Infinite Curiosity Pod with Prateek Joshi

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--------Where to find Tom Chavez: LinkedIn: https://www.linkedin.com/in/tommychavez/--------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--------Where to find Rowan Stone: LinkedIn: https://www.linkedin.com/in/rowan-stone/--------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--------Where to find Rish Gupta: LinkedIn: https://www.linkedin.com/in/profilerish/--------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--------Where to find Alex Levin: LinkedIn: https://www.linkedin.com/in/alexlevin1/--------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, cofounder and CEO of Omni, shares insights from his journey in data platforms. He discusses the significance of data models for consistent decision-making and the irreplaceable role of SQL in business intelligence. Colin explores the challenges of building a Minimum Viable Product and shares go-to-market strategies that drove early success. He delves into the future of AI in data tooling, highlighting how it's transforming efficiency and decision-making in business processes. A fascinating conversation filled with practical wisdom!

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--------Where to find Alvaro Morales: LinkedIn: https://www.linkedin.com/in/alvaro-morales/--------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--------Where to find Jay Madheswaran: LinkedIn: https://www.linkedin.com/in/jayanth1/--------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--------Where to find Anant Bhardwaj: LinkedIn: https://www.linkedin.com/in/anantpb/--------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 

Malte Kosub is the cofounder and CEO of Parloa, an AI agent platform for customer service. They raised their $66M Series B led by Altimeter.Malte's favorite book: The Qualified Sales Leader (Author: John McMahon)(00:01) Introduction(00:26) Overview of AI in Customer Support(01:33) The Current Landscape of AI Agents(02:46) Enterprise Adoption of AI Agents(04:16) The Founding Story of Parloa(06:25) Deciding What Goes into V1 of a Product(07:56) Achieving 99.9999% Accuracy in AI Agents(09:29) How to Identify Customer Needs for AI Products(10:55) Scaling from Early Customers to the Next 10(12:41) Growth Experiments: What Worked and What Didn’t(14:42) Current State of Parloa: Capabilities and Scale(16:36) Structuring Teams for AI-First Companies(18:49) Technology Stack and Internal AI Use Cases(21:29) How to Pitch an AI Product to Enterprises(23:32) Essential Tools Used Inside the Company(25:41) AI’s Role in Daily Life and Workflows(27:54) The Future of AI Agents in Customer Support(28:37) Can AI Agents Fully Replace Human Agents?(29:05) Exciting AI Advancements Impacting Parloa(30:06) Rapid Fire Round--------Where to find Malte Kosub: LinkedIn: https://www.linkedin.com/in/maltekosub/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-infiniteX: https://x.com/prateekvjoshi 

Scott Stevenson is the cofounder and CEO of Spellbook. They launched the first generative AI copilot for lawyers. It's used by more than 3,000 law firms and are growing really fast. They most recently raised $20M Series A from investors such as Inovia, Bling, and Moxxie. Scott's favorite book: Zero to One (Author: Peter Thiel)(00:01) Introduction(00:06) The basics of legal AI and its applications(02:57) How lawyers use AI for contract review and drafting(03:22) Inspiration from GitHub Copilot and AI’s role in legal work(04:19) AI in litigation vs. transactional legal work(06:37) Why AI adoption in legal work accelerated(07:07) The launch story of Spellbook(07:45) Finding the right problem to solve in legal tech(10:11) How GitHub Copilot influenced Spellbook’s early direction(11:42) Spellbook’s first prototype and early traction(13:11) The moment Spellbook realized it had product-market fit(14:31) Measuring actual product usage and customer adoption(15:27) Early learnings from new customers(17:59) Growth experiments: what worked and what failed(20:48) Discovering unexpected customer segments(22:50) Company building philosophy and structuring Spellbook(26:18) Avoiding over-optimization for structure in startups(30:21) How to decide what to ship in a startup(32:21) Pattern-matching vs. narrative reasoning in product development(35:39) Lessons from AI contract review and LLM usage(36:14) Rapid-fire round