Technically Legal - A Legal Technology and Innovation Podcast

In this episode, Dina Segal, Chief Legal Officer at Gusto, talks about her transition from private practice to leading an in-house legal and compliance department. The discussion covers Gusto's mission to support small businesses with payroll, benefits, and HR compliance. Dina outlines the strategic advantages of product counseling for in-house attorneys and details how Gusto's legal team actively integrates artificial intelligence into its daily operations. Key topics include organizing legal hackathons to build automated solutions, managing agentic workflows with human-in-the-loop accountability, and updating hiring practices to prioritize a learning mindset and technological proficiency in modern legal professionals. Things We Talk About in this Episode Roots in Law and Business: Dina shares how her grandfather's legal practice in Ukraine and her father's experience as a small business owner inspired her legal career. Overview of Gusto: A breakdown of how Gusto assists small businesses with payroll, HR, and navigating complex regulatory compliance. Transitioning In-House: Dina discusses her move from Big Law (Winston & Strawn) to in-house roles at Renovate America, Intuit, and eventually Gusto. The Value of Product Counseling: Why getting involved in product counseling is highly recommended for attorneys looking to build trust with business teams and understand commercial objectives. Legal Department Hackathons: How Gusto's legal and compliance team uses internal hackathons to identify operational bottlenecks and build targeted solutions using enterprise AI. Successful AI Workflows: Examples of processes automated by the legal team, including rate change management, commercial contract review, and licensing compliance. Deploying Agentic AI and Accountability: The framework Gusto uses to evaluate AI tools before they go live, focusing on problem identification, compliance risk controls, and maintaining human-in-the-loop oversight. Hiring for AI Proficiency: How Gusto has restructured legal job descriptions and interview processes to screen for a strong learning mindset and systems-building capabilities. Advice for New Lawyers: Practical guidance for law students and young attorneys on navigating the evolving, tech-driven legal landscape and the importance of finding strong mentors.  

Plaintiffs attorney Glen Lerner joins the podcast to discuss the business mechanics of running a national law firm and the growing influence of private equity in the legal sector. Glen also discusses his early career trajectory, the partnership dynamics that helped build his national brand, and the transition from viewing a law practice as a traditional law firm to operating it as a scalable business. The conversation covers the structural use of Management Service Organizations (MSOs) to facilitate non-lawyer investment and operational support, specifically detailing Lerner's recent strategic equity transaction with Atticor. Lerner also analyzes the economics of the personal injury market, noting the significant increase in case acquisition costs. Finally, the episode explores the Lexamica legal referral platform and Lerner's predictions on how artificial intelligence and artificial intelligence will contract the plaintiff's claims market over the next decade. Things We Talk About in this Episode Glen Lerner's background: Duke athletics, religious studies, and his early legal career. Partnership dynamics and managing a national personal injury brand The operational differences between a traditional law practice and a high-volume legal business The historical influx of private equity into mass torts versus single-event cases. Structuring private equity investments in law firms using Management Service Organizations (MSOs). Law firm economics, cash flow, and the rising costs of case acquisition. An overview of Lexamica, a software platform designed to manage and track legal referrals. Market predictions: The impact of artificial intelligence and autonomous vehicles on the future of plaintiff's law.

In this episode of Technically Legal, Jay Madheswaran, CEO of Eve, discusses his career path from the early days of Facebook to becoming a VC and investing in artificial intelligence. His stint as a VC eventually led to the creation of the legal technology platform Eve. The episode explores how Eve utilizes artificial intelligence to assist plaintiffs attorneys with tasks such as case management, drafting demand letters, and processing client intakes. Jay explains how software automation can optimize client outcomes by accelerating routine legal workflows which benefits the contingency-based economic model of plaintiff law firms. Key Segments Jay details his early career experience at Facebook and his subsequent transition into venture capital with a focus on artificial intelligence investing. The discussion covers the initial founding of Butler Labs and the strategic pivot toward building artificial intelligence solutions specifically for the legal industry. Jay outlines the economic structure of plaintiff law firms, noting that their contingency fee models require high efficiency and leverage to remain profitable. The conversation shifts to EveOS and how the software assists attorneys by automating the review of massive medical records and drafting demand letters for personal injury cases. Jay introduces Eve Intake, an automated voice AI agent that handles client calls and gathers initial case information. The episode concludes with a discussion on Eve's Atlas data platform, which structures firm data to make it highly accessible for future legal work. Episode Credits Editing and Production: Grant Blackstock Theme Music: Home Base (Instrumental Version) by TA2MI

We welcome back Sabastian Niles, President and Chief Legal Officer at Salesforce, to discuss his recent "Open Letter to Law Firms." As the legal industry hits a critical inflection point, Sabastian argues that the era of "AI theater" and small-scale pilots is over. The conversation dives deep into the Innovator's Dilemma facing law firms, the shift toward agentic AI, and how firms must reimagine their business models to remain competitive. Sabastian highlights that legal professionals are uniquely positioned to lead the charge in trusted AI transformation, provided they embrace transparency, data integration, and shared efficiency gains with their clients. Specifically,  he offers four systems law firms and other service providers must establish if they want to succeed in the AI era:  System of Engagement: A unified digital interface that replaces fragmented tools with seamless, real-time collaboration between firms and clients. System of Agency: An ethically governed AI framework that scales firm capacity and reimagines service delivery while maintaining strict human oversight and compliance. System of Work: A trusted, enterprise-grade platform that integrates daily professional applications into a cohesive, high-performance workflow. System of Context: A secure "single source of truth" for client data that ensures strategic counsel is grounded in history while protecting attorney-client privilege. Other Things We Talk About in this Episode The End of the Pilot Era: Moving beyond experimentation to integrated, unified AI platforms is no longer optional—it is a prerequisite for competitiveness. The Relationship Challenge: AI should be used to break down internal silos, allowing firms to bring their "tribal knowledge" and collective intelligence to every client engagement. System of Agency: A shift from manual workflows to "agentic" systems where AI agents handle triage, research, and routine queries (e.g., Salesforce's Outside Counsel Support Agent). Value-Based Evolution: Law firms must navigate the friction between the billable hour and AI-driven efficiency by focusing on superior outcomes and shared savings. Trust as Propulsion: In legal services, trust isn't just a guardrail; it's a growth lever. Mastering "Trusted Agentics" ensures human-aligned AI that respects privilege and confidentiality.  

In advance of this year's RelFest in Chicago, Aron Ahmadia, Vice President of Applied Science at Relativity, joins the podcast to discuss AI evaluation, AI benchmarking and the transition from traditional Technology Assisted Review (TAR) to generative AI in legal document review and eDiscovery. The conversation covers the daily operations of a global AI team, the concept of "evaluation as a product," and the methodology behind testing large language models (LLMs) for legal tasks. Aron also discusses a recent study that compared the accuracy and efficiency of TAR and human document review against Relativity's generative AI tool, aiR for Review. Aron talks about: A day in the life of the VP of Applied Science at Relativity. Navigating the rapid pace of AI and predicting what remains constant in legal tech. Aron's background: From early computer networking in a law firm to data science at DARPA and Capital One. Defining "evaluation as a product" and the importance of maintaining private benchmarks for LLMs. The trade-offs between human evaluations and automated AI evaluations. TAR (Predictive Coding) versus Generative AI: How prompt-based reasoning differs from label-based classification. Episode Credits Editing and Production: Grant Blackstock Theme Music: Home Base (Instrumental Version) by TA2MI