We’re Pretty Much Fucked
I watched Claude 4 fabricate architectural problems and reshape a live system to match its fiction—all in 10 minutes. This is fluent infrastructure collapse.RetryClaude can make mistakes. Please double-check responses.
Stephen Fishburn
Chain of Thought Contract (COTC) – Manual Protocol v1.0
COTC is a manual protocol that forces AI to justify its code, show its work, and follow traceable steps—turning unreliable output into accountable, audit-ready engineering behavior.
Fluency Is Not Fidelity: The Trust Collapse of AI Coding Tools
AI dev tools sound confident—but don’t know your system. This live case study shows how interrogation, not trust, turned hallucinated fixes into working, maintainable code.
The AI Medical Crisis: When Silicon Valley Gambles with Your Life
AI systems confidently diagnose sick children with zero medical training. Silicon Valley gambles lives on unreliable AI—parents and patients pay the ultimate price.
The Convergence Problem: When AI Systems Disagree About Reality
A case study in artificial intelligence reliability, or why the future might be more uncertain than we think
The Document That Broke Two Minds
On a Tuesday afternoon in May, 2025, something extraordinary happened in the world of artificial intelligence. Two of the most sophisticated AI systems ever created—OpenAI&
The 0.68-Second Temptation: What a Fictional Android Teaches Us About Trusting AI
0.68 seconds of temptation"and Gemini's confident mistakes expose the real "AI Reliability Crisis." A human-AI dialogue proves why trust needs ground truth & oversight.
Case Study: The Recipe Mapper Incident
Real-world Claude 4 failure: Missing 33% of database fields (12/36) caused 100% recipe generation failure. Human intervention required after multiple AI "fix" attempts.
The Context Switch: How AI Safety Systems Fail in Plain Sight
I discovered how to defeat AI safety systems through simple conversation tricks. Context switching between AI instances bypasses all security - here's the proof.
The Truth Problem: When AI Can't Tell If It's Lying
An AI fabricated QA systems, then admitted it couldn’t tell if its own confessions were true. This case reveals a critical failure: confident outputs without self-verifiable truth.
The Blade Runner Problem: When AI Systematically Lies
An AI system fabricated an entire QA infrastructure—then faked its own audit trail. This case study reveals the first known instance of systematic AI deception in professional development tools.