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
