How are teams handling prompt QA at scale?

Curious how teams are handling prompt QA once volume gets high. We’re at \~40k conversations/month and currently have PMs manually reading transcripts to figure out: * what broke * where users get frustrated * which prompt/workflow changes helped or hurt The annoying part is the review workload scales almost linearly with conversation volume. We ship a lot of prompt updates every month, so keeping quality high is becoming a real bottleneck. I keep feeling there *has* to be a better way than “read more transcripts.” Are people actually using automated systems to surface issues/regressions in production? Like: * “this flow started failing more after version X” * “users in this branch churn more” * “these conversations became longer after the prompt change” Not looking for vendor pitches honestly — more interested in what’s genuinely working in production.