YouTube
A central index for video work connected to the site, including long-form explanations, methodology demonstrations, and related visual essays.
This page collects the YouTube videos connected to the site.
Each video functions as a media version of a larger written thread: a long-form explanation, demonstration, or visual essay linked back into the broader research and art system. The videos are grouped here by format, while the individual posts remain connected to their own conceptual clusters.
Zombie Survival by ChatGPT — Why the AI Lies (and How to Stop It)
This video introduces SDA-3 (Structured Dimensional Analysis) through a zombie-survival stress test. The point is not the zombie scenario itself, but the way it exposes how ChatGPT can produce coherent answers that fail under pressure.
The video shows how SDA-3 shifts the model away from fluent answer-generation and towards structural extraction: identifying hidden assumptions, suppressed variables, unstable recommendations, and the few configurations that survive repeated constraint testing.
Related post: Zombie Survival by ChatGPT — Why the AI Lies (and How to Stop It)
SDA-3 tl;dr: Mapping LLM Response Structure
This video is the short companion to the longer zombie-survival SDA-3 analysis. It explains the method directly: not as a zombie scenario, but as a structural process for making a large language model expose the pressures shaping its response.
The video introduces SDA-3 as a way to distinguish truth from coherent generation. It explains why the method does not reveal a model’s hidden reasoning, chain of thought, weights, or literal embedding space, but instead produces a structured estimate of what the response appears to depend on: central topics, adjacent topics, suppressed material, associated noise, and emerging signals.
Related post: ## SDA-3 tl;dr: Mapping LLM Response Structure
From SEO Keywords to the Haunted Machine: How AI Search Became a Creative Operating System
This video follows the development of a research pipeline for promoting an obscure horror and surrealist art website without flattening it into trend-chasing, generic SEO, or interchangeable AI content.
The video shows how search results can be turned into a semantic network, then analysed for suppressed nodes, emerging structures, weak bridges, and unresolved relationships. The result is not a conventional keyword strategy, but a creative operating system: a way of turning AI-era search research into content strategy, site architecture, and art direction.
AI SEO Strategy: Why Your Creative Work Is Invisible
Originality can be systematically discovered by identifying unresolved structures in existing knowledge networks.
The traditional SEO playbook assumes that value comes from finding existing demand and producing content around it.
Generative AI changes that equation.
As AI systems become better at summarising common information, generic content becomes easier to compress, replace, and ignore. The advantage increasingly shifts toward identifying important missing structures: relationships, explanations, frameworks, and conceptual bridges that nobody has properly connected yet.
In this video I outline a research methodology designed to find those structures.