What does it take to build a good AI-native law firm when the goal is not just efficiency, but giving lawyers more leverage, more agency, and more space for the human judgement at the heart of legal work?

In this episode of AI Sidebar, Irene Liu talks with Ryan Daniels, co-founder and CEO of Crosby AI and a Stanford Law School alum, about what he’s learned building an AI-native law firm focused on commercial contracts. Daniels explains what “AI-native” means in practice, how Crosby differs from both a traditional law firm and a legal tech company, and why it remains, at its core, a law firm. Irene and Ryan also explore how AI can take on repetitive legal work, reshape the law firm business model, and make this an especially exciting time for lawyers who want to innovate.

Learn more about the Stanford Law School AI Initiative

Irene Liu, Executive Director of the Stanford Law School AI Initiative

Connect with Ryan Daniels

Learn more about Crosby

Chapters:

(00:00:00) Introduction

(00:00:53) What Is an AI-Native Law Firm?

(00:02:39) Why Build a Law Firm Instead of Legal Tech?

(00:03:33) Why Commercial Contracts?

(00:04:54) Pricing by Deal, Not by Hour

(00:06:34) Measuring Human Review Time

(00:07:46) Designing AI Around Lawyers

(00:10:44) Keeping Lawyers in Control

(00:12:22) Building Empathy Between Engineers and Lawyers

(00:14:53) Lawyers, Engineers, and the Identity of an AI-Native Firm

(00:16:31) Finding Lawyers for a New Model

(00:18:15) Why Great Lawyers May Become More Valuable

(00:19:50) Why Clients Try Crosby

(00:20:53) The Future of AI-Native Law Firms

(00:21:37) Defining Quality in Legal AI

(00:22:30) Why This Is an Exciting Time to Build

(00:23:18) Advice for Lawyers and Law Students

(00:25:05) Conclusion

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For product lawyers, the agentic era is changing more than the tools; it is changing how products are built, how risks surface, and how legal advice reaches the business. And who better to explore that shift than the creator of Claude for Legal and associate general counsel at Anthropic, Mark Pike.

Drawing on his experience at Slack and Anthropic, Pike offers a firsthand look at what product counseling requires when legal teams are advising not just on AI, but alongside it. Irene and Mark explore how lawyers can build trust with product and engineering teams, why technical curiosity matters, and how tools like Claude for Legal are reshaping the way legal guidance is created, delivered, and scaled. The conversation also points to a broader question for the profession: whether AI will reduce legal work or expand the universe of legal questions that teams are able to see and address.

Learn more about the Stanford Law School AI Initiative

Irene Liu, Executive Director of the Stanford Law School AI Initiative

Connect with Mark Pike

Explore Claude for Legal on GitHub

Watch Mark's Presentation at Stanford

Chapters:

(00:00:00) Introduction

(00:01:15) How Product Counseling Has Changed

(00:03:17) From Pat Signals to AI Agents

(00:04:38) Product Counseling in the Agentic Era

(00:06:41) The Product Lawyer as Miniature GC

(00:08:09) Getting Closer to the Work

(00:09:39) What Happens When Everyone Is a Builder?

(00:12:51) Guardrails, Automation, and Human Judgment

(00:15:13) Training Product Teams With Better Tools

(00:16:38) Making Legal Training Memorable

(00:19:05) Knowing When to Call in Experts

(00:20:42) Using AI to Understand New Legal Issues

(00:22:23) Working With Outside Counsel in the AI Era

(00:23:27) Technical Fluency for Product Lawyers

(00:25:13) Learning by Building

(00:29:16) Managing AI Agents

(00:31:53) Will AI Create More Legal Work?

(00:33:43) What Comes Next for Claude for Legal

(00:35:06) Conclusion

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What does it mean for quality, legal expertise, and judgment when law professors actually prefer AI answers over answers written by other law professors in a blind study?

In this episode of AI Sidebar, Irene Liu talks with Stanford Law Professor Julian Nyarko, faculty director of liftlab and co-director of Stanford Law’s AI Initiative, about his recent study examining how legal experts evaluate AI-generated work. Nyarko explains what the study reveals, why its findings matter for both legal education and practice, and how rigorous research can help the profession determine when AI performs well, when it falls short, and when it should be trusted. He also discusses how liftlab is evaluating AI across legal services, research, and education, including when AI tutors can support student learning and when they may get in the way.

Together, they explore how this research is shaping Stanford Law’s approach to AI in the classroom, from tutoring tools to simulated negotiations, and what it may mean for the future of legal expertise and education.

Learn more about the Stanford Law School AI Initiative

Irene Liu, Executive Director of the Stanford Law School AI Initiative

Julian Nyarko Stanford Profile

Learn more about liftlab

“Law Professors Prefer AI Over Peer Answers”

Chapters:

(00:00:00) Introduction

(00:00:55) What Is liftlab?

(00:02:41) The Four Core Pillars of liftlab

(00:07:39) The Art of Contracts

(00:10:25) How liftlab uses AI

(00:13:54) The Study: “Law Professors Prefer AI Over Peer Answers”

(00:18:56) AI Tutors in Legal Education

(00:21:52) Potential Applications of the Findings

(00:23:02) Study Modifications

(00:24:43) Classroom Adaptation of the Study

(00:28:33) Underrated & Overhyped Uses of AI in Law

(00:33:15) Judgment, Lawyers, and the Future of AI

(00:34:48) Conclusion

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