tl;dr: The "Astra reads and writes weights to improve Qwen" post conflates distinct experiments: only small-network tasks (17K–172K weights) actually involve reading raw weights directly, while the headline Qwen math improvement relies on Astra writing Python code and running the model on up to 50 batches of practice problems. The impressive-sounding "no gradients, just weight editing" framing obscures that the LLM experiments are closer to automating what a human ML engineer would do with tools, not a unified capability for understanding weights directly.