DEVLOG #03 - A crash cannot leave the model half changed

SL-LLM-R compares a model before and after a possible learning update. If that update crashes halfway through, a half-changed model would make every later result impossible to trust. So each update is all or nothing: the system keeps either the old state or the complete new state.