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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.

We closed the conversation feeling both inspired and challenged. The message is clear: law librarians shouldn’t sit on the sidelines of AI. They are uniquely positioned to lead, to teach, and to ensure that the technologies shaping law remain grounded in ethics, accessibility, and the rule of law. For those who want to get involved, Cas directs listeners to the University of Arizona Law Library’s Future of Law Libraries Initiative page, which includes the white paper and volunteer opportunities. This episode reminded us that the future of AI in law won’t be defined by the tools themselves, but by the people—especially librarians—who decide how those tools are used.

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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 Law Librarians Take the Lead: The Future of AI and Legal Information

I’ve been thinking about a story that I believe deserves more attention than it’s getting.

Robin AI, once positioned as a rising star in legal AI, has missed its funding round, cut a third of its staff, and landed on a distressed sale marketplace. The question isn’t whether this is unfortunate. It’s whether this is a harbinger. (Non-Billable)

Is Robin AI’s collapse a one-off execution failure, or the first visible crack in a legal tech AI bubble?

What happened at Robin AI

Robin AI launched in 2019 with a compelling premise: a “lawyer-in-the-loop” contract review system that combined large language models with proprietary contract data. The founding team brought credibility: lawyer Richard Robinson and machine-learning researcher James Clough building something at the intersection of both worlds. In early 2024, they raised $26 million in Series B funding.  The marketing was aggressive: major enterprise clients, ambitious platform expansion across drafting and negotiation, claims of transformative efficiency gains.

By late 2025, the picture had changed dramatically. Internal reports suggested the company failed to secure another major funding round (targeting roughly $50 million), laid off about a third of its workforce, and quietly listed itself for sale on a distressed marketplace.

That trajectory, from high-profile funding to forced sale in under two years, warrants closer examination.

The red flags were there

Robin AI never publicly disclosed its Series B valuation. In a market where lofty valuations typically accompany large deals, that absence now looks less like discretion and more like avoidance. Without a clear number, it’s impossible to assess whether investor expectations matched operational reality or whether growth projections were ever grounded in achievable metrics.

More telling were the employee accounts. Reviews on Glassdoor described a culture of overwork, inadequate support, and marketing claims that outpaced product capability. One reviewer noted the company positioned itself as AI-driven while “in practice most of the work is handled manually by staff.”   Another called it their “worst professional experience to date,” citing a “rule by fear” environment where junior team members shouldered contract reviews with minimal support.

These aren’t just grievances about workplace culture. They’re signals about the gap between what was being sold and what was being delivered.

What looks like a fluke
Continue Reading Is the Collapse of Robin.AI a One-Off or a Sign of a Legal Tech AI Bubble?

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 vLex/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.

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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 Conferences, Catch-ups, and Clio’s Big Swing at Big Law

Artificial intelligence has moved fast, but trust has not kept pace. In this episode, Nam Nguyen, co-founder and COO of TruthSystems.ai, joins Greg Lambert and Marlene Gebauer to unpack what it means to build “trust infrastructure” for AI in law. Nguyen’s background is unusually cross-wired—linguistics, computer science, and applied AI research at Stanford Law—giving him a clear view of both the language and logic behind responsible machine reasoning. From his early work in Vietnam to collaborations at Stanford with Dr. Megan Ma, Nguyen has focused on a central question: who ensures that the systems shaping legal work remain safe, compliant, and accountable?

Nguyen explains that TruthSystems emerged from this question as a company focused on operationalizing trust, not theorizing about it. Rather than publishing white papers on AI ethics, his team builds the guardrails law firms need now. Their platform, Charter, acts as a governance layer that can monitor, restrict, and guide AI use across firm environments in real time. Whether a lawyer is drafting in ChatGPT, experimenting with CoCounsel, or testing Copilot, Charter helps firms enforce both client restrictions and internal policies before a breach or misstep occurs. It’s an attempt to turn trust from a static policy on a SharePoint site into a living, automated practice.

A core principle of Nguyen’s work is that AI should be both the subject and the infrastructure of governance. In other words, AI deserves oversight but is also uniquely suited to implement it. Because large language models excel at interpreting text and managing unstructured data, they can help detect compliance or ethical risks as they happen. TruthSystems’ vision is to make governance continuous and adaptive, embedding it directly into lawyers’ daily workflows. The aim is not to slow innovation, but to make it sustainable and auditable.

The conversation also tackles the myth of “hallucination-free” systems. Nguyen is candid about the limitations of retrieval-augmented generation, noting that both retrieval and generation introduce their own failure modes. He argues that most models have been trained to sound confident rather than be accurate, penalizing expressions of uncertainty. TruthSystems takes the opposite approach, favoring smaller, predictable models that reward contradiction-spotting and verification. His critique offers a reminder that speed and safety in AI rarely coexist by accident—they must be engineered together.

Finally, Nguyen discusses TruthSystems’ recent $4 million seed round, led by Gradient Ventures and Lightspeed, which will fund the expansion of their real-time visibility tools and firm partnerships. He envisions a future where firms treat governance not as red tape but as a differentiator, using data on AI use to assure clients and regulators alike. As he puts it, compliance will no longer be the blocker to innovation—it will be the proof of trust at scale.

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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 Trust at Scale: Nam Nguyen on How TruthSystems is Building the Framework for Safe AI in Law

I’ve been watching the legal-tech landscape for a long time, and this morning’s announcement from Thomson Reuters’ partnership with DeepJudge marks a moment worth pausing over. (DeepJudge) On October 22, 2025, TR disclosed that DeepJudge’s enterprise-search and AI-knowledge-platform capabilities will be integrated into TR’s CoCounsel Legal offering to bring internal-firm knowledge and…

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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[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

Daniel Lewis joins us this week to trace a path from Ravel Law to LexisNexis to LegalOn, with a throughline of data-driven thinking and practical outcomes for lawyers. Stanford roots shaped early work on judicial analytics, then a front-row view inside a global publisher broadened focus to content, guidance, and the daily reality of in-house teams. That experience pointed straight at contract review as a top pain for corporate counsel, which led to LegalOn’s product mission and global push.

Data access still shapes progress. Case law digitization advanced through projects like Harvard’s archive, yet comprehensive coverage, secondary sources, and news remain guarded by incumbents. Daniel explains why large datasets give scale, why startups face steep hurdles, and why thoughtful product scope matters. The lesson, build where data, workflow, and user value intersect.

LegalOn’s hybrid approach blends large models with attorney-built playbooks, practice notes, and suggested clause language. Consistency matters more than clever one-offs, so reviews align to standards, not model whimsy. Daniel shares a memorable demo from a rival where a phantom “California Code section 17” alert appeared, a cautionary tale that underscores the need for guardrails, verification, and explainability.

Conversation turns to multi-step agents and matter management. Picture an intake email from sales, missing key fields. An agent requests what is needed, opens a matter, applies a tailored playbook, highlights non-negotiables and fallbacks, then keeps stakeholders informed as work progresses. LegalOn also converts existing playbooks and prior redlines into AI-ready guidance, reducing setup chores while preserving organizational risk preferences.

Finally, Daniel outlines new muscles for legal teams. Daily AI usage shifts time from line-by-line edits to judgment, negotiation strategy, and process leadership. Tech fluency, business orientation, and change leadership rise in importance, along with a steady diet of outside-legal analysis from voices like Ben Thompson and Benedict Evans. The message, free lawyers from sludge, raise the ceiling on strategic work, and build for long-term improvement across the legal function.

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 Building Consistent AI for Contract Review with LegalOn’s Daniel Lewis