Episode 128: Building Trust with Founders, VC Funding For The Cloud, and The Next Platform For Data Apps with Jason Risch

Timestamps(01:45) Jason shared the formative experiences of his upbringing in the Bay Area and coming of age in the “Moneyball” era of baseball.(05:03) Jason described his overall academic experience at Stanford - where he studied Mathematical and Computational Science with a minor in Classical Studies.(09:15) Jason reflected on his experience participating in the Mayfield Fellowship at Stanford.(12:03) Jason recalled his time being a part of the business operations team during a high-growth period at Opendoor.(14:25) Jason talked about lessons learned working as a management consultant at McKinsey’s Bay Area practice.(15:59) Jason reminisced about his time at the AI Fund startup studio - where he launched AI-enabled SaaS startups by iterating on prototypes, signing design partners, and recruiting the founding team.(19:25) Jason explained his decision to join the investment team at Greylock Partners.(22:24) Jason walked through his journey proving value as a new investor.(24:41) Jason unpacked his checklist for evaluating early-stage enterprise investment opportunities.(27:09) Jason explained his seed investment in Onehouse - a cloud-native managed lakehouse service that makes data lakes easier, faster, and cheaper.(30:31 ) Jason explained his Series A investment in Baseten - which builds a powerful software toolkit that empowers technical data science teams to serve, integrate, design, and ship their custom ML models efficiently.(33:23) Jason touched on advice for his portfolio companies in hiring decisions and navigating product/GTM strategy.(37:00) Jason unpacked key takeaways from Greylock’s Castles in the Cloud project.(39:58) Jason dissected key trends in the markets of security, AI/ML, management and governance, and edge computing (as shown in "VC Funding for the Cloud").(46:24) Jason elaborated on his vision of "The Next Cloud Data Platform" - which examines how the data warehouse, lakehouse, and semantic layer could combine to create a platform for data applications.(50:55) Jason shared a few books that have greatly influenced his life.(52:22) Closing segment.Jason's Contact InfoLinkedInTwitterGreylockMentioned ContentBooks"Moneyball" (by Michael Lewis)"Why The West Rules For Now" (by Ian Morris)"Snow Crash" (by Neil Stephenson)"Cryptonomicon" (by Neil Stephenson)"Termination Shock" (by Neil Stephenson)"Principles for Dealing with the Changing World Order" (by Ray Dalio)PeopleDavid Luan (Founder and CEO of Adept)Alex Ratner (Co-Founder and CEO of Snorkel AI)Frank Slootman (CEO of Snowflake)Clement Delangue (Co-Founder and CEO of HuggingFace)Notes

My conversation with Jason was recorded back in late 2022. Since then, I recommend checking out these resources:

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.