Flatiron Law Group's Lennie Nuara on Talent-First AI, M&A Workflows, and the Future of Legal Practice

Own the Graph: Stephen Costigan on Private AI, Knowledge Infrastructure, and Law Firm Advantage

For law firms, artificial intelligence has often arrived as a choice between speed and control. Stephen Costigan [https://www.linkedin.com/in/stephencostigan/], founder of Atlas AI [http://www.atlas-ai.io], argues that choice deserves a rethink. In this episode of The Geek in Review, we speak with Costigan about private legal AI infrastructure, knowledge graphs, and why a firm’s internal work product may become its most valuable long-term asset. Atlas AI focuses on turning documents, matter history, precedents, clauses, parties, and obligations into a curated legal knowledge graph inside a firm’s own environment. Costigan contrasts this approach with standard vector search and retrieval systems, which find text with similar language but often lack context around clients, matters, entities, and relationships. A knowledge graph offers structure, linking people, documents, clauses, and legal concepts in ways closer to how lawyers understand their work. The conversation also explores data quality, a subject with enough baggage to fill a records room. Costigan argues firms no longer need year-long cleanup projects before seeing results. Agent-led curation, entity extraction, duplicate resolution, and ontology mapping reduce much of the manual sorting traditionally associated with knowledge management. Human judgment still matters, especially around practice-area vocabularies and lower-confidence results, but the machines get assigned more of the janitorial work. Security and governance sit at the center of Costigan’s model. Rather than asking firms to trust a vendor’s assurances around privileged data, Atlas AI runs within a firm’s Azure environment, under firm-controlled keys and policies. Costigan frames this as a shift from confidentiality as a contractual promise to confidentiality as an architectural decision. For legal organizations handling sensitive client information, the location of data, embeddings, audit trails, and model interactions matters as much as the interface lawyers see on screen. Looking ahead, Costigan predicts a divide between firms renting generic AI tools and firms building durable knowledge infrastructure from their own experience. As routine drafting, diligence, and review work compress, firms with structured and reusable internal intelligence may productize expertise, offer new fixed-fee services, and rely less heavily on traditional leverage models. The future question, Costigan suggests, will not center on which AI tool sits on a lawyer’s desktop. The bigger question will ask who owns the knowledge behind the work. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://podcasts.apple.com/us/podcast/the-geek-in-review/id1401505293] |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://open.spotify.com/show/53J6BhUdH594oTMuGLvANo?si=XeoRDGhMTjulSEIEYNtZOw] | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.youtube.com/@thegeekinreview] | ⁠Substack⁠ [https://thegeekinreview.substack.com/] [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ [https://www.legaltechnologyhub.com/] for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript:

AALL 2026 Annual Meeting Preview with Foster and Whytock: Leading with Aloha, Legal AI, and the Future of Law Libraries

This week we welcome American Association of Law Libraries leaders Jenny Foster [https://www.linkedin.com/in/jenny-foster-56604416a/], AALL President for 2025-2026, and Jessica Whytock [https://www.linkedin.com/in/jessica-whytock-58ba2b8/], AALL Vice President and President-Elect. The conversation offers a preview of the 2026 AALL Annual Meeting & Conference [https://www.aallnet.org/conference/] in Cleveland, Ohio, along with a thoughtful look at how the association is supporting legal information professionals during a period of institutional, technological, and professional change. Foster reflects on a leadership year focused on transparency, communication, and meaningful opportunities for member participation. From strengthening channels between members and AALL leadership to intentional volunteer appointments across committees and juries, she describes an association built through relationships. The goal is to ensure newer, mid-career, and seasoned law librarians all have a visible place in shaping the profession’s future. Advocacy also plays a central role in the discussion. Foster explains how AALL continues its work on access to legal information, public policy, and coalition-building, even amid staffing transitions. The association’s Government Relations Committee has continued meeting with members, offering advocacy training, rebuilding connections with peer organizations, and aligning its work with AALL’s strategic priorities. For law librarians, advocacy is both a long-term commitment and a practical responsibility tied to preserving authoritative legal information. The 2026 conference theme, “Leading with Aloha,” gives the Cleveland meeting its distinct point of view. Foster shares how aloha, rooted in kindness, unity, humility, patience, and meaningful connection, became a framework for leadership during uncertain times. More than 65 programs will explore topics ranging from generative AI and legal scholarship to physical collection strategy, access challenges, and the changing role of legal information professionals. Local programming connected to Cleveland’s history will bring an added sense of place to the gathering. Whytock looks ahead to her upcoming presidency with a focus on clear pathways for engagement, leadership, grants, scholarships, committee service, and professional growth. Both leaders see artificial intelligence as a catalyst for a deeper conversation about the identity and value of legal information professionals. Their message is straightforward: the future of law librarianship rests in human judgment, critical thinking, ethical discernment, context, access, and a community willing to bring more voices into the room. The 2026 AALL Annual Meeting in Cleveland offers a place for those conversations to move from aspiration into action. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://podcasts.apple.com/us/podcast/the-geek-in-review/id1401505293] |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://open.spotify.com/show/53J6BhUdH594oTMuGLvANo?si=XeoRDGhMTjulSEIEYNtZOw] | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.youtube.com/@thegeekinreview] | ⁠Substack⁠ [https://thegeekinreview.substack.com/] [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ [https://www.legaltechnologyhub.com/] for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠   Transcript:

LexisNexis CTO Greg Dickason on Agentic Legal AI, Protégé, Shepard’s Verify, and the Future of Legal Work

In this episode of The Geek in Review, we welcome Greg Dickason [https://www.lexisnexis.com/en-us/about-us/leadership/global-leadership/greg-dickason.page], Chief Technology Officer at LexisNexis [https://www.lexisnexis.com/], for a wide-ranging conversation on agentic legal AI, Lexis+ AI Protégé, and the movement from AI chat toward AI work. Dickason frames the shift through a simple contrast: earlier legal AI answered questions, while agentic workflows take on multi-step assignments, conduct research, create drafts, verify citations, and move legal professionals closer to finished work product. For law firms and legal departments trying to understand where AI goes next, this episode places agentic AI squarely inside legal workflow, legal research, drafting, and risk management. A major theme of the conversation is trust. Dickason explains how Shepard’s Verify extends the familiar Shepard’s signal beyond traditional research screens and into uploaded work product. Rather than asking lawyers to rely on AI-generated text without a verification layer, LexisNexis is building citation checking into the workflow, giving lawyers a path to confirm whether cited authority exists, whether authority is still good law, and how later courts treated the cited case. For lawyers worried about hallucinated citations, AI-generated briefs, and unreliable authority, this verification layer becomes part of the product architecture, rather than an afterthought. The discussion also explores the relationship between LexisNexis and Anthropic, along with the rise of legal AI skills. Dickason describes a market where model choice, orchestration, and legal skills increasingly matter as separate layers. Anthropic, OpenAI, Google, and other model providers offer impressive foundations, yet legal work needs more than general-purpose intelligence. Large law workflows require legal content, expert reasoning, matter-specific playbooks, and firm-defined processes. Dickason notes the ability to upload firm playbooks as skills, giving firms a path to bring their own way of working into Protégé. Security receives equal billing with accuracy. As firms place client documents into AI vaults and connect work product to legal AI platforms, Dickason explains bring your own key, or BYOK, through a practical office-and-locked-cabinet analogy. The point is control: client content sits encrypted, access depends on the user’s key, and access stops when the key is withdrawn. He also discusses legal chunking, indexing, vector stores, retrieval-augmented generation, and knowledge graphs as part of building AI systems suited for legal documents, rather than generic file handling. The episode closes with a broader view of legal AI’s impact on junior associates, legal training, and access to law. Dickason does not predict the end of junior lawyers. Instead, he sees AI helping junior lawyers become senior faster through mock trials, mock depositions, and richer training environments. He also warns of risks from agent volume, security vulnerabilities, and legal systems struggling to keep pace with AI-enabled industries. The message is pragmatic and optimistic: agentic legal AI will change legal work, yet the winners will be those who combine trusted content, secure systems, verification, workflow design, and human judgment. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://podcasts.apple.com/us/podcast/the-geek-in-review/id1401505293] |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://open.spotify.com/show/53J6BhUdH594oTMuGLvANo?si=XeoRDGhMTjulSEIEYNtZOw] | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.youtube.com/@thegeekinreview] | ⁠Substack⁠ [https://thegeekinreview.substack.com/] [Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ [https://www.legaltechnologyhub.com/] for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript:

Legal AI, Trust, and Agents: Joel Hron on Thomson Reuters, Anthropic, and the Future of CoCounsel

In this episode of The Geek in Review, Greg Lambert and Marlene Gebauer welcome back Joel Hron [https://www.linkedin.com/in/joel-hron-90a3421a/], Chief Technology Officer at Thomson Reuters [https://www.thomsonreuters.com], for a timely conversation about the shifting relationship among foundation models, legal content providers, legal tech platforms, and the lawyers trying to make sense of the mess. Recent moves by Anthropic, including Claude’s legal practice area tools and MCP connections into legal platforms, raise a larger question for the market. Is a model provider still sitting behind the scenes, or is it starting to become a legal work environment of its own? Hron explains Thomson Reuters’ commitment to what it calls fiduciary-grade AI [https://www.linkedin.com/pulse/fiduciary-grade-ai-what-why-matters-how-buy-thomson-reuters-hx0fe/], a standard built around trust, verification, transparency, and accountability. For TR, legal AI needs more than a fast answer. It needs systems lawyers trust enough to stand behind. Hron points to Westlaw, Practical Law, KeyCite validity signals, citation ledgers, and verification tools as core ingredients in building AI systems suited for high-stakes professional work. In his view, almost right is not good enough when clients, courts, regulators, and professional obligations sit on the other side of the output. The conversation turns to how CoCounsel and Westlaw Deep Research use legal content across far more than traditional research tasks. Hron explains that when AI systems gain access to trusted legal content and verification tools, they begin researching throughout the workflow, even while revising contract language or analyzing provisions. He also describes Litigation Document Analyzer, internally nicknamed the BS Detector, a tool designed to review claims in a document and map them to supporting authority, weak support, or no support at all. For lawyers who spend as much time verifying AI output as generating it, tools like these aim to move verification from a manual scavenger hunt into a structured process. Greg and Marlene also press Hron on Anthropic’s legal plugins, MCP, and the idea of headless legal technology. Hron argues that MCP changes access, not advantage. In his view, the application layer is shifting, but the real competitive value sits in trusted content, expert systems, governance, and domain-specific intelligence. CoCounsel’s user interface represents one expression of TR’s legal agent capabilities, while MCP opens other ways for those capabilities to appear inside broader work environments. Some work will still need a purpose-built legal interface; other work might happen through email, Word, Claude, or another agentic workflow with little visible interface at all. The episode closes with a larger discussion about what happens when AI starts performing more of the work itself. Hron shares TR’s internal engineering OKR, where more than 50 percent of pull requests should be written by AI, and explains why 51 percent serves as a useful mental model. Once AI performs a controlling share of the work, the human role shifts from doing the task to governing the system. For legal professionals, the same transition is coming. The key question is no longer only whether AI produces useful work. It is whether lawyers have built the systems, context, safeguards, and verification layers needed to trust the work, defend the work, and remain accountable for the work. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://podcasts.apple.com/us/podcast/the-geek-in-review/id1401505293] |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://open.spotify.com/show/53J6BhUdH594oTMuGLvANo?si=XeoRDGhMTjulSEIEYNtZOw] | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.youtube.com/@thegeekinreview] | Substack [https://thegeekinreview.substack.com/] [Special Thanks to ⁠Legal Technology Hub⁠ [https://www.legaltechnologyhub.com/] for their sponsoring this episode.]   ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

The Flight Simulator for Lawyers: Abdi Shayesteh and Jeanine Conley Daves on AI, Deliberate Practice, and the Future of Legal Training

This week on The Geek in Review, we talk with Abdi Shayesteh [https://www.linkedin.com/in/abdishayesteh/], CEO of AltaClaro [https://www.altaclaro.com/], and Jeanine Conley Daves [https://www.linkedin.com/in/jeanineconleydaves/], Littler’s [https://www.littler.com/] New York office managing shareholder, about a different question in the legal AI conversation. Instead of asking whether AI will write the brief, summarize the contract, or replace the junior associate, they focus on whether AI might help lawyers learn how to practice law. Their recent work around AltaClaro’s DepoSim points toward a model of legal training built less on passive observation and more on structured repetition, feedback, and skill development. Shayesteh traces the origin of AltaClaro back to his own early years at King & Spalding, where he benefited from proximity to a mentor willing to explain the work. That experience also showed him the unevenness of the old apprenticeship model. Access to assignments, feedback, and sponsorship often depended on luck, relationships, and office geography. For Shayesteh, the idea of a “flight simulator for lawyers” grew out of the realization that pilots, athletes, and musicians all practice in structured environments before performance, while lawyers too often learn in front of clients, courts, and opposing counsel. DepoSim [https://www.altaclaro.com/deposim] applies this flight simulator concept to one of litigation’s highest-pressure skills: taking and defending depositions. The platform gives attorneys a simulated witness, opposing counsel, court reporter, and feedback system, with options to vary the difficulty and personalities involved. Conley Daves explains why this kind of realism matters. In a real deposition, a lawyer might face an evasive witness, a hostile witness, an aggressive opposing counsel, or a combination of all three. The simulator lets lawyers practice those moments repeatedly, receive targeted feedback, and return to specific skills such as exhibit handling, follow-up questions, or managing objections. The conversation also connects AI training to equity in professional development. Conley Daves notes that access to high-quality assignments and sponsorship has not always been distributed evenly across firms. A standardized, rubric-based feedback system gives more lawyers a chance to build core skills without waiting to be selected by the right partner or assigned to the right matter. Shayesteh adds that firms seeing the strongest results are not treating training as an after-hours side quest. They are creating protected time for deliberate practice, pairing AI feedback with human mentorship, and using simulation as a bridge rather than a substitute for coaching. Looking ahead, Shayesteh and Conley Daves see simulation moving well beyond depositions. Oral argument, cross-examination, meet-and-confer sessions, negotiations, client interviews, and even Supreme Court preparation all fit within this training model. The larger shift is not automation for its own sake. It is the use of AI to help lawyers build judgment before the stakes are real. For law firms, that means better preparation, more consistent training, stronger associate development, and a clearer path toward delivering value to clients. For the profession, it suggests a future where competence is practiced deliberately, measured thoughtfully, and taught more fairly. Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://podcasts.apple.com/us/podcast/the-geek-in-review/id1401505293] |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://open.spotify.com/show/53J6BhUdH594oTMuGLvANo?si=XeoRDGhMTjulSEIEYNtZOw] | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ [https://www.youtube.com/@thegeekinreview] | Substack [https://thegeekinreview.substack.com/] [Special Thanks to ⁠Legal Technology Hub⁠ [https://www.legaltechnologyhub.com/] for their sponsoring this episode.]   ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript: