Ethan Mollick Flags Weight-Space Programming Claim as a Big Deal Pending Replication

What happened

Waiting for replication but this is a pretty big deal. Quoted post by @rikiyatakehi: We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: https://rikiyat.github.io/blog/weight-space-programming/

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The story so far

Ethan Mollick called a claim about editing model weights a big deal, while saying it still needs replication. The claim, posted by Rikiya Takehi, says GPT-6 Astra directly changed 0.016% of Qwen3.5-0.8B’s weights without gradients or training. The post says the edits fixed reasoning loops, improved math performance by up to 6x, and increased instruction following by 3x. Takehi calls the approach “Weight-Space Programming” and says frontier language models can read and write neural network weights. These results and broader claims are reported by Takehi; Mollick has not described them as independently confirmed.