AI Run Identity vs Tracing

What Tracing Does

Tracing follows a request through a system. It connects spans across services. It reconstructs the path that execution took from entry to completion.

A trace is assembled after execution. It is built from instrumentation embedded in the executing system. It shows the sequence and duration of operations.

Tracing answers path questions. Which services were involved. How long each step took. Where latency accumulated. These are performance questions. They are not identity questions.

What Identity Requires

Identity defines what an AI system was at the moment of execution. It captures the full composition. The model. The prompt. The context. The configuration. All before output is produced.

Identity is not reconstructed. It is declared. It does not depend on instrumentation in the executing system. It exists independently of the execution path.

Identity must be verifiable without access to the system that ran. A trace requires the system's own instrumentation. This is a structural difference. It cannot be resolved by adding more spans.

Why They Are Different Categories

Tracing and identity operate at different layers. Tracing operates at the execution path layer. Identity operates at the composition layer. One reconstructs what the system did. The other defines what the system was.

A trace with more spans is still a trace. A trace with richer metadata is still a reconstruction. Adding detail to a trace does not change its structural category.

This is a missing category in AI systems. Tracing fills the path reconstruction category. Identity fills the composition declaration category. These categories do not overlap.

Tracing reconstructs execution. Identity defines it. These are not the same category.