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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
451 פרקים
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
451 פרקים
Player FM סורק את האינטרנט עבור פודקאסטים באיכות גבוהה בשבילכם כדי שתהנו מהם כרגע. זה יישום הפודקאסט הטוב ביותר והוא עובד על אנדרואיד, iPhone ואינטרנט. הירשמו לסנכרון מנויים במכשירים שונים.