Why AI Agents Fail Quietly in Production
Most AI agents deployed in production today fail silently. They hallucinate, loop endlessly, and make confident but incorrect decisions—all because they lack proper context. Traditional observability stacks have no visibility into what's happening inside these agents, leaving SRE teams blind to cascading failures, context drift, and reliability issues that can take down critical systems.
In this exclusive interview with Swapnil Bhartiya at TFiR, Andre Elizondo, Director of Innovation at Mezmo, introduces AURA—an open source agent harness built specifically for production SRE workloads. Unlike proprietary agent frameworks, AURA provides batteries-included orchestration with self-correcting reasoning loops, transparent execution, and horizontal scalability designed for mission-critical operations.
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