Super Data Science: ML & AI Podcast with Jon Krohn

Jon Krohn
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71 snips
Jan 30, 2026 • 12min

962: Wharton Prof Ethan Mollick on Why Your AI Strategy Is Already Obsolete

Ethan Mollick, Wharton associate professor who co-directs the Generative AI Lab and wrote Co-Intelligence, explores how AI shifts collaboration and management. He discusses AI acting like teammates, why firms should run internal experiments instead of relying on consultants, frameworks for adoption (leadership, lab, crowd), and using frontier models now to learn and capture hidden productivity gains.
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22 snips
Jan 27, 2026 • 1h 9min

961: Distributed Artificial Superintelligence, with Dr. Vijoy Pandey

Dr. Vijoy Pandey, head of Cisco’s OutShift and researcher-executive focused on multi-agent systems, discusses building distributed artificial superintelligence. He covers multi-agent collaboration instead of isolated AIs. He explains semantic protocols for shared intent, a cognitive memory fabric for persistent knowledge, and how agent societies could accelerate drug discovery, climate action, and innovation.
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13 snips
Jan 23, 2026 • 41min

960: In Case You Missed It in December 2025

Penelope LaFeuille, a data scientist dedicated to fitness and health, shares her journey from burnout to balanced living through structured routines. Jeff Lee, a senior data scientist from Netflix, provides tips on securing top tech roles, including the 'briefcase technique.' Stanford's Sandy Pentland emphasizes the importance of designing AI systems that account for human behavior to avoid pitfalls. Lastly, Josh Clemm warns against 'work slop' in AI adoption, advocating for clear goals and effective retrieval strategies for better results.
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95 snips
Jan 20, 2026 • 1h 5min

959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir)

Sinan Ozdemir, an AI entrepreneur and bestselling author of Building Agentic AI, dives into the nuances of agentic AI versus traditional workflows. He discusses how to evaluate AI models effectively beyond just accuracy and shares insights on the right types of models for specific tasks. Sinan also highlights the importance of context windows in agent systems, the trade-offs between precision and recall, and the implications of hybrid workflows. Expect surprising findings on reasoning mechanics and practical guidance for deploying agentic AI.
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32 snips
Jan 16, 2026 • 24min

958: Without Trusted Context, Agents are Stupid (featuring Salesforce’s Rahul Auradkar)

In this engaging discussion, Rahul Auradkar, EVP at Salesforce, dives into the importance of unified data engines, particularly following the company’s acquisition of Informatica. He explains how Data 360 facilitates actionable insights, while contrasting the concepts of context versus data in AI models. Discover how Tableau enhances analytics and why trusted context is critical for intelligent agent behavior. Rahul also shares insights on upskilling teams with no-code tools and envisions the future of agent-driven workflows by 2026.
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62 snips
Jan 13, 2026 • 60min

957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva

Ashwin Rajeeva, cofounder and CTO of Acceldata, dives into the world of AI agents in data management. He explains how Acceldata raised over $100 million to automate data quality and streamline operations using autonomous pipelines that repair errors without human help. Ashwin emphasizes the importance of having humans in the AI loop for validation. He also discusses solving data sprawl, his leadership philosophy, and techniques for retaining tech talent. Get insights into effective engineering practices and the balance between innovation and enterprise needs.
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33 snips
Jan 9, 2026 • 26min

956: From Agent Demo to Enterprise Product (with Ease!) feat. Salesforce’s Tyler Carlson

Tyler Carlson, SVP and Head of Product at Salesforce, dives into transforming AI agents from demo to enterprise-ready with the AgentForce 360 Platform. He discusses the ease of building customer-focused applications using low- and pro-code tools like Salesforce's WYSIWYG schema builder. Tyler highlights the common pitfalls innovators face, emphasizing a user-centric approach when commercializing AI solutions. He also explores whether AI agents could outpace traditional applications, suggesting a future where they complement rather than replace existing systems.
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85 snips
Jan 6, 2026 • 1h 9min

955: Nested Learning, Spatial Intelligence and the AI Trends of 2026, with Sadie St. Lawrence

Sadie St. Lawrence, an AI futurist and founder of the Human Machine Collaboration Institute, joins to discuss the AI landscape. They recap predictions for 2025, revealing agentic AI's growth and its impact on everyday devices. Sadie shares five exciting forecasts for 2026, highlighting specialized models, continual learning, a return to fundamental research, spatial intelligence in robotics, and the emergence of AI operations roles. Their engaging banter adds humor as they award the year's standout moments in AI.
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21 snips
Jan 2, 2026 • 4min

954: Recap of 2025 and Wishing You a Wonderful 2026

Jon Krohn reflects on the dual nature of agentic AI in 2025, both celebrated and critiqued. He emphasizes the need for robust data preparation and security as machine autonomy rises. Listeners get a sneak peek of upcoming trends and discussions, including awards for notable moments from the past year. Jon shares heartfelt gratitude for his audience, reminisces about memorable guests, and hints at exciting plans for future milestones, all while wishing everyone a brighter 2026.
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58 snips
Dec 30, 2025 • 51min

953: Beyond “Agent Washing”: AI Systems That Actually Deliver ROI, with Dell’s Global CTO John Roese

John Roese, Global CTO and Chief AI Officer at Dell Technologies, dives into the crucial concept of 'agent-washing' and what true autonomy means for AI. He shares insights on achieving impressive ROI, revealing Dell's success in driving revenue growth significantly. John outlines his forward-thinking predictions for AI by 2026, including the importance of knowledge layers and AI factories, essential for data management and security. His emphasis on governance and disciplined AI use cases highlights a strategic roadmap for the future of technology.

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