Educational analysis of LLM alignment, safety behavior, and framing-sensitive response patterns.

SoftPrompt-IR is a low-level symbolic annotation layer for LLM prompts, making intent strength, direction, and priority explicit. It is not a DSL or framework, but a minimal, composable way to reduce ambiguity, improve safety, and structure prompts.

DSPy framework for detecting and preventing safety override cascades in LLM systems. Research-grade implementation for studying when completion urgency overrides safety constraints.

🌐 Detect and prevent safety overrides in LLM systems with this DSPy-based framework, ensuring actions align with safety constraints.

Explore glider aviation safety through in-depth data analysis. This project leverages incident reports and manufacturing data, utilizing Python and Jupyter Notebooks for trend identification, risk assessment, and safety enhancement in glider aviation.