1017: Vector Search, Agentic Memory and Effective RAG, with MongoDB’s Pete Johnson

1017: Vector Search, Agentic Memory and Effective RAG, with MongoDB’s Pete Johnson

Author: Jon Krohn August 11, 2026 Duration: 57:24
In Episode #1017, Pete Johnson (Field CTO of AI at MongoDB) joins Jon Krohn to explain why four out of five organizations have AI steering committees and success metrics, yet only one in five sees a return on the investment. Having made nineteen stops across six countries this year advising more than a hundred companies on their AI strategies, Pete has an unusually wide view of what is actually working in production. In this episode, he traces the history of SQL and denormalization, unpacks why the embedding model is the most underrated choice in a RAG pipeline, explains Matryoshka embeddings and lays out what better agentic memory looks like. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.superdatascience.com/1017⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (00:06:34) Why the AI ROI gap happens and what to do differently (00:18:21) Jevons paradox, bank tellers and toll booth workers (00:24:05) From Codd’s 1970 paper to denormalization (00:32:31) Why the embedding model is not a commodity (00:40:20) What better agentic memory looks like

Hosted by Dr. Jon Krohn, Super Data Science: ML & AI Podcast with Jon Krohn is a deep and accessible exploration of how artificial intelligence and machine learning are reshaping our world. Each episode features conversations with leading researchers, engineers, and entrepreneurs from both academia and industry, breaking down complex ideas into something tangible and relevant. You'll hear firsthand about emerging techniques, practical applications, and the evolving landscape of data-driven careers. The sheer volume of data in our world is growing at a staggering rate, and this podcast serves as a guide to understanding that expansion and finding your place within it. Rather than offering abstract theory, these discussions focus on real-world impact, from cutting-edge algorithms to the human stories behind major breakthroughs. Tune in for a thoughtful, nuanced look at the tools and trends that are defining the future, all through the lens of experts who are building that future every day. Whether you're actively working in the field or simply curious about the forces driving technological change, this podcast provides a consistent source of insight and inspiration, demystifying the science that is quietly transforming every aspect of our lives.
Author: Language: English Episodes: 50

Super Data Science: ML & AI Podcast with Jon Krohn
Podcast Episodes
1026: OpenAI’s GPT-6 Astra [not-audio_url] [/not-audio_url]

Duration: 19:37
In Episode #1026, Jon Krohn breaks down GPT-6 Astra, OpenAI’s new flagship that its president has floated as a possible marker of AGI. Jon covers what the model is, what it costs, its state-of-the-art results across comp…
1024: In Case You Missed It in August 2026 [not-audio_url] [/not-audio_url]

Duration: 34:23
In ICYMI Episode #1024, Jon Krohn tracks the gap between AI investment and AI return, from the technology side to the people side. Hear from Pete Johnson, Jerry Yurchisin, Priyanka Vergadia and Tristan Handy, discussing…
1023: Agentic AI Skills That Matter Now, with Aishwarya Srinivasan [not-audio_url] [/not-audio_url]

Duration: 1:18:05
In Episode #1023, Aishwarya Srinivasan (Co-Founder of The Gen Academy) joins Jon Krohn to work out where a competitive moat comes from once anything you can build in ten minutes, somebody else can build in ten minutes to…