“The life of the law has not been logic: it has been experience.”
— Oliver Wendell Holmes Jr., The Common Law (1881)
Legal realism is the view that jurisprudence should emulate the methods of natural science — that is, it should rely on empirical evidence.
Applied to AI, that means testing hype against actual results on real legal problems.
Data and methods are open source, inviting scrutiny, replication, and extension by the broader legal and technical community. The mission is to advance an evidence-based understanding of where AI genuinely serves the practice of law and where it does not.
Topics#
Current series include:
- The Legal AI Landscape — how the underlying technology works, what tools exist, what firms are actually doing with them, and where the limits are
- AI Playbook — practical workflows for lawyers using AI in their practice today
- The Client Side — what clients expect from firms using AI, and how that reshapes pricing and competition
- AI Under the Hood — deeper dives into the technical mechanics behind legal AI tools
Standalone posts cover topics like privilege issues with AI use, how judges are adopting AI, and the government’s data advantages in enforcement. More topics are on the way as AI reshapes new areas of practice.
Bio#
I’m a lawyer specializing in investigations and litigation. I studied cognitive science, symbolic systems, and philosophy of mind.
I started LegalRealist to test AI claims against real legal problems by scraping public data and vibe coding.
Contact#
Get in touch if you have questions or comments about my work, or want to collaborate.