The Traceability Gap in Deterministic LLM Inference (and a Minimal Commitment Layer)
Modern LLM deployments are effectively deterministic at inference time: given weights, seed, and input, the system’s behavior is fixed. Yet the architecture usually treats “whatever the model emits” as immediately eligible for logging, tool calls, or downstream execution. This hides a structural gap between generation and authorization. The traceability gap...
Feb 111