How are you guys figuring out why users churn?

​ Building a PLG AI tool is… a special kind of pain. With traditional SaaS, at least you could kind of look at click funnels to see where users drop off. With AI agents, the failure mode is usually that the AI gave a technically correct answer that missed the actual intent, the user got frustrated, and they closed the tab. At my last company, we'd ship an update and watch engagement stall, but our observability dashboards were fine. You don’t get error reports. After talking to other founders, I realized everyone is dealing with these problems. One even told me their entire debug workflow was copying traces out of Cloudflare, pasting them into Claude, and asking "what went wrong?" one conversation at a time. Another CEO running an AI sales agent company explained to me how every weekly release was a "gut check" because they had no idea if a prompt tweak helped conversion or tanked it Question for the other founders here: how are you connecting agent quality to business outcomes like retention?