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AI Data Engineers - Data Engineering After AI // Vikram Chennai // #309

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Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

Join the Community: https://go.mlops.community/YTJoinIn

Get the newsletter: https://go.mlops.community/YTNewsletter

// 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

~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

Join our Slack community [https://go.mlops.community/slack]

Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

Sign up for the next meetup: [https://go.mlops.community/register]

MLOps Swag/Merch: [https://shop.mlops.community/]

Connect with Demetrios on LinkedIn: /dpbrinkm

Connect with Vikram on LinkedIn: /vikram-chennai/

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

  continue reading

449 episodes

Artwork
iconShare
 
Manage episode 479055373 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

Join the Community: https://go.mlops.community/YTJoinIn

Get the newsletter: https://go.mlops.community/YTNewsletter

// 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

~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

Join our Slack community [https://go.mlops.community/slack]

Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

Sign up for the next meetup: [https://go.mlops.community/register]

MLOps Swag/Merch: [https://shop.mlops.community/]

Connect with Demetrios on LinkedIn: /dpbrinkm

Connect with Vikram on LinkedIn: /vikram-chennai/

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

  continue reading

449 episodes

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