I wrote a spontaneous LinkedIn post because Generative Engine Optimization is getting way too much hype – and I decided to share my thoughts here on our blog as well.
Everyone’s talking about Generative Engine Optimization like it’s some new SEO religion. It’s not.
If your content doesn’t rank – it doesn’t get retrieved.
If it doesn’t get retrieved – it won’t be cited.
That’s the chain.
People ask me: “Dmitriy, how do we optimize for ChatGPT/Gemini/Perplexity?”
Wrong question.
There’s no secret method for “optimizing for AI answers”.
No prompt tricks or embedding hacks will save you if your core content is weak.
The only thing that consistently works:
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Real topical depth
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Semantic coverage
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Clean structure
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Intent-focused language
Not prompt voodoo.
LLM answers don’t come from nowhere – they’re layered on top of traditional ranking systems.
Document → Passage → Generation
Break that chain at the start, and you’re out of the game before it begins.
People keep optimizing for model behavior. But models change. Retrieval logic evolves.
What doesn’t change?
Clear content architecture, language clarity, and intent alignment.
Trying to outsmart the model is short-term thinking. Designing content that ranks, aligns, and survives updates? That’s long-term SEO.
Use LLMs as tools – not as your strategy.
And don’t get fooled by every new Tool/Platform/Dashboard telling you your “cosine similarity is too low”.
Focus on meaning, not math.
We’re putting together a deep-dive guide on Generative Engine Optimization – what actually drives visibility inside LLMs, how retrieval really works, and what it takes to be cited. No shortcuts. No hype. Just signal. Stay tuned.