AI Evaluation for Legal Professionals: How Product Lawyers Lead the Way

In today’s fast-changing legal tech landscape, the rise of artificial intelligence (AI) brings both opportunity and risk. The question facing many in-house legal teams is no longer “Should we use AI?” but “How do we use it responsibly?” That’s where AI evaluation for legal professionals becomes essential.

In this conversation with Rayan Krishnan and Langston Nashold—Stanford graduates and co-founders of a platform designed to assess large language models (LLMs) for legal applications—we explore how product lawyers can lead the charge in shaping governance, trust, and strategy.

Watch the full conversation with Rayan Krishnan and Langston Nashold here:

The legal industry is embracing AI to streamline tasks like document review, risk assessment, and legal research. However, without structured AI evaluation for legal professionals, these tools can produce misleading or even harmful results. Ryan and Langston saw a critical gap between engineers building AI models and the lawyers using them. Their platform introduces a solution tailored for legal standards and professional accountability.

By embedding AI evaluation into legal workflows, professionals—especially product lawyers—can better assess compliance, ethical integrity, and risk exposure.

At the core of their platform is the concept of “unit testing,” a practice used in software development to validate small, functional components. But when applied to LLMs, traditional answers don’t always apply. Legal reasoning often has multiple valid interpretations, requiring more nuanced analysis.

Their evaluation platform goes beyond right or wrong answers. It uses semantic scoring to assess legal logic, the completeness of arguments, and the contextual strength of responses. This kind of AI evaluation for legal professionals helps ensure outputs reflect the nuance and responsibility expected in legal practice.

AI systems can’t rely solely on human oversight—especially in legal departments where resources are limited. That’s where scalable AI evaluation becomes crucial. Ryan and Langston’s platform enables early detection of problems before models go live, saving valuable legal review time.

For product lawyers, this means the ability to deploy AI-enabled legal tools faster, with higher confidence and fewer risks. It’s about making evaluation as repeatable and trustworthy as possible—without burdening teams.

Product lawyers are uniquely positioned to lead responsible AI integration. They bridge compliance, technology, and business strategy. Through consistent AI evaluation, legal professionals ensure that legal tech tools meet ethical expectations, support privacy rights, and avoid algorithmic bias.

In doing so, they redefine their roles—not just as legal gatekeepers, but as forward-thinking enablers of safe and effective innovation. AI evaluation for legal professionals becomes the foundation for strategic advisory and long-term impact.

As open-source models grow and regulations like the EU AI Act take effect, legal teams need consistent standards. AI evaluation provides the framework for this shift. Think of it as a legal equivalent of a bar exam for AI tools—clear, reliable, and scalable.

Product lawyers help implement these benchmarks, fostering a culture of ethical AI across legal, IT, and compliance functions. Whether it’s through policy, auditing tools, or employee training, these efforts build lasting trust in AI.

Watch the full conversation here:  Notes to My (Legal) Self: Season 6, Episode 11 (ft.Rayan Krishnan and Langston Nashold)

At Notes to My (Legal) Self®, we’re dedicated to helping in-house legal professionals develop the skills, insights, and strategies needed to thrive in today’s evolving legal landscape. From leadership development to legal operations optimization and emerging technology, we provide the tools to help you stay ahead.

What’s been your biggest breakthrough moment in your legal career? Let’s talk about it—share your story.