AI Data Engineers - Data Engineering after AI // MLOps Podcast #309 with Vikram Chennai, Founder/CEO of Ardent AI.

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// Abstract

A discussion of Agentic approaches to Data Engineering. Exploring the benefits and pitfalls of AI solutions and how to design product-grade AI agents, especially in data.

// Bio

Second Time Founder. 5 years building Deep learning models. Currently, AI Data Engineers

// Related Links

Website: tryardent.com

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Timestamps:

[00:00] Vikram's preferred coffee

[00:09] Takeaways

[00:42] Please like, share, leave a review, and subscribe to our MLOps channels! You can give us up to 5 stars on Spotify and leave your reviews!

[01:53] Product User Categories

[02:47] AI Data Engineer Role

[05:40] AI Coding Limits Enterprise

[09:22] Creating Feedback Loops

[14:23] Breaking Down Big Tasks

[19:39] Marketing Data Agent Scope

[28:03] Clear Success Metrics

[32:20] Creating Agent Glossary

[36:43] AI Prompt Toolkits

[38:54] Pricing Strategy Discussion

[43:20] Compute Abstraction and Pipelines

[45:23] Agent Surprises and Logs

[47:12] Wrap up