r/MachineLearning: RFE-Core2 Mechanistic Interpretability Synthesis — Full Probe Arc Across Multilayer-Lock, Gate Decomposition, and Attractor Migration Released June 9

A researcher posted a comprehensive synthesis of RFE-Core2 mechanistic interpretability findings to r/MachineLearning on June 9, covering why downstream fixes to AI system rigidity consistently failed to produce results and documenting a full probe arc from multilayer-lock mechanisms through gate decomposition, attractor migration, reconstruction ablation, and generative probe stages. The writeup is framed as the 'clearest picture' of ongoing research into what internal mechanisms actually govern model behavioral rigidity. Posted with a [R] research tag, the synthesis is generating discussion among ML practitioners working on interpretability tooling.