Episode

Does AgenticRAG Really Work?

Podcast
MLOps.community
Published
Dec 12, 2025
Duration seconds
3699
Processing state
failed
Canonical source
https://podcasters.spotify.com/pod/show/mlops/episodes/Does-AgenticRAG-Really-Work-e3c72eg
Audio
https://anchor.fm/s/174cb1b8/podcast/play/112478096/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-11-11%2F414187232-44100-2-8bab1d0a4ce58.mp3
JSON
/v1/public/podcasts/mlops-community/episodes/does-agenticrag-really-work
Markdown
/podcast/mlops-community/does-agenticrag-really-work.md

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Summary

Satish Bhambri is a Sr Data Scientist at Walmart Labs, working on large-scale recommendation systems and conversational AI, including RAG-powered GroceryBot agents, vector-search personalization, and transformer-based ad relevance models. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // Abstract The MLOps Community Podcast features Satish Bhambri, Senior Data Scientist with the Personalization and Ranking team at Walmart Labs and one of the emerging leaders in applied AI, in its newest episode. Satish has quietly built one of the most diverse and impactful AI portfolios in his field, spanning quantum computing, deep learning, astrophysics, computer vision, NLP, fraud detection, and enterprise-scale recommendation systems. Bhambri's nearly a decade of research across deep learning, astrophysics, quantum computing, NLP, and computer vision culminated in over 10 peer-reviewed publications released in 2025 through IEEE and Springer, and his early papers are indexed by NASA ADS and Harvard SAO, marking the start of his long-term research arc. He also holds a patent for an AI-powered smart grid optimization framework that integrates deep learning, real-time IoT sensing, and adaptive control algorithms to improve grid stability and efficiency, a demonstration of his original, high-impact contributions to intelligent infrastructure. Bhambri leads personalization and ranking initiatives at Walmart Labs, where his AI systems serve more than (5% of the world’s population) 531 million users every month, roughly based on traffic data. His work with Transformers, Vision-Language Models, RAG and agentic-RAG systems, and GPU-accelerated pipelines has driven significant improvements in scale and performance, includin…