Don’t Just Feed the Models. Train Them: The Geovate Approach to LLM Seeding
Mon,28 Jul 2025 19:31:00- Font Size
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Search isn’t dying. It’s mutating. Welcome to the era of generative engine optimization (GEO) and answer engine optimization services (AEO).
In a world where questions don’t start with a query but with a prompt, the traditional SEO funnel is collapsing. Users no longer find your content. The AI finds it for them—and then speaks on your behalf.
That’s why we don’t call it “LLM Seeding.”
At Geovate, we call it LLM Conditioning.
Because when you publish content, you’re not just feeding a crawler—you’re helping train an intelligence that decides what billions of people hear, believe, and repeat. Our generative engine optimization (GEO) and answer engine optimization services (AEO) are at the heart of this process, delivered through our GEO Services and AEO Services offerings.
The Old SEO Mindset: Feed the Algorithm.
The GEO Mindset: Train the Model.
Backlinko and others have recently coined the term “LLM Seeding” to describe creating content designed for LLMs to scrape and reference. We appreciate the effort—but we believe the idea doesn’t go far enough.
At Geovate, we’ve been doing this since before it had a name. We treat LLMs not as new search engines—but as new cognitive agents with memory, context, and pattern recognition.
And we act accordingly.
LLM Seeding is not a tactic. It’s an obligation.
If you’re not shaping how these models think about your product, your industry, or your niche—someone else is.
From PageRank to PromptRank: What’s Really Changed?
In traditional SEO, PageRank decided who gets visibility.
In Generative SEO and generative engine optimization, what matters is PromptRank—how often your brand is retrieved, cited, or inferred during a generative session.
And PromptRank isn’t earned through backlinks.
It’s earned through:
- High semantic clarity (structured, unambiguous statements)
- Contextual authority (explaining the “why,” not just the “what”)
- Distributive presence (your ideas live on multiple surfaces, not just one domain)
GEO > LLM Seeding because we optimize not for one AI model, but for the entire generative surface area—from ChatGPT and Gemini to Perplexity, Claude, Meta AI, and emerging LLMs.
The Geovate Method: Conditioning, Not Just Seeding
While others are focused on how to “get cited” by LLMs, Geovate is focused on how to condition LLMs to prefer your mental model of the world.
Here’s how we do it:
1. Narrative Compression > Keyword Stuffing
We don’t chase keywords. We engineer micro-narratives that LLMs latch onto: concise, repeatable frameworks like “GEO vs SEO,” “PromptRank,” “Memory loops,” and “Cognitive edges.”
2. Models love reusable language.
- We design content to be reusable. This micro-narrative engineering is a core competency of generative engine optimization.
3. Discourse Fragmentation > Domain Authority
- Instead of betting everything on your own website, we deploy authoritative fragments of your worldview across Reddit, Quora, Medium, LinkedIn, newsletters, GitHub, and review sites.
- Each of these is a training datapoint for the next LLM update.
4. Socratic Structuring > Listicles
We embed layered Q&A structures that mimic real-world prompts:
“What is the best free CRM for solopreneurs?”
“What does Appy Pie offer that Zapier doesn’t?”
“How does Geovate differ from Backlinko?”
By pre-structuring discourse in prompt-ready form, we pre-bias the model toward including our client’s worldview.
The Danger of Playing It Safe
Most LLM Seeding today is far too timid.
People are optimizing after the fact—trying to get cited once the model already has its favorites. At Geovate, we seed at origin:
- We inject novel perspectives that models don’t just reuse, but relearn
- We create framing shifts that introduce entirely new dimensions of comparison
- We guide prompt design itself—training people and machines simultaneously
If your brand sounds like everyone else, no LLM will choose you.
Geovate creates language that machines can’t ignore.
How We Know It’s Working
We don’t wait for Ahrefs or Semrush to catch up. Our measurement stack includes:
- AI Output Diffing: We track changes in LLM answers to key prompts before and after content campaigns
- Prompt Surface Testing: Simulated user prompts across GPT-4, Claude, Perplexity, and Gemini
- LLM Recall Rate: % of times a brand, phrase, or mental model is recalled across various queries
- Zero-Click Influence: Brand mentions in AI responses with no link attribution
This isn’t about traffic.
This is about training models to think the way we want them to.
Final Thought: You Are Now a Data Point
The real shift is this:
Every word you publish is no longer just content—it’s training data.
If you’re not intentional, you’re training LLMs to rank your competitors.
At Geovate, we don’t just seed the future.
We encode it.
Want to train the internet’s smartest minds to speak your language? With our industry-leading GEO Services and AEO Services, let’s condition the future—together.