Agent systems do not fail gracefully by default. When memory breaks, tools fail, context disappears, or models behave unpredictably, trust in the entire system quickly collapses. As autonomous workflows become more deeply embedded into enterprise operations, engineering teams are being forced to design for failure from the start, building systems that can recover, escalate, explain decisions, and operate safely under uncertainty. This panel explores how teams are approaching reliability, guardrails, fallback mechanisms, human oversight, and evaluation strategies to build agentic systems that users can realistically trust in production.