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 work

• Judge Schlegel bio page. Judge Scott Schlegel

• Louisiana Fifth Circuit Court of Appeal profile page for Judge Schlegel. Fifth Circuit Court of Appeal

• Judge Schlegel’s Tech & Gavel landing page. Judge Scott Schlegel

• Tech & Gavel on Apple Podcasts. Apple Podcasts

AI-in-courts guidance, plus his newsletter

• “AI in Chambers: A Framework for Judicial AI Use” (includes the download link). Judge Scott Schlegel

• Schlegel Tech Substack newsletter. [sch]Legal Tech Substack

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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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 page
• Wolters Kluwer ELM Solutions homepage
• LegalVIEW Insights reports homepage
• LegalVIEW DynamicInsights page
• TyMetrix 360° page

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

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: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

In this episode of The Geek in Review, we welcome three powerhouse guests—Cas Laskowski, Taryn Marks, and Kristina (Kris) Niedringhaus—who are charting a bold course for Artificial Intelligence & the Future of Law Libraries. These three recently co-authored a major white paper, Artificial Intelligence and the Future of Law Libraries (pdf), which we see as less of a report and more of a call to arms. Together, we explore how law librarians can move from reactive observers of AI’s rise to proactive architects shaping its ethical and practical integration across the legal ecosystem.

Cas Laskowski, Head of Research Data and Instruction at the University of Arizona College of Law, shares how the release of ChatGPT in 2022 jolted the profession into action. Librarians everywhere were overwhelmed by the flood of information and hype surrounding AI tools. Cas’s response was to create a space for collective thinking and planning: the Future of Law Libraries initiative and a series of roundtables designed to bring professionals together for strategic collaboration. One of the paper’s most ambitious recommendations—a centralized AI organization for legal information professionals—aims to unify those efforts, coordinate training, and sustain a profession-wide vision. Cas compares the idea to data curation networks that transformed academic libraries by pooling expertise and reducing duplication of effort.

Kris Niedringhaus, Associate Dean and Director of the University of South Carolina School of Law Library, takes the conversation into education and training. She makes a compelling case that “AI-ready librarians,” much like “tech-ready lawyers,” need flexible skill-building models that recognize different levels of engagement and expertise. Drawing from the Delta Lawyer model, Kris calls for tiered AI training—ranging from foundational prompt literacy to higher-level data ethics and system design awareness. She also pushes back against the fear surrounding AI in academia, noting that students are often told not to use AI at all. We couldn’t agree more with her point that we’re doing students a disservice if we don’t teach them how to use these tools effectively and responsibly. Law firms now expect graduates to come in with applied AI fluency, and that expectation will only grow.

When we turned to Taryn Marks, Associate Director of Research and Instructional Services at Stanford Law School’s Robert Crown Law Library, the discussion moved to another key recommendation: building a centralized knowledge hub for AI-related best practices. Taryn describes how librarians are eager to share materials, lesson plans, and policy frameworks, but the current efforts are fragmented. A shared repository would “reduce duplication of effort” and allow ideas to evolve through open collaboration. It’s similar to how standardized models like SALI help the legal industry align without giving away anyone’s secret sauce. We loved this idea of a commons where librarians, educators, and technologists work together to lift the entire profession.

As we explored the broader implications, all three guests agreed that intentionality is key. Cas emphasizes that information architecture—the design of how knowledge is gathered, tagged, and retrieved—is central to AI’s success. Kris points to both the promise and peril of automated legal decision-making, warning that “done well, AI can expand access to justice; done poorly, it can amplify bias.” And Taryn envisions a future where legal information professionals are trusted collaborators across the entire lifecycle of data and decision-making.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week on The Geek in Review, Greg Lambert and Marlene Gebauer sit down to compare notes from a busy conference season. Marlene shares her experience at the American Legal Technology Awards where The Geek in Review was honored for excellence in journalism. She recounts the surreal joy of being recognized among friends and peers in legal tech, including fellow nominees like Steve Embry, and how a spontaneous speech turned out to be one of the night’s highlights. The duo reflects on how events like this underscore the sense of community that continues to define the innovation side of the legal industry.

Greg takes listeners behind the scenes at ClioCon, describing it as one of the most energetic user conferences around. He dives into his conversation with Clio CEO Jack Newton and how the company’s recent vLex acquisition signals a bold expansion into the Big Law space. With $900 million in funding, Clio appears ready to bridge the divide between small-firm technology and enterprise-level workflows. Greg also teases an illuminating hallway chat with Ed Walters, now at Clio Library (formerly Fastcase), about the major leap forward in legal research accuracy driven by improvements in RAG (retrieval-augmented generation) and vector database indexing.

Marlene offers her own takeaways from the Association of Corporate Counsel (ACC) Annual Meeting, where AI and governance dominated the agenda. She describes a landscape where in-house lawyers are wrestling with both the promise and peril of generative AI, from shadow AI concerns to data hygiene challenges. Her biggest surprise was seeing law firms themselves exhibiting at the ACC conference, signaling a shift toward direct engagement between firms and their corporate clients in shared learning spaces.

Together, Greg and Marlene unpack the emerging themes of human-centered governance, the evolving role of AI in matter management, and the race among vendors to automate core workflows without losing the human touch. From Clio’s plans to build AI-driven workflow mapping that could auto-draft documents, to Marlene’s caution about how bespoke law firm processes might resist one-size-fits-all automation, their discussion paints a picture of a profession both accelerating and self-checking at once.

The episode winds down with lighter reflections on travel mishaps, conference after-parties, and the long arc of Richard Susskind’s The End of Lawyers? conversation—still ongoing, now infused with cautious optimism about AI’s role in expanding access to justice. As always, they end where The Geek in Review thrives: at the intersection of humor, humility, and the hopeful chaos of legal innovation.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript: