AI engineering lifecycle

Tracify is most useful when the same run can move through the whole improvement loop:

1. Instrument the agent with spans, sessions, costs, and prompt versions.
2. Inspect timelines, payloads, failures, and quality signals.
3. Build evaluators and datasets from representative traces.
4. Compare prompt and model candidates against the same dataset.
5. Promote only after the release gate passes, then monitor production drift.

Stable trace and project identifiers keep each decision connected to its evidence.