The Geek In Review

Hosted by Greg Lambert & Marlene Gebauer

BusinessInterviews guests

Website RSS feed LinkedIn Facebook YouTube

Episodes

368

Latest episode

Aug 2026

Language

EN-US

About the show

Welcome to The Geek in Review, where podcast hosts, Marlene Gebauer and Greg Lambert discuss innovation and creativity in legal profession.

Listen to episodes

60 recent

September 7, 2026Episode 36940 min

Beyond the Law Firm Pyramid: Manuel Deó on Ambar, Fractional Legal Talent, and the Future of Legal Delivery

What happens when you separate elite legal talent from the traditional law firm structure? This week on The Geek in Review , we talk with Manuel Deó , co-founder and co-CEO of Ambar Partners , about a model designed around senior independent lawyers, flexible capacity, enterprise technology, and client choice. Deó explains why he and co-founder Rosa Espín did not set out to replace Big Law, but instead to address a gap between permanent in-house hiring and traditional outside counsel. At the center of Ambar’s model is a simple idea: legal demand comes in different shapes, and the delivery model should match the problem. Deó describes how Ambar gives lawyers control over the clients, projects, fees, and schedules they take on, while giving clients greater visibility into cost and the individual lawyers doing the work. He also discusses Ambar’s recent Chambers recognition and argues that the term “alternative” is starting to lose some of its usefulness as clients grow more comfortable assembling legal services from a wider range of providers. Deó walks through what Ambar calls its legal operating system, built around belonging, business, backbone, and badge. The model combines a professional community with business development, compliance, contracting, billing, technology, and institutional credibility for independent lawyers and specialist boutiques. Ambar’s public materials describe a shared technology environment that includes tools such as Harvey, Microsoft Copilot, Legora, and other legal technology products. The goal, according to Deó, is to give independent lawyers access to the infrastructure associated with a large firm without requiring them to give up professional independence. The conversation also turns to AI, knowledge, and professional judgment. Deó argues that legal knowledge is becoming more abundant while judgment grows more valuable. He describes Ambar’s work on “expert twins,” where approved knowledge, prior work, playbooks, and experience associated with an individual lawyer form a trusted layer for AI-assisted work. That emphasis on institutional knowledge and permissions echoes a broader trend across legal AI, where vendors are increasingly focused on connecting AI systems to trusted internal work product and organizational context. Finally, Deó offers a broader view of where legal delivery is heading. He sees legal departments assembling teams dynamically from in-house lawyers, traditional firms, independent specialists, boutiques, managed services, and AI agents based on the needs of a particular matter. Instead of asking which firm to hire, clients increasingly have reason to ask what combination of people, technology, expertise, and risk structure best fits the work. For Deó, the future belongs less to a single dominant delivery model and more to legal departments acting as orchestrators of capability. Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email : geekinreviewpodcast@gmail.com Music : Jerry David DeCicca LINKS Ambar Partners Ambar Community Ambar Hauss Membership Plans Dr. No Newsletter

August 31, 2026Episode 36845 min

Judicaid: Bringing AI Mediation to Everyday Legal Problems

For millions of people, an everyday legal dispute never justifies the cost of a lawyer or a private mediator, no matter how much the outcome matters to them. Judge Victoria Wood saw that problem over and over during her years on the Napa County Superior Court bench. This week, Wood joins Judicaid Chief Strategy Officer Valerie Clemen to explain how those years led to Judicaid, an AI-assisted mediation platform built to help people resolve everyday disputes before time, expense, and emotion push them deeper into litigation. Wood traces Judicaid's origins to two problems she kept running into as a judge and mediator. Traditional settlement conferences arrive late in a case, after the parties have spent real money and dug into their positions. Then there are the lower-value landlord-tenant, contractor, neighbor, probate, and small-claims disputes where professional mediation rarely pencils out at all. Wood puts a number on the access problem. The State Bar of California's 2024 Justice Gap Study, released in 2025, found that Californians received no legal help, or inadequate help, for 85 percent of their civil legal problems. Judicaid aims at a slice of that gap by giving people an earlier and cheaper chance to communicate and negotiate. Clemen walks Greg Lambert and Marlene Gebauer through Judicaid's "shuttle-style" mediation process. Each participant talks privately with an AI mediator named Jude, so the two sides never have to speak to each other directly. Jude gathers each side's account of the dispute, identifies priorities and possible settlement terms, and moves between the participants while filtering out insults, anger, and inflammatory language. If the parties find common ground, the platform prepares a proposed settlement for review and electronic signature. Wood is careful about one boundary throughout the conversation. Jude is a facilitative mediator, and it stays away from evaluating legal rights. It will not decide who is legally correct, predict who will win, or give legal advice. The conversation then turns to Judicaid's pilot with Napa County Superior Court, and the role courts could play in expanding AI-assisted dispute resolution. In the court model, a court subscribes to the service and hands litigants' access through a QR code, with no integration into the court's technology systems. The pilot has already surfaced a behavioral lesson. Offering mediation as an optional service does not mean parties will use it, and Wood and Clemen see more potential where courts actively encourage or require litigants to attempt dispute resolution before proceeding. Language is another piece of the story, since Judicaid lets participants who speak different languages work through the same mediation without arranging multiple interpreters. Wood and Clemen also see mediation as just the starting point. Wood uses the phrase "intelligent dispute resolution" for a broader category of AI-assisted tools covering mediator proposals, parent coordination, and other structured approaches to conflict. The bigger ambition is a change in habits, where people reach for structured communication and settlement before a disagreement hardens into a lawsuit. Clemen boils that aspiration down to three words she hopes become part of the vocabulary of everyday disputes: "Just Judicate it." Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email : geekinreviewpodcast@gmail.com Music : Jerry David DeCicca LINKS Judicaid State Bar of California, California Justice Gap Study 2024 California Justice Gap Study Napa County Superior Court, Small Claims

August 24, 2026Episode 36755 min

From Search Rankings to Vibe Coding: How Best Lawyers Is Rebuilding for the AI Era

What happens when a 40-year-old legal data company decides its employees should start building their own software? This week on we talk with Best Lawyers CEO Phillip Greer and Senior Vice President of Research and Product Strategy Elizabeth Petit about an internal AI transformation that reaches far beyond adding ChatGPT to the corporate toolkit. Best Lawyers is experimenting with generative engine optimization, internal agentic systems, vibe coding, and an AI development environment where employees across research, finance, marketing, and other departments build applications around the company’s data. Greer begins with a challenge facing every law firm marketing team: traditional search is changing. Google AI Overviews and answer engines such as ChatGPT, Claude, and Gemini increasingly give users answers without sending them to the familiar list of blue links. Greer argues that SEO still matters, but law firms now need to think about Generative Engine Optimization, or GEO, and the signals AI systems use when deciding which sources deserve trust. Structured data, schema markup, substantive content, and third-party validation all become part of the equation. For Best Lawyers, its long history of peer-reviewed rankings offers an interesting advantage. The company’s data serves as an independent signal that AI systems might weigh differently from content produced by a firm’s own marketing department. Petit explains how Best Lawyers is applying the same thinking to legal marketing through Smithy AI, a system designed to help attorneys and law firm marketers develop profile content without endlessly copying the same biography across websites. Smithy draws from Best Lawyers’ structured information and existing lawyer content to produce a starting point that attorneys and marketers then edit. The larger goal is authenticity. As generative systems make producing generic legal content almost effortless, Greer argues that distinctive expertise, voice, and credible third-party signals become more valuable rather than less. The conversation then moves inside Best Lawyers, where Greer has taken a far more unusual approach to AI adoption. After building a secure data layer connecting systems including SQL databases, HubSpot, Gong, Google Analytics, and accounting data, he created an internal Best Lawyers App Store where employees use natural language to build applications against company data. What began with roughly 30 percent of the workforce vibe coding has grown to around 40 percent, according to Greer. Petit describes building research and KPI dashboards despite coming from a research rather than software engineering background. Projects that once required Excel formulas, Power BI reports, development queues, and weeks of waiting now sometimes move from a question at 9:30 to a working internal application by 10:30. That shift also changes the role of professional software engineers. Rather than spending their time building another reporting screen or internal form, Best Lawyers’ engineers increasingly concentrate on architecture, data infrastructure, performance, governance, and the guardrails surrounding employee-built applications. Greer describes moving parts of the company’s data architecture toward Elasticsearch and developing “Bestie,” an internal agentic AI team member. Yet speed introduces another problem. Petit and Greer describe an “AI vampire” effect, where instant feedback encourages people to keep working because the machine never gets tired, goes home, or stops responding. Human judgment includes knowing when the human needs to stop. Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email : geekinreviewpodcast@gmail.com Music : Jerry David DeCicca

August 17, 2026Episode 36645 min

Patrick Forquer on Legora’s Agentic AI, Legal Engineering, and Consumption-Based Pricing

In this episode of The Geek in Review, we talk with Patrick Forquer , Chief Revenue Officer at Legora , about legal AI’s move from experimentation into daily legal work. Forquer explains why Legora has invested heavily in legal engineers, lawyers with practice experience who work alongside clients on adoption, workflow design, prompt and context engineering, and change management. The conversation also explores an emerging career path for lawyers who pair substantive legal knowledge with AI fluency, especially as firms search for people able to translate practice needs into working systems. Legora’s acquisition strategy provides another lens on the company’s ambitions. Forquer describes a strategy aimed at building breadth across legal work while adding depth in litigation, commercial real estate, regulatory monitoring, and legal research. Recent acquisitions such as Wexler , Cadastral , and Graceview bring specialized capabilities into a broader agentic platform. Legora’s own 13-day acquisition process also serves as an example of how M&A diligence, document review, drafting, and analysis are beginning to move through shared AI environments. A major portion of the discussion focuses on the difference between traditional workflow automation and agentic AI for legal work. Forquer draws a line between prebuilt automation and agentic systems: workflows follow predetermined steps, while agents receive a goal, gather context, form a plan, call tools, and work across longer tasks with human review. Context engineering therefore becomes increasingly important. Matter data, firm knowledge, permissions, legal skills, and connections to systems through tools such as MCP all shape the quality of agentic work. M&A due diligence already represents one area where longer-horizon agentic processes are gaining traction. Legora describes the same architecture through its agentic operating system, or aOS. The episode closes with a look at what law firm innovation leaders should prepare for next. Forquer identifies the data layer as one of the central issues behind successful agentic AI. Secure access to documents, matter-level permissions, governance, firm knowledge, and well-structured context determines how far agents progress into complex legal work. Talent matters alongside infrastructure, which brings the conversation back to legal engineers and new hybrid roles spanning law, AI, knowledge management, and data governance. The episode leaves innovation and KM leaders with a practical agenda: improve data governance, build legal engineering skills, align stakeholders around risk and outcomes, and measure value through work product, adoption depth, and client impact. Legora Legora aOS, Agentic Operating System Legora Introduces Consumption-Based Pricing for Agent Pro Crowell & Moring Marks Six Months of Legora Integration Measuring the Impact of AI on Law Firms, Ari Kaplan and Legora Legora Acquires Wexler Legora Acquires Cadastral Legora Acquires Graceview How Legora Uses Its Platform to Close M&A Deals in Days Legora Series D Funding Announcement Legaltech Hub ILTACON 2026 Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email : geekinreviewpodcast@gmail.com Music : Jerry David DeCicca

August 10, 2026Episode 36548 min

Who Governs Big Tech? Hannah Bloch-Wehba on AI Regulation, Police Surveillance, and Public Accountability

It turns out that tech companies don’t sit outside of government as just ordinary vendors. This week on The Geek in Review podcast, we welcome back Texas A&M University School of Law professor Hannah Bloch-Wehba to talk about accountability of Big Tech, AI regulations, government surveillance, and the intertwining of public authority and private tech infrastructure. Bloch-Wehba traced the dependency between the two powers all the way back to the 1930s in her article “ How Tech Took Over ,” in how the tech sector became a foundation for national security and economic growth. Today’s hybrid form of governance, where Bloch-Wehba explains how a handful of private companies supply data and cloud systems, along with decision-making infrastructures across multiple governmental agencies. It is a struggle for traditional constitutional doctrines to adjust to the modern technology and the operations provided by contractors that are providing their core foundational operations. The issues also enter into the criminal law enforcement areas and Bloch-Wehba’s “ Rights, Knowledge, and Capture in the Datafied State ,” discusses how trade-secret claims are throwing a barrier between proprietary data systems and criminal defendant’s ability to examine the systems that are being used to convict them in the courts. There is a strangeness in the judicial systems where corporate choices are shaping the legal process being followed, rather than corporate governance following established legal norms. Bloch-Wehba’s “ Information Law Pluralism ” covers how privacy rules, audits, impact assessments, disclosure duties, researcher access, and independent review as parts of a broader system governing exactly how knowledge is shared, validated, and even produced. There seems to be no single device that transparently provides accountability. In addition, she lists how a political campaign program against states attempting to regulate AI companies and products is weakening state transparency even further. Finally, we cover Bloch-Wehba’s “ Rethinking Federal Support for Journalism ” where she argues that platform payments give rise to the risk of replacing a governmental dependency gets switched for journalist and new organizations being financially tied to companies they must scrutinize. Ideas floated like an AI tax provide some alternative funding possibilities for supporting local and public-interest journalists. LINKS Hannah Bloch-Wehba’s website Hannah Bloch-Wehba, Texas A&M University School of Law “How Tech Took Over,” SSRN “Rights, Knowledge, and Capture in the Datafied State,” SSRN “Information Law Pluralism,” Indiana Law Journal “Who’s Regulating Police Technology? It’s Not the Courts,” Tech Policy Press “Rethinking Federal Support for Journalism,” Knight First Amendment Institute Google Maps: Updates to Location History and on-device Timeline storage National Science Foundation Act of 1950 National Science Foundation history Flock Safety license plate reader cameras Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email : geekinreviewpodcast@gmail.com Music : Jerry David DeCicca

August 3, 2026Episode 36440 min

Brad Blickstein on Private Equity Thinking, AI Pricing, and the Law Firm Business Model

We welcome back Brad Blickstein , CEO at Blickstein Group , to discuss how private equity principles may provide law firms with an alternative approach to profitability, governance, and even long-term growth. Blickstein's new book, WWPED: What Would Private Equity Do? was written to walk firms through how treating topics like pricing, technology, talent, and client relationships as part of the enterprise value instead of overhead expenses after year-end partnership distributions. Pulling from Jae Um's topics of Cream, Core, and Commodity framework, Blickstein talks about the legal work as the primary competitive battleground. Much like businesses that provide baked goods, firms have to separate the customized legal judgment from the repeatable legal processes, technology, and what alternative legal services providers offer. Law firm leaders should understand what scalable work is, begin building consistent systems to deliver that work, and truly professionalize pricing over relying upon what a partner's gut tells them. We also cover the Blickstein Group's 2026 Law Firm COO Survey where technology adoption and investment ranks as the leading strategic initiative with 38.1% identified practice silos as the largest structural issue and 27% of COOs listed lack of operational authority as another prime issue. COOs are struggling with being tasked with modernizing law firms, but not given the authority to actually overcome the base issues of decentralized partnerships, competing incentives, and overall firm political structures. Add AI into the mix, and the pricing question becomes even more important. Some two-thirds of the COOs surveyed confessed that they were not formally measuring any return on investment (ROI) in which they could later measure any law productivity or direct revenue increases. Blickstein points out that faster work in a billable hour model is not the type of math that law firms want to calculate, and that firms have to address this directly and redesign their overall pricing model on value received by the client, not hours worked by the lawyers. We all discuss the issues of alternative fee arrangements (AFAs) have face in the more than 30 years since Blickstein originally published an article titled "Alternative Billing Making a Comeback." AFAs bring with it issues of shadow billing, client trust factors, and the need to express value not tied to the amount to time spent on the work. We also break down the corporate buyer side and address the Blickstein Group's 18th Annual Law Department Operations Survey which identifies AI pilot projects in corporate legal departments, but very few operational deployments. These may be tied to the long running issue of poor data hygiene along with business objectives that are not clearly tied to overall corporate strategy. Brad gets to be one of the first to answer our new question of "what's true today that wasn't true a year ago?" A nice lead in to our Crystal Ball question. We cover AI token pricing and having to compete with the new "AI native firms" that are spinning up from former BigLaw partners. Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Blickstein Group WWPED: What Would Private Equity Do? 2026 Law Firm COO Survey findings Law Department Operations Survey Cream, Core, and Commodity legal-work framework Legaltech Hub: The Arithmetic of AI, Tokens and Claude in Legal Work Legaltech Hub: Five Prompting Habits Costing You Tokens and Accuracy Legora introduces consumption-based pricing Kirkland & Ellis and its $500 million AI investment Anthropic Claude Code LINKSTranscript:

July 27, 2026Episode 36345 min

From AI Personas to Rogue Agents: Rethinking Legal Training, Security, and Value

Fresh from AALL in Cleveland, Greg reflects on a conference filled with legal information professionals who understand how technology performs under real working conditions. These librarians purchase products, train users, support law schools and courts, and often serve as internal advocates for legal technology. Their expertise makes vendor engagement especially valuable, yet major product announcements were scarce. Marlene balances Greg’s conference report with stories from her hiking trip through Zion and Bryce Canyon, plus a brief comparison of Ohio and Utah karaoke culture. The conversation turns to the rapid growth of innovation attorney positions across law firms and legal organizations. Greg and Marlene describe these professionals as translators who connect legal practice, technology, workflow design, and organizational change. Firms are searching beyond traditional legal career paths for people who combine technical fluency with strong interpersonal skills. For law students and junior lawyers facing uncertainty around AI, these emerging roles offer broader career options beyond the familiar associate track. Marlene explores the growing use of AI personas and simulations for professional development. Deposition witnesses, opposing counsel, negotiation partners, and drafting reviewers now appear as interactive characters with distinct goals and behaviors. Lawyers receive a place to practice, make decisions, and receive feedback before working with clients or appearing in court. Greg connects simulation-based learning with legal fiction, including his Beyond the Model series, which uses a fictional law firm to explain AI systems, business pressures, and changes in legal work. The discussion takes a serious turn with a reported AI benchmarking incident involving an agentic model, a breached sandbox, and unauthorized access to Hugging Face resources in search of an answer key. Greg and Marlene examine the episode as a warning about containment, accountability, and excessive faith in technical guardrails. From there, they consider the renewed importance of knowledge management and security as AI systems gain access to documents, financial information, client data, and institutional expertise. Greg predicts growing attention around AI harnesses, structured software layers designed to guide model behavior and produce predictable outputs. Marlene closes with examples of AI moving into client intake, business qualification, and workflow decisions, including an AI legal receptionist designed for smaller firms. The larger shift involves moving beyond simple tool adoption toward redesigned workflows, staffing models, pricing structures, and client service. Token costs are creating immediate budget pressure, while clients are questioning which AI expenses belong on their bills. Greg and Marlene argue firms must connect AI spending with legal judgment, measurable value, and responsible delivery, rather than treating consumption as a proxy for progress. Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript:

July 20, 2026Episode 36237 min

AI Is Shifting the Bottleneck: Actionstep’s Triona Buckley on Building Smarter Mid-Market Law Firms

In this episode of The Geek in Review, Greg Lambert hosts a solo conversation with Triona Buckley , Chief Product Officer at Actionstep , about generative AI’s growing influence on mid-market law firms. Buckley challenges a common assumption about legal AI: faster task completion does not always remove friction. An associate might produce a draft within seconds, only to transfer the burden upstream to a senior lawyer responsible for reviewing sources, reconstructing reasoning, and correcting mistakes. Buckley argues law firms should shift their attention from speed to systems. Standalone drafting and research tools address individual tasks, while system-level AI connects work across an entire legal matter. Embedded within everyday workflows, AI helps lawyers locate information, reduce administrative work, and preserve more time for client advice and professional judgment. The goal is a smoother operating model, rather than a collection of isolated tools producing faster documents. The conversation also examines institutional knowledge, especially within firms lacking large knowledge management or innovation teams. Buckley describes an approach where AI captures decisions, context, and reasoning as lawyers work. This creates a continuously expanding record of how the firm handles matters, advises clients, and applies professional judgment. Governance still plays a central role, including clear audit trails showing whether a person or an AI agent performed each action. Greg and Triona then explore AI as an individual tutor for junior lawyers. Remote and hybrid work have weakened the traditional apprenticeship model built around observation and informal office conversations. Drawing upon decades of firm experience, an AI tutor might question an associate’s assumptions, prompt additional research, and reinforce the firm’s preferred methods. Such systems offer structured practice while preserving the essential mentoring relationship between senior and junior lawyers. Another major theme is the hidden cost of delayed time entry. Actionstep’s Trace passive time capture technology monitors work across practice management, email, and document applications, then presents lawyers with matter-linked, billing-ready entries. More accurate records help firms recover otherwise forgotten time while producing better data for pricing, staffing, client estimates, and profitability analysis. Those insights grow more important as clients push firms toward fixed fees and output-based pricing. Buckley believes mid-market law firms hold several advantages during the AI transition. They often operate with fewer systems, maintain closer client relationships, and move through organizational change faster than larger enterprises. Success will still require disciplined implementation, trusted internal champions, connected data, and sustained attention to client service. Her message is optimistic but direct: firms with strong relationships, clean data, and a clear economic strategy will be better prepared for agentic AI and the changing business of law. Actionstep's U.S. Midsize Law Firm Priorities Report Metatags: legal AI, mid-market law firms, Triona Buckley, Actionstep, law firm innovation, AI legal training, legal practice management Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript:

July 14, 2026Episode 36155 min

Why AI Will Create More Legal Work, Not Less: Filevine's Rizner and Anderson on Research, Access, and Human Judgment

Predictions about artificial intelligence often focus on job losses and shrinking demand for lawyers. Filevine CEO and co-founder Ryan Anderson and product manager John Rizner offer a sharply different forecast. Drawing on the Jevons paradox, they argue greater efficiency will make legal services accessible to more people, encourage deeper legal research, and create work once excluded by cost. AI might reduce the effort required for individual tasks while expanding the overall volume and ambition of legal representation. The shift holds major implications for the access-to-justice gap. Faster drafting, research, and document review would allow lawyers to serve more clients without sacrificing professional judgment. Anderson expects family law, immigration, bankruptcy, criminal defense, and employment litigation to experience some of the earliest growth. Motions, witnesses, and legal theories once abandoned over expense become economically viable, although courts face their own capacity crisis as more disputes and arguments enter the system. Rizner explains how Filevine’s legal AI platform, Lois, applies machine learning to one of legal research’s oldest problems: traditional citators often return different results. Lois combines citation graphs with semantic analysis to locate opinions discussing related legal doctrines even when no direct citation connects the cases. A panel of models then evaluates potential conflicts and produces a structured memo. The goal is richer legal analysis focused on the precise holding or proposition a lawyer needs, rather than a simple flag attached to an entire opinion. Accuracy still demands disciplined human review. Filevine organizes citation verification into three levels: confirming the cited case exists, determining whether the case supports the claimed proposition, and checking whether the authority is still good law. The conversation also examines Rizner’s research into how different large language models approach efficient breach of contract. OpenAI, Google, and Anthropic models produced dramatically different recommendations, revealing embedded legal and economic preferences beneath seemingly neutral answers. The guests also explore how AI changes legal drafting, law firm economics, and the billable hour. Filevine’s acquisition of Pincites, now Lois for Word, reflects Microsoft Word’s continuing role as the shared language of legal documents, redlines, formatting, and negotiations. Efficiency does not automatically eliminate hourly billing. Lawyers might instead use saved time to produce more thoroughly researched arguments, stronger contracts, and work product approaching senior-level depth. Firms still need incentives rewarding efficiency rather than treating faster work as lost revenue. Looking ahead, Anderson and Rizner predict a proliferation of frontier and open-source models tailored to firms, individual lawyers, and specific client relationships. Legal teams will increasingly pair proprietary knowledge with selected models to produce highly specialized analysis. Yet model choice introduces jurisprudential bias, accuracy risks, and serious training concerns for junior lawyers. AI expands the range of available options, while experienced legal judgment decides which arguments deserve trust, which sources require verification, and which advice should reach the client. John Rizner Slides Filevine Primary Presentation - 2026 Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript:

July 6, 2026Episode 36045 min

Nikki Shaver on Legal AI Strategy, Agentic Governance, and Trusted Judgment

What does legal AI value look like once speed stops serving as the headline metric? In this episode of The Geek in Review , Greg Lambert and Marlene Gebauer speak with Nikki Shaver , co-founder and CEO of Legal Technology Hub and a member of the inaugural Financial Times Law 50 . Shaver argues that law firms need to move beyond time saved toward efficacy: stronger output, stronger client outcomes, and more effective legal advice. The conversation examines why the billable hour is far from finished yet no longer serves as the sole measure of legal value. Shaver compares hourly timekeeping to a taxi meter: useful for internal visibility, yet insufficient as the price signal for work transformed by AI. Workflow mapping, client discussions, and pricing discipline become central where an AI-enabled process compresses weeks of effort into hours. Corporate legal departments are adopting AI at a faster pace, bringing new pressure to outside counsel. Some in-house teams see AI as a route to keep more work inside, while others see room for firms to take on work that previously sat outside budget limits. Shaver frames the strategic question around delivering more for clients, especially in practice areas where a firm holds differentiated expertise. AI has not produced the promised empty calendar. Instead, lawyers report fuller schedules, longer documents, and a growing verification tax. Shaver flags the rise of 40-page forms, bloated redlines, and outputs that look polished yet lack sound reasoning. The episode makes a practical case for concise drafting, human review, and critical reasoning before any AI-generated material reaches a client or counterparty. Agentic AI raises the stakes. Legal Technology Hub’s AI Agents in Law Map tracks hundreds of solutions, yet governance has not kept pace with new autonomy, connectors, and downstream system access. Shaver urges firms to establish traceability, unique identifiers, risk-based human oversight, enforceable policies, and a clear view of where data travels. For firms aiming past baseline adoption, Shaver draws a line between routine personal use and strategic transformation. Daily use builds fluency, but competitive advantage grows from proprietary workflows, data foundations, client-facing collaboration spaces, and focused investment in the practices where a firm already excels. Her crystal-ball view is blunt: trusted judgment will become a scarce premium asset, AI-native firms will rise, and traditional firms will launch AI-native subsidiaries of their own. Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠ [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript: