Adventures In Legal Tech

Jared Correia

"Adventures In Legal Tech" explores effective solutions to unique technology issues. Each episode provides actionable steps to solve everyday problems lawyers encounter. It's kind of like "This Old House" — but with way more law.

  1. 4h ago

    Mind Map - The Intersection of Artificial Intelligence & Knowledge Management

    Summary Law firms are drowning in scattered knowledge, and AI can't fix disorganized data on its own. Rachel Shields Williams, Director of AI and Knowledge Management at Bass, Berry & Sims and President of the Legal Marketing Association, joins Jared Correia to explain why structured data has to come before any AI rollout, and how firms can build the human relationships that make AI adoption safe. Key Takeaways AI can't structure your data for you. A firm's data represents its relationships and intellectual property, and only humans understand that context well enough to organize it. Treat AI as the "middle layer" between two things you control: your structured data and your firm's unique expertise. You can't control LLM pricing or availability, so keep those other two pieces solid. Shadow AI risk isn't just about lawyers pasting client data into a chatbot. It also includes open-source code pulled from GitHub that can carry hidden backdoors. Change management works better in small, steady steps. A firm that gets 1% better most weeks of the year ends up roughly 48% better, without blowing up anyone's workflow. A new "translator" role is emerging in law firms: someone who can move between lawyers, IT, and business leadership to explain why data structure matters and what AI can realistically deliver. Links and Resources Red Cave Law Firm Consulting: redcavelegal.com Bass, Berry & Sims: bassberry.com Legal Marketing Association: legalmarketing.org Keywords knowledge management, legal AI, AI in law firms, shadow AI, structured data, law firm data management, legal technology, Bass Berry Sims, Legal Marketing Association, LMA, change management, law firm innovation, AI governance, legal knowledge management, AI as junior associate, law firm technology adoption, data governance law firm, AI risk management, legal marketing, law firm AI strategy Episode Highlights [00:03:00 - 00:04:00] Rachel introduces her "Fibber McGee's closet" metaphor for law firm data chaos. [00:06:00 - 00:06:30] Rachel says if AI could structure firm data on its own, she'd be retired. [00:07:00 - 00:08:00] Rachel frames AI as the uncontrollable "middle layer" between structured data and firm expertise. [00:12:00 - 00:12:30] Rachel warns that open-source code from bad actors is a bigger shadow AI risk than most firms realize. [00:13:30 - 00:14:00] Rachel compares vetting AI use to letting a niece use a safety knife instead of a chef's knife. [00:17:00 - 00:17:30] Rachel argues a firm that's 1% better most weeks ends the year roughly 48% better. [00:27:30 - 00:28:00] Rachel describes the emerging "translator" role bridging lawyers, IT, and business needs. [00:31:00 - 00:31:30] Jared and Rachel joke about AI's "Uber Black" pricing phase before costs rise.

  2. 3d ago

    Grand Central Station - The Value of Case Management Software in the Age of Artificial Intelligence

    Summary "Attorney Matt Damon" needs to draft a demand letter, but the facts he needs are scattered across medical records, deposition transcripts, case notes, and email threads. Jared Correia brings in Claude Simpson, Vice President of Client Operations at Smart Advocate, to unpack why that scattered data problem is nearly universal in legal practice. Claude explains that documents, not buzzwords, still run the practice of law, and that AI only works well when it is pulling from a structured case management system. They cover client portals, the real costs of switching platforms, data ownership disputes with cloud vendors, and how to measure ROI beyond time saved. Key Takeaways AI is only as good as the data feeding it, and case management software is what gives that data structure. Client portals are underused by most firms, even though clients already expect 24/7 self-service access from their bank and doctor. Centralizing case data beats stacking disconnected point solutions, even when integration with existing tools is required. Switching case management systems is harder than adopting one for the first time, and change management is the real obstacle. ROI on case management software shows up in turnaround time, error rates, client satisfaction, and staff retention, not just hours saved. About the Guest Claude Simpson is the Vice President of Client Operations at Smart Advocate, a case management platform built for law firms. He has been with the company since 2013, bringing a background as a practicing trial attorney, including medical malpractice litigation, along with early technology experience dating back to building one of the first local area networks at the New York State Supreme Court's Appellate Division in the 1980s. Links and Resources Red Cave Law Firm Consulting: redcavelegal.com Smart Advocate: smartadvocate.com Keywords case management software, legal technology, law firm AI, Smart Advocate, legal case management system, AI in law firms, client portal, law firm client experience, legal tech ROI, law firm technology adoption, cloud case management, law firm data security, legal ethics technology, change management law firm, law firm staff retention, demand letter drafting, personal injury case management, law firm KPI, legal AI adoption, shadow AI Episode Highlights [00:03:03 - 00:03:45] Claude Simpson explains that despite AI hype, documents, physical or electronic, still control the practice of law. [00:05:37 - 00:06:04] Jared and Claude agree AI needs structured data, and case management software provides that backbone. [00:10:38 - 00:11:24] Claude Simpson makes the case for client portals: clients expect 24/7 access the same way they get it from their bank or doctor. [00:13:14 - 00:14:03] Claude Simpson warns that disjointed systems create frustration and increase the risk of missed information. [00:16:53 - 00:17:34] Claude Simpson on convincing a 30-year veteran attorney to switch systems: show them they can be even more successful. [00:26:53 - 00:27:44] Claude Simpson flags a real risk: what happens if a firm and its cloud host end up in a contract dispute over data access. [00:29:19 - 00:30:31] Claude Simpson breaks down ROI beyond time saved: turnaround, error rate, client satisfaction, and staff retention. [00:33:00 - 00:34:00] Claude Simpson predicts AI bots listening in on firm discussions to suggest case values in real time.

  3. 5d ago

    Skills Acquisition: How One Litigator Uses Claude to Build His Case Strategy

    Summary Jared Correia sits down with Luis Vargas Rivera, head of litigation at Embedded Counsel, to unpack a problem most solo and small firm litigators never get to solve: a real moot before a hearing. Luis built a Claude skill called Adversarial Review that simulates a three-judge panel, each with a different mindset, to attack his motions before a judge ever does. From there, the conversation covers AI accountability and Rule 11, Luis's move from big law to a boutique firm, why marketing to referral sources beats paid ad spend, and how cross-practice litigation experience wins cases other lawyers can't see. They close on a shared obsession with a concept album about The Odyssey. Key Takeaways A Claude skill can run a three-persona Adversarial Review panel, a fact-focused judge, a procedural judge, and a pragmatist judge, that pressure tests a motion before oral argument. Citation tools like Lexis and Westlaw confirm your sources are accurate; they don't tell you where your argument is weakest. That's a different job. AI hallucinations are an accountability problem, not a technology problem. Rule 11 already requires lawyers to investigate what they sign, AI just removes the excuse for skipping that step. Marketing to other lawyers as referral sources can outperform paid ad spend aimed directly at clients, especially in crowded practice areas. Cross-practice litigation experience, moving ideas from civil litigation into a probate case, for example, can produce solutions opposing counsel doesn't see coming. Links and Resources Red Cave Law Firm Consulting: redcavelegal.com Embedded Counsel: embeddedcounsel.com Keywords Claude skills for lawyers, AI legal tech podcast, adversarial review AI skill, moot court AI simulation, AI argument testing for litigators, AI judge personas, legal AI ethics, Rule 11 AI hallucinations, boutique law firm AI, small firm litigation technology, AI referral marketing for lawyers, LinkedIn marketing for attorneys, cross-practice litigation strategy, probate litigation technology, AI generated evidence, deepfake chain of custody, Claude versus Westlaw, legal tech for solo practitioners, AI in law school, shadow AI in law firms Episode Highlights [00:02:10 - 00:04:00] Luis explains the Adversarial Review Claude skill and its three AI judge personas. [00:05:00 - 00:05:50] Luis contrasts a custom Claude skill with citation-checking tools like Lexis and Westlaw. [00:12:00 - 00:12:30] Luis estimates judges ask him questions his AI panel already raised 20 to 40 percent of the time. [00:13:10 - 00:14:05] Jared and Luis agree AI hallucinations are a lawyer accountability problem, not a technology problem. [00:14:10 - 00:16:00] Luis explains why he left big law for a boutique litigation practice at Embedded Counsel. [00:17:00 - 00:18:10] Luis lays out his thesis on marketing to referral sources instead of paid client acquisition. [00:21:00 - 00:22:20] Luis tells the story behind his $75,000 retainer LinkedIn hook. [00:25:30 - 00:27:00] Luis describes a cross-practice motion strategy that won a probate intervention in 15 minutes. [00:29:00 - 00:31:00] Luis and Jared discuss AI-generated evidence and chain-of-custody verification for deepfakes.

  4. Jun 24

    Voyage of Discovery: Why Managing ESI for Lawyers Is Easier Than Ever

    Summary Law firms and legal departments sit on mountains of electronically stored information, and most have no real system for dealing with it. Warren Parrino, Regional Vice President of Solution Sales at TrustPoint.One, has a clear starting point: email threading, date filters, and search terms. From there, an early case assessment environment can cut review costs before a single document hits a reviewer's queue.   Warren and Jared also cover modern attachments, audio and video redaction, and when AI actually earns its place in the workflow. The bottom line: AI only pays off after you have already done the basics. Crawl, walk, then run. About the Guest Warren Parrino is Regional Vice President of Solution Sales at TrustPoint.One, an e-discovery and legal services company. A former practicing attorney in Birmingham, Alabama, he most recently co-led the company's project management team before moving into his current role, giving him a view from both the operational and client-facing sides of a project. He still holds his bar license, attributing that decision entirely to how hard the exam was. Key Takeaways Start with email threading, date filters, and search terms before anything else. These three basics narrow your data set before you spend a dollar on document review. Early case assessment (ECA) databases are the single most effective way to cut e-discovery costs, yet most firms skip them because they have never heard of the approach, not because of cost. Modern attachments (hyperlinked files stored in OneDrive or SharePoint rather than attached directly to email) are the biggest current landmine in discovery, though workable solutions are emerging. Audio and video redaction that once cost thousands of dollars and required a production team can now be done at a desk in minutes using off-the-shelf tools. AI in e-discovery only delivers real savings after you have already cut your data set down. Throwing AI at a terabyte of raw data inflates your bill, it does not shrink it. Links and Resources TrustPoint.One: trustpoint.one Red Cave Law Firm Consulting: redcavelegal.com Keywords e-discovery, ESI, electronically stored information, early case assessment, ECA, email threading, modern attachments, hyperlinked files, data management, RelativityOne, shadow AI, legal technology, law firm data, e-discovery costs, solo practitioner, small law firm, audio video redaction, document review, TrustPoint.One, e-discovery consultant Episode Highlights [00:03:49 - 00:04:46]  Warren lays out the three starting points for any firm overwhelmed by data: email threading, date filters, and search terms, in that order, before anything else. [00:05:56 - 00:08:13]  Warren explains early case assessment, how it works in RelativityOne, and why communications analysis often surfaces the witness you never knew you needed. [00:08:13 - 00:09:02]  The reason most firms skip ECA is not cost. It is lack of knowledge, because if cost were the issue, everyone would already be doing it. [00:09:08 - 00:10:44]  Email threading today means reviewing one file instead of 15. It is not the labor-intensive process it once was, and the savings in time and cost are significant. [00:11:19 - 00:12:54]  Modern attachments (hyperlinked files in SharePoint or OneDrive) create versioning, custodian, and association problems that traditional e-discovery workflows were not built to handle. [00:14:59 - 00:17:28]  Audio and video redaction that once required a production team and thousands of dollars can now be done with off-the-shelf software at a desk. Warren shares a real transit authority case. [00:20:33 - 00:22:14]  There is no minimum data threshold for engaging an e-discovery consultant. The only question is whether the hassle of managing the data yourself outweighs your willingness to deal with it. [00:24:33 - 00:28:06]  AI in e-discovery is real and capable, but it only delivers savings after you have already cut the data set down. Warren describes what Relativity's AIR tools can do once the groundwork is done.

  5. Jun 15

    Search Engine: How to Create Content for the New Algorithm

    Summary Alan Alda runs his own firm and figured AI tools would make content creation easy. He was half right. Jared Correia sits down with David Arato, founder of Lexicon Legal Content, to unpack why mass AI publishing is triggering Google penalties, what compliance risks law firms are ignoring in their marketing content, and how the rise of AI overviews is reshaping the entire game.   David explains the EEAT framework, breaks down a three-level compliance review process for AI-generated content, and outlines what law firms should actually be doing to get cited in AI search results. The short version: less slop, more substance, and a human with a law degree reading everything before it goes live. About the Guest David Arato is the founder of Lexicon Legal Content, a content agency that has served law firms and legal marketing agencies for 15 years. A law school graduate who got his start writing legal blog posts for extra money while studying for the bar in 2009, David built Lexicon into a white-label content partner for major legal marketing agencies before pivoting to serve law firms directly. He is also a former professional cellist, which explains the hustle. Find him at lexiconlegalcontent.com. Key Takeaways "Scaled content abuse" triggers Google penalties. Publishing AI content at volume without editorial oversight risks manual penalties and lost search visibility overnight. 78% of legal searches now trigger AI overviews, pushing organic results below the fold and increasing zero-click searches that never land on your website. AI tools do not know your state bar's advertising rules. Terms like "expert," "specialist," and "best attorney" can trigger bar complaints without a human review step. The EEAT framework (Expertise, Experience, Authority, Trust) holds law firm websites to a higher standard than most sites because they fall under "your money or your life" (YMYL) categories. Trust is the pillar. Great content still ranks. Adding genuinely new information to the conversation is what earns Google's attention and gets your firm cited in AI overviews, ChatGPT, and Perplexity. Links and Resources Lexicon Legal Content: lexiconlegalcontent.com Red Cave Law Firm Consulting: redcavelegal.com Keywords AI-generated legal content, law firm SEO, Google AI overviews, legal content marketing, EEAT framework, YMYL websites, bar advertising rules, scaled content abuse, legal blog content, zero-click searches, AI content penalties, law firm website content, Google search quality rater guidelines, legal marketing compliance, content freshness SEO, Lexicon Legal Content, AI overviews for lawyers, law firm marketing strategy, shadow AI, law firm blog strategy Episode Highlights [00:03:06 - 00:04:01] David explains why the rise of AI tools actually increased demand for quality legal content, not killed it [00:06:10 - 00:07:07] The problem with "scaled content abuse" and why mass AI publishing tanks law firm sites [00:07:57 - 00:09:09] The compliance and malpractice risks hiding in AI-generated marketing content [00:19:04 - 00:20:43] 78% of legal searches trigger AI overviews, and what that means for your rankings [00:21:23 - 00:22:09] Traffic declines and the rise of zero-click searches reducing referrals to law firm websites [00:23:11 - 00:24:51] Three-level compliance review: catching what AI tools miss in legal marketing content [00:26:02 - 00:27:58] EEAT and YMYL explained: why law firm sites face a higher content bar than most

  6. Jun 5

    Launch Protocol: How Law Firms Are Adopting AI in Real Time

    Summary Jared Correia sits down with Sean McTigue, a partner at Bartko Pavia LLP and one of the more technically fluent attorneys in practice today. Sean unpacks how his firm navigated the leap from legal-specific AI tools to a direct enterprise deployment of Anthropic's models, and why he thinks that distinction matters a lot more than most firms realize. The conversation covers practical ground: how to use Westlaw's Quickcheck as a verification loop, why lawyers overestimate what AI will do for them on the first try, and how to find the early adopters inside a firm and turn their discoveries into firm-wide workflows. Sean also looks ahead at what AI means for the billable hour model and why the legal profession can't afford to stay in the way. About the Guest Sean McTigue is a partner at Bartko Pavia LLP in San Francisco, where he handles complex litigation with a particular focus on integrating AI into the practice of law. He has been following the development of large language models closely since GPT-4's launch and has led the firm's rollout of Anthropic for Enterprise. Sean studied philosophy at the University of Utah and earned his law degree at Berkeley Law. Key Takeaways Hallucination risk in AI outputs is a solved problem, using tools like Westlaw's Quickcheck as a verification flywheel alongside AI drafting, not a reason to avoid AI entirely. Legal-specific tools rarely add value beyond a general foundation model; the wrapper around the model matters less than most vendors claim. Direct enterprise deployment of a foundation model lets firms ride the frontier rather than being stuck on whatever model a SaaS vendor last tested. The billable hour model is under pressure, and firms that build internal AI capital now are better positioned to shift toward fixed-fee and alternative-fee arrangements. Adoption inside a firm starts with finding the heavy users, learning what they figured out, and distributing those workflows to everyone else. Links and Resources Red Cave Law Firm Consulting Bartko Pavia LLP Westlaw CoCounsel Westlaw Quickcheck - available inside your Westlaw subscription Anthropic for Enterprise Keywords AI adoption in law firms, legal AI tools, Westlaw Quickcheck, AI hallucinations legal, foundation models for lawyers, Anthropic for Enterprise, billable hours AI, legal tech vendor evaluation, Sean McTigue, Bartko Pavia, Jared Correia, Adventures in Legal Tech, CoCounsel Westlaw, AI verification legal, small firm AI, legal workflow automation, enterprise AI deployment, AI research tools lawyers, prompt engineering legal, alternative fee arrangements AI Episode Highlights [00:02:01 - 00:04:54] Sean introduces Westlaw Quickcheck as the underused verification tool that turns hallucination risk into a manageable step in the workflow. [00:05:00 - 00:07:57] Sean explains why lawyers who try AI once, find it imperfect, and dismiss it are missing the workflow question entirely. [00:08:13 - 00:09:28] The hammer-and-nail analogy: being handed a tool and told to use it without any guidance on what the full project actually looks like. [00:19:14 - 00:23:27] Sean describes the frustration of vetting legal AI vendors who can't tell you what model they're running, including an e-discovery platform using Haiku 3 on million-document reviews. [00:24:54 - 00:28:05] The case for direct foundation model deployment over legal-specific SaaS wrappers, and what you can do with a generalist model that a niche tool will never offer. [00:36:44 - 00:40:43] The future of legal billing: from the billable hour back toward fixed-fee engagements, and why firms that build AI capital now are better positioned. [00:41:50 - 00:47:23] Sean's starter recommendation: Westlaw citing references downloaded in bulk and fed to an LLM, plus why Google AI Overview is already AI whether lawyers know it or not.

  7. May 25

    The Ontological Argument: What's Real & Not in Artificial Intelligence in LegalTech

    SUMMARY Teo Doremus traded a litigation desk in China for a startup in San Francisco, and along the way he became convinced that the legal industry's AI moment is right now. On this episode, Teo makes the case for starting an AI-native law firm, walks through how he thinks about hallucination risk, and explains the "digital desk" concept behind Advocacy, a platform built to connect the narrative silos of litigation that have historically lived in Microsoft Word and nowhere else. Teo also shares what he got wrong about law practice, why he thinks lawyers misunderstand what AI actually does when it "helps" them, and draws the most useful analogy you will hear about what lawyers get paid for in an AI world. The pilot and the autopilot are not enemies. Neither are lawyers and AI. The question is figuring out who does what. KEY TAKEAWAYS Start building your AI-native practice now. The advantage goes to whoever gets comfortable with the technology first, not whoever waits for it to be perfect. Before deploying AI in your firm, learn what it actually is and what it is not. Understanding its fundamental limitations is your best defense against hallucinations. AI adoption in law is high on subscriptions and low on genuine daily use. Real adoption means using AI regularly enough that it changes how you work, not just having a login. Specialized legal AI tools and general AI tools are not competitors. Use both strategically depending on how much precision your task requires. The lawyer's value in an AI-assisted practice looks like the pilot who no longer holds the stick for seventeen hours: rested, prepared, and ready for whatever the automation cannot handle. WHO IS THE GUEST? Teo Doremus is the CEO and co-founder of Advocacy, a litigation-focused AI platform built around what he calls the "digital desk," a place where all the narrative silos of a case live together and AI connects them. Before founding Advocacy, Teo practiced law in China and the United States as both a litigator and a transactional attorney. He studied law in France after picking it almost by accident at 18, fell in love with it along the way, and eventually made his way to San Francisco, where a deep dive into AI convinced him the legal industry needed something that did not yet exist. Advocacy can be found at advocacy.ai.   LINKS AND RESOURCES Advocacy: advocacy.ai Red Cave Law Firm Consulting: redcavelegal.com Adventures in Legal Tech Podcast: Available on Apple Podcasts, Spotify, Amazon Music, and YouTube.   KEYWORDS AI-native law firm, legal AI, artificial intelligence for lawyers, AI hallucinations in law, litigation AI tools, Advocacy AI, legal tech software, law firm technology, AI adoption in legal, legal software selection, AI-powered litigation, law practice management, Red Cave Law Firm Consulting, Teo Doremus, Jared Correia, AI governance for lawyers, digital desk litigation, specialized legal AI, general AI for law firms, Adventures in Legal Tech EPISODE HIGHLIGHTS [00:02:02 - 00:02:48] Teo's immediate, unhedged answer on the AI-native firm question: do it, do it now, and do it because the technology rewards early commitment. [00:04:35 - 00:06:03] Why the hallucination conversation needs multiple angles at once, and why no single answer is going to hold. [00:06:04 - 00:06:44] What lawyers fundamentally misunderstand about AI: it does not actually understand you. When it does not know the answer, it just agrees with you. [00:10:37 - 00:11:26] Teo describes the moment AI went from a five-minute curiosity to a full obsession that changed the direction of his career. [00:13:55 - 00:14:28] The origin of the "digital desk" concept and why Microsoft Word from 1984 is still, technically, the competition. [00:21:40 - 00:23:11] The pilot analogy: if planes have flown themselves for twenty years, what exactly are pilots for? And what does that tell us about lawyers?

  8. May 11

    First Light: Structural Intelligence Must Come Before Artificial Intelligence

    🧾 Episode Summary In this episode of Adventures in Legal Tech, host Jared Correia sits down with Tim Follett, CEO and co-founder of StructureFlow, to unpack one of the most overlooked yet critical challenges in legal work: structural complexity. From corporate transactions to litigation strategy, legal professionals rely heavily on understanding relationships—between entities, obligations, and flows of value. Yet, the tools used to map these structures haven't meaningfully evolved in decades. Tim introduces the concept of structural intelligence, explaining how visual models and semantic data layers can transform diagrams into powerful interfaces for both humans and machines. The conversation explores how diagrams function as "context-loading mechanisms," why AI needs structured foundations to be effective, and what the future of legal interfaces might look like—hint: think Minority Report. This episode blends legal tech, cognitive science, and AI strategy into a compelling argument: if you don't structure your data properly, AI might accelerate your work—but in the wrong direction. 🔗 Links & Resources StructureFlow: https://structureflow.co redcavelegal.com 🔑 Keywords legal tech legal innovation structural intelligence information architecture AI in law legal workflows data visualization diagramming corporate law litigation strategy knowledge management graph data RAG systems legal AI StructureFlow productivity tools legal design ⏱️ Episode Highlights 00:00–01:18 – Introduction to the podcast and the problem of structural complexity in legal work 01:18–02:09 – Why outdated tools (PowerPoint, spreadsheets) still dominate legal workflows 02:09–03:12 – Defining the problem: increasing complexity in professional and personal contexts 03:12–04:16 – Historical roots of diagramming—from early businesses to modern law firms 04:16–05:33 – Why visualizing relationships is essential to understanding structure 06:09–07:20 – What StructureFlow does and how it differs from traditional diagram tools 07:20–08:14 – The power of semantic meaning behind diagrams (data + visuals) 08:14–09:00 – Use cases across law firms, accounting, and corporate environments 10:11–11:02 – Diagrams as knowledge assets and tools for rapid context recall 15:30–16:08 – Diagrams as "context-loading mechanisms" for the human brain 16:08–17:08 – Visual processing vs. text: why diagrams accelerate understanding 17:08–18:14 – Graph structures explained and their role in representing relationships 18:14–19:22 – RAG systems and how AI retrieves and processes structured knowledge 21:01–22:09 – Why AI needs structure: "acceleration without direction" risk 24:51–26:27 – The "Minority Report" vision for the future of legal interfaces

5
out of 5
6 Ratings

About

"Adventures In Legal Tech" explores effective solutions to unique technology issues. Each episode provides actionable steps to solve everyday problems lawyers encounter. It's kind of like "This Old House" — but with way more law.

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