As enterprises rush to prepare for AI, most of the attention is focused on models, GPUs, and applications. But what if the real starting point isn’t AI at all?
In this episode of the Built for Trust Podcast, Nick Lippis sits down with Patrick Heinz from Ameriprise to explore why observability is the true foundation of AI-ready infrastructure. Patrick draws on decades of experience spanning service providers, startups, and large enterprises to explain why AI systems depend on continuous, high-quality data and why visibility across networks, applications, and service providers is no longer optional.
The conversation dives into synthetic path monitoring, breaking down data silos, contextualizing massive volumes of telemetry, and how “data without context is dangerous.” Patrick also shares real-world examples of how improved visibility builds trust with users, operations teams, and service providers while reducing outages, escalations, and firefighting.
If you’re thinking about AI readiness, automation, or agentic systems, this episode makes one thing clear: you can’t automate what you can’t see, and trust starts with visibility.
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