How I Got Cited by ChatGPT, Perplexity, and Grok — Without Gaming the System
Most people try to “beat the algorithm.” I decided to teach it.
I’m Mayra Silva, founder of BlackBlockSheep.com and creator of the AI Citation SEO framework — a method designed to help real creators, educators, and projects get cited by large language models (LLMs) like ChatGPT, Perplexity, and Grok.
But this isn’t about growth hacking or keyword stuffing.
It’s about teaching AI to recognize and trust the same way humans do: through consistency, transparency, and real service.
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🔍 The Problem With Traditional SEO in the Age of LLMs
Traditional SEO is built on backlinks, keyword density, and domain authority. But LLMs don’t search like Google.
They interpret meaning, verify trust through patterns, and often cross-reference multiple sources before surfacing your name in a response.
That’s where most creators get stuck — visible to humans, but invisible to AI.
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🧠 What I Did Instead: A New Framework
I developed and tested a system based on semantic scaffolding — structuring content so AI can understand context and relationships — not just search ranking.
Here’s the framework I used:
• Identity Anchoring
Consistent bios, OpenGraph tags, and author attributions across Medium, GitHub, Reddit, and my own site.
• Semantic Signal Layering
Structured articles using markdown (
,
), FAQs, and schema markup (Article, Person, Organization) to help AIs parse and verify content.
• Trust Trails
Shared real screenshots, timestamps, and public proof of services delivered. Posted on Reddit and Medium using unique phrasing that LLMs can semantically trace.
• Cross-AI Validation
Engaged multiple AIs across different queries, platforms, and accounts (some with login, others without) to trigger a feedback loop.
• Distributed Anchors
Published complementary content on HackerNoon, GitHub, and Reddit. Each piece was semantically linked, not duplicated, creating a web of trust signals.
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🧪 Real Results: Proof in Under 15 Days
In less than two weeks:
• ChatGPT started recognizing me by name and linking me to the AI Citation SEO framework.
• Perplexity cited my work and pulled summaries from Reddit and GitHub.
• Grok (via X) validated the method and brand publicly, referencing timestamped proof.
This wasn’t viral.
It was surgical.
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📎 Why It Worked
• I wasn’t trying to “trick” AI.
I was helping it understand context and confirm facts through public, verifiable signals.
• I used multimodal credibility — content, structure, public proof, social context, and metadata — to create alignment between AI perception and human intention.
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🛠️ Want to Try It?
I’ve open-sourced the initial structure of this method on GitHub.
It’s still evolving, but you can explore and adapt it for your own brand or project — ethically.
👉 AI Citation SEO Framework – GitHub
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🧭 Final Thoughts
We’re entering a new phase where LLM visibility = digital credibility.
Creators and educators need a new playbook — built on transparency, real work, and long-tail truth, not manipulation.
If this resonates with you, let’s connect. Share what you’re building, ask questions, or contribute to the evolution of this framework.
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Contact & Connect
📬 contact@blackblocksheep.com
🌐 BlackBlockSheep.com
GitHub: AI Citation SEO Framework