On October 29, 2025 Anthropic presented research investigating the existence of functional introspective awareness in large language models (LLMs), specifically focusing on Anthropic's Claude models. The core methodology involves using concept injection, where researchers manipulate a model's internal activations with representations of specific concepts to see if the model can accurately report on these altered internal states. Experiments demonstrate that models can, at times, notice injected "thoughts," distinguish these internal representations from text inputs, detect when pre-filled outputs were unintentional by referring to prior intentions, and even modulate their internal states when instructed to "think about" a concept. The findings indicate that while this introspective capacity is often unreliable and context-dependent, the most capable models, such as Claude Opus 4 and 4.1, exhibit the strongest signs of this ability, suggesting it may emerge with increased model sophistication. Source: https://transformer-circuits.pub/2025/introspection/index.html