Model Surgery: Can an AI directly edit and make another AI forget facts?

The author reports an experiment in which Claude Opus 5.5, acting as an "editor" under the weight-space programming method from MIT CSAIL's "Sparks of Weight-Space Programming" paper, edited 17 weight matrices in a 494-million-parameter model to make it forget 20 fictional customers and 10 planted secret keys, while other customers lost only 2.5 points of accuracy. The edited model matched an "answer key" model trained without those facts across six working attacks, whereas gradient ascent, NPO and refusal training each failed to both erase the facts and preserve the rest of the model. Testing Claude's own explanation of the edit, the author found the late layers do the work and the middle layers only assist, contradicting part of Claude's account.