Scaling Regulated Data Workflows Without Lock‑In - with Juan Orlandini of Insight
Legacy financial systems often trap organizations in "data swamps" where AI is mistakenly treated as a magic fix for fundamentally broken manual architectures. In this episode, Juan Orlandini, CTO of North America at Insight, outlines why senior executives must distinguish between statistical AI outputs and the mathematical precision required for financial compliance to avoid significant reporting risks. The conversation provides a roadmap for building a scalable operating layer by prioritizing data engineering and leveraging established vendor knowledge to protect long-term investment. This episode is sponsored by K1x. Learn how brands work with Emerj and other Emerj Media options at https://go.emerj.com/partner

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Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

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LIVE: Conan O’Brien speaks at Harvard graduation ceremony (full)

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MIT Economist on Finance, AI, and Human Behavior

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The Architecture Shift Behind Reliable Enterprise AI - with Ravi Marwaha of Arango

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The Insane Genius of a Formula 1 Gearbox

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Felix Oberholzer-Gee on the Frameworks of Business Strategy

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How I Use Aspirin to Unclog Arteries

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The 7 Skills You Need to Build AI Agents

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7 AI Terms You Need to Know: Agents, RAG, ASI & More

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Leading in the Age of AI: A Conversation with NVIDIA CEO Jensen Huang | Global Conference 2026

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Info Session on Mentor-Led Data Science Internship Program

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Why the Way AI Feels Is as Important as How It Works - with Carsten Wierwille of HTEC

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If You Have A Bad Memory, I’ll Help You Fix It In 28 Minutes

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V.G. Narayanan on How Accounting Connects the Business World

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The Leadership Principles Explained by Amazon CEO Andy Jassy | Full Length Video

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The Pricing Shift Reshaping Enterprise AI Spend - with Adam Mansfield of UpperEdge

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Agentic Commerce: What Will & Won’t Be | Michael Komasinski at Web Summit 2025

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Designing Data-Intensive Applications: Chapters 1 and 2

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Skill Issue: Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI

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