Essays, articles, and research on legal AI implementation, legal education, benchmarking, and practical deployment.
Diffuse AI // Forthcoming
Forthcoming in Diffuse AI, led by Daniel Bashir of OpenAI and The Gradient Podcast, Clara Collier of Asterisk, and Charles Yang of the Center for Industrial Strategy, this piece examines why legal AI adoption still runs into structural limits inside real practice.
National Law Journal // March 17, 2026
Explores how law schools can adapt curricula, pedagogy, and institutional strategy to prepare students for an AI-transformed legal profession.
ABA Law Practice Magazine // March/April 2026
ABA Law Practice Magazine article on how always-on AI and wearable interfaces can reshape legal workflows, client intake, and professional responsibility boundaries.
3 Geeks and a Law Blog // February 18, 2026
A practical guide to creating legal AI skills/plugins and why execution quality now matters more than feature checklists.
UNT Dallas Law Review On The Cusp / SSRN // August 22, 2025
Examines why current LLMs do not reliably replicate human juror reasoning and where controlled jury simulation may still be useful.
Archive
ABA Journal // 2026
ABA Journal piece on how law librarians are helping legal institutions evaluate, teach, and adopt AI responsibly.
ALM // 2025
Co-authored practical framework for prompt training that emphasizes repeatable quality control and lawyer-ready workflows.
Edward Elgar // 2025
Reference contribution focused on document review workflows, constraints, and implementation guidance in legal AI systems.
AALL Spectrum // 2025
Explores benchmark design tradeoffs and why legal AI evaluation needs context-aware methods beyond headline scores.
SSRN // November 8, 2024
A framework for Socratic AI assessment that increases engagement while preserving transparent evaluation criteria.
SSRN // May 12, 2023
Explores custom chatbot workflows to improve legal learning and high-frequency feedback loops.
SSRN // 2023
Argument for pragmatic optimism in legal research use cases when model outputs are paired with structured verification practices.
For speaking, training, advisory, and applied AI work across legal organizations, government, and higher education.