There is a specific type of anxiety that comes with deploying an autonomous AI agent into a production enterprise environment. It is not the fear that the system will crash immediately upon launch. The true fear is silent degradation.
In this episode, Ari Joury (PhD, particle physics; Founder & CEO of Wangari Global) breaks down the anatomy of “The Slow Collapse” — the phenomenon where an AI system continues to run, but the quality of its outputs imperceptibly declines over time. Ari explains the three primary drivers of silent degradation (Data Drift, Model Drift, and Context Window Saturation) and outlines the observability and governance frameworks required to catch them before they cause catastrophic business impact. And yes, he will explain why your AI agent is basically a tired intern who forgot what they were doing on page 35.
Topics covered: AI observability, silent degradation, data drift, model drift, context window saturation, LLM monitoring, AI governance, enterprise AI deployment, automated evaluation pipelines.
Wangari is the newsletter and podcast for practitioners and leaders navigating the real work of enterprise AI. New episodes every Thursday.
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