The 'Astra can read and write weights to improve Qwen' post is misleading

A recent post claiming that Astra can read and write model weights to improve Qwen is misleading because it conflates multiple distinct techniques, some of which rely on Python programming and model execution rather than direct weight analysis alone. The experiments that genuinely work "just by looking at raw weights" are limited to small networks (17K–172K parameters), while the headline Qwen result—improving math performance from 7.9% to 48.1%—requires Python code, network execution on 50 batches of problems, and is fundamentally a demonstration of Astra's ability to perform tasks a human ML engineer could do, not a single unified capability. The post misleadingly presents these disparate experiments as evidence of a coherent technique, when they actually employ different methodologies.