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(See Day Two Coverage for the In-House Programs over on The Geek in Review Substack page – GL)

Day One of Texas Trailblazers in Dallas had a different tone than most legal tech conferences I attend. The conversations stayed close to the work. Less speculation, more discussion about what people are doing right now, where it is working, and where it is breaking.

Organized by Cosmonauts in partnership with LegalOps.com and held at The Statler Dallas, the Private Practice Day brought together law firm leaders, legal operations professionals, and technology vendors for a full day of keynotes, panels, and product demos. Joy Heath Rush, CEO of ILTA, chaired the day and opened with a fireside on the new era of conversations between general counsel and outside counsel. Her framing set the tone: AI is living at the intersection of business and technology, and it is creating conversations that simply did not exist two years ago.

Across the sessions and hallway conversations that followed, a few themes kept showing up. They were consistent whether the speaker came from a law firm, an in-house team, or a vendor building the tools.

Trust in AI is becoming a workflow problem

Rowan McNamee, Co-Founder and COO of Mary Technology, opened the sponsor keynote with a point that came up repeatedly throughout the day. AI outputs are persuasive. They read well. They look complete. That creates a tendency to move forward without enough friction in the process.

McNamee cited a recent study on what researchers call “cognitive surrender,” based on the work of Sean Hay and building on the framework in Thinking, Fast and Slow. Under time pressure, people rely on AI even when they know they should verify the result. In a series of experiments, override rates improved from 20% to 42% when participants had real money on the line. Even then, more than half still followed the AI’s answer. “You can reduce it, but you can’t eliminate it just by telling people to be careful,” McNamee noted.

In a legal setting, the implication is straightforward. Review cannot be optional. It has to be built into the process in a way that does not depend on someone remembering to slow down.

That concern echoed later in the day during the panel I moderated. Laura Ewing-Pearle, Senior Manager of eDiscovery and Practice Support Technology at Baker Botts, described a clear split even among e-discovery practitioners who are enthusiastic about AI. They lean heavily toward document interrogation and querying. They are far less comfortable with AI making responsiveness calls, and they are “definitely not comfortable with AI making privilege calls.” The line between assistance and reliance is still being worked out in real time.

Adding urgency to the conversation, panelists referenced a recent New York case in which a court ruled that AI-generated legal advice obtained through a public tool was not protected by attorney-client privilege. The ruling was specific to a consumer-facing chatbot, but the message landed clearly: enterprise AI tools with proper security and licensing are becoming a matter of professional risk management.

Adoption follows incentives, not access

The panel on Culture, Change, and Collaboration brought together Emma Dowden of Burges Salmon, Thom Wisinski of Haynes Boone, Kelley Lugo of Bryan Cave Leighton Paisner, Rowan McNamee, and Tammy Covert of Nachawati. The discussion stayed focused on what actually drives adoption inside organizations.Continue Reading What I Took Away from Texas Trailblazers

This week we welcome Paula Reichenberg, founder of Neuron, for a sharp and thoughtful conversation about legal translation, artificial intelligence, and what happens when professional expertise collides with tools that look polished but still miss the mark. Paula shares her path from M&A and capital markets law into business school, legal services, machine learning, and finally legal tech entrepreneurship. What started as frustration with inefficiencies inside law firms grew into a translation business, then evolved again as machine translation improved and forced a harder question about survival, adaptation, and quality.

Paula explains how her early company, Hieronymus, found success by handling sensitive, high-stakes legal translations in Switzerland, especially where precision and confidentiality mattered most. But as machine translation improved, the market for average work started to disappear. Clients began doing more on their own, leaving only the hardest, highest-value assignments for specialists. Rather than ignore the shift, Paula leaned into it. That decision led her back to university, into data science and machine learning, and toward building Neuron, a company focused less on replacing expertise and more on improving the process around imperfect AI output.

A central theme of the discussion is the uncomfortable truth that many users do not care as much about excellence as professionals do. Paula makes the point with refreshing honesty. AI often produces work that is mediocre, but for a large share of users, mediocre is enough. That creates both a market shift and a professional dilemma. In legal translation, as in legal drafting more broadly, the issue is rarely whether AI produces something flawless. The issue is whether the user notices what is wrong, has the time to fix it, and has the systems in place to improve the result efficiently. Paula argues that the real value is not in claiming perfection. It is in helping experts find the mistakes faster, correct them with less pain, and avoid wasting hours doing work that feels like cleanup on aisle five.

The conversation also digs into trust, user behavior, and the strange authority people give to AI-generated answers. Paula recounts how, in one negotiation, a party trusted ChatGPT’s answer more than a human tax lawyer’s detailed explanation, even when the AI response was wrong. That anecdote opens up a broader discussion about confidence, presentation, and why polished outputs often feel more persuasive than expert judgment. Greg and Marlene connect that idea to legal systems, translation quality, and access to justice, especially where technology might offer better service than overworked and underfunded human systems. The result is not a simple pro-AI or anti-AI position. It is a grounded look at where human excellence still matters, where automation fills gaps, and where the future may split between mass-market convenience and premium, highly tailored expertise.

Looking ahead, Paula sees consolidation coming to legal tech, along with a growing push toward seamless interfaces that bring best-in-class features into one place. For Neuron, that means becoming an embedded layer inside other legal tools rather than forcing lawyers to juggle yet another standalone platform. Her crystal ball view is both stylish and sobering. She compares the future of legal services to retail and fashion, with more ready-to-wear solutions for everyday needs and a smaller, more exclusive market for bespoke legal work. It is a vivid way to frame what may be coming. The legal industry is not simply moving toward automation. It is sorting itself into tiers of service, quality, and expectation. And if Paula is right, the future belongs to those who understand where “good enough” ends and where true expertise still earns its premium.

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

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

Continue Reading From Translation to Transformation: Paula Reichenberg on AI, Legal Quality, and the Future of Good Enough

This week we go “talk show mode” for a special episode where Marlene recaps her trip to the Women + AI 2.0 Summit at Vanderbilt Law, hosted by Cat Moon, and shares why the event felt different from the standard conference grind, more energy, more structure, and yes, a DJ.

The summit’s core focus sits right on a tension point in the wider AI conversation. There’s a persistent narrative that women use AI less than men. Cat Moon’s framing, if it’s true, it’s a problem, and if it’s false, it’s also a problem, sets the tone for a day built around participation and peer connection. The format uses “spark” cards, mini, midi, and maxi prompts, to push attendees into small conversations, deeper reflection, and a final takeaway.

Marlene also highlights sobering research shared during the opening, including an “AI competence penalty” dynamic where identical work is judged differently depending on whether evaluators believe a man or a woman used AI. The discussion lands on why these biases matter inside legal workplaces, and what leaders and peers can do to reduce the social cost of being open about AI usage.

Interspersed throughout are short interviews with attendees and speakers. Nicole Morris (Emory) captures the day’s purpose, expanding AI knowledge, talking risks, and connecting across roles. Sabra Tomb (University of Dayton School of Law) reframes AI as a leadership amplifier, moving from day-to-day management overload toward strategy and vision. Adele Shen (Vanderbilt) offers a funny but sharp taxonomy of AI “experts,” including “technocratic oracles,” “extinction alarmists,” and “touch grass humanists,” which sparks a candid side conversation about self-promotion, authority vibes, and who becomes “the story” in AI discourse.

The episode closes with a look at how education and training can work better. Marlene and Greg lean into peer show-and-tell sessions, leadership modeling, and safe spaces, both governance-safe and learning-safe. A two-person segment from Suffolk Law (Chanal Neves McClain and Dyane O’Leary) adds a teaching twist, integrating AI tools into skills instruction without isolating “AI week” from real lawyering judgment. The final note comes from Stephanie Everett (Lawyerist) on the power of stories, and the reminder that people do not need to internalize the narrative someone else hands them.

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

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

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

Transcript

Continue Reading Women + AI Summit, Real Talk: Leadership, Learning, and Not Letting “The Trap” Write Your Story

The billable hour has survived a lot of threats, from alternative fee arrangements to client procurement, but this episode makes the case that AI changes the pressure level. We open with a blunt assessment, time compresses, clients push back, and the old strategy of “work more to earn more” stops scaling. Enter Stefan Cisla, co-founder and CEO of Ayora, who frames the moment as less a tech problem and more an operating model problem. Law firms still place P&L accountability on individual partners who carry deep legal specialization, then ask them to moonlight as revenue managers. Stefan argues firms are starting to replace that fragile setup with tools that support decision-making across pricing, budgeting, and matter management.

Stefan’s origin story is half high finance, half clinical decision science. He came out of investment banking and professional services transactions, his co-founder Dr. Gordon McKenzie came out of surgery and a PhD path tied to decision science and software. Together they pulled lessons from clinical triage and continuous improvement into the law firm context, focusing on how experts make better decisions under constraints. The hosts tease out the cultural weirdness at the center of the partnership model. Partners often take the long view for client relationships, yet short-term firm economics still take damage through write-offs, scope creep, and messy budgeting. Stefan’s pitch is reconciliation, align client-first instincts with firmer, data-backed pricing and project discipline.

A core anchor for the conversation is the often-quoted $36 billion annual “value gap,” described as preventable revenue leakage tied to write-offs, weak billing practices, bad data, and poor working capital hygiene. Stefan suggests the number matters less than the trend line. AI pushes a new kind of risk, mispricing innovation. If AI reduces billable hours, firms face a squeeze between steep rate increases and client resistance, then end up forced to express value in new ways. The show leans into a spicy idea, the push to change is no longer only client-driven. Stefan sees rising pressure from inside firms, often from the CFO and operations leaders trying to fund AI investment and protect cash flows in a higher-interest-rate environment. Greg sums it up with the line, “the call is coming from inside the house.”

Ayora’s product angle lands on two hard truths, pricing tools in legal have a rough track record, and law firm data quality has been a “25-year overnight problem.” Stefan explains why earlier tools struggled, low urgency when billable hours printed money, ugly underlying time and matter data, and products that were either too complex for occasional users or too simplistic for real-world exceptions. Ayora’s bet is that the data problem is solvable. Their system uses large language models plus proprietary approaches, including work-type ontologies, to extract signal from messy time narratives and matter metadata. The goal is consistent fields and usable categorization across tasks and phases, even when client taxonomies differ. Stefan claims field-level reconstruction and normalization at high accuracy, enough to power a chatbot-style interface that generates a pricing proposal in roughly 90 to 120 seconds by finding precedent matters and adapting them to the new scope.

The conversation closes on the part everyone in a partnership feels in their bones, culture beats software. Moving away from the billable hour is not only a finance shift, it is an identity shift, habit shift, and trust shift. Stefan describes adoption as a joint change strategy, with peers inside the firm as allies, and lots of direct conversations with lawyers to build trust in the recommendations. On the “generational gap” question, he leans toward curiosity over age. Some of their heaviest users have plenty of gray hair, and they tend to be the lawyers who care about how a practice runs. For his personal AI usage, Stefan gives an honest founder answer, meal planning for a two-year-old, automating company chores, and using AI as a sparring partner, with Notion as his favorite tool.His crystal ball point is one law firm leaders should underline twice, gross margin dynamics get messier as tech and LLM costs become part of the delivery mix, and the distance between inputs and outputs grows, driving both consolidation pressure and a new wave of innovation.

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 Revenue Leakage, Metadata, and the Post Billable Hour Playbook, Stefan Ciesla of Ayora

A fresh Anthropic announcement set off a week of market jitters and existential questions: what happens when the big model shops ship “legal productivity” features and the public markets flinch. This week, we bring Otto von Zastrow back for a rapid-response conversation, with a front-row view from New York and a blunt take: software grows cheaper to reproduce, so value migrates. The discussion lands on a key distinction, interface versus data, and why the old guard still holds leverage even as new entrants sprint.

From there, the conversation zooms in on “systems of record” and the uneasy truth that the safest vault often loses mindshare when a new interface sits on top. Otto points to email, calendar, SharePoint, DMS platforms, and the growing power of a single chat workspace to become the place where work happens. The hosts press on a critical nuance for lawyers: legal research data is not flat, and “good law” demands hierarchy, treatment, and reliable citation context, not a pile of cases plus vibes.

Otto frames Midpage.ai as a data company first, built on continuous court ingestion plus normalization that used to demand armies of editors. He argues AI turns messy inputs into structured repositories at a scale that favors speed and breadth, yet accuracy still requires process design and verification loops. Greg sharpens the point for litigators: the bar is not clever answers, the bar is defensible citations, negative treatment, and confidence that the record matches reality. Otto agrees on the need for trust, then flips the lens: many annotation tasks look like grind work where modern models, paired with strong QA, start to outperform large manual pipelines.

The headline feature is integration via Model Context Protocol, described as a USB-C style connector for tools and models. Midpage chose distribution inside Claude and ChatGPT rather than forcing lawyers into yet another standalone site. Otto explains the wager: lawyers want fewer surfaces, and general chat platforms ship features at a pace no niche vendor matches alone, so the smart move is to meet users where daily work already lives. The demo story centers on research inside chat, with Midpage returning real case links and citations, then letting the user push deeper with uploads and follow-on tasks, while keeping verification one click away.

The back half turns to second-order effects: pricing, agent spend, and the rise of “vibe” work where professionals act more like managers of agent teams than sole authors of first drafts. Marlene raises governance and liability when internal DIY tools pop up outside formal review, and Otto predicts a pendulum toward professionalized deployment plus change management. The conversation closes on Midpage’s “holy grail” topic, citators and the case relationship graph, plus a clear-eyed forecast: standalone research websites shrink as a primary workspace, while research becomes groundwork performed by agents, with lawyers spending more time interrogating results than running searches.

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

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

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

Transcript

Continue Reading Midpage Goes Native: Legal Research Inside Claude and ChatGPT, with Otto von Zastrow

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.

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[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

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

The promise of generative artificial intelligence (AI) in legal practice is seductive: speed up document review, contract drafting, legal research, and thereby shave down hours billed. Yet the reality for many law firms is different. A recent survey by the Association of Corporate Counsel (ACC) and Everlaw found that nearly 60% of in-house counsel reported…

Few people understand the intersection of legal practice, data analytics, and diversity like Catherine Krow, Managing Director of Diversity and Impact Analytics at BigHand. In this episode of The Geek in Review, hosts Greg Lambert and Marlene Gebauer sit down with Krow to trace her journey from a high-powered trial lawyer to an influential legal tech leader. After seventeen years at firms like Orrick and Simpson Thacher, Krow’s turning point came when a client challenged her team’s billing after a major courtroom victory—a moment that sparked her mission to fix what she calls the “business of law.”

That single moment led to the creation of Digitory Legal, a company designed to give law firms the data and transparency they desperately needed but didn’t yet value. Krow describes how her framework—plan, measure, refine—became the basis for improving cost predictability and strengthening client trust. When BigHand acquired Digitory Legal in 2022, Krow’s vision found a larger stage. Now, her “data refinery” powers better pricing, resource allocation, and even equity within firms. As she explains, clean data doesn’t only improve profitability, it reveals hidden inequities in work allocation and helps firms retain their most promising talent.

Krow also digs into one of her favorite topics: “data debt.” Law firms are drowning in data but starved for information. She explains how poor data hygiene—like inconsistent time codes and messy narratives—has left firms unable to use their most valuable resource. BigHand’s impact analytics tools attack this problem head-on, transforming raw billing data into usable intelligence that drives decision-making across finance, staffing, and diversity efforts. And while the technology is powerful, Krow is clear that solving data debt is as much a cultural challenge as it is a technical one.

Another major theme is the evolving role of business professionals within law firms. Krow argues that lawyers’ traditional discomfort with financial forecasting and project management is holding firms back. Her solution? Combine legal expertise with the commercial acumen of allied professionals. Together, they can meet client demands for budgets, accountability, and measurable value—especially as AI begins to reshape how legal services are delivered and priced.

The episode closes with Krow’s broader reflection on the next decade of legal innovation. She warns that the biggest shift ahead isn’t about AI or analytics—it’s about mindset. Firms that embrace data-driven decision-making now will define the future of law; those that don’t will be left behind. Through her work at BigHand, Krow is helping to ensure that future is both more efficient and more equitable.

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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 Debt, Diversity, and the Business of Law: A Conversation with BigHand’s Catherine Krow

This week we are joined by Anusia Gillespie, Enterprise Lead at vLex and debut novelist, as she shares her unique vantage point on the intersection of legal technology and the human side of law. Anusia traces her journey from commercial real estate finance attorney to global innovation leader, with roles at Harvard, UnitedLex, and Eversheds Sutherland, all driven by a mission to help lawyers by rethinking the systems they work in. Along the way she discovered that business-of-law blind spots, like a shocking embezzlement incident early in her career, revealed deeper structural issues that inspired her focus on system change.

Anusia describes how legal tech adoption often falters when lawyers’ reactions—especially negative ones—are misunderstood. Far from being a setback, she sees strong reactions as opportunities to engage skeptics and convert them into champions. She shares a vivid example from her current work at vLex, where an initially frustrated lateral partner became one of the firm’s most enthusiastic adopters after receiving attentive support and seeing immediate client impact.

The conversation pivots to Anusia’s new novel Soul Toll, which blends contemporary and fantasy storytelling to examine the personal cost of high-performance legal culture. The book’s central metaphor, the “soul toll,” measures the tradeoff between meaningful work and draining obligations. Through her protagonist Ember, a high-achieving lawyer on a seemingly predestined path, Anusia explores how professional ambition can be engineered and how easy it is to let subtle daily tolls overwhelm the soul. Her goal is to give lawyers and other readers a practical framework for assessing that balance in their own lives.

As AI reshapes legal work, Anusia argues that lawyers need both the courage and the space to “fight for their light,” a phrase she uses as both a personal mantra and a rallying call in the novel. She emphasizes that the industry’s relentless pace will not slow down on its own, so lawyers and firm leaders must deliberately set boundaries and create pauses to prevent burnout. The discussion also explores how technology can relieve drudgery while prompting a new definition of professional competence that values human insight as much as efficiency.

Anusia closes with a challenge to law firm leaders: confront the mindsets shaped by the billable hour and empower lawyers to think beyond six-minute increments. From her perspective, real change begins in how lawyers structure their time and measure success. Whether she is leading enterprise strategy at vLex or writing visionary fiction, Anusia keeps a single purpose in view—helping lawyers build healthier, more sustainable careers. Listeners can find Soul Toll on Amazon and connect with Anusia on LinkedIn to continue the conversation.

Order Soul Toll today on Amazon

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

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

Transcript:

Continue Reading Fighting for Your Light: Anusia Gillespie on AI, Legal Innovation, and the Soul Toll of Law