Researcher shows LLM internals are interpretable, challenging the black box narrative

Jay Hack argues that large language models aren't actually opaque—their internal mechanisms can be understood and inspected. This matters to indie builders relying on LLMs: better interpretability means fewer surprises in production and more control over model behavior.