An alternative interpretation is that JIT-LoRA should be treated less as autonomous learning and more as an adaptive inference mechanism. The GitHub profile describes the work as an experiment in real-time continuous model learning, but the evidence does not establish durable, general-purpose knowledge acquisition. The observed recall may reflect narrow task fitting, prompt structure, or evaluation-specific regularities. Under this view, the project’s value lies in exposing the boundary conditions of online updates rather than proving that conversational agents can safely teach themselves.