This week, we welcome back Kara Peterson and Rich DiBona of Descrybe to talk about the company’s rapid growth and its expanding role in legal research. Since their last appearance, Descrybe has not only built out new tools but also entered academia by joining the curriculum of more than 350 universities around the world. Kara reflects on her earlier career in legal education and how this new partnership feels like coming full circle. Together, she and Rich share how Descrybe is positioning itself to fill the gap left by other providers while keeping affordability and accessibility at the core of their mission.

A major highlight of the discussion is Descrybe’s unique approach to legal citators. Unlike traditional tools that often provide a blunt “treatment” of a case, Descrybe’s citator allows issue-level analysis and even introduces a “backwards citator.” This means researchers can see not only how later courts interpreted a case but also how the judges who wrote the opinion cited and treated earlier authorities. Rich explains the technical challenges involved in training their system on 30 million citations, while Kara describes how these innovations give researchers new storytelling and analytical power when building arguments.

The conversation also dives into the Legal Research Toolkit, Descrybe’s paid tier that offers a collection of tools designed for professionals who need more advanced case law analysis. While the company continues to provide free access to its core research platform, the toolkit adds features such as issue explorers and advanced citator functions. Kara emphasizes the company’s deliberately simple pricing model, which prioritizes trust and accessibility. At just $10 a month for non-commercial use and $20 for commercial users, the service is priced more like everyday software than the traditional high-cost legal research platforms.

The discussion moves into broader industry trends, including the wave of acquisitions by major players like Thomson Reuters and Clio. Kara and Rich note that while consolidation is reshaping the market, it also leaves space for new entrants to innovate. With data becoming the most valuable commodity in legal tech, Descrybe is building curated and clean datasets across statutes, regulations, state constitutions, and even attorney general opinions. Both guests highlight the importance of accuracy, data hygiene, and minimizing hallucinations, explaining how their closed-system approach helps ensure that results remain grounded in actual legal documents rather than speculative AI outputs.

Finally, the episode touches on ethics, recognition, and the future. Descrybe recently won the Anthem Award for Ethical AI, a nod to its safeguards against hallucinations and commitment to transparent data practices. At ILTACon, the team found themselves impressing not only potential clients but also leaders from larger companies who were curious about how such a lean startup was able to achieve so much. Looking ahead, Kara predicts the pace of change in legal technology will only accelerate, challenging law firms to keep up, while Rich warns of the commoditization of AI capabilities and stresses the importance of staying ahead of the curve. Together, they bring both humor and insight, reminding listeners that the legal research market is shifting quickly and that affordability, accuracy, and ethics will shape its next chapter.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

In this episode of The Geek in Review, we welcome back Pablo Arredondo, VP of CoCounsel at Thomson Reuters, along with Joel Hron, the company’s CTO. The conversation centers on the recent release of ChatGPT-5 and the rise of “reasoning models” that go beyond traditional language models’ limitations. Pablo reflects on his years of tracking neural net progress in the legal field, from escaping “keyword prison” to the current ability of AI to handle complex, multi-step legal reasoning. He describes scenarios where entire litigation records could be processed to map out strategies for summary judgment motions, calling it a transformative step toward what he sees as “celestial legal products.”

Joel brings an engineering perspective, comparing the legal sector’s AI trajectory to the rapid advancements in AI developer tools. He notes that these tools have historically amplified the skills of top performers rather than leveling the playing field. Applied to law, he believes AI will free lawyers from rote work and allow them to focus on higher-value decisions and strategy. The discussion shifts to Deep Research, Thomson Reuters’ latest enhancement for CoCounsel, which leverages reasoning models in combination with domain-specific tools like KeyCite to follow “breadcrumb trails” through case law with greater accuracy and transparency.

The trio explores the growing importance of transparency and verification in AI-driven research. Joel explains how Deep Research provides real-time visibility into an AI’s reasoning path, highlights potentially hallucinated citations, and integrates verification tools to cross-check references against authoritative databases. Pablo adds historical and philosophical perspective, likening hallucinations to a tiger “going tiger,” stressing that while the risk cannot be eliminated, the technology already catches a significant number of human errors. Both agree that AI tools must be accompanied by human oversight and well-designed workflows to build trust in their output.

Looking to the future, Joel predicts that the adoption of AI agents will reshape organizational talent strategies, elevating the importance of those who excel at complex decision-making. Pablo proposes “ambient AI” as the next frontier—intelligent systems that unobtrusively monitor legal work, flagging potential issues instantly, much like a spellchecker. Both caution that certain legal tasks, especially in judicial opinion drafting, warrant careful consideration before fully integrating AI. The episode closes with practical insights on staying current, from following AI researchers on social platforms to reading technical blogs and academic papers, underscoring the need for informed engagement in this rapidly evolving space.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

• Academic Papers:
  Weekly research for trends.
  scholar.google.com,
  ssrn.com,
  arxiv.org

• François Chollet: Balanced AI insights.
  x.com/fchollet
  fchollet.com
  
• Jason Wei (OpenAI): Reinforcement learning updates.
  x.com/jason_d_we
  openai.com/blog
• Geoffrey Hinton: AI research insights.
  x.com/geoffreyhinton
• Richard Sutton: Reinforcement learning and philosophical takes.
  incompleteideas.net
  Reinforcement Learning: An Introduction (Book):
  http://incompleteideas.net/book/RLbook2020.pdf
  Seminal work by Turing Award winner.
• University of Alberta Lab: https://rlai-lab.github.io
  Current research on scalable AI methods.

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

This week, we welcome back Tom Martin, CEO of LawDroid, to discuss his widely read “AI Law Professor” column for Thomson Reuters and his five-level roadmap for legal AI. Martin explains that the framework was inspired by a leaked OpenAI memo and aims to give legal professionals a clearer picture of AI’s trajectory. The five levels range from basic chatbots to fully AI-run organizations, with intermediate stages such as reasoners, agents, and innovators. According to Martin, while we are still in the early stages, the release of GPT-5 and its reasoning capabilities has accelerated progress toward higher levels, especially in the development of autonomous agents.

The conversation turns to the implications of GPT-5’s hybrid reasoning model, which combines inference with step-by-step reasoning to deliver more relevant answers. Martin sees this as a significant shift for the legal industry, moving beyond single-response chatbots toward sustained, goal-oriented AI. He predicts that while the technology for fully autonomous legal agents could be available within a year, widespread adoption in law firms and corporations will take closer to three years. However, with these advancements come ethical concerns. Martin outlines four principles for responsible AI agents: transparency, autonomy, reliability, and visibility, cautioning that AI’s knowledge is always bounded and potentially incomplete.

Reflecting on the legal industry’s pace of change since their last discussion, Martin notes that while some firms are sprinting to adopt AI, others may already be too late to catch up. He warns that professional services organizations must actively integrate AI to remain competitive. The discussion explores the potential for tech giants or AI companies to acquire major legal information providers, and Martin argues that the future lies in blending software, consulting, and education into a unified service model. This integrated approach, he believes, will be necessary for survival in a market where AI is capable of generating solutions without traditional software development cycles.

Beyond the legal tech roadmap, Martin shares insights from his teaching at Suffolk University Law School and his observations from producing the “Last Week in Legal AI” news series. He sees both opportunities and risks for the next generation of lawyers, particularly in acting as translators between AI systems and legal practice. The discussion touches on generational attitudes toward AI, with younger users showing both skepticism and heavy reliance on AI for personal and professional support. Martin also addresses societal concerns, from AI in mental health applications to job displacement, and stresses the importance of curating AI outputs with human judgment.

The episode wraps with Martin’s update on the American Legal Technology Awards, set for October 15 at Suffolk University Law School in Boston, which he describes as “the Oscars of legal tech.” When asked about the biggest challenge for the next few years, Martin points to the uncertainty of where professionals will fit in a rapidly shifting world. He envisions a possible new model that combines service, education, and software to deliver legal help at scale, but stresses that no one knows exactly how the future will unfold. His hope is that the AI-driven abundance ahead will be shared broadly, without excluding people from its benefits.

Links:

• Keep up with Tom's podcast and latest thoughts on the law and innovation at: lawdroidmanifesto.com
• Nab some tickets to this year's Oscars of Legal Innovation at: americanlegaltechnology.com

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

This week, we welcome longtime friend and legal tech veteran Ken Crutchfield, founder of Spring Forward Consulting. Ken brings his extensive experience from major legal information vendors like Thomson Reuters, Bloomberg, and Wolters Kluwer into a timely and candid discussion about the current phase of artificial intelligence in the legal industry. Comparing today’s generative AI surge to the American Industrial Revolution, Ken describes this moment as the “Wild West” era—full of promise, hype, overinvestment, and, critically, few rules.

Drawing historical parallels to railroads, oil barons, and steel magnates, Ken illustrates how unchecked growth and technological innovation can outpace regulation until market forces or policy catch up. He notes the resurgence of large-scale infrastructure investment, now not in steel or steam, but in compute power and data centers. Just as J.P. Morgan helped stabilize chaotic markets in the 19th century, Ken suggests today's AI frontier needs a similar recalibration, and possibly new rules of engagement.

The conversation shifts toward the practical realities of legal tech adoption. Ken emphasizes that law firms' expectations of perfection often collide with startups’ resource limitations. Vendors need to rethink how they engage with firms by building credibility, focusing on integration, and delivering actual use-case wins. Firms, in turn, must move beyond the billable hour mindset and consider new metrics like Return on Experience. Adoption is no longer optional, it’s strategic, competitive, and increasingly client-driven.

Ken also unpacks the looming implications of content rights and data ownership in the age of AI. If firms aren’t investing in data hygiene now, they risk being left behind when more sophisticated AI tools demand clean, structured, and secure datasets. AI isn’t just about automating workflows, it’s about being ready to plug into a future where interoperability, metadata, and permissions will dictate who thrives and who gets leapfrogged.

Finally, Ken calls for scenario planning: not just reacting to what OpenAI or Anthropic might do next, but anticipating it. Firms and vendors alike should double down on what works, define success before launching new projects, and invest in meaningful adoption strategies. In a world moving this fast, it’s no longer about who gets there first, it’s about who gets there with a plan.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

This week, we welcome Christian Geyer, founder and CEO of ACTFORE, for a deep dive into the world of automated breach response. From his early days in military intelligence to founding a disruptive forensics firm, Christian shares how his diverse experiences shaped a data‑driven approach to tackling one of corporate America’s thorniest problems: managing the chaos of a data breach. Along the way we hear about secret clearances, cabinet making, and the humble beginnings of a startup launched from a literal closet.

Christian’s journey is anything but ordinary. Recruited straight into an intelligence agency at nineteen, he cut his teeth on top‑secret work before supporting Navy research labs with data dashboards that informed mission‑critical funding decisions. When an injury sidelined him from field ops, he turned to carpentry, framing houses and crafting cabinets during the mid‑2000s flip boom. That hands‑on trade remains Christian’s reminder that some skills can’t be automated, even as he builds AI to do the heavy lifting elsewhere.

He carried that disruptive spirit into Crypsis Group, undercutting the incident response market with half‑price forensics and skyrocketing revenue from zero to $20 million in four years. COVID’s budget cuts then prompted a pivot: leveraging ActiveNav’s data‑discovery engine to automate breach notification. What began as a side project in a shared office closet evolved into ACTFORE, a company that in a single four‑and‑a‑half‑day engagement processed 3 million patient records across 2 000 endpoints, cementing its reputation for speed, accuracy, and onshore security.

At the heart of ACTFORE’s offering is an automated extraction platform powered by “infant AI” tailored to each client. Rather than shipping data overseas for human review, Christian’s team uses software instances—deployed globally or on‑premise, to scan, fingerprint, and parse structured and unstructured files. Their Trace tool brings the automation into one‑click point‑and‑extract workflows, slashing keystrokes and crushing review timelines by weeks without sacrificing human‑in‑the‑loop oversight where it matters most.

Looking ahead, Christian warns of a new insider threat: AI models trained on proprietary data that could be weaponized from within. While ACTFORE continues to focus on reactive breach response, Christian sees advisory and proactive scanning services on the horizon, particularly in regions with more robust data regulations. As breach frequency rises and AI proliferates, ACTFORE aims to stay ahead of the curve, turning its combination of automation, human expertise, and a closet‑born scrappiness into the next frontier of cybersecurity.

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

This week, we sit down with Ilona Logvinova, Director of Practice Innovation at Cleary Gottlieb, and Max Junestrand, CEO and Founder of Legora, for a deep dive into how their partnership is reshaping the legal landscape through AI-driven innovation. The conversation kicks off with the origin story behind Cleary’s strategic alliance with Legora, a legal tech platform focused on collaborative, AI-first workflows. The two share how this relationship, built on a year-long pilot and mutual alignment in vision, is now delivering real-world benefits across Cleary’s legal teams.

Max walks listeners through the evolution of Legora’s product suite, which includes a general-purpose assistant, tabular contract review, and a Microsoft Word plugin, all wrapped into a seamless collaborative workspace. Ilona elaborates on Cleary’s multi-pronged AI strategy, emphasizing a hybrid approach that integrates both in-house tools (such as Springbok AI) and external partnerships like Legora. This merger of internal and external capabilities reflects a broader shift in legal innovation—from static solutions to agile, embedded systems designed for continuous learning and adaptation.

One major theme explored is the shift in legal AI from isolated tools to interoperable ecosystems. Max stresses the importance of collaboration and avoiding silos, pointing to a future where legal tech isn’t just smarter, but also more connected. Ilona reinforces this by describing Cleary’s vision of AI as a co-worker, not a replacement, likening AI oversight to supervising junior associates. The goal, they argue, isn’t to eliminate human involvement, but to elevate it—using AI to take over repetitive tasks while freeing lawyers to focus on high-value strategy and creativity.

The episode also covers practical aspects of deployment and adoption, offering insight into why Cleary's rollout has been so successful. Ilona credits the intuitive design and high-value use cases as key drivers of firmwide engagement. From Zoom calls with 1,000 attendees to chatbots that feel more like using Google than enterprise software, Cleary’s AI integration strategy is centered on simplicity, accessibility, and a relentless focus on user experience. The team’s use of analytics and continuous feedback loops further ensures the platform evolves to meet real-world needs.

In the crystal ball finale, Max and Ilona speculate on what’s next. Max anticipates a dramatic consolidation in user experience across legal tech platforms, driven by agents and large language models that enable seamless workflows. Ilona envisions a future shaped by AI-native infrastructure and even screenless computing environments, where collaboration is immersive and spatial rather than tethered to screens. Their shared message is clear: the future of legal work is collaborative, AI-enhanced, and closer than we think. Whether you're a tech-savvy partner or a cautious associate, this episode offers a compelling look at how forward-thinking firms are already building the legal practice of tomorrow.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

In this episode, we welcome Matthew Dickinson, CEO and founder of Vable, to discuss the rapidly changing landscape of legal information and current awareness. Matthew reflects on how, until recently, current awareness in law firms relied heavily on manual curation, Boolean searches, and email alerts—often resulting in information overload and a lack of personalization. With the advent of generative AI, expectations have shifted dramatically. Lawyers now want more than just a flood of articles; they expect relevant, actionable insights delivered seamlessly and intuitively, tailored to their specific needs and workflows.

Matthew explains how Vable and similar platforms are moving beyond simply delivering news. The goal is to provide context-rich, actionable intelligence that integrates with other firm systems, such as CRM platforms. Instead of sending a list of articles about data breaches, for example, the new approach is to alert lawyers when a top client is affected, summarize the implications, and identify who else in the firm needs to know. This shift requires a blend of robust technology, thoughtful workflow design, and a deep understanding of the different roles within a law firm.

A significant portion of the conversation centers on the ethical boundaries of using AI in legal information services. Matthew outlines four pillars for ethical current awareness: trust, transparency, accuracy, and inclusion. He emphasizes the importance of clear labeling when AI is used, maintaining high standards for accuracy (especially for client-facing content), and ensuring a diversity of sources to avoid echo chambers. Vable’s approach includes strong relationships with publishers, transparent rights management, and tools that allow human review and curation before information is distributed.

Matthew discuss best practices for using news and current awareness to support practice development and client engagement. While many firms still rely on newsletters and headlines, there is a growing trend toward more personalized, branded, and interactive content—such as Vable Connect, which allows firms to deliver tailored digests to clients. Automation is on the rise, but the human element remains crucial: lawyers use curated content as a springboard for client conversations, and AI is seen as a tool to empower, not replace, professional judgment.

As the episode wraps up, Matthew shares his perspective on the future of legal information services. He predicts that the next wave of innovation will bring even more personalization, prediction, and integration—potentially leading to “personalized current awareness bots” for every lawyer. However, he cautions that while AI can supercharge productivity, humans must remain in control, especially in high-stakes legal environments. The unique culture and high standards of law firms mean that technology providers must deeply understand their clients’ needs to build trust and deliver real value.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

In this week's episode of The Geek in Review, Greg Lambert flies solo while co-host Marlene Gebauer enjoys some well-deserved relaxation. Greg welcomes Trevor Quick, Strategic Business Development lead at Harvey.ai, to discuss one of the most talked-about companies in legal tech today. With a staggering $300 million Series E funding round and a $5 billion valuation, Harvey is rewriting the narrative of what legal AI can be, as well as who it is for. Trevor, a longtime listener turned guest, brings an insider’s view of the company’s evolution and its ambitions for reshaping the legal services ecosystem.

Trevor provides behind-the-scenes insight into how Harvey has become such a magnet for both capital and attention. He attributes the rapid growth to the company’s structure—where legal expertise and AI engineering are in constant collaboration. From founder Winston Weinberg’s legal acumen to co-founder Gabe Pereyra’s technical leadership, Harvey’s DNA has always been rooted in practical use cases for lawyers. The company's commitment to building with, not just for, the legal community has led to the development of a GTM team composed of practicing attorneys who work directly with law firms and corporate legal departments to customize AI solutions that align with real workflows.

One of the most talked-about moves is Harvey’s deepening partnership with LexisNexis. Trevor explains how integrating Lexis’s data directly into Harvey’s platform removes the friction lawyers face when juggling multiple research tools. With access to Shepard’s citations and native case law lookup, attorneys can now verify and trust the results Harvey generates—turning it from a generative assistant into a full-fledged research companion. This update not only boosts confidence but also meets the rigorous standards legal professionals demand, especially those skeptical of AI’s early stumbles.

The conversation also touches on Harvey’s new functionalities like the Workflow Builder, Vault document review enhancements, and Deep Research Mode. Trevor likens these innovations to “agentic” workflows that let users build custom solutions with low or no code. Whether it's KM teams building tailored research processes, or attorneys streamlining diligence reviews, Harvey is giving legal professionals the ability to shape how AI works with them, not around them. Trevor emphasizes that Harvey’s success comes from its honesty, adaptability, and the trust it has earned by meeting lawyers where they are—not forcing them to change how they work overnight.

In closing, Greg asks Trevor to gaze into the crystal ball, and while Trevor jokingly admits that predicting the future in AI is a fool’s errand, he offers a vision rooted in intuition, collaboration, and democratized access to justice. From expanding into tax, compliance, and marketing workflows, to becoming a central hub for legal and adjacent industries, Harvey is on a path to not only augment what lawyers do, but to enhance how they feel about the work itself. With world-class partnerships and a relentless pace of innovation, Trevor makes a compelling case that Harvey isn't just a tool—it might just be the toolbelt.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

In this episode of The Geek in Review, guest host Marcie Borgal Shunk of the Tilt Institute joins Marlene Gebauer for a thought-provoking discussion with Avaneesh Marwaha, CEO of Litera. As someone who led the company through both pre- and post-AI boom eras, Avaneesh offers an insider’s perspective on what it takes to guide a legal tech organization through profound technological and cultural shifts. He speaks candidly about why he returned to Litera, what has changed internally, and how AI is being integrated not just into products, but into the DNA of the company itself.

Avaneesh shares how Litera transitioned from an acquisition-heavy growth strategy to one that prioritizes internal AI innovation. This shift required rethinking everything from leadership talent to product development cycles. He emphasizes that meaningful adoption of AI goes far beyond surface-level integrations, calling instead for a reinvention of workflows, organizational structure, and employee mindsets. Daily AI usage is expected at Litera, but not in a checkbox kind of way. Instead, teams are challenged to use AI tools to accelerate decision-making, increase efficiency, and share insights across departments.

One of the more pressing challenges Avaneesh highlights is “adoption fatigue.” While excitement around generative AI brought in billions of investment dollars and an explosion of legal tech startups, the sheer volume of pilots and proof-of-concept tools is starting to wear thin with law firm users. To combat this, Avaneesh argues that AI needs to be native to workflows—integrated directly into Word, Outlook, and other familiar environments—so lawyers aren’t forced into unnatural digital pivots just to use new tools.

The conversation also explores agentic workflows—AI-driven processes that take action based on inputs, like automatically triaging emails or assisting in business development. Avaneesh shares that Litera has several of these tools set to launch, all co-built with customers. But he’s cautious: if AI doesn’t return value within a six-minute lawyer mindset, the tools get dropped. It’s not about flash, it’s about results.

Looking ahead, Avaneesh envisions a legal industry where AI removes the "busy work" and gives lawyers the space to tackle truly complex problems. Rather than displacing attorneys, AI will help them focus on higher-order thinking, better client service, and proactive problem-solving. But for that future to arrive, the industry needs to move past its fear of change, embrace a growth mindset, and be willing to reimagine what legal work looks like from the ground up.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

In this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert sit down with Otto von Zastrow, the founder and CEO of MidPage.AI, an AI-native legal research platform. With a recent $4 million seed round and an ambitious mission to rival legacy research tools, MidPage is drawing attention across the legal industry. Otto shares his unconventional journey from AI-powered lawn robotics to transforming how litigators interact with case law. His pivot into legal tech was fueled by a combination of technical curiosity, the rise of language models, and firsthand insight from his lawyer friends overwhelmed by inefficient research workflows.

Otto walks listeners through the core of MidPage’s offering, which includes the usual suspects—case law, statutes, regulations—but with a twist: smarter search tools, intuitive UI, and features like a proprietary citator and their newly launched Proposition Search. This feature aims to solve the long-standing “needle-in-a-haystack” problem by surfacing judicial language that matches precise arguments, accompanied by contextual metadata and filters. Otto highlights that the goal isn't just to match or mimic tools like Lexis or Westlaw, but to rethink what legal research should feel like when modern AI capabilities are built in from the ground up.

One of the more unique aspects of MidPage’s product development is their internal "kangaroo court"—a monthly teamwide challenge where employees, regardless of role, must conduct legal research using MidPage or traditional tools. Otto notes that this process not only improves product design but builds real empathy for the user experience. Engineers and designers are encouraged to think like litigators, helping identify pain points and close functionality gaps. As a result, the product continually evolves based on firsthand user scenarios, not just speculation.

The episode also delves into the data-side challenges that have historically prevented innovation in legal research. Otto explains why now—thanks to improved AI models and open access to data—is a rare inflection point for startups. He emphasizes the strategic importance of MidPage building its own case law dataset to avoid being beholden to incumbents. This independence allows them to innovate more freely, enhance precision, and lay the groundwork for broader API access that could empower the next generation of legal tech tools.

Finally, the conversation looks ahead. Otto predicts that AI will amplify the capabilities of individual lawyers, enabling them to process more data at greater depth. In a world where clients are increasingly self-educating with tools like ChatGPT, MidPage aims to provide lawyers with the means to maintain credibility and efficiency while ensuring accuracy. As AI models grow more capable and agentic, Otto sees an evolution not just in how legal research is conducted, but in how lawyers interact with knowledge, data, and ultimately their clients.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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

Blue Sky: ⁠⁠@geeklawblog.com⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: [email protected]
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript