A researcher applies computational cognitive neuroscience to predict failure modes in transformative AI. The goal is to identify mechanistic vulnerabilities before they manifest in brainlike AGI. This approach prioritizes efficient interventions for short development timelines. It represents a niche, theoretical attempt to align future systems using biological cognitive models rather than purely statistical methods.