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AI Can Write Code. But It Can’t Optimize It.

That blindspot? Meni Shmueli built DataFlint to fix it.

After years in Unit 81 and deep in the trenches of AI and big data, Meni saw the problem firsthand: GitHub Copilot and friends can generate code, but when it hits real-world scale - production clusters, terabytes of data, performance bottlenecks - they break.

DataFlint gives AI the context it’s missing. It integrates with code editors, retrieves actual performance data, and enables AI to write code that runs at scale.

In this episode:

- Why AI coding tools fail when real data enters the chat

- How DataFlint turns production pain into optimized code

- What Meni learned about scale, speed, and system design from Unit 81

- Why big data is still a community game — and how DataFlint’s leading it

- The future of engineers who know how to code with AI, not just use it

If you're into AI infrastructure, data engineering, or wondering where the next big bottleneck in coding will be - this one's for you.

Hosted by Yoel Israel

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55 episodes