I learn the most from people who can explain hard things simply, and my conversation on The Ravit Show with Patricia Moore, AI Field CTO at Boomi, was one of those at Boomi World 2026.

Patricia was direct about why so many AI agent pilots stall. Most teams rush to deployment before doing the work on context, data readiness, and governance. That is the gap between the enterprises getting real value and the ones still running experiments.

We spent real time on context engineering. Everyone uses the phrase, but very few can explain it. Patricia made it obvious why context is not just another feature. It is what decides whether an agent can be trusted inside a real business. The same thinking applies to hallucinations. The fix is not bigger models. It is better grounding, cleaner data, and tighter checks around the agent.

The part I enjoyed most was her view on the shift happening inside enterprises moving from experiments to real outcomes. The leaders getting it right are not chasing AI for the sake of AI. They are tying every initiative to outcomes that actually matter.

My takeaway. The companies winning with agents are treating context, governance, and outcomes as the real product. The model is just one part of the story.

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