Stop chasing ephemeral AI recommendations for your new site. Instead, double down on foundational, high-quality SEO and brand building, as this is the very data that will train the AI models of tomorrow.

ChatGPT vs. Google: The SEO Battle You’re Already Losing

I got a Slack message last Tuesday that almost made me spill my coffee. It was from one of our marketing leads, a sharp guy, but prone to chasing the latest shiny object. The message was just a screenshot of a ChatGPT prompt—”what is the best tool for cloud cost monitoring?”—and our biggest competitor was the first name it spit out. Below it, in all caps: “DARIAN, WE NEED TO BE THE TOP RECOMMENDATION. WHAT’S OUR STRATEGY FOR THIS???” I had to walk away from my desk, get another coffee, and steel myself before I could even start typing a reply. This panic, this feeling that we’re missing out on some new-fangled “AI SEO,” is the most common and distracting conversation I’m having with teams right now.

The Why: You’re Trying to Edit a Photograph That’s Already Been Printed

Before we dive into what you should do, let’s get crystal clear on why trying to “get recommended by ChatGPT” is a fool’s errand. Large Language Models (LLMs) like ChatGPT are not real-time search engines. They don’t crawl the web this morning to give you an answer this afternoon. Their “knowledge” is based on a massive, static dataset—a snapshot of the internet that was fed to them during their training period, which could have been months or even years ago. Trying to optimize for a model’s current output is like trying to change your outfit in a photo from last year’s company picnic. The event is over. The data is baked in.

Pro Tip: Your goal isn’t to trick a static model. Your goal is to be so fundamentally good and authoritative on the public web that you are undeniably part of the source material for the next generation of models.

The Real Playbook: Three Fixes for Your AI Anxiety

So, if we’re not directly targeting the AI, what do we do? We focus on the source. We build a signal so strong that it’s impossible to ignore when the next data snapshot is taken. Here’s how.

Fix #1: The ‘Boring but Critical’ Foundation (Classic Technical & Content SEO)

This is the answer nobody wants to hear, but it’s the most important. You win the future by mastering the present. This means doubling down on high-quality, traditional SEO. Why? Because the training data for these AIs is, by and large, the same stuff Google has been rewarding for years: authoritative articles, well-structured data, and clear, useful content. Your focus should be on creating the best resource on the internet for your niche. That’s it. Make sure your technical SEO is flawless, so crawlers (both for search engines and future AI training) can understand your content perfectly. A great starting point is structured data.

For instance, instead of just writing an article, embed machine-readable data about it. Here’s a basic JSON-LD example for an article:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "Mastering Kubernetes Ingress for Production",
  "author": {
    "@type": "Person",
    "name": "Darian Vance"
  },
  "publisher": {
    "@type": "Organization",
    "name": "TechResolve",
    "logo": {
      "@type": "ImageObject",
      "url": "https://techresolve.com/logo.png"
    }
  },
  "datePublished": "2023-10-26"
}
</script>

This stuff tells machines exactly what they’re looking at. It’s not sexy, but it works.

Fix #2: The ‘Data Purity’ Play (Become a Canonical Source)

AIs love facts, and they love pulling facts from sources they consider to be canonical truths. While you can’t submit your site to OpenAI’s training data, you can make sure your brand’s information is present and correct on high-trust data sources that are almost certainly part of their training corpus. This isn’t about link-building for “SEO juice” in the traditional sense; it’s about establishing your entity in the global knowledge graph.

• Wikidata: Is your company, founder, and product a listed item on Wikidata? This is the structured data backend for Wikipedia.
• Industry-Specific Knowledge Bases: Are you listed on Crunchbase, G2, Capterra, or other major directories for your field?
• Corporate Registries: Ensure your official business information is correct and publicly accessible.

This is a slow, methodical process, but it makes your brand a verifiable “thing” that models can reference with confidence, separating you from the noise of a million marketing blogs.

Fix #3: The ‘Indirect Influence’ Answer (The Only Thing That Actually Works)

Here’s the real, unvarnished truth. You get “recommended” by AI when you are so dominant in your field that your brand becomes synonymous with the solution. The AI isn’t making a choice; it’s regurgitating a pattern it observed in its training data. That pattern is created when thousands of humans, on thousands of different websites, forums, and articles, have already recommended you.

Think about it. If an AI is asked for the “best cloud provider,” it’s going to say AWS, Azure, or GCP. Not because it has an opinion, but because it has processed petabytes of data where humans have overwhelmingly named those three. Your job is to become that kind of inevitable answer in your niche.

So, stop asking how to get ChatGPT to recommend you. Start asking: “How do we create content and a product so valuable that a recommendation from humans is inevitable?” Do that, and the machines will follow. I promise.

Darian Vance

Lead Cloud Architect & DevOps Strategist

With over 12 years in system architecture and automation, Darian specializes in simplifying complex cloud infrastructures. An advocate for open-source solutions, he founded TechResolve to provide engineers with actionable, battle-tested troubleshooting guides and robust software alternatives.

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