but the most established brands, making it impossible for any small or boutique businesses to get recommended in AI results.

But Google understands that this would be a horrible search experience.

Big brands already have an inherent advantage.

Which is why Google is already going out of their way to try to promote smaller niche brands.

The problem is there isn't a corpus of trusted information on these niche brands.

Often the only way the AI can get the information they need on the brand is to look at their own website.

And this is why for most brands, creating content on your own website is the most effective strategy for getting recommended by large language models.

And these same problems exist for discussion forms, press releases and 3rd party website.

Is Google really gonna stop citing Reddit or the top news publications?

They could of course limit their citations to the most trusted third party websites, but then they're giving that small handful of websites all the power.

The closer you look, the more you'll see there's no way out of this puzzle, at least for the foreseeable future.

AI will be dependent on websites that can be manipulated.

The good news is that it's still easier to be recommended if you're running a good business, easier to get reviews and easier to have people talking about you online.

However, if your competitor is running an effective AISCE campaign and you're not, it's probably not gonna matter.

They're gonna end up getting recommended more often.

Source Intelligence

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The source argues models rely on trusted web pages, so recommendations on pages a model trusts can shape AI recommendations.

2 related signals · AI visibility / cited-page influence / First-party content / niche brands

  • Map cited and trusted sources in each niche, then assess whether accurate brand recommendations on those sources correlate with AI recommendations.
  • Build complete, structured, verifiable first-party content so AI systems can understand the brand's offer, proof, and fit.

Questions this source answers

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What is this source mainly about?

The source argues models rely on trusted web pages, so recommendations on pages a model trusts can shape AI recommendations.

What should an operator take from it?

Map cited and trusted sources in each niche, then assess whether accurate brand recommendations on those sources correlate with AI recommendations.

Which topics does it connect to?

This source is connected to AI visibility / cited-page influence, First-party content / niche brands.

What public evidence supports the record?

d honestly, I've got to see any of that tricky stuff be very effective. What I'm talking about is what actually works right now. It's paying attention to the types of pages that these large language models site before giving their response and then placing recommendations for your brand on those types of pages, primarily by creating content...