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
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry 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
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Links
Transcript

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

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.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Links (as shared by Quinten):
Transcript

Continue Reading From Legal Aid to LIT Lab: Quinten Steenhuis and the Builder’s Approach to AI

[Ed. Note – We have launched The Geek in Review Substack page to put out content in a new way. One example of this content is a series of stories that I’ve been working on as I’ve learned more about how AI and automation tools are developed, and what works, and doesn’t work. As well as the improvements made as foundational models get better, or as the industry learns how to leverage the tools more effectively. Below is Chapter One of my “Beyond the Models” story where I start to dive in on why after two years of some pretty mediocre legal research tools, these tools are suddenly getting much, much better. We’ll still be posting here, but Substack gives us an interesting platform to work with that expands what we can do here on the blog. Including a lot more opportunities for us to hear from you! Come join us and see what all the Substack fuss is about. – Greg]

Beyond the Model: Part One – How Legal AI Got Smart

Preface

Any sufficiently advanced technology is indistinguishable from magic” – Arthur C. Clarke

For those of us in the legal industry, the past three years have created an enthusiasm around the practice and business of law that I’ve never seen before. The introduction of Generative AI created an immediate push into the legal industry, and legal research was seen as the most obvious and easiest candidate to be ‘fixed’ by AI. It has turned out to be one of the hardest.

I’ve spent the last three years trying to keep up. Change isn’t measured in quarterly updates, it is measured in weekly, and sometimes daily increments. Just understanding some of the basics can be challenging. So, I wanted to take a different approach to explaining some of the basics around why legal research seemed like an easy solution, and why it has taken a couple of really awful years of GenAI legal research tools before we started actually seeing some decent results.

Instead of going through all of the data and presenting information in a technical way, I took a page out of my friend Anusia Gillespie’s book and decided to explain it in stories. Storytelling might be a way for some of us to better wrap our heads around what it takes for AI to truly make sense of legal research.

Part one of the story introduces Cooper, Jesse, and Maya. A law firm innovator, a startup data scientist, and a law firm partner. The kind of people who I work with every day. We start off talking about how throwing LLMs at millions of documents of legal decisions doesn’t just work ‘out of the box.’ The near daily news articles of attorneys being sanctioned for “hallucinations” in their legal writings is a direct result of this misconception.

We needed a middle layer to connect the power of the LLM to the legal information, and for a couple of years the answer was Retrieval Augmented Generation (RAG). As you’ll learn from the story, it was a good first step but introduced some of its own problems.

I hope you enjoy this first of what I hope will be many stories of how innovation plays out in the legal field.

(Full article available on Substack)

Introduction

For the past couple of years, lawyers and technologists have marveled at how AI-powered legal research tools seem to be getting smarter every month. Tools like Lexis Protégé, Westlaw CoCounsel, and Vincent by Clio deliver answers that feel almost prescient. The assumption was simple: better foundational models like ChatGPT 5.2, Claude Opus 4.5, and Gemini 3.0 Pro equal better answers.

Continue Reading Check out our new Substack Page — Beyond the Model: How Legal AI Got Smart

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.]

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

LINKS:

CAT MOON
Vanderbilt AI Law Lab
VAILL Substack
Women + AI Summit
Practising Law Institute (PLI)
American Arbitration Association (AAA)
Legal Technology Hub

MARK WILLIAMS
Hotshot Legal
The Information
Understanding AI (Timothy B. Lee)
One Useful Thing (Ethan Mollick)
SemiAnalysis
ISO/IEC 42001 standard overview
EU AI Act (Regulation (EU) 2024/1689)
Chip War (Chris Miller, publisher page)

Transcript

Continue Reading Tiara Time and Data Center Politics: Vanderbilt’s AI Governance Playbook with Cat Moon and Mark Williams

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.

Links

Judge Schlegel, his court, and his work

AI-in-courts guidance, plus his newsletter

Deepfakes, provenance, and content credentials

  • C2PA, Coalition for Content Provenance and Authenticity, “About” page. C2PA

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 Bot Overlords, Deepfakes, and the Weight of the Robe: Judge Scott Schlegel on AI in the Courts

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 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. When an AFA starts drifting, both sides raise their hands early, instead of waiting for invoice rejection drama. When a client invests in “law firm days” that include more than relationship partners, the firm learns the business context, the work improves, and outcomes improve. 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:

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 Data First, Partner Better. Jennifer McIver on Legal Ops Benchmarks, AI Agents, and Pricing Reality Checks

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.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading From Bad Data to Better Deals: John Tertan on Narrative, Pricing, and Law Firm Relationships