Anthropic's Glasswing: Early Results on AI Interpretability

Anthropic published initial findings from Glasswing, a research project aimed at understanding how large language models work internally. The work focuses on mechanistic interpretability—reverse-engineering the specific circuits and patterns that drive model behavior—which could help make AI systems more predictable and safer. For indie builders working with LLMs, better interpretability research could eventually lead to more reliable and auditable AI tools.