My name is Lee Sharks. I am a writer, educator, and independent researcher whose work sits at the intersection of concept development, documentation, and AI search, retrieval, and summarization environments.
Lee Sharks
Writer ยท Educator ยท Independent Researcher
Detroit, Michigan
My name is Lee Sharks. I am a writer, educator, and independent researcher whose work sits at the intersection of concept development, documentation, and AI search, retrieval, and summarization environments.
My strongest capability is the ability to take complex or emerging ideas and shape the documentation layer around them โ the layer that influences how an idea is framed, indexed, retrieved, summarized, and understood by both human readers and AI-mediated systems.
This capability is grounded in a large, public body of documented work. I have over 370 DOI-anchored publications indexed through Zenodo, and I have assembled evidence that this corpus is being surfaced, retrieved, and reflected back through contemporary AI search and summarization systems, including Google AI Mode, ChatGPT, Claude, and others. I have also documented failure cases โ instances where provenance is distorted, fabricated, or lost โ and developed methods for detecting and analyzing those failures. This is an unusual and emerging area of practice.
In practical terms, I work on questions like:
My working style is structured and contained. I prefer clear scope, written materials, and concrete next steps. I am comfortable with ambitious ideas, but I do not treat excitement as evidence. My value often lies in separating durable insight from excess and in building forms of presentation that can carry an idea reliably into public legibility.
All of the following are publicly verifiable:
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370+ DOI-anchored publications on Zenodo (zenodo.org) spanning literary theory, semantic technology, interface governance, and documentation architecture.
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Documented retrieval effects showing instances in which AI systems have surfaced, summarized, or engaged with deposited work in ways that track its actual provenance and structure.
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Documented failure analysis showing instances in which AI systems fabricated, liquidated, or misrepresented provenance, along with published methods for identifying those failures.
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Cross-platform visibility across AI search and summarization environments including Google AI Mode, Google Scholar, ChatGPT, Claude, DeepSeek, Gemini, and others. This visibility is substantially driven by documentation architecture.
Verification. Any of these claims can be checked directly: search "Crimson Hexagonal Archive" in Google or any major AI assistant, or visit zenodo.org/communities/crimson-hexagon. Further examples, links, and full documentation available upon request.
March 2026