According to DeepLearning.AI, researchers at Anthropic and partner research and safety institutions identified persona vectors, patterns in LLM layer outputs that encode traits such as sycophancy and hallucination, by averaging representations of a trait and subtracting its opposite to isolate and control these behaviors, source: DeepLearning.AI — X, Dec 8, 2025; The Batch summary hubs.la/Q03Xh6MW0. Finding these vectors allows engineers to pre-screen fine-tuning datasets to predict personality shifts before training, making workflows safer and more predictable, source: DeepLearning.AI — X, Dec 8, 2025; The Batch summary hubs.la/Q03Xh6MW0. The results indicate high-level LLM behaviors are structured and editable, enabling more proactive control over model personalities during deployment, source: DeepLearning.AI — X, Dec 8, 2025; The Batch summary hubs.la/Q03Xh6MW0. The source does not announce products, datasets, or affected market assets and does not mention cryptocurrencies or tokens, so no immediate crypto market impact is indicated, source: DeepLearning.AI — X, Dec 8, 2025; The Batch summary hubs.la/Q03Xh6MW0.