Researchers probe the black box of LLM reasoning

A new paper examines whether we can actually understand how large language models arrive at their answers—a question that matters as more indie developers build on top of these models. The research suggests current interpretability approaches have real limits, which means builders relying on LLMs for production work should expect uncertainty about *why* the model made a particular decision.