// IMPROVE · GOAL OPTIMIZATION
Optimize for conversion, not just correctness.
Correct-but-useless is still useless. Define the outcomes you actually want, like conversion, resolution or approval, as scores on every run, then drive the loop until those numbers move.
THE PROBLEM
A 0.94 faithfulness score doesn't pay the bills
An agent can be factual, polite and fast while quietly failing at its job: the checkout that doesn't convert, the support thread that doesn't resolve. Quality metrics are table stakes; goal metrics are the point.
// HOW RUNAGAIN SOLVES IT
Any outcome you can measure becomes a score on the trace, from built-in judges and trajectory checks to your own goal signals attached as metadata. Numeric, boolean or categorical, all queryable.
Because traces carry your business context (tier, cohort, region, version), you optimize where it counts: the premium checkout agent's conversion, not a blended average that hides it.
Experiments score every variant against your goal metrics with confidence intervals and significance tests, so the prompt that "reads nicer" but converts worse never ships.
Drift monitors and eval alerts watch the metrics you're not optimizing, so a conversion win can't quietly buy itself with a faithfulness loss.
support-bot
last 24h
Goal metrics tracked live, per agent, against baseline.
COMMON USE CASES
RELATED SOLUTIONS
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