Technically Legal - A Legal Technology and Innovation Podcast

Percipient - Chad Main
  • 4.8 (25)
  • Technology
  • Updated Biweekly

Technically Legal is a legal tech podcast exploring how technology is transforming the legal landscape. Each episode features insightful interviews with legal innovators, tech pioneers, and forward-thinking educators who are leading this change. Our guests share their experiences and insights on how technology is reshaping legal operations, revolutionizing law firm practice, and driving the growth of innovative legal tech companies. We also explore the broader implication of technology on everyone involved in the legal system, from practitioners to clients. The podcast is hosted by Chad Main, an attorney and founder of Percipient, a tech-enabled legal services provider. Chad launched Percipient on the belief that when technology is leveraged correctly, it makes legal teams more effective. Technically Legal Podcast is an ABA Web 100 Best Law Podcasts Honoree.

  1. Oct 15

    How Plaintiffs Lawyers Can Unlock Law Firm Leverage With AI & Automation ( Jay Madheswaran - CEO Eve)

    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

  2. Oct 1

    Best of TL: Legal's Moment to Move Beyond AI Experimentation (Sabastian Niles, President & CLO Salesforce)

    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.

  3. Sep 17

    On AI Evals, TAR vs. LLMs and What Will be Different Next Year - Aron Ahmadia (VP Applied Science, Relativity)

    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

  4. Sep 3

    Moving Beyond the Billable Hour: Pricing Legal Work in the AI Age (Emily Logan Stedman - Husch Blackwell)

    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.

  5. Aug 20

    AI Regulation: Where it is and Where it Might (or Should) Go (Justin Wales CLO @ Crypto.com & Author of AI Legal Handbook)

    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

  6. Aug 6

    From Managing Partner to Intel CLO: Career Lessons and Thoughts on Modern Legal Practice (April Miller Boise)

    In this episode April Miller Boise, with stints as Chief Legal Officer at Intel and managing partner at Thompson Hine, shares insights from her career. The conversation explores the shifting dynamics between corporate legal departments and outside counsel and the necessity of embracing legal technology. April also provides advice for junior lawyers on developing long-term expertise and trusted relationships in an AI-driven environment. Things we Talk About in this Episode Career progression: From Wall Street M&A partner and law firm managing partner to Chief Legal Officer. The fundamental differences between driving P&L at a law firm versus serving on an executive leadership team in-house. Addressing the widening gap between corporate expectations and traditional law firm service delivery models. Experience navigating global manufacturing, innovation, and supply chain transformations at Eaton and Intel. Practical approaches to generative and agentic AI adoption in legal departments and outside counsel. Key attributes for modern legal talent: Intellectual curiosity, agility, and comfort with calculated risks. Career advice for young lawyers: Balancing AI efficiency tools with the 10,000-hour principle of skill-building. Why historical legal tech struggled to scale and how current enterprise AI investments are fundamentally altering the legal landscape.

  7. Jul 23

    When Machines Have the Answers, Build Better Humans With AI Augmentation Not Automation (Vivienne Ming, Scientist, Professor, Author)

    In this episode, theoretical neuroscientist Vivienne Ming discusses her new book, Robot Proof - When Machines Have All the Answers, Build Better People.  The conversation examines the intersection of artificial intelligence and knowledge work, exploring how professionals can adapt to an increasingly automated economy. The discussion contrasts the limitations of basic AI task automation with the advantages of human-AI collaboration—the "cyborg" model—for solving complex, ill-posed problems. Ming highlights her research on forecasting market outcomes, the critical role of endogenous motivation, and how the legal industry and other elite professions must rethink entry-level training. Key Topics Discussed Theoretical Neuroscience and Early AI: Ming's background and the evolution of machine learning models from early academic research to modern agentic AI. The Polymarket Experiment: An analysis comparing the forecasting accuracy of standalone AI, unassisted humans, and human-AI collaborators, revealing the superiority of deep human-machine integration. Automation vs. Augmentation: The pitfalls of the traditional "human-in-the-loop" model and why replacing menial tasks often neglects essential human problem-solving skills. Well-Posed vs. Ill-Posed Problems: Identifying the specific areas where AI excels (algorithmic, factual answers) and where human intelligence remains superior (navigating uncertainty and undefined parameters). Labor Disruption and Economic Shifts: Examining historical technological revolutions, the Jevons paradox, and the future demand for specific, highly adaptable human skill sets. Endogenous Motivation: How internal drivers like curiosity, resilience, and perspective-taking predict professional success more accurately than standard extrinsic incentives. Practical AI Strategies: Actionable methods for professionals to refine their skills, including using AI as a critical "nemesis" to challenge assumptions and encourage deep, effortful processing. The Future of Elite Professions: The macro-level challenges facing organizations in developing junior talent—such as associate attorneys—when the entry-level tasks traditionally used for training are automated. Things We Talk About in this Episode Socos: Vivienne Ming's philanthropy and research newsletter (socos.org). Thinking, Fast and Slow: Authored by Daniel Kahneman. Anthropic Research: A study published in Science detailing the productivity of AI-assisted programmers. BCG AI Study: Research analyzing AI integration and performance among management consultants. Raj Chetty: Economic research regarding peer role modeling, education, and socioeconomic mobility.

  8. Jul 9

    Inside Microsoft Legal: A Look at AI Use Built for Scale (Rebecca Anderson - Head of Legal EMEA Microsoft)

    This episode features a discussion between host Chad Main and Rebecca Anderson, Head of Legal EMEA, Associate General Counsel at Microsoft, regarding the integration of artificial intelligence in corporate legal departments. The conversation covers Rebecca's career progression from a law firm associate to an international in-house counsel role. The core of the discussion examines Microsoft's internal AI deployment strategies, including the shift from personal productivity to intent engineering. Additionally, the episode addresses changing expectations for outside counsel regarding AI adoption and outlines the necessary skills for future legal professionals. Episode Highlights AI Deployment Phases: AI integration in legal departments progresses through three stages: personal productivity (prompt engineering), context engineering (curating institutional knowledge), and intent engineering (autonomous agents operating with human guardrails). Scaling Legal Support: Corporate legal teams can manage high volumes of client requests by utilizing AI-driven triage systems overseen by paralegals, which allows senior lawyers to focus on complex, high-value legal work. Expectations for Outside Counsel: Corporate clients expect law firms to implement AI strategies to improve efficiency, which will likely shift the industry's economic focus from billable hours to value-based billing. Future Legal Skills: While AI literacy and data curation are critical, foundational skills such as human judgment, emotional intelligence, and strategic business context remain essential for legal professionals. Things we talk about: Copilot for Legal

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4.8
out of 5
25 Ratings

About

Technically Legal is a legal tech podcast exploring how technology is transforming the legal landscape. Each episode features insightful interviews with legal innovators, tech pioneers, and forward-thinking educators who are leading this change. Our guests share their experiences and insights on how technology is reshaping legal operations, revolutionizing law firm practice, and driving the growth of innovative legal tech companies. We also explore the broader implication of technology on everyone involved in the legal system, from practitioners to clients. The podcast is hosted by Chad Main, an attorney and founder of Percipient, a tech-enabled legal services provider. Chad launched Percipient on the belief that when technology is leveraged correctly, it makes legal teams more effective. Technically Legal Podcast is an ABA Web 100 Best Law Podcasts Honoree.

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