Researchers have made a significant discovery about the behavioral connections between foundational large language models (LLMs) and their specialized multimodal variants, which are formed into distinct model lineages. By analyzing head-level context-truthfulness scores, they found a correlation between the truthfulness of the foundational LLMs and their downstream variants1. This suggests that the behavioral traits of the foundational models are inherited by their variants, which has significant implications for the development and deployment of AI models. The study sheds light on the importance of understanding the relationships between models in a lineage, particularly in terms of their truthfulness and contextual grounding. This matters to practitioners because it highlights the need to carefully evaluate the foundational models used to develop specialized variants, as their behavioral traits can have a lasting impact on the performance and reliability of the resulting models.