Observe
Measured in work, not in tokens.
A business owner deciding whether an agent is worth keeping needs to know what it finished, what it needed help with and what went wrong. Token counts and model call volumes are real numbers that answer none of those questions, so they live in the developer view.
Tasks completed, and how many needed a person
The ratio between them is the single most useful figure about an agent. An agent that finishes everything alone may be under-supervised; one that asks about everything is not saving time.
Error rate, stated plainly
How often runs fail, and why. Shown rather than smoothed, because an agent whose error rate is climbing is worth catching in week two.
Outcome measures where they exist
Collections recovered, meetings booked, customers helped, cases closed. Only where the connected system actually records the outcome — an invented business metric is worse than none.
Model usage, for the people who want it
Calls, tokens, latency and cost per model, in the developer view. Available, labelled, and not presented as the measure of whether the agent worked.
Observability
The rest of this area.
Run timelines, reasons, metrics and cost — in business terms.
The run timeline
One run, step by step, in the order it happened.
Why did it do that?
Any action, expanded into the records and rule behind it.
Exception-based management
Agents handle the routine. You handle the exceptions.
Impact
Thirty days of one agent, in figures you can check.
Cost
What an agent costs to run, estimated before you deploy it.
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