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“Cost per outcome” is the metric most teams actually need. In prod we saw totals look fine while cost/outcome drifted due to retries + fallback paths + context creep. Are you planning a before/after deploy comparison (prompt/version) to catch regressions, or anomaly alerts on cost/outcome slope?

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Yes, we are building both

Nice — those two features tend to unlock the “why” behind drift. One thing we found especially useful was pairing cost/outcome alerts with a root-cause slice: when slope jumps, immediately show top contributing endpoint/feature + tenant/user + prompt version changes + retry ratio/context size trend. For your event_id model: how do you handle partial outcomes (e.g., success after fallback/escalation) and do you keep pricing snapshots by timestamp so historical cost/outcome comparisons stay consistent across model price changes?

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