Welcome back to The Hedgineer Podcast, where host Michael Watson dives into the world of AI, data, and technology within asset management, hedge funds, and financial services. In this episode, Michael sits down with Jonathan Regenstein, who leads AI within Financial Services at Snowflake.

This conversation explores the critical role of data and platform strategy in the successful enterprise deployment of AI, moving beyond purely technical wins to focus on commercial outcomes. Jonathan and Michael dissect the evolution of Snowflake from a powerful SQL engine to a unified platform for AI, and debate where the intelligence layer should reside for maximum effectiveness.

• The Power of Data Sharing: How Snowflake's seamless data sharing and Marketplace revolutionized the consumption of alternative data on the buy side, drastically simplifying security and licensing workflows.
• The AI Layer Debate: A deep dive into whether the AI runtime should live natively within the data platform (Snowflake) using tools like Cortex and Intelligence, or be orchestrated externally by hyperscalers or model providers.
• Beyond the Technical Win: The shift from technology-driven AI Proofs-of-Concept (POCs) to projects scoped by commercial outcomes—revenue generation or cost reduction.
• Evaluations are the Product: The crucial importance of robust evaluation frameworks (like those provided by TruEra/TruLens) for agentic workflows to avoid "chaos at scale," and how to involve business leaders—not just engineers—in defining what success looks like.
• The Semantic Layer's Role: The concept of the semantic model as a first-class citizen in Snowflake, acting as the translator between business language and data, driving accuracy in Text-to-SQL (Cortex Analyst), and building trust with non-technical users.
• The Future of BI: How AI is driving the complete rethinking of the Business Intelligence (BI) stack, moving beyond static dashboards to dynamic, generative BI that surfaces insights and visualizations on demand.

Jonathan Regenstein is a key leader in the AI for Financial Services division at Snowflake, driving the platform's strategy in machine learning and artificial intelligence for banks, asset managers, and insurance companies.

Follow The Hedgineer Podcast:

YouTube: (https://www.youtube.com/@hedgineer)

LinkedIn: (https://www.linkedin.com/company/90976838)

Twitter: (https://x.com/hedgineering)

Instagram: (https://www.instagram.com/hedgineer/)

Don't forget to like, subscribe, and hit the notification bell to stay updated on our latest episodes!

Hedgineer.io

Hosted on Acast. See acast.com/privacy for more information.

Welcome back to The Hedgineer Podcast. In this episode, host Michael Watson sits down with crowd-favorite returning guest, Lucas Rooney.

Lucas pulls back the curtain on the "0 to 1" journey of building a new fund, from diligencing the initial idea and recruiting top-tier talent to making the critical "build vs. buy" decisions for a foundational technology stack.

But how does launching a fund today differ from just a few years ago? One answer is AI.

Michael and Lucas dive deep into how the proliferation of AI reframes the entire approach to building systems, forcing a new focus on taxonomy, data labeling, and codifying the "thought process" of an investment from day one.

The conversation shifts to one of the most critical questions facing the industry: How do incentive structures change when an individual's knowledge and intellectual property (IP) can be instantly captured and instilled into the organization's systems?. They explore how firms must re-evaluate compensation and talent, as value shifts from executing perfunctory tasks to the high-level synthesis and compounding of IP.

• The "0 to 1" process of launching a new fund.
• Key strategies for recruiting passionate technologists and investors.
• The foundational tech stack: Designing the data/ETL, analytical, trading, and risk layers from scratch.
• How AI forces better data hygiene and process documentation.
• The "IP Capture" Problem: Rethinking talent compensation when AI can learn and retain an employee's knowledge permanently.
• Why hiring is shifting from "task execution" to "IP synthesis" and "compounding".
• The "Negative Space": Why capturing the bad ideas and hypotheses you didn't run is the next frontier for evaluating skill.

Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.

Follow The Hedgineer Podcast:

• YouTube: (https://www.youtube.com/@hedgineer)
• LinkedIn: (https://www.linkedin.com/company/90976838)
• Twitter: (https://x.com/hedgineering)
• Instagram: (https://www.instagram.com/hedgineer/)

Don't forget to like, subscribe, and hit the notification bell to stay updated on our latest episodes!

Hedgineer.io

Hosted on Acast. See acast.com/privacy for more information.

Beyond the AI Hype with Jason Strimpel

In this episode of The Hedgineer Podcast, host Michael Watson sits down with Jason Strimpel, founder of PyQuant News, long-time Pythonista, and AI enthusiast.

They dive deep into the practical and philosophical implications of artificial intelligence in both asset management and daily life. They break down how the agentic loop works with the Anthropic Agent SDK, the components of good evaluation frameworks, and even how to talk to your kids about AI

Key topics covered in this episode:

• Drugs, Sex, and AI: Jason shares his thoughts for new parents: the three things you now need to talk to your kids about are drugs, sex, and AI. Michael and Jason then discuss the difficulty of explaining the difference between humans and AI-powered avatars or toys to children.

• The "Agentic Loop": The discussion breaks down the simplicity and power of the agentic loop, identifying it as the "core substrate" of modern agentic frameworks. This framework allows a language model to loop, use tools, and determine when to exit to solve complex problems.

• "Evals are the Product": Michael and Jason iterate on the concept that a robust set of evaluations is the real product. If you can use evals to demonstrate that an agent has harnessed intelligence to solve a specific problem space, you "own that problem".

• AI vs. Python's Rise: They draw parallels between the current AI boom and the rise of Python in the early 2010s. Both technologies were initially met with skepticism for being "black box" interpreted systems, yet they unlocked massive productivity boosts.

• Capital Allocation and Moats: The conversation tackles the modern challenge of allocating capital and defending a "software moat" when new AI tools and infrastructure are being commoditized by hyperscalers at an incredible speed.

• The PyQuant News Story: Jason shares the origin story of his popular PyQuant newsletter, which started as a personal WordPress site for bookmarking research papers and grew into a major resource for the quantitative finance community.

Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.

Follow The Hedgineer Podcast:

YouTube: (https://www.youtube.com/@hedgineer)

LinkedIn: (https://www.linkedin.com/company/90976838)

Twitter: (https://x.com/hedgineering)

Instagram: (https://www.instagram.com/hedgineer/)

Don't forget to like, subscribe, and hit the notification bell to stay updated on our latest episodes!

Hedgineer.io

Hosted on Acast. See acast.com/privacy for more information.