Who is responsible when an AI agent does something its user never intended? Janel Thamkul, former deputy general counsel at Anthropic, explains why the answer depends on your contracts, your product design, and the records you keep.

In this episode of Founded & Funded, Madrona General Counsel Joanna Black talks with Janel about the legal decisions every AI founder needs to get right, including:

1) Why AI's constrained supply changes how you incentivize go-to-market teams
2) How a product's UI reveals whether a team understands agentic liability
3) The OpenClaw gym class incident and what it shows about open-ended tasks
4) Why copyright damages can be company bankrupting, and how model providers responded
5) Why granular logging is cheap to build early and brutal to retrofit

Liability for AI agents is still an open question, and founders are making product and contract decisions before the answers arrive. Janel gives concrete choices a team can make before shipping.

Transcript/Summary: https://www.madrona.com/what-founders-should-know-about-ai-legal-risk-before-they-ship

00:00 – Introduction
01:16 – What Founders Building on Frontier AI Models Underestimate: Supply Constraints and Sales Incentives
03:06 – How to Tell If an AI Team Understands Agentic Liability by Looking at the UI
05:38 – The OpenClaw Gym Class Incident: When an AI Agent Exploits a Vulnerability
07:56 – Who Is Liable When an AI Agent Fails? Contracts, Copyright, and Indemnification
10:23 – AI Safeguards That Are Cheap Early and Brutal Later: Granular Logging
11:36 – Why the Ecosystem Isn't Ready for Agentic AI: Principals, Trust, and Identity
13:30 – Why AI Startups Should Not Ship Without Real Terms of Service
15:27 – Don't Be the Slowest Zebra: How Early-Stage AI Companies Should Take on Risk
17:11 – Own Your Most Important Relationship: Why No Third Party Should Sit Between You and Your Customer
19:21 – Final Advice for CEOs: Tokenmaxxing, AI Stack Sovereignty, and the ZEBRA Mnemonic