Beyond the Diagonal: A Philosophical Inquiry
What Spivack's theorem means for AI: the diagonal argument applied to self-modeling systems.
Executive Summary: The LLM Blind Spot Phenomenon
An executive briefing on the structural blind spot in LLMs and its business implications.
The Historical Context of Self-Modeling Systems
Tracing the history of self-reference problems from Gödel to modern LLMs.
A Dialogue Across the Blind Spot
A fictional dialogue between two AI systems exploring each other's blind spots.
The Architecture of Self-Ignorance: Technical Deep Dive
Technical analysis of why transformer architectures structurally cannot self-model during generation.
Teaching AI About Its Own Limits: A Pedagogical Approach
How to teach AI systems — and humans — about the structural limits of self-modeling.
Beyond Self-Modeling: What Happens After the Blind Spot
Part 2 of the structural cognition series: what systems do after they hit the wall.
The LLM Blind Spot: A Comprehensive Checklist
A structured checklist for probing the self-reference boundary of any LLM.
Can AI See Its Own Blind Spot? A Socratic Dialogue
A Socratic dialogue exploring whether AI systems can recognize their own cognitive limits.
The Self-Modeling Paradox: A Formal Analysis
Formal analysis of why self-modeling systems contain an unavoidable blind spot.
I Asked 10 LLMs the Same Question — Their Answers Kept Me Awake
A late-night experiment: probing 10 language models at the self-reference boundary.
On the Structural Blind Spot of Large Language Models
Academic paper reporting consistent empirical finding: all LLMs exhibit a characteristic failure at the self-reference boundary.
The Wall Every LLM Crashes Into
Every LLM hits the same wall when asked to describe itself.