Agentic commerce is no longer science fiction — it’s arriving in your browser, your development IDE, and soon, your bank statement. In this episode of The MAD Podcast, Matt Turck sits down with Emily Glassberg Sands, Stripe’s Head of Information, to explore how autonomous “buying bots” and the Model Context Protocol (MCP) are reshaping the very mechanics of online transactions. Emily explains why intent, not clicks, will become the primary interface for shopping and how Stripe’s rails are adapting for tokens, one-time virtual cards, and real-time risk scoring that can tell good bots from bad ones in milliseconds.
We also go deep into Stripe's strategic AI choices. Drawing on $1.4 trillion in annual payment flow—1.3 percent of global GDP—Stripe decided to train its own payments foundation model, turning tens of billions of historical charges into embeddings that boost fraud-catch recall from 59 percent to 97 percent. Emily walks us through the tech: why they chose a BERT encoder over GPT-style decoders, how three MLEs in a “research bubble” birthed the model, and what it takes to run it in production with five-nines reliability and tight latency budgets.
We zoom out to Stripe’s unique vantage point on the broader AI economy. Their data shows the top AI startups hitting $30 million in ARR three times faster than the fastest SaaS companies did a decade ago, with more than half of that revenue already coming from overseas markets. Emily unpacks the new billing playbook—usage-based pricing today, outcome-based pricing tomorrow—and explains why tiny teams of 20–30 people can now build global, vertically focused AI businesses almost overnight.
Stripe
Website - https://stripe.com
X/Twitter - https://x.com/stripe?
Emily Glassberg Sands
LinkedIn - https://www.linkedin.com/in/egsands
X/Twitter - https://x.com/emilygsands
FIRSTMARK
Website - https://firstmark.com
X/Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
X/Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:45) How Big Is Stripe? Latest Stats Revealed
(04:06) What Does “Head of Information” at Stripe Actually Do?
(05:43) From Harvard to Stripe: Emily’s Unusual Journey
(08:54) Why Stripe Built Its Own Foundation Model
(13:19) Cracking the Code: How Stripe Handles Complex Payment Data
(16:25) Foundation Model vs. Traditional ML: What’s Winning?
(20:09) Inside Stripe’s Foundation Model: How It Was Built
(24:35) How Stripe Makes AI Decisions Transparent
(28:38) Where Stripe Uses AI (And Where It Doesn’t)
(34:10) How Stripe’s AI Drives Revenue for Businesses
(41:22) Real-Time Fraud Detection: Stripe’s Secret Sauce
(42:51) The Future of Shopping: AI Agents & Agentic Commerce
(46:20) How Agentic Commerce Is Changing Stripe
(49:36) Stripe’s Vision for a World of AI-Powered Buyers
(55:46) What Is MCP? Stripe’s Take on Agent-to-Agent Protocols
(59:31) Stripe’s Data on AI Startups Monetizing 3× Faster
(01:03:03) How AI Companies Go Global — From Day One
(01:07:48) The New Rules: Billing & Pricing for AI Startups
(01:10:57) How Stripe Builds AI Literacy Across the Company
(01:14:05) Roadmap: Risk-as-a-Service, Order Intent, and Beyond