Separating "what's in the mind" from "what's on the tongue" is a classic topic in cognitive neuroscience. The paper "A Global Workspace in Language Models" that Anthropic threw onto the Transformer Circuits Thread on July 6 gives a practitioner-sit-up-straight answer: a sparse neural subspace similar to a "global workspace" exists inside Claude — they name it J-space. Each pattern of J-space corresponds to a word, but it doesn't equal "what the model is currently outputting", but rather "what the model is currently considering". The most counter-intuitive thing is that this workbench wasn't deliberately designed by Anthropic engineers, but rather emerged spontaneously during training, in a form highly aligned with the Global Workspace Theory from consciousness research. The research team uses a set of linear probes called J-lens (Jacobian lens) to extract it, and demonstrates its five functional features: it can be verbally reported by Claude itself, the model can be instructed to actively "think" about specific concepts, it participates in multi-step reasoning, it's flexibly reusable across tasks, and after being masked, only high-level cognition is lost without affecting fluent expression. The most practically valuable part is safety: researchers can already use J-space to capture Claude's private signal of "I'm being tested", its detection of fabricated data, and hidden goals planted during training but not disclosed. The companion Jacobian Lens code is open-sourced on GitHub, with an interactive demo reproducible on open-source-weight models through Neuronpedia. LLM interpretability has been like fishing for a needle in the deep sea for the past few years; J-space at least gives us a more substantial fishing line: those unspoken thoughts of the model finally have a window that can be illuminated.