{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"START","title":"START: Agaaz Singhal, Founder & CEO, Tranzmit AI \"Self-improving AI paywalls\"","html":"","width":"100%","height":180,"duration":339,"description":"96% of users aren't saying no to your product.\nThey're saying no to your paywall.\nAnd the only tool most teams have for that is manual A/B tests.\nThousands of dollars per experiment. Weeks to trust one result. One variable at a time. Every test starts from zero.\nStop guessing. Start compounding.\nTranzmit AI builds, tests, and evolves paywalls instead.\nAnalyze the behavioral data, generate variants, score them against simulation and conversion history, ship the winner with guardrails and auto-rollback.\n50x faster than manual A/B.\n25M paywall views a month feeding the loop. Every result sharpens the next one.\nFour months ago, Agaaz Singhal was pointing the same engine at the opposite end of the funnel.\nWe recorded this episode in March, when Tranzmit sat on top of the cancel button:\nDetected at-risk customers before they cancelled\nIntervened with personalized conversations\nIdentified the root cause of frustration\nFiled live Jira tickets for engineering\nRecovered customers who were ready to leave\nFive lines of code. Three-minute setup.\nNot just to stop churn. To understand it.\nRead the behavioral data, generate the intervention, measure it, loop.\nSame engine. The screen changed.\nIn the episode Agaaz describes product teams flying blind for weeks, stitching together analytics dashboards while customers walked. Behavioral data, an intervention at the moment that decides revenue, measured and fed back.\nSame loop, pointed at the front door. Running 24/7. \"Building self-improving software infrastructure\"\n🎙️ Agaaz Singhal, Founder, Tranzmit AI on Fondo START pod\n00:26 Building AI product teams to reduce churn on consumer platforms\n00:42 AI-native cancel buttons that understand why customers leave\n01:11 Five lines of code. Three-minute implementation.\n01:25 Predicting churn before users hit cancel\n02:05 Recovering up to 28% of customers at the point of cancellation\n02:35 Why product teams spend weeks trying to understand churn\n03:20 Scaling a consumer platform to 700K...","thumbnail_url":"https://img.transistorcdn.com/q-E1hh7K6IS4AfZiNy2p4MYVGcUOO8lQP92h8QbOEOA/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80NzVj/MDEzNjkxNjU1N2Uy/NDFhMDQ3M2ZhNWI3/NWY0MS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}