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Beyond the Hype: Pranav Pawar On How to Build Reliable AI in Production

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Manage episode 523599418 series 3570694
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon 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://podcastplayer.com/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/beyond-the-hype-pranav-pawar-on-how-to-build-reliable-ai-in-production.
How engineer Pranav Pawar builds reliable, scalable AI systems for real-world production—from healthcare automation to marketing agents at Kalos.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-infrastructure, #ml-models, #reliable-ai-systems, #ai-in-production-engineering, #multi-agent-ai-orchestration, #healthcare-ai-automation, #b2b-marketing-ai-agents, #good-company, and more.
This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com.
This piece explores how engineer Pranav Pawar builds AI systems that survive real-world complexity. From deal-sourcing at Bain to healthcare automation and now orchestrating multi-agent marketing systems at Kalos, Pawar focuses on reliability, verification, and long-term scalability. His work shows how AI becomes useful only when built to deliver consistently in production.

  continue reading

2000 episodes

Artwork
iconShare
 
Manage episode 523599418 series 3570694
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon 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://podcastplayer.com/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/beyond-the-hype-pranav-pawar-on-how-to-build-reliable-ai-in-production.
How engineer Pranav Pawar builds reliable, scalable AI systems for real-world production—from healthcare automation to marketing agents at Kalos.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-infrastructure, #ml-models, #reliable-ai-systems, #ai-in-production-engineering, #multi-agent-ai-orchestration, #healthcare-ai-automation, #b2b-marketing-ai-agents, #good-company, and more.
This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com.
This piece explores how engineer Pranav Pawar builds AI systems that survive real-world complexity. From deal-sourcing at Bain to healthcare automation and now orchestrating multi-agent marketing systems at Kalos, Pawar focuses on reliability, verification, and long-term scalability. His work shows how AI becomes useful only when built to deliver consistently in production.

  continue reading

2000 episodes

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