Technically Legal - A Legal Technology and Innovation Podcast

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

Emily Logan Stedman, commercial litigator at Husch Blackwell, discusses moving beyond the billable hour not just to modernize legal billing but to also prioritize lawyer well-being. The conversation explores the practical steps required to transition traditional litigation models toward Alternative Fee Arrangements (AFAs). Emily details her methodical approach to utilizing secure legal AI tools to analyze historical time entries, allowing her to offer phased flat fees, strategic counsel subscriptions, and predictable contract review pricing. The discussion also covers strategies for maintaining mental health in demanding legal environments, taking control of chaotic schedules, and reframing the billable hour as a tool for career management rather than a burden.
Things We Talk About in this Episode
Emily's transition from bankruptcy law to general commercial litigation after moving to Wisconsin.

The motivation behind launching The Grace Period podcast and advocating for lawyer well-being in big law.

Strategies for managing the billable hour, shifting daily mindsets, and setting strict boundaries for deep work.

The genesis of applying Alternative Fee Arrangements (AFAs) to unpredictable, complex litigation matters.

Structuring strategic counsel subscriptions and granular phased flat fees to provide cost predictability for corporate clients.

Utilizing AI to analyze historical billing data and build accurate, profitable flat-fee pricing models that secure firm buy-in.

Leveraging secure legal AI agents like Legora and Prompt Composer to map out discrete litigation phases and draft modern engagement letters.

In this episode, Justin Wales, Chief Legal Officer for Crypto.com makes a second visit to the podcast. This time around, he discusses his new book, The AI Legal Handbook, the emerging regulatory landscape, liability frameworks, and practical applications of artificial intelligence. Justin outlines how attorneys and regulators should approach modern AI models, the mechanics behind AI, and the effect of generative AI on legal education. The discussion covers key regulatory principles, the balance between strict liability and negligence frameworks, copyright issues in machine learning training, and the governance challenges of artificial general intelligence (AGI).
Things We Talk About in this Episode
Transitioning from cryptocurrency regulation to developing a unified framework for artificial intelligence law

The importance of legal professionals understanding underlying model mechanics and token prediction to evaluate hallucination risks

Generative AI's disruption of law school assessments and the pedagogical shift from written assignments to oral examinations

The convergence of cryptocurrency rails, agentic AI systems, and decentralized compute infrastructure

Foundational principles for AI regulation, emphasizing proportional oversight, human-centered accountability, and transparency over outright bans

Managing the "black box problem" and balancing algorithm explainability with technical efficiency

Comparative analysis of sector-specific guidelines versus federal mandates and the adaptability of existing rules of professional conduct

Evaluating legal liability standards: applying negligence versus strict liability to autonomous vehicles, healthcare diagnostic tools, and AI chatbots

Intellectual property considerations, fair use, and style mimicry in generative model training data

Preparing legal, economic, and governance frameworks for artificial general intelligence (AGI)

Where to buy The AI Legal Handbook: JustinWales.com or Amazon.
Episode Credits
Editing and Production: Grant Blackstock
Theme Music: Home Base (Instrumental Version) by TA2MI