What is AI agent performance? Measure outcomes, runs, and cost
Performance is the aggregate view of what the agent system is doing and how well it is working. It helps a team compare activity over time instead of judging the platform from one memorable run.
The concept
A plain-language definition before the product implementation.
Performance connects model activity to operational outcomes
Useful evaluation combines several signals: whether runs complete, how often they fail, what they consume, and whether the resulting work is accepted. No single chart proves quality, but a consistent aggregate makes changes and regressions visible.
How AI Agent uses it
See the aggregate before opening individual traces
AI Agent Performance summarizes agent and run activity at company scope. Use it to spot trends and outliers, then move into the relevant runs, agents, or audit events for the underlying detail.
Trend view
Compare system activity across a meaningful period.
Operational signals
Track completion, reliability, usage, and cost where available.
Drill into evidence
Open the runs behind an aggregate change before acting on it.
From idea to a working system.
- 01
Aggregate
Collect company-scoped activity from agents and workflows.
- 02
Compare
Review trends, changes, and outliers over time.
- 03
Investigate
Open the detailed run or audit trail behind a signal.
Use aggregates to find the runs worth investigating
Best for
Comparing activity, completion, reliability, usage, and cost signals over time before drilling into an outlier.
Choose another pattern when
Proving why one result happened or whether a domain-specific outcome was good. Open its trace and apply an explicit scorecard.
Included in AI Agent
The product capabilities behind the idea.
- Company-scoped performance view
- Time-based trends
- Run and usage summaries
- Paths into detailed evidence
Frequently asked questions
Keep exploring
Related product guides
Audit Log
Audit Log is the event-level record of agent activity. Where Performance shows the aggregate, Audit Log helps a team inspect the individual actions and state changes behind it.
Overview
Overview is the control panel for a company using AI agents. It brings the signals that matter now into one place, so the next decision does not require opening every agent, workflow, project, and table.
Workflows
A workflow turns a business process into an explicit graph. The model can reason inside an agent step, while the surrounding sequence keeps triggers, tools, branches, approvals, and outputs predictable.
Build the smallest useful version first.
Start with the agent and one real task. Add workflow control, context, and approvals when the work shows you where they matter.