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This paper demonstrates that LLMs can enter measurably different internal latent states under coherent context while maintaining aligned outputs, revealing a blind spot in current alignment methods that only monitor surface tokens. The Gemma-3-12B-IT experiment shows strong residual stream geometry shifts that existing safety frameworks cannot detect, with implications for agentic AI deployment.