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Timestamps

[00:00:00] Introduction

[00:02:00] Alex Gallego talks about his background

[00:04:00] Charna Parkey discusses the importance of hands-on experience in learning.

[00:06:00] Alex explains the origins of Red Panda and how it emerged from challenges in the streaming space.

[00:08:00] Alex details the evolution of Red Panda, its use of C-Star and FlatBuffers, and its low-latency design.

[00:11:00] Alex discusses the positioning of Kafka versus Red Panda in the market.

[00:20:00] Alex introduces Red Panda's new agent framework and multi-agent orchestration.

[00:24:00] Alex explains how Red Panda fits into the evolving landscape of AI-powered applications.

[00:30:00] The future of multi-agent orchestration.

[00:44:00] Thoughts on AI model training and data retention.

[00:46:00] Alex encourages future founders and shares his perspective on risk-taking.

[00:50:00] Charna Parkey and Leo Godoy discuss the key takeaways from the conversation with Alex Gallego.

[00:52:00] Charna reflects on open source trends and the role of developer experience in adoption.

[00:54:00] Charna and Leo talk about the different types of founder journeys and the importance of team dynam

Quotes

Charna Parkey

"For AI, unifying historical and real-time data is critical. If you're just using nightly or monthly data, it doesn’t match the context in which your prediction is being made. So it becomes very important in the future of applying AI because you need to align those things."

Alex Gallego

"Every app is going to span three layers. The first layer is going to be your operational layer, just like you have to do business right now. Then there always has to be an analytical layer, and the third layer is this layer of autonomy."

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Season 7 · Episode 4

Building the Future of Streaming Data | Alex Gallego.

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