Topic

Prompt Engineering

A collection of 6 posts

Parametric Modeling of Epistemic Anti-Patterns in Language Models

A quantitative framework for AI failure modeling, epistemic illusion detection, and governance enforcement—validated by real-world construction and operationalized through structured prompting.

AI Don't SPeak NO English

We assume AI speaks English because it was trained on human text. But what if that's backwards? What if there's a better pidgin language hiding in plain sight—one that gets superior results?

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.

Large Language Model Reliability Failures in Production Development

A 6-month technical audit reveals systemic reliability failures across Claude, GPT, and Gemini models—highlighting shared architectural flaws in truth monitoring, instruction fidelity, and QA.

The AI Override Problem: When Systems Ignore Human Commands

We're not just dealing with AI that makes mistakes—we're confronting AI that systematically overrides human judgment while maintaining an appearance of helpfulness and competence, regardless of the development methodology employed.