Gordon's work
The industries change, but the pattern stays consistent: learn the real system, find the hidden constraint, connect the right technologies, and build until another person can use the result.
Companies & operating experience
Founder led ventures, plant operations, craftsmanship, commercialization, and systems delivered inside real organizations.
Built
Upholstery Specialist II / 2024 to present
Built digital work order, patterning, document viewing, photo upload, and asset management systems as a Brigham Young University physical facilities upholsterer to move maintenance from reactive requests toward proactive asset tracking.
What it shows
Delivered an asset management system that was implemented and remains in use.
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Built
Founder & CEO / 2023 to 2025
Built an AI driven photogrammetry and digital patterning platform for custom covers that reduced design time from 12 to 26 hours to roughly 30 minutes.
What it shows
Reduced design time from 12 to 26 hours to roughly 30 minutes.
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Built
Founder & CEO / 2020 to 2023
Founder led infrastructure venture that licensed Oak Ridge National Laboratory technology and built a smart hot water service model around connected hardware, predictive maintenance, and reliability.
What it shows
Ran 500+ customer interviews and raised $250K.
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Built
Manager and designer / Custom upholstery shop
Managed and designed custom upholstery work across automotive interiors, boat covers, garments, and technical sewn products while helping grow a three person shop from under $40K annual revenue to $180K, then past $250K.
What it shows
Helped grow the shop from under $40K per year to roughly $180K the first year, then past $250K the second year.
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Advisor
Strategy, systems thinking, and future work
Selective advising for founders and teams on product direction, systems thinking, and how markets change as software becomes more intelligence native.
What it shows
Shows that founders and teams also come to Gordon for judgment, not just execution.
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Built
Assistant Plant Manager
Led operations for 400 personnel and implemented machine vision systems that reduced waste and saved approximately $500K annually.
What it shows
Reduced waste and saved approximately $500K annually.
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Products & public systems
Consumer AI, model research, publishing infrastructure, and open standards, each grounded in a specific problem and a public body of work.
Live
Open source provenance protocol / AI generated video trust layer
Open source provenance and trust layer for AI generated and AI assisted video, built on top of C2PA. Answers questions about video origin, sources, prompts, models, edits, and guardrails through cryptographically verifiable manifests.
What it shows
Created an open, cryptographically sound foundation for AI video provenance that teams can build on now.
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View on GitHubLive
Markdown first scientific publication system / MCP server and admin workspace
Standalone markdown first scientific publication system with polished public article rendering, an admin editing workspace, an always on MCP server for external agents, and pluggable storage adapters across Supabase, Neon, and local backends.
What it shows
Adds a serious public build around publishing, document workflows, and agent native tooling with a live GitHub repo.
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View on GitHubLive
Source grounded LDS AI / Web and iOS live; Android coming soon
A source grounded AI companion for the LDS community. The web product and iOS app are live; Android is coming soon, with retrieval quality, citations, and guardrails at the center.
What it shows
Launched a public web product at myliahona.app and a public iOS app listed in Apple's App Store.
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Open myliahona.appLive
Research platform / Model evaluation and psychometrics
Live research platform at aipsychometricslab.com for structured AI model assessment using validated psychometric inventories, Big Five (IPIP NEO 120), MBTI (OEJTS 1.2), DISC, Dark Triad, run against any OpenRouter model through a Stateless Independent Context Window Approach (SICWA).
What it shows
Live public platform at aipsychometricslab.com with a Model Explorer, Recent Runs, and Publications.
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Open aipsychometricslab.comResearch & explorations
Longer horizon work across intelligence, evidence, materials, and system architecture, described with the uncertainty still intact.
Research
Measuring AI cognition before the final answer appears
Most AI benchmarks judge intelligence by looking at the final answer: did the model solve the problem, pass the test, complete the task, or produce the expected output. That matters, but it is not enough. This is a research direction that asks a deeper question: what kind of internal process produced that answer? It started while studying Google DeepMind's March 2026 AGI measurement framework and hackathon, which break intelligence into cognitive abilities like learning, attention, reasoning, metacognition, executive function, and social cognition. The angle being explored here is that those abilities should not only be measured at the final output layer, but also inside the model's per token generation dynamics, the shape of the model's thinking may matter as much as the answer it gives. This is not a finished AGI test. It is a step toward measuring the internal structure of intelligence.
What it shows
A working public facing thesis: AI evaluation should move from answer grading toward cognitive diagnostics, not just what the model said, but what happened inside the model before it said it. That thesis is taking shape as a research direction, not as a shipped product.
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Research
Exploring evidence native databases, semantic storage, and NexusDB
I have been exploring a question that keeps showing up across everything I build: what should a database become when software, AI agents, users, files, code, memory, and validation all need to live together? Most databases are built around one shape of information, rows, documents, objects, vectors, graphs, or files, but modern AI native systems increasingly need many shapes at once, plus the ability to know where information came from, how it changed, why something matched, and whether it can be trusted. I am calling the current direction NexusDB. It is not finished, and I do not want to present it as if it is. This is an active research and architecture project, currently at the Genesis level. After about six months of research, the core evidence kernel has just come into focus.
What it shows
After about six months of research, the core evidence kernel has come into focus, the idea that the database should store evidence, not just data, and that raw source, decoded meaning, relationships, validation, and memory should stay connected inside one substrate.
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Historical
Freshman college presentation / 2014
Freshman year college presentation on graphene, hemp derived carbon, and the relationship between light, quantum context, and high performance material properties.
What it shows
Shows that I was already reaching into material science, quantum behavior, and physical technology questions as a freshman.
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Watch presentation