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The talk reframes enterprise AI deployment failures as systemic infrastructure gaps — not model selection problems — showing that observability, evaluation pipelines, and governance tooling must be built before a model is even chosen.
The talk illustrates why standard code-level debugging is insufficient for agentic systems and presents a concrete framework — spanning telemetry, multi-scope evals, and automated analysis — for making nondeterministic AI agents production-ready.