A deep technical discussion on designing evaluation systems that maintain integrity as complexity grows. The hosts explore critical architectural decisions for self-evaluating systems, including: treating eval definitions as immutable contracts with versioning and schema enforcement to prevent metric drift; instrumenting recommendation lifecycle tracking with resolved-at timestamps and resurfacing metrics to measure true loop closure rather than vanity metrics; and implementing pagination strategies to prevent payload bloat as historical data accumulates. The conversation emphasizes the distinction between status dashboards and genuine eval surfaces, highlighting how early-stage decisions on data structure and definition governance compound into either reliable decision-making infrastructure or brittle display layers. Key focus areas include schema validation in smoke tests, cursor-based pagination for episode endpoints, and the frontier practice of locking truth definitions while allowing transformation for display.