Jan Liphardt is the founder of OpenMind, where they're building an operating system for intelligent machines. He is an associate professor at Stanford and was previously an associate professor at UC Berkeley. He got his PhD from University of Cambridge.

Jan's favorite books: The Little Prince (Author: Antoine de Saint-Exupéry)

00:01 — Introduction
00:32 — Gap Between Movie Robots and Real-World Robotics
02:35 — Vision for a New Robotics OS
07:14 — Robotics OS Stack Breakdown
11:01 — Biggest Technical Challenges in Robotics
15:06 — Data Volume, Processing, and Cloud vs. Local
19:09 — Shared Intelligence Layer: What is Fabric?
23:15 — Filtering Good vs. Bad Ideas in a Robot Network
26:06 — Business Model for Robots and Machine Economy
29:55 — Standards and Interoperability in Robotics
33:14 — Most Exciting AI Advancements Today
35:00 — Rapid Fire Round 

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Where to find Jan Liphardt: 

LinkedIn: https://www.linkedin.com/in/jan-liphardt/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Anna Patterson is the cofounder of Ceramic, an AI infrastructure platform for large scale model training. They raised their seed round led by NEA along with amazing investors such as Lukas Biewald, Laszlo Bock, Sean Carey, Jeff Hammerbacher, Ankit Jain, Seval Oz, Joanna Rees, Gokul Rajaram, and Ram Sriram. She was previously the founder and managing partner at Gradient Ventures. She was the VP Engineering at Google for 14 years. 

Anna's favorite book: Books she reads with her daughters as part of their family book club

(00:01) Introduction & AI Infra 101
(01:11) Budget Breakdown: Training vs Inference
(02:16) Mapping the AI Infra Landscape
(04:18) Verticalized vs General-Purpose Infrastructure
(06:22) Why Ceramic Was Built From Scratch
(08:35) MVP Tradeoffs and Decision Framework
(10:16) Achieving 2.5x Speedup in Long Context Training
(11:50) Short vs Medium vs Long Context: A Primer
(13:38) Long Context vs RAG (Retrieval-Augmented Generation)
(15:24) Real-World Impact of Long Context Models
(16:38) Bottlenecks at 96K Token Contexts
(17:51) Data Pruning 101: What to Keep, What to Drop
(21:01) What Is “Good Data” in Subjective Domains?
(22:32) How to Grade Reasoning, Not Just Answers
(24:15) Synthetic Data: Use Cases & Limits
(26:19) Staying Current in Fast-Moving Domains
(27:30) Will Every Company Have Its Own Model?
(29:23) Unlocking the Next 10x in Infra
(31:27) Favorite Recent AI Advancements
(32:33) Rapid Fire Round

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Where to find Anna Patterson: 

LinkedIn: https://www.linkedin.com/in/anna-patterson-15921ba/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Tom Chavez is the cofounder of super{set}, a startup studio that founds, funds, and builds data and AI startups. Prior to this, he was the CEO and co-founder of Krux, a martech platform acquired by Salesforce in 2016. Before Krux, he was the CEO and co-founder of Rapt, a provider of software for media monetization acquired by Microsoft in 2008. He went to Harvard for undergrad and Stanford for his PhD.

Tom's favorite book: The Three Musketeers (Author: Alexandre Dumas)

(00:01) Origin Story and Starting Superset
(02:58) How Superset Evaluates Ideas and Risk
(06:24) What Is a Venture Studio and How Superset Works
(10:49) Underfunded Layers in AI Infrastructure
(14:55) Orchestration Opportunities in LLM Workflows
(15:49) The Future of Data Infra and ETL in the AI Era
(20:46) Code Infra: Code Quality and AI-Generated Software
(24:55) Model Infra, MLOps, and Why It’s Underwhelming
(27:22) Cloud Economics and Gross Margins in AI Companies
(32:15) Early Team Structure in AI Infra Startups
(34:49) Full Stack vs Composable Infra in AI
(37:52) Fragmentation vs Consolidation in AI Tooling
(41:02) Where Moats Will Accumulate: Data In, AI, Data Out
(45:10) Biggest Challenge in Building Superset
(46:23) Rapid Fire Round

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Where to find Tom Chavez: 

LinkedIn: https://www.linkedin.com/in/tommychavez/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Rowan Stone is the CEO of Sapien, a decentralized data foundry where AI models can access verified human expertise worldwide. They've raised raised a $10.5M round led by Variant. He's also the co-creator of Coinbase's layer 2 network called Base.

Rowan's favorite book: Outlive (Author: Peter Attia)

(00:01) Introduction
(01:09) The Flaws in Centralized Data Models
(04:10) Mechanism of Knowledge Transfer and Expert Incentives
(07:08) Supply, Demand, and Market Dynamics for Training Data
(10:22) Chain of Thought Reasoning and 3D/4D Data Use Cases
(12:22) Building the MVP: What Worked and What Didn’t
(15:17) Acquiring the First Five Customers
(17:59) What They Got Right and What They’d Change
(20:15) How to Scale from Early Customers: Advice to Founders
(22:02) Data Infrastructure Opportunities in 2025
(25:57) Designing AI-Native Databases
(28:04) Biggest Startup Challenge: Messaging and Clarity
(30:22) Future of Data Collection Mechanisms (2 to 5 Years Out)
(32:07) Autonomous Vehicles and Demand for 4D Data
(35:33) Emerging AI Use Cases: Memory, Wearables, and Robotics
(36:19) Rapid Fire Round

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Where to find Rowan Stone: 

LinkedIn: https://www.linkedin.com/in/rowan-stone/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Rish Gupta is the cofounder and CEO of Spot AI, a video AI platform for the physical world. They've raised $93M from amazing investors such as Scale, Bessemer, and Qualcomm Ventures.

Rish's favorite book: Atlas Shrugged (Author: Ayn Rand)

(00:01) Introduction
(00:32) Video-AI basics: ingesting camera feeds across diverse networks ​
(02:42) Edge-vs-cloud trade-offs for compute, storage, and bandwidth ​
(05:40) Mapping the sector: hardware waves to cloud cameras to pure-software layer ​
(07:43) Founding insight: why Spot AI attacked the video layer now ​
(11:35) Bare-bones MVP: two-page dashboard that unified camera access ​
(15:34) First-10-customer lessons & pruning the ideal customer profile (ICP) ​
(18:54) Go-to-market experiments: ICP variants, pain points, and channels ​
(23:00) Early-team blueprint: engineering-heavy, founders run sales ​
(24:03) Hardware stance: free IP cameras to simplify one-vendor buying ​
(26:01) Biggest tech hurdle: supporting thousands of camera brands & configs ​
(27:00) Sales challenge: outbound fatigue forces novel GTM motions ​
(28:55) Future vision: each camera becomes an autonomous AI agent with a "job" ​
(30:25) Key AI unlock: massive context windows enabling flow-state reasoning ​
(32:14) Rapid-fire round

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Where to find Rish Gupta: 

LinkedIn: https://www.linkedin.com/in/profilerish/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Alex Levin is the cofounder and CEO of Regal, a platform for AI phone agents. They've raised $82M from amazing investors such as Emergence Capital.

Alex's favorite book: The PayPal Wars (Author: Eric M. Jackson)

(00:01) Introduction
(02:37) Evolution of customer contact tools and legacy players
(06:02) Launching Regal: Origin story and early challenges
(08:41) MVP strategy and problems worth solving
(11:46) Lessons from 0 to 10 customers: Growth mistakes and hiring
(16:13) Ideal early-stage team construction and hiring philosophy
(19:06) Sequencing hires as company scales
(20:58) What makes a good investor and how to leverage them
(25:42) Best and worst experiments while building Regal
(29:04) Internal use of AI at Regal across teams
(31:49) The future of AI phone agents and near-term blockers
(34:13) Rapid Fire Round

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Where to find Alex Levin: 

LinkedIn: https://www.linkedin.com/in/alexlevin1/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Colin Zima is the cofounder and CEO of Omni, a data platform that combines the consistency of a shared data model with the speed and freedom of SQL. They recently raised their $69M Series B led by ICONIQ Growth. He was previously the Chief Analytics Officer at Looker.

Colin's favorite book: Blink (Author: Malcolm Gladwell)

(00:01) Introduction
(01:10) What Is a Data Model and Why It Matters
(03:27) Gaps in the Modern Data Stack
(05:38) The Staying Power of SQL
(07:29) Origin Story: Why Omni Was Created
(10:13) Lessons from Building the MVP
(12:48) Go-to-Market Insights: Zero to Ten Customers
(16:02) Founder-Led Sales and Marketing Tactics
(18:58) Company Building: Recruiting and Product Challenges
(21:34) Product Positioning in a Crowded Market
(23:26) Design Philosophy in Enterprise Software
(28:21) Omni's Tech Stack and Development Strategy
(28:57) Real-World Use of AI Inside the Company
(31:01) Future of Data Tooling and Role of AI
(33:49) Rapid Fire Round

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Where to find Colin Zima: 

LinkedIn: https://www.linkedin.com/in/colinzima/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite
X: https://x.com/prateekvjoshi 

Alvaro Morales is the cofounder and CEO of Orb, a usage-based billing product for modern software companies. They've raised $44M to date from amazing investors such as Mayfield, Menlo Ventures, and Greylock. 

Alvaro's favorite book: Conversation in the Cathedral (Author: Mario Vargas Llosa)

(00:01) Introduction 
(00:35) What is Usage-Based Billing?
(02:27) Challenges in Metering Usage
(04:14) Examples of Consumption-Based Products
(05:49) Tools for Usage Metering and Billing
(09:08) Founding Story and Validation of Orb
(12:11) Building the MVP for a Billing System
(14:48) Acquiring the First 10 Customers
(18:33) Scaling Sales & Marketing After Initial Traction
(21:09) Building the Team & Ideal Candidate Profile
(23:26) Technology Stack Behind Orb
(25:55) Real-Time Analytics vs Streaming for Billing
(27:18) Other Key Components of Orb's Solution
(28:38) Why Incumbents Haven’t Solved This Problem
(31:09) How Orb Uses AI Internally
(32:53) Most Exciting AI Advancements for the Future
(34:30) Rapid Fire Round

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Where to find Alvaro Morales: 

LinkedIn: https://www.linkedin.com/in/alvaro-morales/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite 
X: https://x.com/prateekvjoshi 

Jay Madheswaran is the cofounder and CEO of Eve, a legal AI platform for plaintiff law firms. They recently raised their $47M Series A from Andreessen Horowitz, Lightspeed, and Menlo Ventures. He was previously a partner at Lightspeed and the first engineer at Rubrik.

Jay's favorite book: The Truth Detector (Author: Jack Schafer)

(00:01) Introduction
(00:44) Overview of Legal AI and Industry Impact
(03:53) Daily Operations in Plaintiff Law Firms
(05:49) Identifying and Launching Eve's MVP
(08:58) Framework for Building an Effective MVP
(12:02) Acquiring Early Customers (Zero to Ten)
(14:20) Scaling Beyond Early Customers: Growth Strategies
(16:08) Encouraging Word-of-Mouth and Inbound Growth
(18:21) Product Development and Customer Feedback Loops
(20:27) Eve's Technology Stack and Internal AI Usage
(22:16) Team Structure and Leadership Development
(24:20) Role and Impact of Designers in Early Startups
(27:15) Future Trends in Legal AI: Consolidation vs. Specialization
(30:29) Exciting AI Advancements Relevant to Eve
(31:58) Rapid Fire Questions

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Where to find Jay Madheswaran: 

LinkedIn: https://www.linkedin.com/in/jayanth1/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi 

Anant Bhardwaj is the founder and CEO of Instabase, an AI-native unstructured data platform. They've raised $322M in funding to date from NEA, Andreessen Horowitz, Greylock, and Index Ventures. He did his masters from Stanford and PhD from MIT. 

Anant's favorite book: The Singularity Is Near (Author: Ray Kurzweil)

(00:07) Defining Unstructured Data
(01:18) The Growth of Unstructured Data and Its Challenges
(02:05) Evolution of Tools for Analyzing Unstructured Data
(04:25) How Large Language Models (LLMs) Changed Data Processing
(05:27) Do We Still Need ETL in the LLM Era?
(06:05) Structured Queries vs. Direct Unstructured Querying
(08:22) Applying LLMs in Enterprise Settings
(09:34) Ensuring Accuracy in AI-Driven Data Analysis
(11:29) SQL vs. AI-Driven Queries in Business Use Cases
(13:48) Retrieval-Augmented Generation (RAG) for Enterprise AI
(15:02) The Founding of Instabase and Its Early Vision
(19:03) Building the MVP of Instabase
(22:52) First 10 Customers: Lessons from Early Sales
(26:01) Scaling Customer Acquisition: Experiments and Failures
(30:35) When to Hire a Sales Team: Key Lessons
(33:52) AI Adoption at Instabase for Internal Productivity
(37:48) The Technology Stack Behind Instabase
(42:36) Transition from OS-Based Architecture to LLM-Based System
(43:45) Rapid Fire Questions

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Where to find Anant Bhardwaj: 

LinkedIn: https://www.linkedin.com/in/anantpb/

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Where to find Prateek Joshi: 

Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 
X: https://x.com/prateekvjoshi