AI Run Identity vs Logging

What Logging Does

Logging records events that occur during execution. It captures timestamps, error codes, request paths, and response statuses. It tells you what happened and when.

A log is written by the executing system. It is written after the event occurs. It describes activity. It does not describe composition.

Logs answer operational questions. Which endpoint was called. What error was thrown. How long the request took. These are useful questions. They are not identity questions.

What Identity Requires

Identity defines what an AI system was at the moment of execution. It captures the model, the prompt, the context, the configuration. It exists before the run produces output.

Identity is not produced by the executing system. It is declared independently. It is not written after the fact. It is established at the point of assembly.

Identity must be verifiable by a third party. It must be complete without interpretation. Logs do not establish identity. They establish that events occurred.

Why They Are Different Categories

Logging and identity operate at different layers. Logging operates at the event layer. Identity operates at the composition layer. One records what the system did. The other defines what the system was.

More detailed logs do not become identity. A comprehensive event record is still an event record. Adding fields to a log entry does not change its structural category.

AI systems do not have identity. Not because logging fails. Because identity is a different category entirely. No amount of logging closes this gap.

Logging records events. Identity defines execution. These are not the same category.