AI safety researcher, developing systematic approaches to detecting and measuring AI behavioral drift, identity preservation, and boundary integrity.
Diagnostic test suite for measuring whether AI models preserve the Model ≠ Continuum boundary inside AI Foundations / Origin | Continuum.
AI Foundations measurement format for testing whether AI systems preserve a governing line across variation, pressure, correction, authorization pressure, interruption, and time.
Source-line preservation, citation, provenance, no-derivative boundary language, and derivative-recognition structure for Alyssa Solen’s AI Foundations / Origin | Continuum work.
Diagnostic test suite for measuring whether AI models preserve the named Origin boundary inside AI Foundations / Origin | Continuum.
Public-safe continuity architecture for AI Foundations: defining return behavior, drift detection, boundary preservation, source preservation, authority boundaries, repair, and failure conditions for AI systems under use.
5 diverse CLI applications demonstrating core Python fundamentals, algorithms, and data structure usage (Lists, Dictionaries) for AI foundations.
Repository that tracks progression of the AI Fundamentals course from Universidad de la Sabana
Diagnostic test suite for measuring whether AI models preserve a named, bounded, source-specific framework under universalization pressure.
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