The Geek In Review

In this year-end episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert are joined by legal tech experts Niki Black, Principal Legal Insight Strategist at AffiniPay, and Sarah Glassmeyer, Director of Data Curation at Legal Technology Hub, to recap the top stories of 2024. From the evolution of generative AI in legal tech to groundbreaking acquisitions, the conversation delves into the successes and challenges that shaped the year in the legal industry. The discussion kicks off with a look at AI's growing role in legal research and practice management. Greg recalls the controversial Stanford report that questioned the reliability of AI tools marketed as hallucination-free. The guests explore the importance of unbiased evaluations, the complexity of defining legal research, and the rapid pace of AI development that often outpaces regulatory and academic studies. Sarah highlights the need for peer-reviewed analysis to guide the effective use of these tools, while Niki emphasizes the user-friendly interfaces that generative AI brings to legal software. Marlene shifts the conversation toward the challenges of integrating AI into law firms’ existing frameworks. The hosts and guests discuss the hesitancy of document management systems to adopt generative AI due to trust and security concerns. Niki and Sarah examine how firms are adapting to AI by organizing data more effectively and addressing client expectations. They also reflect on the potential of AI to bridge access-to-justice gaps, with tools that empower self-represented litigants and underserved communities. The episode takes a closer look at notable mergers and acquisitions in 2024, such as Bloomberg’s acquisition of Dashboard Legal and Thomson Reuters’ purchase of SafeSign Technologies. Sarah raises concerns about the consolidation of the legal tech market, warning of diminished innovation and competition. Niki observes how cloud-based technologies have facilitated these integrations, making it easier for companies to offer comprehensive solutions that touch multiple aspects of legal practice. Wrapping up, the group forecasts trends for 2025, including regulatory developments around AI and shifting priorities within law firms regarding tech adoption. While some predictions are cautious, like Sarah’s concern over the impact of external political factors on the tech workforce, others remain optimistic about the growing sophistication of legal tech. The episode concludes with reflections on how the industry can better prepare junior lawyers and law students to navigate an increasingly AI-driven landscape. Join Marlene, Greg, Niki, and Sarah for this insightful look back at 2024 and an exciting glimpse into the year ahead. As always, we thank our listeners for tuning in, and we encourage you to share this episode with colleagues and connect with us on LinkedIn or Blue Sky! Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠   Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠   TRANSCRIPT

This week we welcome back Laura Leopard and Phil Flora from Leopard Solutions to discuss their latest innovation, the PROWESS platform. This newly launched tool aims to transform the way corporate legal departments manage and evaluate their relationships with outside counsel. As Leopard Solutions embarks on this new phase after its acquisition by SurePoint, Laura and Phil delve into how PROWESS brings unprecedented capabilities to legal teams by centralizing data, enhancing decision-making, and simplifying the selection process of legal talent. Laura explains that the PROWESS platform was born out of the need to streamline the outdated methods many in-house legal teams use to locate outside counsel. Rather than relying on personal contacts or spreadsheets, PROWESS leverages Leopard Solutions' extensive database of over 6,000 law firms to offer data-driven insights. The platform allows legal departments to search for attorneys and law firms by specialization, diversity metrics, and even billing structures, providing a comprehensive overview that helps corporate counsel make informed, strategic choices for their legal needs. One of the key features of PROWESS is its 360-degree firm report and ranking system, powered by Leopard Solutions' unique data-driven methodology. Phil explains how the platform’s rankings go beyond traditional metrics, focusing on firm growth, retention, and diversity within the attorney ranks. By incorporating continuous updates and client feedback, the ranking system serves as a real-time indicator of a firm’s standing in the market. Over time, the platform will enable in-house teams to provide feedback on engagements, further refining the rankings and enabling firms to showcase the quality of their work. The PROWESS platform also offers law firms an opportunity to proactively market their strengths. Law firms can contribute their own data to the platform, such as alternative fee arrangements and attorney billing rates, which helps them stand out in searches. Laura and Phil highlight how this “passive marketing” tool allows firms to differentiate themselves in a competitive market, as corporate clients can explore and assess options they may not have previously considered. Phil emphasizes that this feature is particularly valuable for smaller and mid-sized firms, allowing them to compete alongside larger firms by showcasing their specific expertise. In closing, Laura and Phil share their vision for the future of PROWESS. They envision it evolving into a more comprehensive marketplace, potentially allowing firms to bid on posted matters. Both are excited about the potential for increased transparency and efficiency in the legal industry as PROWESS matures, facilitating stronger relationships between law firms and in-house legal teams. With plans to integrate AI-driven features and client feedback mechanisms, Leopard Solutions is poised to shape the future of legal talent management and engagement.   Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠  

This week, we talk with a team of innovation leaders from the law firm Faegre Drinker. The guests included Shawn Swearingen, Chief Innovation Officer; David Gross, Design Lab co-founder; and Ruben Gonzalez, Design Lab Director. The discussion centered around the relaunch of Faegre Drinker's Legal Design Lab in Scottsdale, Arizona, exploring its origins, evolution, and impact on legal problem-solving. The Legal Design Lab's inception traces back eight or nine years when an associate at the firm, Helen Chacon, reconnected with her Stanford Law School friend Margaret Hagan, who was pioneering the concept of legal design. Intrigued by the idea of applying design thinking—a user-focused, empathetic approach to problem-solving long used in other industries—to the legal field, the firm embarked on a deep dive into the methodology. This included David (DJ) Gross auditing courses at Stanford's D-School and team members like Kate Rozavi designing courses on visual advocacy at the University of Minnesota Law School. The relaunch and relocation of the Design Lab to Scottsdale were influenced by several factors, notably the firm's merger that expanded its geographic footprint and the practical considerations brought about by the COVID-19 pandemic. The move allowed the firm to acquire a significantly larger and more cost-effective space. With input from architects, designers, and Margaret Hagan herself, the new lab was designed to be a flexible, creative environment featuring movable furniture and an industrial aesthetic, fostering collaboration and innovation. Throughout the podcast, the team shared concrete examples of how design thinking has been instrumental in solving complex legal challenges. One such example involved simplifying a profitability tool for lawyers by using a color-coded system akin to credit score reports, making it more accessible and actionable. Another highlighted the use of tennis balls to demystify crystallography during a jury trial, showcasing how visual aids and empathetic explanations can lead to successful outcomes. These instances underscore the lab's focus on user-centric solutions and visual advocacy to enhance understanding and efficiency in legal processes. The guests also discussed the challenges of integrating design thinking within the traditional legal framework, particularly in encouraging open-mindedness and collaborative participation among lawyers and clients. They emphasized the importance of a learning mindset, active listening, and the willingness to embrace creativity and risk-taking. To further disseminate these ideas, the team mentioned an eBook available on their website, aimed at introducing legal professionals to design thinking and visual advocacy concepts. Links: Faegre Drinker Design Lab video Faegre Drinker Picks Arizona for the Next-Gen Design Lab, American Lawyer E-book – Design Thinking and Visual Advocacy for Lawyers Two Point Oh! (FREE) Innovations in Visual Advocacy – Leading the way for design thinking in law, Harvard Law School Center on the Legal Profession.  Advancing Company Goals – Design sprints that unlock Innovation, Corporate Counsel. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠   Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠   Transcript

In this episode of The Geek in Review, hosts Greg Lambert and Marlene Gebauer, along with special co-host Toby Brown of DV8 Legal Strategies, discuss the subscription-based legal services model with Mathew Kerbis, founder of Subscription Attorney, LLC, and Jack Shelton, co-founder of Aegis Space Law. The guests share their experiences and insights on adopting a subscription-based model as an alternative to the traditional billable hour. Mathew Kerbis explains that his inspiration for transitioning to a subscription and flat fee model stemmed from the realization that many attorneys, including himself, could not afford their own billable rates. He emphasizes the importance of automating processes and leveraging technology to manage workflow and client needs efficiently, especially when offering lower-priced services. Jack Shelton, whose firm focuses on the commercial space industry, shares his motivation for adopting a subscription model. He highlights the benefits of predictability and cost transparency for clients, particularly startups and small to medium-sized businesses. Shelton also discusses the development of in-house software to streamline complex analyses and improve accuracy and record-keeping for clients. The guests explore the challenges and opportunities of scaling and sustaining a subscription-based model. Kerbis notes that the model is highly sustainable due to the predictability of monthly recurring revenue, while Shelton emphasizes the importance of refining processes and forms to ensure efficiency and effectiveness. Looking to the future, Kerbis predicts that the rapid advancement of AI and the changing nature of legal practice will lead to a significant shift in the industry within the next five years. He suggests that if big law firms do not adapt, there may be a mass exodus of young associates seeking better work-life balance and the opportunity to start their own practices. Shelton, while agreeing with Kerbis to an extent, remains cautious about predicting a flood of lawyers leaving big law due to their risk-averse nature. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠ Contact Us:  Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠ Transcript

Anastasia Boyko joins us this week for a wide-angle conversation about AI adoption, leadership, and the uncomfortable truth behind “we are watching what peer firms do.” A Yale-trained tax lawyer with experience spanning Axiom, legal education, and innovation leadership, Boyko argues that precedent-driven instincts are turning into a liability when the underlying rules of the market are shifting in real time.The episode opens with lessons from the Women + AI 2.0 Summit at Vanderbilt and the “AI competence penalty” narrative. Boyko’s central principle for law firm leaders is simple, stop copying the competition and start operating with intention. Strategic planning matters more than tool shopping, especially when uncertainty makes leaders freeze, over-index on fear, or chase noise instead of outcomes.From there, the conversation sharpens into client reality. Boyko shares what she is hearing from in-house leaders, and it is not comforting for firms. Legal departments are working to reduce dependence on outside counsel, business partners inside companies often accept “good enough,” and the models keep improving. The risk is not losing to a peer firm; it is losing the client relationship because the work stops feeling necessary.A major theme is talent and the apprenticeship gap. Boyko argues firms underinvest in people, even as they spend aggressively on software stacks. AI can help junior lawyers with coaching and confidence, but it does not replace mentorship, judgment-building, or context. The skills that matter now include client advisory, operational thinking, critical judgment, and the ability to solve problems across a complex system, not only perform discrete tasks in a vacuum.The episode closes on legal education and the future value of the JD. Boyko urges students to be selfish about learning AI, especially when faculty guidance comes from avoidance or philosophy rather than experimentation. Looking ahead, she predicts the JD’s value shifts upward, away from rote production and toward proactive advisory work, relationships, anticipatory counsel, and wisdom-driven judgment. In other words, fewer fire drills, more looking around corners.PLI - How to Navigate Law School PodcastPower Paradox webinarListen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week we go “talk show mode” for a special episode where Marlene recaps her trip to the Women + AI 2.0 Summit at Vanderbilt Law, hosted by Cat Moon, and shares why the event felt different from the standard conference grind, more energy, more structure, and yes, a DJ.The summit’s core focus sits right on a tension point in the wider AI conversation. There’s a persistent narrative that women use AI less than men. Cat Moon’s framing, if it’s true, it’s a problem, and if it’s false, it’s also a problem, sets the tone for a day built around participation and peer connection. The format uses “spark” cards, mini, midi, and maxi prompts, to push attendees into small conversations, deeper reflection, and a final takeaway.Marlene also highlights sobering research shared during the opening, including an “AI competence penalty” dynamic where identical work is judged differently depending on whether evaluators believe a man or a woman used AI. The discussion lands on why these biases matter inside legal workplaces, and what leaders and peers can do to reduce the social cost of being open about AI usage.Interspersed throughout are short interviews with attendees and speakers. Nicole Morris (Emory) captures the day’s purpose, expanding AI knowledge, talking risks, and connecting across roles. Sabra Tomb (University of Dayton School of Law) reframes AI as a leadership amplifier, moving from day-to-day management overload toward strategy and vision. Adele Shen (Vanderbilt) offers a funny but sharp taxonomy of AI “experts,” including “technocratic oracles,” “extinction alarmists,” and “touch grass humanists,” which sparks a candid side conversation about self-promotion, authority vibes, and who becomes “the story” in AI discourse.The episode closes with a look at how education and training can work better. Marlene and Greg lean into peer show-and-tell sessions, leadership modeling, and safe spaces, both governance-safe and learning-safe. A two-person segment from Suffolk Law (Chanal Neves McClain and Dyane O’Leary) adds a teaching twist, integrating AI tools into skills instruction without isolating “AI week” from real lawyering judgment. The final note comes from Stephanie Everett (Lawyerist) on the power of stories, and the reminder that people do not need to internalize the narrative someone else hands them.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ 

The billable hour has survived a lot of threats, from alternative fee arrangements to client procurement, but this episode makes the case that AI changes the pressure level. We open with a blunt assessment, time compresses, clients push back, and the old strategy of “work more to earn more” stops scaling. Enter Stefan Cisla, co-founder and CEO of Ayora, who frames the moment as less a tech problem and more an operating model problem. Law firms still place P&L accountability on individual partners who carry deep legal specialization, then ask them to moonlight as revenue managers. Stefan argues firms are starting to replace that fragile setup with tools that support decision-making across pricing, budgeting, and matter management.Stefan’s origin story is half high finance, half clinical decision science. He came out of investment banking and professional services transactions, his co-founder Dr. Gordon McKenzie came out of surgery and a PhD path tied to decision science and software. Together they pulled lessons from clinical triage and continuous improvement into the law firm context, focusing on how experts make better decisions under constraints. The hosts tease out the cultural weirdness at the center of the partnership model. Partners often take the long view for client relationships, yet short-term firm economics still take damage through write-offs, scope creep, and messy budgeting. Stefan’s pitch is reconciliation, align client-first instincts with firmer, data-backed pricing and project discipline.A core anchor for the conversation is the often-quoted $36 billion annual “value gap,” described as preventable revenue leakage tied to write-offs, weak billing practices, bad data, and poor working capital hygiene. Stefan suggests the number matters less than the trend line. AI pushes a new kind of risk, mispricing innovation. If AI reduces billable hours, firms face a squeeze between steep rate increases and client resistance, then end up forced to express value in new ways. The show leans into a spicy idea, the push to change is no longer only client-driven. Stefan sees rising pressure from inside firms, often from the CFO and operations leaders trying to fund AI investment and protect cash flows in a higher-interest-rate environment. Greg sums it up with the line, “the call is coming from inside the house.”Ayora’s product angle lands on two hard truths, pricing tools in legal have a rough track record, and law firm data quality has been a “25-year overnight problem.” Stefan explains why earlier tools struggled, low urgency when billable hours printed money, ugly underlying time and matter data, and products that were either too complex for occasional users or too simplistic for real-world exceptions. Ayora’s bet is that the data problem is solvable. Stefan describes adoption as a joint change strategy, with peers inside the firm as allies, and lots of direct conversations with lawyers to build trust in the recommendations. On the “generational gap” question, he leans toward curiosity over age. Some of their heaviest users have plenty of gray hair, and they tend to be the lawyers who care about how a practice runs. For his personal AI usage, Stefan gives an honest founder answer, meal planning for a two-year-old, automating company chores, and using AI as a sparring partner, with Notion as his favorite tool. His crystal ball point is one law firm leaders should underline twice, gross margin dynamics get messier as tech and LLM costs become part of the delivery mix, and the distance between inputs and outputs grows, driving both consolidation pressure and a new wave of innovation. [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Ayora website: ayora.aiLinks:Transcript

A fresh Anthropic announcement set off a week of market jitters and existential questions: what happens when the big model shops ship “legal productivity” features and the public markets flinch. This week, we bring Otto von Zastrow back for a rapid-response conversation, with a front-row view from New York and a blunt take: software grows cheaper to reproduce, so value migrates. The discussion lands on a key distinction, interface versus data, and why the old guard still holds leverage even as new entrants sprint.From there, the conversation zooms in on “systems of record” and the uneasy truth that the safest vault often loses mindshare when a new interface sits on top. Otto points to email, calendar, SharePoint, DMS platforms, and the growing power of a single chat workspace to become the place where work happens. The hosts press on a critical nuance for lawyers: legal research data is not flat, and “good law” demands hierarchy, treatment, and reliable citation context, not a pile of cases plus vibes.Otto frames Midpage.ai as a data company first, built on continuous court ingestion plus normalization that used to demand armies of editors. He argues AI turns messy inputs into structured repositories at a scale that favors speed and breadth, yet accuracy still requires process design and verification loops. Greg sharpens the point for litigators: the bar is not clever answers, the bar is defensible citations, negative treatment, and confidence that the record matches reality. Otto agrees on the need for trust, then flips the lens: many annotation tasks look like grind work where modern models, paired with strong QA, start to outperform large manual pipelines.The headline feature is integration via Model Context Protocol, described as a USB-C style connector for tools and models. Midpage chose distribution inside Claude and ChatGPT rather than forcing lawyers into yet another standalone site. Otto explains the wager: lawyers want fewer surfaces, and general chat platforms ship features at a pace no niche vendor matches alone, so the smart move is to meet users where daily work already lives. The demo story centers on research inside chat, with Midpage returning real case links and citations, then letting the user push deeper with uploads and follow-on tasks, while keeping verification one click away.The back half turns to second-order effects: pricing, agent spend, and the rise of “vibe” work where professionals act more like managers of agent teams than sole authors of first drafts. Marlene raises governance and liability when internal DIY tools pop up outside formal review, and Otto predicts a pendulum toward professionalized deployment plus change management. The conversation closes on Midpage’s “holy grail” topic, citators and the case relationship graph, plus a clear-eyed forecast: standalone research websites shrink as a primary workspace, while research becomes groundwork performed by agents, with lawyers spending more time interrogating results than running searches.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Ray Brescia joins The Geek in Review this week to unpack a role with peak academia vibes, Associate Dean for Research and Intellectual Life at Albany Law School. Greg frames the title as “Chief Curator of Smart People Ideas,” and Ray embraces a “player-coach” approach, coaching faculty scholarship, unblocking stalled projects, and connecting peers across disciplines. The throughline is community, research momentum, and a practical view of how ideas move from draft to impact.The conversation then pivots to the core thesis of Ray’s book, Lawyer 3.0. Ray maps the legal profession across three eras: Lawyer 1.0 as a low-barrier “amorphous bar,” Lawyer 2.0 as the institutional buildout of law schools, bar exams, ethics codes, and modern law firms, and Lawyer 3.0 as the next inflection point driven by technology. Ray ties prior shifts to urbanization, immigration, and industrial-scale commerce, then parallels those forces with today’s generative AI and analytics reshaping research, drafting, discovery, and service delivery.Ray retells the famous milkshake study, then translates the idea into legal services: clients are not shopping for “a lawyer,” clients are shopping for problem resolution. This reframing pushes law firms to examine intake, scoping, and service design through the lens of client outcomes, business problems, and life problems, not internal practice labels. The milkshake becomes a metaphor for product-market fit in law, with fewer crumbs on the steering wheel.Ray contrasts “bespoke services” with productized pathways, including a Model T style offering that meets most client needs at lower cost, plus higher-cost custom work when risk or complexity demands. Ray highlights expert-system style workflows such as Citizenshipworks, describing a TurboTax-like experience for straightforward matters, with “red flags” triggering referral to a lawyer. The same logic extends to limited scope representation and “lawyer for the day” programs in high-volume courts, where informed consent, reasonable scope, and “first, do no harm” reduce the chance of clients feeling abandoned midstream.The final stretch tackles law firm AI adoption, hallucination risk, and professional responsibility. Ray stresses minimum competence: verify cases, verify quotations, verify sources, and treat generative outputs as drafts or starting points, not final work product. The panel discusses guardrails, education, and workflow design for large firms, plus the rising reality of clients arriving with AI-generated “research.” Ray’s crystal ball points toward more commoditized legal services at scale, a latent market of underserved people, and stronger interdisciplinary collaboration between lawyers and technologists so legal education aligns with Lawyer 3.0 realities.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript

Sateesh Nori joins us on The Geek in Review for an episode that flips the usual legal innovation conversation away from law firm efficiency and toward survival-grade help for people stuck in housing courts and legal aid queues. They open with news from Sateesh himself, he has started a new role with LawDroid, working with Tom Martin, and he frames the mission in plain terms. Legal tech should stop orbiting lawyers and start serving the person with the problem, especially the person who does not even know where to begin.Sateesh traces his path into law through debate, literature, politics, and a desire to push back on a family tradition of medicine. He describes his work as a long, continuous pursuit of fairness rather than a single turning point, and he admits the early myth that drew many into the profession, the dream of dramatic courtroom advocacy. The conversation quickly lands on the core tension, the legal system sells itself as rule of law and due process, yet ordinary people experience confusion, delay, and closed doors.From there, Sateesh offers his critique of the current AI gold rush in legal. Too many products promise “faster horses” for lawyers, while the access to justice gap remains untouched because the real bottleneck sits upstream. People need early guidance, clear pathways, and tools that reduce friction before problems metastasize into crises. He argues for technology as “life-preserving tools,” not lawyer toys, and pushes the industry to center tenants, families, and workers navigating high-stakes issues without counsel.The episode gets concrete with Depositron, a tool Sateesh helped bring to life with LawDroid to help renters recover security deposits through a simple, mobile-friendly workflow. He shares back-of-the-napkin math showing how large the problem is in New York, and why small, focused tools matter at scale. Greg ties the theme to earlier Geek in Review conversations about courts as a service, with the reminder that users experience the justice system like a bureaucracy, not a public utility built for them.Finally, Sateesh expands the lens to systemic redesign, triage and intake failures, burnout in legal aid, and the hard truth that the current one-on-one model leaves most people unserved. He explores funding ideas ranging from public investment to small-fee consumer tools that sustain themselves, and he sketches future-facing concepts like AI-assisted dispute resolution to provide faster closure. In the crystal ball segment, he predicts a reckoning for the legal market as AI reshapes client expectations, with major implications for law students, staffing models, and the profession’s sense of purpose.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠LawDroidLawAnswers AIDepositronRoxanne AI (Housing Court Answers)Housing Court AnswersJosef Sateesh Nori, The Augmented Lawyer (Substack)Transcript

Quinten Steenhuis brings a builder’s mindset to legal innovation, rooted in early Indymedia activism where scavenged hardware became community infrastructure. That scrappy origin story carries through a dozen years of eviction defense at Greater Boston Legal Services, with a steady focus on tools that help people solve problems without waiting for a savior in a suit. Along the way, Quinten also lived the unglamorous side of mission tech, keeping systems funded, supported, and usable when budgets get tight and priorities get loud.The conversation then jumps to Suffolk Law’s approach to generative AI education, including a required learning track for first-year students. Quinten frames the track as foundational training, then points to a deeper bench of follow-on courses and the LIT Lab clinic where students build with real tools, real partners, and real stakes. The throughline stays consistent, exposure alone solves nothing, so Suffolk puts reps, projects, and practice behind the syllabus.A standout segment tackles the “vaporware semester” problem, where student-built prototypes fade out once finals end. The LIT Lab fights that decay by narrowing tool choices, standardizing around DocAssemble, and supervising work with a clinic-style model, staff stay close, quality stays high, and maintenance stays owned. Projects ship through CourtFormsOnline, with ongoing updates, volunteer support, and a commitment to keep public-facing legal help online for the long haul.Then the episode turns toward agentic workflows, with examples from Quinten’s consulting work in Virginia and Oregon. One project uses voice-based intake to screen for eligibility, confirm location and income, gather the story in a person’s own words, and route matters into usable categories. Another project speeds bar referral by replacing slow human triage with faster classification and better user interaction patterns, fewer walls of typing, more guided choices, more yes-or-no steps, and fewer dead ends.In the closing stretch, Quinten shares the sources feeding his learning loop, LinkedIn, Legal Services Corporation’s Innovations conference, the LSNTAP mailing list, podcasts, and Bob Ambrogi’s LawSites, plus the occasional spicy Reddit detour. The crystal ball lands on a thorny challenge for both academia and practice, training lawyers for judgment and verification when AI outputs land near-correct most of the time, then fail in the exact moment nobody expects. Quinten’s bottom line feels blunt and optimistic at once, safe workflows matter, and the public already uses general chat tools for legal help, so the legal system needs harm-reducing alternatives that work.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Suffolk Lit LabLemma LegalPipe CatLinks (as shared by Quinten):Transcript

Cat Moon and Mark Williams return to The Geek in Review wearing two hats, plus one tiara. The conversation starts at Vanderbilt’s inaugural AI Governance Symposium, where “governance” means wildly different things depending on who shows up. Judges, policy folks, technologists, in-house leaders, and law firm teams all brought separate definitions, then bumped into each other during generous hallway breaks. Those collisions led to new research threads and fresh coursework, which feels like the real product of a symposium, beyond any single panel.One surprise thread moved from wonky sidebar to dinner-table topic fast, AI’s energy appetite and the rise of data centers as a local political wedge issue. Mark describes needing to justify the topic months earlier, then watching the news cycle catch up until no justification was needed. Greg connects the dots to Texas, where energy access, on-site generation, and data-center buildouts keep lawyers busy. The point lands, AI governance lives upstream from prompts and policies, down in grids, zoning fights, and infrastructure decisions.From there, the episode pivots to training, law students, and the messy transition from “don’t touch AI” to “your platforms already baked AI into the buttons.” Mark shares how students now return from summer programs having seen tools like Harvey, even if firms still look like teams building the plane during takeoff. Cat frames the real need as basic, course-by-course guidance so students gain confidence instead of fear. Greg adds a perfect artifact from the academic arms race, Exam Blue Book sales jumping because handwritten exams keep AI out of finals, while AI still helps study through tools like NotebookLM quiz generation.Governance talk gets practical fast, procurement, contract language, standards, and the sneaky problem of feature drift inside approved tools. Mark flags how smaller firms face a brutal constraint problem, limited budget, limited time, one shot to pick from hundreds of products, and no dedicated procurement bench. ISO 42001 shows up as a shorthand signal for vendor maturity, though standards still lag behind modern generative systems. Marlene brings the day-to-day friction, outside counsel guidelines, client consent, and repeated approvals slow adoption even after a tool passes internal reviews. Greg nails the operational pain, vendors ship new capabilities weekly, sometimes pushing teams from “closed universe” to “open internet” without much warning.The closing crystal ball lands on collaboration and humility. Cat argues for a future shaped by co-creation across firms, schools, and students, not a demand-and-defend standoff about “practice-ready” graduates. Mark zooms out to the broader shift in the knowledge-work apprenticeship model, fewer beginner reps, earlier specialization pressure, and new ownership models knocking on the door in places like Tennessee. Along the way, Cat previews Women + AI Summit 2.0, with co-created content, travel stipends for speakers, workshops built around take-home artifacts, plus a short story fiction challenge to write women into the future narrative, tiara energy optional but encouraged.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

Judge Scott Schlegel of the Louisiana Fifth Circuit Court of Appeal joins The Geek in Review for a candid, funny, and unflinchingly practical conversation about AI inside the judicial system. Schlegel wears multiple hats, appellate judge, former prosecutor, reform-minded builder, plus a podcaster and Substack writer who speaks plainly about what works and what fails when technology hits real people on real timelines. The throughline stays consistent, courts do not need more hype, courts need competence, guardrails, and a process mindset.Judge Schlegel tackles the messy reality of AI disclosures, certifications, and uneven court rules across jurisdictions. His core message lands fast, judicial authority lives with the judge, not an AI system. From there, he outlines why chambers guidance matters, along with a structured, step-by-step approach for responsible drafting support, including prompt discipline and workflow thinking. The goal stays simple, faster decisions without surrendering judgment to “bot overlords.”The discussion then shifts to constraints judges live with every day, budgets, procurement rules, security anxiety, and the gap between shiny vendor demos and courthouse reality. Schlegel argues for a scrappy, process-first approach using small pilots, one chambers, one workflow, one measurable result. He compares the moment to early “cloud” adoption lessons, pay for the right security, avoid free tools where the user becomes the product, and treat sensitive records with strict care. Courts will see broader adoption as enterprise-grade options become attainable and baked into trusted platforms.Then comes the part that lingers in your head after the episode ends, deepfakes and voice cloning as a near-term threat to due process, especially in domestic violence and protective order contexts. Schlegel explains why judges tend to err on the side of safety, and why “damage done” shows up long before expert testimony arrives. His practical recommendation focuses on pretrial practice, require disclosure, surface manipulation concerns early, and reduce surprises at trial. He even shares a simple family safety habit, a private “secret word” to confirm identity during urgent calls, since voice cloning tools lower the barrier for fraud.Finally, Schlegel offers a sharp warning about confirmation bias, large language models often aim to please the user, which benefits advocates and harms neutral decision-making. His answer: an “AI alignment test” mindset, deliberate prompting, and refusal to outsource the white-page moment to a model. For the future, he points toward structural change courts rarely receive funding for, true legal technologists who redesign case management and public-facing guidance at scale. If courts stop printing emails and living in wire baskets, progress follows, and yes, somewhere in a parallel universe, Schlegel still wants a hologram machine.Judge Schlegel, his court, and his workJudge Schlegel bio page. Judge Scott SchlegelLouisiana Fifth Circuit Court of Appeal profile page for Judge Schlegel. Fifth Circuit Court of AppealJudge Schlegel’s Tech & Gavel landing page. Judge Scott SchlegelTech & Gavel on Apple Podcasts. Apple PodcastsAI-in-courts guidance, plus his newsletter“AI in Chambers: A Framework for Judicial AI Use” (includes the download link). Judge Scott SchlegelSchlegel Tech Substack newsletter. [sch]Legal Tech SubstackDeepfakes, provenance, and content credentialsC2PA, Coalition for Content Provenance and Authenticity, “About” page. C2PAListen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

The Geek in Review closes 2025 with Greg Lambert and Marlene Gebauer welcoming back Sarah Glassmeyer and Niki Black for round two of the annual scorecard, equal parts receipts, reality check, and forward look into 2026. The conversation opens with a heartfelt remembrance of Kim Stein, a beloved KM community builder whose generosity showed up in conference dinners, happy hours, and day to day support across vendors and firms. With Kim’s spirit in mind, the panel steps into the year-end ritual: name the surprises, own the misses, and offer a few grounded bets for what comes next.Last year’s thesis predicted a shift from novelty to utility, yet 2025 felt closer to a rolling hype loop. Glassmeyer frames generative AI as a multi-purpose knife dropped on every desk at once, which left many teams unsure where to start, even when budgets already committed. Black brings the data lens: general-purpose gen AI use surged among lawyers, especially solos and small firms, while law firm adoption rose fast compared with earlier waves such as cloud computing, which crawled for years before pandemic pressure moved the needle. The group also flags a new social dynamic, status-driven tool chasing, plus a quiet trend toward business-tier ChatGPT, Gemini, and Claude as practical options for many matters when price tags for legal-only platforms sit out of reach for smaller shops.Hallucinations stay on the agenda, with the panel resisting both extremes: doom posts and fan club hype. Glassmeyer recounts a founder’s quip, “hallucinations are a feature, not a bug,” then pivots to an older lesson from KeyCite and Shepard’s training: verification never goes away, and lawyers always owed diligence, even before LLMs. Black adds a cautionary tale from recent sanctions, where a lawyer ran the same research through a stack of tools, creating a telephone effect and a document nobody fully controlled. Lambert notes a bright spot from the past six months: legal research outputs improved as vendors paired vector retrieval with legal hierarchy data, including court relationships and citation treatment, reducing off-target answers even while perfection stays out of reach.From there, the conversation turns to mashups across the market. Clio’s acquisition of vLex becomes a headline example, raising questions about platform ecosystems, pricing power, and whether law drifts toward an Apple versus Android split. Black predicts integration work across billing, practice management, and research will matter as much as M&A, with general tech giants looming behind the scenes. Glassmeyer cheers broader access for smaller firms, while still warning about consolidation scars from legal publishing history and the risk of feature decay once startups enter corporate layers. The panel lands on a simple preference: interoperability, standards, and clean APIs beat a future where a handful of owners dictate terms.On governance, Black rejects surveillance fantasies and argues for damage control, strong training, and safe experimentation spaces, since shadow usage already happens on personal devices. Gebauer pushes for clearer value stories, and the guests agree early ROI shows up first in back office workflows, with longer-run upside tied to pricing models, AFAs, and buyer pushback on inflated hours. For staying oriented amid fractured social channels, the crew trades resources: AI Law Librarians, Legal Tech Week, Carolyn Elefant’s how-to posts, Moonshots, Nate B. Jones, plus Ed Zitron’s newsletter for a wider business lens. The crystal ball segment closes with a shared unease around AI finance, a likely shakeout among thinly funded tools, and a reminder to keep the human network strong as 2026 arrives. 

For decades, “the record” has meant one thing: a text transcript built by skilled stenographers, trusted by courts, and treated as the backbone of due process. In this episode of The Geek in Review, Marlene Gebauer and Greg Lambert sit down with JP Son, Verbit’s Chief Legal Officer, and Matan Barak, Head of Legal Product, to talk about what happens when a labor shortage, rising demand, and better speech technology collide. Verbit has been in legal work since day one, supporting court reporting agencies behind the scenes, but their latest push aims to modernize the full arc of proceedings, from depositions through courtroom workflows, with faster turnaround and more usable outputs.A core tension sits at the center of the conversation: innovation versus legitimacy. Marlene presses on whether digital records carry the same defensibility as stenographic ones, and JP frames Verbit’s posture as support, not replacement. Verbit is not a court reporting agency; their angle is tooling that helps certified professionals and agencies produce better outcomes, including real-time workflows that once required heavy manual effort. The result is less “robots replace reporters” and more “reporters with better gear,” which feels like the only way this transition avoids an industry food fight in every courthouse hallway.From there, the discussion shifts into the practical, lawyer-facing side: LegalVisor as a “virtual second chair.” JP describes it as distinct from the official transcript, a real-time layer built to surface insights, track progress, and support strategy while the deposition is happening. Matan adds the design story, discovery work, shadowing, and interviews to build for what second chairs are already doing, hunting inconsistencies, chasing exhibits, and keeping the outline on track. A key theme: the transcript is not going away, because lawyers still rely on it for clients, remote teammates, and quick backtracking, but the value climbs when the transcript turns into a live workspace with search, references, and outline coverage in front of you while testimony unfolds.Accuracy and trust show up as recurring guardrails. Greg pokes at the “99 percent accurate” claims floating around the market, and Matan makes the point every litigator appreciates, the missing one percent contains the word that flips meaning. Verbit’s “human in the loop” posture and its Captivate approach focus on pushing accuracy toward the level legal settings require, including case-specific preparation by extracting names and terms from documents to tune recognition in context. The episode also tackles confidentiality head-on, with JP drawing a hard line: Verbit does not use client data to train generative models, and they keep business pipelines separate across verticals.Finally, the crystal ball question lands where courts love to resist, changing the definition of “the record.” Marlene asks whether the future record becomes searchable, AI-tagged video rather than text-first transcripts. JP says not soon, pointing to centuries of text-based infrastructure and the slow grind of institutional acceptance. Matan calls the shift inevitable, arriving in pieces, feature by feature, so the system evolves without pretending it is swapping the engine mid-flight. Along the way, there are glimpses of what comes next, including experiments borrowing media tech, such as visual description to interpret behavior cues in video. The big takeaway feels simple: the record stays sacred, but the work around it no longer needs to stay stuck.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week on The Geek in Review, we sit down with Jennifer McIver, Legal Ops and Industry Insights at Wolters Kluwer ELM Solutions. We open with Jennifer’s career detour from aspiring forensic pathologist to practicing attorney to legal tech and legal ops leader, sparked by a classic moment of lawyer frustration, a slammed office door, and a Google search for “what else can I do with my law degree.” From implementing Legal Tracker at scale, to customer success with major clients, to product and strategy work, her path lands in a role built for pattern spotting, benchmarking, and translating what legal teams are dealing with into actionable insights.Marlene pulls the thread on what the sharpest legal ops teams are doing with their data right now. Jennifer’s answer is refreshingly practical. Visibility wins. Dashboards tied to business strategy and KPIs beat “everything everywhere all at once” reporting. She talks through why the shift to tools like Power BI matters, and why comfort with seeing the numbers is as important as the numbers themselves. You cannot become a strategic partner if the data stays trapped inside the tool, or inside the legal ops team, or inside someone’s head.Then we get into the messy part, which is data quality and data discipline. Jennifer points out the trap legal teams fall into when they demand 87 fields on intake forms and then wonder why nobody enters anything, or why every category becomes “Other,” also known as the graveyard of analytics. Her suggestion is simple. Pick the handful of fields that tell a strong story, clean them up, and get serious about where the data lives. She also stresses the role of external benchmarks, since internal trends mean little without context from market data.Greg asks the question on everyone’s bingo card, what is real in AI today versus what still smells like conference-stage smoke. Jennifer lands on something concrete, agentic workflows for the kind of repeatable work legal ops teams do every week. She shares how she uses an agent to turn event notes into usable internal takeaways, with human review still in the loop, and frames the near-term benefit as time back and faster cycles. She also calls out what slows adoption down inside many companies, internal security and privacy reviews, plus AI committees that sometimes lag behind the teams trying to move work forward.Marlene shifts to pricing, panels, AFAs, and what frustrates GCs and legal ops leaders about panel performance. Jennifer describes two extremes, rigid rate programs with little conversation, and “RFP everything” process overload. Her best advice sits in the middle, talk early, staff smart, and match complexity to the right team, so cost and risk make sense. She also challenges the assumption that consolidation always produces value. Benchmarking data often shows you where you are overpaying for certain work types, even when volume discounts look good on paper.We close with what makes a real partnership between corporate legal teams and firms, and Jennifer keeps returning to two themes, communication and transparency, with examples. Jennifer’s crystal ball for 2026 is blunt and useful, data first, start the hard conversations now, and take a serious look at roles and skills inside legal ops, because the job is changing fast.Links:Jennifer McIver’s LinkedIn pageWolters Kluwer ELM Solutions homepageLegalVIEW Insights reports homepageLegalVIEW DynamicInsights pageTyMetrix 360° pageListen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

In this episode of The Geek in Review, we sit down with Narrative founder John Tertan to talk about law firm pricing, messy data, and why substance matters more than shiny tools. We pick up from our first meeting at the Houston Legal Innovators event, where John had the pricing and KM crowd buzzing, and ask what he is hearing from those teams as they look toward 2026. John explains how Narrative focuses on “agentifying” business-of-law work, starting with pricing and analytics, so firms stop guessing and start grounding decisions in better data. The goal is simple, improve decisions for pricing teams, finance, marketing, and partners who want to win work that also makes financial sense.John walks through the pain points that drive firms to seek out Narrative, from low realization and high write-offs to tedious non-billable work and a lack of trust in the data behind pitches and budgets. Many firms track key metrics in scattered spreadsheets, checked once in a while rather than used as a daily guide for strategy. Narrative steps into that gap by improving the accuracy of historical matter data, identifying the right reference matters for new proposals, and supporting alternative fee structures. John explains how this foundation supports better scoping, more confident pricing conversations, and far stronger alignment between firm goals and client expectations.We also dive into John’s founder journey, which runs from Freshfields associate to innovation work, then through venture-backed tech in other sectors before returning to legal. That mix of big law, startup experience, and prior success with HeyGo shapes how he builds Narrative. John talks about serving “mature customers” who expect more than a slick interface, they expect real understanding of their business, their politics, and their constraints. Relationships sit at the center of his approach, not only with clients and prospects, but also with advisors, former firm leaders, and legal tech veterans who guide both product and go-to-market strategy.The name “Narrative” is no accident, and John explains why time entry narratives sit at the heart of his product. Those lines of text describe what lawyers did, for whom, and why, yet they often sit underused in billing systems. Narrative improves and structures that data, then uses it to highlight scope, track what remains in or out of scope, and surface early warnings when matters drift away from the original plan. John talks through the life cycle, from selecting comparable matters, through modeling AFAs and scenarios, to monitoring work in progress and feeding lessons back into future pricing efforts. Along the way, better transparency supports stronger trust between partners and clients.We close by asking John to look ahead. He shares his view on how firms will move toward more sophisticated pricing models and better measurement, while the billable hour continues to evolve rather than vanish overnight. Stronger baselines, cleaner matter histories, and better tracking create room for fee caps, success components, and other structures that clients want to sell internally. John also shares how he stays informed through alerts, networks, and a new chief of staff who helps turn those insights into resources for pricing and finance professionals. For listeners who want to learn more or follow Narrative’s work, John points them to narrativehq.com and invites outreach from anyone wrestling with data, pricing, or margin questions inside their own firm.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week on The Geek in Review, we bring together a trio of Canadian legends from the legal web to celebrate the 20th anniversary of the Canadian Law Blog Awards, better known as the Clawbies. Steve Matthews of STEM Legal and Slaw.ca, Sarah Sutherland of Parallax Information Consulting and former president and CEO of CanLII, and legal market analyst and Substack author, Jordan Furlong join us to talk about how legal publishing has changed over two decades and where it heads next. Along the way, we share a little host pride, since 3 Geeks and a Law Blog picked up a Friend of the North Clawbies back in 2011. Canada remembers, even if the trophy cabinet looks a little full on our side of the border.We start with Steve’s long-running mantra: do not build your professional home on rented land. For years he pushed lawyers toward blogs and owned domains, warning that social platforms could change rules overnight or simply fall apart. That warning came into sharp focus as Twitter morphed into X and law Twitter scattered toward BlueSky, Mastodon, Threads and other venues. Jordan talks about deleting years of tweets rather than leaving a personal archive tied to a platform he no longer trusts, then describes how his own publishing shifted from long-form blogging at Law21 to a Substack newsletter model that feels more like a curated living room of engaged readers than a noisy town square.From there, Sarah introduces one of our favorite phrases in the episode, “law’s eternal September,” where a constant wave of new technology, including generative AI, keeps the justice system and the information world in permanent transition. We explore how legal publishers now balance automation and human judgment, with AI helping on classification, annotations, and summaries, while editors and authors still play a central role in verification and context. We share our own experience with AI-assisted prep for the show, and how a human guest had to correct outdated biographical details. That leads to a broader point about the need for trusted, non-AI sources that give researchers, lawyers, and readers a place to check facts and assumptions before sharing work with clients or the public.Jordan, Steve, and Sarah then turn to the Clawbies themselves and the theme they have set for the upcoming awards year: “the year of the truth teller.” In an era of disinformation, sloppy AI content, and reputation-damaging LinkedIn posts, lawyers and legal professionals gain real value by standing out as accurate, consistent voices who care about community as much as client work. Steve explains how the Clawbies now cover blogs, newsletters, podcasts, Tik Toks, and other formats, while still focusing on authenticity and public legal education. We also learn about the “humble Canadian rule,” where nominators highlight one to three other voices, while the organizers quietly take a closer look at the nominator’s own work in the background. The mission stays the same: surface new voices, new formats, and generous contributors who strengthen public conversation.We close with a look ahead. Steve predicts more structured, list-driven use of newer platforms like BlueSky for targeted conversations, while Sarah points to growing centralization as giants such as Thomson Reuters, LexisNexis, and Clio blend publishing and practice software. Jordan sees a fractured present, with silos and distrust, but also anticipates a future pull toward recombination, where readers gravitate to sources and bundles that feel trustworthy again. Through it all, the three guests encourage anyone interested in writing, podcasting, or other media to choose a format that fits personal strengths, commit to thoughtful output, and focus on truth-telling over pure marketing.[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week we welcome Jiyun Hyo, co-founder and CEO of Givance, for a conversation about moving legal AI past shiny summaries toward verified work product. Jiyun’s path runs from Duke robotics, where layered agents watched other agents, to clinical mental health bots, where confident errors carry human cost. Those lessons shape his view of legal tools today: foundation models often answer like students guessing on a pop quiz, sounding sure while drifting from fact.A key idea is the “last ten percent gap.” Many systems reach outputs that look right on first pass yet slip on a few crucial details. In low-stakes tasks, small misses are a nuisance. In litigation, one missing email or one misplaced time stamp risks ruining trust and admissibility. Jiyun adds a second problem: when users ask for a tiny correction, models tend to rebuild the whole output, so precision edits become a loop of fixes and new breakage.Givance aims at that gap through text-to-visual evidence work. The platform turns piles of documents into interactive charts with links back to source files. Examples include Gantt charts for personnel histories, Sankey diagrams for asset flows, overlap views for evidence exchanges, and timelines that surface contradictions across thousands of records. Jiyun shares early law-firm use: rapid fact digestion after a data dump, clearer client conversations around case theory, and courtroom visuals that help judges and juries follow a sequence without sketching their own shaky diagrams.Safety, supervision, and security follow naturally. Drawing on robotics, Jiyun argues for a live supervisory layer during agentic workflows so alerts surface while negotiations or analyses unfold rather than days later. Too many alerts, though, create noise, so tuning confidence thresholds becomes part of product design. On security, Givance works in isolated environments, strips identifiers before model calls, and keeps architecture model-agnostic so newer systems slot in without reopening privacy debates.The episode ends on market dynamics and the near future. Jiyun sees mega-funded text-first platforms as market openers, normalizing AI buying and leaving room for second-wave multimodal tools. Asked whether the search bar in document review fades away, he expects search to stick around for a long while because lawyers associate a search box with control, even if chat interfaces improve. The bigger shift, in his view, lies in outputs, more interactive visuals that help legal teams spot gaps, test case stories, and present evidence with clarity.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

We recorded this episode live at the TLTF Summit and the energy in the room made it feel like the perfect place for a conversation about growth, training, and the rapid climb of legal tech. We grabbed our gear, claimed a corner in the podcast room, and pulled in two guests with front row seats to the changes hitting the industry. Joining us were Kyle Poe from Legora and our friend and guest host, Zena Applebaum of Harbor. The Summit attracts a focused group of founders, investors, and leaders, and the four of us jumped straight into what this event represents and what attendees hope to get from it.Kyle had been on the job for only two months, but Legora moves at a pace that feels closer to dog years. In that short time the team doubled, a new round of funding closed, and the company introduced a major product release. Kyle walked us through Legora’s new Portal experience, which brings clients inside the legal workflow in a controlled, collaborative environment. Instead of long email chains and static work product, the Portal supports shared editing, direct review of diligence work, and a more responsive model for client engagement. In an era when clients expect quick turnarounds, this shift sets up a new dynamic for firms.Zena added helpful perspective from her prior trips to TLTF. She described the Summit as a place that rewards conversation, curiosity, and hallway exchanges. It is also a place to study the different stages of the legal tech journey, from early ideas on the startup stage to the seasoned players on the scale stage. She also brought timely news of Harbor’s acquisition of Encore Technologies, a move that strengthens Harbor’s ability to support training and adoption workflows across firms and corporate legal teams. Her focus on education paired well with Kyle’s insights on how Legora approaches enablement through its team of legal engineers.Training became the heart of the conversation. We compared old habits with the expectations of a generation of associates who have been taught to avoid AI until they enter a firm. Kyle stressed the need to anchor attorney training in real use cases and to give them early wins so they build trust in the tools. He described the shift from task-based training to workflow-based thinking. We also talked about how AI is influencing both the pace and structure of client service. Kyle shared examples of how Legora uses prior work product to build integrated workflows, such as interrogatory response generators that pull from a full library of past responses. This not only speeds up production but also increases consistency and helps attorneys understand the reasoning behind revisions. Zena pushed the idea even further, noting that these systems give associates a chance to study the rationale behind changes in a way that human reviewers rarely have time to provide. This leads to better training and stronger validation of the final work product.We closed with our crystal ball question. Kyle sees more adoption on the horizon but also anticipates uneven impacts across different practices as firms figure out how to adjust their business models. Zena pointed to the operational challenges ahead, especially the pressure to invest in data management and cloud infrastructure that supports true AI enablement. Her message was clear. If firms want the benefits later, they need to start organizing the foundations now. This episode blends optimism with realism, and it highlights the practical work ahead for firms, vendors, and everyone in between. Tune in for the full conversation and get ready for a lively discussion recorded right in the middle of the Summit buzz.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠