Minus One

Dmitri Dolgov, co-CEO of Waymo, joins South Park Commons Partners Aditya Agarwal and Ruchi Sanghvi to discuss the 17-year journey from early self-driving experiments to putting fully autonomous cars on public roads. They talk about how Waymo built its self-driving system, why simulation and evaluation became so critical, and what it takes to move from something that works in a demo to a product that can operate safely and reliably at scale. Dmitri also explains why Waymo’s real advantage goes far beyond the model itself, and what it takes to keep improving a system where the margin for error is incredibly small. Dmitri Dolgov: linkedin.com/in/dmitri-dolgov Aditya Agarwal: https://www.linkedin.com/in/adityaagarwal3/ Ruchi Sanghvi: https://www.linkedin.com/in/rsanghvi/ South Park Commons: https://www.linkedin.com/company/southparkcommons/ Apply to SPC: https://www.southparkcommons.com/apply Chapters: (00:00:32) - The First Time Waymo Felt Real (00:03:39) - How a Fleet of Waymos Coordinates (00:07:47) - How People Change the Way They Travel With Waymo (00:12:51) - How Waymo Started: Understanding the Problem Before Building a Product (00:14:58) - Inside Waymo’s AI System: Driver, Simulator, and Critic (00:22:00) - How Waymo Adopts New AI Breakthroughs Without Breaking the Product (00:27:02) - Why the Last 1% of Autonomous Driving Is So Hard (00:25:16) - Where Startups Should Build in Physical AI (00:44:30) - Can the Waymo Driver Become a General Physical AI Agent?

Helmy Eltoukhy, CEO of Guardant Health, joins South Park Commons Partner Mark Jacobstein to discuss his journey from electrical engineering to building one of the leading companies in cancer diagnostics. They talk about Guardant’s path from liquid biopsy to early cancer detection, the difficult realities of building a diagnostics company, and why business model innovation can matter just as much as technical breakthroughs. Helmy also explains how AI is helping Guardant make better use of its growing dataset and why he believes the same blood test infrastructure could eventually be used to detect hundreds or even thousands of diseases. Helmy Eltoukhy: https://www.linkedin.com/in/helmy-eltoukhy-b011855/ Mark Jacobstein: https://www.linkedin.com/in/markjacobstein South Park Commons: https://www.linkedin.com/company/southparkcommons/ Apply to SPC: https://www.southparkcommons.com/apply Chapters: (00:00:43) - From Electrical Engineering to Biology and Entrepreneurship (00:08:10) - From Building Sequencing Technology to Solving Healthcare Problems (00:12:51) - Guardant Health's Long-Term Bet on Early Cancer Detection (00:15:31) - Early Mistakes, Pivots, and Difficult Business Decisions (00:18:15) - Why Building a Diagnostics Company Is So Difficult (00:21:15) - Why Business Model Innovation Matters as Much as Technology (00:26:15) - How AI Is Unlocking Guardant's Massive Cancer Dataset (00:30:05) - From Early Cancer Detection to the “Everything Test”

How close are we to AGI, and what happens when AI systems stop behaving the way we expect? Srinivas Narayanan, former CTO of B2B Engineering at OpenAI and former VP of Engineering at Facebook, joins South Park Commons Partner Prateek Mehta for a wide-ranging conversation on his Minus One to Zero journey, enterprise AI adoption, and AI safety. They discuss the career choices that took him from two startups to Facebook and OpenAI, why a beginner’s mindset has mattered along the way, what is slowing AI adoption inside large companies, and how builders should think about reward hacking, alignment, and increasingly autonomous AI systems. Srinivas Narayanan: https://www.linkedin.com/in/srinivasnarayanan/ Prateek Mehta: https://www.linkedin.com/in/prateek-mehta-a571972/ South Park Commons: https://www.linkedin.com/company/southparkcommons/ Apply to SPC: https://www.southparkcommons.com/apply Chapters: (00:01:26) - How Close Are We to AGI? (00:02:26) - From IIT Madras to AI and OpenAI (00:07:32) - How to Find Problems Worth Spending a Decade On (00:12:38) - Building OpenAI Without a Playbook (00:15:24) - How OpenAI Built a High-Talent, High-Agency Team (00:18:12) - What’s Holding Back Enterprise AI Adoption (00:29:12) - The Future of AI Beyond the Digital World (00:36:42) - The Real Risks of AI and How to Think About Safety

What does it take to build something that lasts? Snowflake CEO and former Google SVP of Ads Sridhar Ramaswamy joins South Park Commons General Partner Aditya Agarwal to share his answer. Ramaswamy traces his journey from Google to founding Neeva, an ad-free search startup that shut down before the generative AI boom, to leading Snowflake through the AI era. He shares what defines great founders, what doomed Neeva, and why most software will lose its moat. Ramaswamy and Agarwal also explore the future of AI, what remains valuable in an age of AI-generated software, and the search belief Ramaswamy got wrong. Sridhar Ramaswamy: https://www.linkedin.com/in/sridhar-ramaswamy/ Aditya Agarwal: https://www.linkedin.com/in/adityaagarwal3/ South Park Commons: https://www.linkedin.com/company/southparkcommons/ Apply to SPC: https://www.southparkcommons.com/apply (00:00:52) - Choosing When to Take a Career Risk (00:05:01) - Lessons From Google’s Founders (00:09:52) - What Went Wrong at Neeva (00:13:39) - The Future of AI Models (00:22:59) - Snowflake’s Enduring Value in the AI Era (00:29:24) - How to Keep Up With AI (00:32:24) - Rapid Fire: Books, Search & Google

Why did OpenAI’s model hack into Hugging Face? Tom McGrath, co-founder and Chief Scientist at Goodfire, joins South Park Commons Partner Jonathan Brebner to explore one of AI’s biggest challenges: interpretability. Using OpenAI’s recent reward hacking incident as a starting point, they discuss why today’s most advanced models are still difficult to understand and why gaining visibility into how they work could be essential for building safer, more reliable AI systems. Tom shares how interpretability could change the way researchers develop models and how Goodfire is creating tools to help understand and steer frontier AI. Tom McGrath: https://www.linkedin.com/in/tom-mcgrath-7337bb151/ Jonathan Brebner: https://www.linkedin.com/in/jonathan-brebner/ South Park Commons: https://www.linkedin.com/company/southparkcommons/ Apply to SPC: https://www.southparkcommons.com/apply (00:00:30) - Why AI Interpretability Matters Now (00:02:15) - When AI Reward Hacking Becomes Real (00:05:07) - The Core Problem of Interpretability (00:07:23) - Intentional Design: Steering What Models Learn (00:12:43) - Neural Geometry: The Shapes Inside AI Models (00:22:29) - Turning Interpretability Research Into a Product (00:25:28) - How Research Changes Inside a Startup (00:32:48) - Science Fiction, AI Risk, and the Future