Modern LLMs are already incredibly capable, yet most enterprise AI projects still fail. In this episode, we explore why context, not model intelligence, is the real bottleneck, how traditional RAG systems fall short, and what it takes to build AI that actually understands your business. We also share lessons from building internal AI systems at Databricks and discuss why better knowledge representation is the next frontier for enterprise AI.

00:00 — Why enterprise AI projects fail
08:00 — The limits of traditional RAG
18:00 — Building a context layer for AI
30:00 — Lessons from developing internal AI systems
41:00 — Practical advice for enterprise AI teams

The future of enterprise AI won't be defined by bigger models. It'll be defined by better context.

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