This week on The Geek in Review, we talk with Andrew Thompson, CTO of Orbital, about why legal AI built for a specific practice area has a strong claim in a market crowded by general-purpose models. Thompson explains how Orbital focuses on real estate law, using AI, spatial intelligence, and legal workflow design to support transactions involving property portfolios, title review, survey analysis, and complex documentation. With more than 200,000 property transactions processed and a major $60 million, Series B investment fueling its U.S. expansion, Orbital sits at the center of the debate over whether the future of legal AI belongs to broad model platforms or tools built for the messy details of actual legal work.

Thompson’s path into legal technology brings a practical operator’s mindset to the conversation. Before Orbital, he worked across software, fintech, proptech, and real estate marketplaces, where speed, accuracy, and operational friction shaped business outcomes. That background informs his view that successful legal AI starts with the work itself rather than the model alone. For Orbital, the key is teaching AI to think like a real estate lawyer at the right level of abstraction, then pairing the model with domain-specific tools, data, and workflows.

The conversation gets especially interesting when Thompson walks through Orbital’s use of spatial intelligence. Real estate law often turns written legal descriptions, old maps, title documents, surveys, and boundaries into high-stakes decisions about physical land. Thompson explains the challenge of moving from words on a page to points, lines, curves, and property boundaries on a map. This leads to a broader discussion of large language models, visual language models, OCR, and classical machine learning, with Thompson making clear that the best current systems still require a toolbox rather than blind faith in one model.

We also explore Thompson’s concept of the “prompt tax,” the hidden maintenance burden created when model behavior changes faster than product teams expect. Thompson describes Orbital’s mantra of “betting on the model,” which means building for where AI capabilities are heading while still delivering value today. He separates durable domain expertise from brittle prompt tricks, arguing that legal AI companies need reusable legal knowledge, strong evaluation habits, and a willingness to rebuild assumptions as models improve.

Looking ahead, Thompson sees the impact of AI arriving faster than the standard three-to-five-year forecast. He points to software engineering as an early signal for what legal work might experience next, with professionals increasingly orchestrating humans and AI agents together. The billable hour, client value, accountability, empathy, and judgment all come under pressure as AI handles more cognitive labor. For real estate lawyers and legal technologists, Thompson’s message is direct: the winners will be those who understand the work deeply, build with technical humility, and know when the map matters as much as the document.

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Orbital CTO Andrew Thompson on Practice Area AI, Real Estate Law, and the Future of Legal Work

This week on The Geek in Review, we talk with Greg Mazares Sr., CEO of Purpose Legal, about what it takes to lead through one of the most important transition periods in legal services. Drawing on decades of experience across business, litigation support, and e-discovery, Mazares brings a steady, practical view to a market flooded with AI claims and rapid change. His message is clear from the start. The legal industry has faced major shifts before, from paper banker boxes to digital workflows, and this moment is another chapter in that longer story. Rather than treating AI as a threat, he sees it as a tool for adaptation, growth, and smarter client service.

A central theme in the conversation is Mazares’ belief that AI works best when paired with people and disciplined process. He argues that the future does not belong to technology alone, but to organizations that know how to combine tools, talent, and operational rigor. That philosophy sits behind Purpose Legal’s acquisition of Hire Counsel and its broader push to reunite technology and staffing under one roof. In Mazares’ view, clients do not simply want software. They want experienced professionals who know how to apply AI in defensible, repeatable ways that improve outcomes without sacrificing judgment.

The discussion also highlights Purpose Legal’s new offerings, including Purpose Xi and Case Optics, which aim to deliver early case insights in days rather than weeks. What makes Mazares’ framing stand out is his insistence that speed alone is not the point. Faster results matter only when paired with expert validation, tested workflows, and credible guardrails. He describes a legal market where clients once assumed AI would let them bring everything in-house, but now increasingly value outside experts who bring both technological fluency and hard-earned experience. That shift, he suggests, is raising the level of service providers from operational support teams to strategic partners embedded more deeply in legal work.

Greg and Marlene also press Mazares on data security, client trust, and the cultural pressures that come with rapid growth. Here again, his answers return to discipline and execution. He points to major investments in cloud security, around-the-clock protection teams, and tighter controls over on-site review environments. He also argues that many of the greatest risks still come from human behavior, which makes vetting, supervision, and protocol design as important as any technical control. On culture, Mazares emphasizes recognition, communication, and adaptability as the backbone of a company that wants to grow without losing its identity. For him, scaling a business is not only about revenue. It is about building a place where people feel seen, trusted, and prepared for change.

The episode closes on a thoughtful look at the next few years for litigation, junior associates, and the billable hour. Mazares predicts that junior lawyers will not disappear, but their role will shift toward becoming guides in the use of AI, both inside firms and in conversations with clients. As routine work becomes more compressed, he expects associates to provide higher-value service in fewer hours, with stronger technical fluency and a more consultative posture. It is a fitting end to an episode grounded in realism rather than hype. Mazares does not present AI as magic, and he does not dismiss its significance either. Instead, he offers a view of the future shaped by adaptability, experience, and the belief that in legal services, the winning formula still comes down to people, process, and sound judgment.

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:

Continue Reading Greg Mazares Sr. on AI, E-Discovery, and the Future of Human-Led Legal Services

This week on The Geek in Review, we talk with Gregory Mostyn, CEO of Wexler.ai, about how his company is building a sharper form of legal AI for litigation. In a market crowded with broad platforms that aim to handle every legal task at once, Mostyn describes Wexler as a focused system built for one of the hardest problems in disputes, understanding the facts. He shares how the idea grew from watching his father, a judge, carry home stacks of ring binders and spend late nights reviewing case materials by hand. That early picture of legal work, heavy with paper and pressure, became the spark for a company aimed at helping lawyers work through massive records with more depth, speed, and precision.

A central idea in the conversation is Wexler’s view that the most useful unit of analysis in litigation is not the document, but the fact. Mostyn explains that lawyers are often handed a mountain of emails, messages, filings, and exhibits, yet what they need is a clear understanding of what happened, why it matters, and where the pressure points sit. Wexler is designed to pull out events, inconsistencies, and supporting details from that record so litigators are working from a factual map rather than a pile of files. That shift matters because disputes are rarely neat. Important evidence may be tucked inside an offhand message, a late footnote, or an exchange written in vague, coded language. Wexler’s aim is to turn that mess into something a trial team can use to shape strategy.

Mostyn also walks through the mechanics that separate Wexler from more general legal AI products. He describes a detailed fact extraction pipeline that processes unstructured material and turns it into structured data before the system reasons over it. That design helps Wexler deal with the disorder of litigation, where timelines blur, people contradict each other, and key details are easy to miss. He also points to the scale of the platform, noting that it handles large document sets and supports work such as deposition preparation, trial preparation, summary judgment briefing, and early case assessment. One of the more striking features is real-time fact checking during depositions, where the platform helps lawyers spot contradictions in testimony as the questioning unfolds. The effect is less like using a search box and more like working with a tireless junior team member who has read the whole file.

Trust, accuracy, and restraint are another major part of the discussion. Mostyn is careful not to oversell what AI can do. He openly states that no system is perfect, yet he argues that Wexler reduces risk by staying inside the record given to it. It does not search the internet, does not drift into outside material, and ties its outputs back to specific text in the source documents. That discipline is important in litigation, where a made-up citation or invented fact is more than embarrassing, it is dangerous. Mostyn presents Wexler as a tool that helps lawyers verify, question, and sharpen their understanding of the case. The result is less time spent slogging through repetitive review and more time spent thinking about how to use the facts in a meaningful way.

The conversation closes on a bigger question about where this kind of technology leads the profession. Mostyn believes that as AI takes on more of the burden of document review and fact development, the value of human lawyering rises in other areas. Strategy, advocacy, witness preparation, courtroom performance, and judgment all become more important when the groundwork is assembled faster and more thoroughly. He also suggests that clients are beginning to care less about how many hours were spent reviewing documents and more about whether their lawyers are prepared, informed, and effective. For listeners interested in litigation, legal AI, and the next stage of law firm economics, this episode offers a thoughtful look at a company betting that the future belongs to tools built for depth, discipline, and the hard realities of dispute work.

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:

Continue Reading From Document Review to Fact Intelligence, Gregory Mostyn on How Wexler.ai Is Reshaping Litigation

This week we welcome back Niki Black to unpack the findings from the newly released 2026 Legal Industry Report from 8am The conversation centers on a legal profession moving into a new phase of AI adoption, where individual lawyers are embracing general purpose AI tools at a striking pace, while many firms still lack even basic policies or training. Niki explains that this disconnect is especially visible among solo, small, and mid-sized firms, where limited resources often slow formal governance even as day-to-day use rises fast.

A major theme of the discussion is the widening gap between personal experimentation and institutional readiness. Niki notes that lawyers are not waiting for permission, and many are already relying on AI to support research, drafting, and routine work. At the same time, firms are struggling to provide guidance, training, and guardrails. The episode highlights the growing risk of shadow AI in legal practice, especially when lawyers and staff turn to unsanctioned tools to keep pace with client demands. For smaller firms, the answer is not elaborate bureaucracy, but practical direction, clear expectations, and a recognition that even a modest policy is better than none.

The conversation also turns to client expectations and the economic pressure AI is placing on the traditional law firm model. Greg and Marlene press Niki on whether firms are truly ready to move away from the billable hour as AI compresses the time needed to complete legal work. Niki argues that large firms face deep structural obstacles because compensation systems, staffing models, and internal economics remain tied to hourly billing. Still, she sees pressure building from in-house counsel, boutique competitors, and smaller firms that use technology to deliver comparable work at lower cost. The result is a market that may resist change, but not escape it.

Another standout part of the episode explores how AI is reshaping access to justice. Niki points to the promise of generative AI as a force multiplier for legal aid lawyers and public defenders, especially when paired with trusted tools and better funding. She rejects the idea that technology alone will solve the justice gap, but makes a strong case that AI, combined with stronger institutional support, helps lawyers serve more people with better results. At the same time, the hosts and Niki acknowledge the risks of a two-tiered system, where wealthier clients benefit from high quality tools while vulnerable users face lower quality, error-prone outputs.

By the end of the episode, the conversation expands from AI tools to a broader structural shift across firms, clients, and law schools. Niki sees the next three to five years as a period of deep change, where pricing, training, competition, and professional expectations all evolve at once. She also shares her own methods for keeping up, including RSS feeds, trusted blogs, and LinkedIn, with a few playful complaints about Substack making life more complicated. The episode leaves listeners with a clear message: the biggest issue is no longer whether AI will affect legal practice. It already is. The real question is whether the profession can adapt fast enough to manage the consequences wisely.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Niki Black on AI Adoption, Billing Pressure, and the Governance Gap in Legal

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.

Links:

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Anastasia Boyko on Advisor Mode, Training Lawyers for the Post-Pyramid Firm

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.com
Music⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Lawyer 3.0 and the Milkshake Test: Ray Brescia on Legal AI, Client Value, and the Next Wave of Lawyering

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.com
Music⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Links
Transcript

Continue Reading Sateesh Nori Joins LawDroid: AI Tools for Access to Justice, Housing Court, and Legal Aid

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.

Sarah Glassmeyer

Niki Black

Marlene Gebauer

Greg Lambert

Transcript

Continue Reading Receipts, RAG, and Reboots: Legal Tech’s 2025 Year-End Scorecard with Niki Black and Sarah Glassmeyer

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.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading The Record, Rewired: Verbit and the Next Era of Court Reporting – JP Son and Matan Barak

This week, we talk with Gabe Pereyra, President and co-founder at Harvey, about his path from DeepMind and Google Brain to launching Harvey with Winston Weinberg; how a roommate’s real-world legal workflows met early GPT-4 access and OpenAI backing; why legal emerged as the right domain for large models; and how personal ties to the profession plus a desire to tackle big societal problems shaped a mission to apply advanced AI where language and law intersect.

Gabe’s core thesis lands hard, “the models are the product.” Rather than narrow tools for single tasks, Harvey opted for a broad assistant approach. Lawyers live in text and email, so dialog becomes the control surface, an “AI associate” supporting partners and teams. Early demos showed useful output across many tasks, which reinforced a generalist design, then productized connections into Outlook and Word, plus a no-code Workflow Builder.

Go-to-market strategy flipped the usual script. Instead of starting small, Harvey partnered early with Allen & Overy and leaders like David Wakeling. Large firms supplied layered review, which reduced risk from model errors and increased learning velocity. From there the build list grew, security and data privacy, dedicated capacity, links to firm systems, case law, DMS, data rooms, and eDiscovery. A matter workspace sits at the center. Adoption rises with surface area, with daily activity approaching seventy percent where four or more product surfaces see regular use. ROI work now includes analysis of write-offs and specialized workflows co-built with firms and clients, for example Orrick, A&O, and PwC.

Talent, training, and experience value come next. Firms worry about job paths, and Gabe does not duck that concern. Models handle complex work, which raises anxiety, yet also shortens learning curves. Harvey collaborates on curricula using past deals, plus partnerships with law schools. Return on experience shows up in recruiting, PwC reports stronger appeal among early-career talent, and quality-of-life gains matter. On litigation use cases, chronology builders require firm expertise and guardrails, with evaluation methods that mirror how senior associates review junior output. Frequent use builds a mental model for where errors tend to appear.

Partnerships round out the strategy. Research content from LexisNexis and Wolters Kluwer, work product in iManage and NetDocuments, CLM workflows via Ironclad, with plans for data rooms, eDiscovery, and billing. Vision extends to a complete matter management service, emails, documents, prior work, evaluation, billing links, and strict ethical walls, all organized by client-matter. Global requirements drive multi-region storage and controls, including Australia’s residency rules. The forward look centers on differentiation through customization, firms encode expertise into models, workflows, and agents, then deliver outcomes faster and at software margins. “The value sits in your people,” Gabe says, and firms that convert know-how into systems will lead the pack.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading The Models Are the Product: Gabe Pereyra on Building an AI Associate and Matter-Centric Workflows