Post by DataStax

Most AI systems aren’t failing because of the models...they’re failing because the data isn’t ready. In the next episode of Context Window Podcast, Ed Anuff and Anant Jhingran sit down with Jun Rao (Co-founder of Confluent and one of the key architects behind modern real-time data infrastructure) to unpack why data has become the biggest bottleneck in enterprise AI. From co-creating Kafka at LinkedIn to building Confluent, Jun has helped shape how the industry thinks about data in motion, streaming systems, and real-time infrastructure. We’ll dive into: 👉 Why AI agents break on traditional data systems 👉 The difference between data at rest vs. data in motion 👉 Why better models alone won’t solve enterprise AI adoption 👉 What “data-ready” companies will look like in the AI era 👉 What enterprises are underestimating right now 📅 Friday, May 29 ⏰ 11 AM PT Join us live, and don't forget to follow our new Context Window Podcast page!

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