Fast and cheap tells you nothing about whether it worked.
For engineering and leadership — task success, not just latency and cost.
An agent can run fast, run cheap, and fail half its tasks — and every dashboard you own would call it healthy. Speed and spend measure the engine, never the outcome.
We measure the engine, not the result.
Latency and cost are easy to capture, so that's what gets watched. Whether the agent actually did its job goes unmeasured.
Cheap, fast, and failing
An agent retrying its way through a task looks efficient on the metrics that exist — and no one would know it's failing.
Rework is invisible
Human intervention and retries are real cost and real risk, and nothing rolls them up.
No signal on quality
Without an outcome measure, you can't tell a reliable agent from one that's quietly degrading.
Measure whether the job got done.
Track success, not speed
Task success rate, intervention rate, and rework per agent and workflow — the outcome metrics latency can't capture.
Fix the failures first
A roadmap ranked by failed-task volume, so the worst-performing workflows get attention before the cosmetic ones.
Be honest about the signal
Each agent is labeled measured, inferred, or none — so you know which numbers are evidence and which are still estimates.
Measure outcomes, not just effort.
Success, intervention, and rework — the metrics that say whether it worked.