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Brad Pitt's firm doesn't have a missing-tool problem. It has a tools-that-don't-talk problem, and a person sits between every pair of systems re-keying the same client data. Alejandro Castellano of Caddi joined me to unpack how AI agents can take over that back office work, and how to keep them on a short leash. If your team spends its week clicking between systems, this one's for you. Key Takeaways Map where your people re-key data between intake, matters, documents, signatures, and billing, because those hand-offs are where the time goes. Look at back office automation before billable-work automation, since saving operational time puts money in your pocket without changing what you bill. Constrain AI agents to the steps you've taught them, set permissions through IT, test before anything goes live, and require an audit log of every action. Set firm-wide rules for agents, such as agents can draft client emails but never send them on their own. Start with a low-risk experiment, like an agent that sorts your email into folders, and move off on-prem systems that limit what agents can do. About the Guest Alejandro Castellano is the CEO and co-founder of Caddi, an AI back office platform for law firms and other professional services firms. Born in Peru, he spent more than 10 years implementing technology in professional services, including real estate and financial services, before focusing on legal over the last three to four years. He studied electrical engineering in Peru, earned his master's at Cornell Tech in New York, and was accepted into the Allen Institute for AI Incubator in Seattle. He's the guest who comes to Brad Pitt's rescue in this episode's opening scenario. Links and Resources Caddi: trycaddi.com Red Cave Law Firm Consulting: redcavelegal.com Listen: Apple Podcasts, Spotify, Amazon Music, Deezer, YouTube, RSS Keywords law firm software integration, siloed systems, law firm automation, back office automation, AI agents for law firms, AI agents, legal AI tools, AI governance, law firm technology, legal tech, legal technology, practice management software, vibe coding, law firm operations, small law firm, solo practitioner, flat fee billing, Caddi, Jared Correia, Adventures in Legal Tech Episode Highlights [00:01:00 - 00:02:00] The vexing problem: intake, matters, documents, signatures, and billing live in separate tools, and people re-key data between them. [00:03:00 - 00:04:00] Alejandro says roughly half of an expert's time, plus staff time, goes to clicking things around between systems. [00:04:00 - 00:06:00] How Caddi works: a Discover agent finds automation opportunities, and Automate agents learn your process like a new employee. [00:05:00 - 00:07:00] Time entries began as a way to measure capacity for everyone at the firm, and firms lost visibility into staff operations. [00:06:00 - 00:08:00] Why automating the back office fits a law firm's business model better than automating the work you bill for. [00:08:00 - 00:09:00] Flat fees and subscriptions: clients push prices down, yet distrust fixed pricing, and one attorney's subscription offer got a no from every client. [00:09:00 - 00:11:00] Governance: agents constrained to the steps you teach them, plus oversight across departments and practice areas. [00:14:00 - 00:16:00] Vibe coding horror stories: thousands of dollars burned on a job a $20 tool could do, and 2,000 records updated the wrong way. [00:16:00 - 00:18:00] Permissions, workarounds, and testing before launch, plus a low-risk first experiment: sorting your email. [00:26:00 - 00:29:00] No big clean-up needed first, the on-prem problem, and why Caddi now maps AI opportunities and ROI.

Diana Prince's firm just hit 75 lawyers, and the infrastructure behind those lawyers didn't grow with them. Beth Thompson of Actionstep joined me to unpack how a firm of any size can grow with software, clean processes, and better numbers instead of just more headcount. If your pre-bill queue is a mess and your reports only tell you what already happened, this one's for you. Key Takeaways Write down your growth plan and map every step a matter takes, including who touches the file and how often the client hears from you, before you add people or software. Don't onboard new hires onto technology and processes that no longer serve you, because you're setting them up to fail. Grow without adding headcount by making your current people more effective, taking on new practice areas, and sometimes skipping the backfill when someone leaves. Make your firm earn AI: clean data, defined processes, and automation first, and check which tools you already pay for have added AI before you buy anything new. Review your metrics regularly, meet about them, and act on them. A monthly report nobody can explain is just paper. Links and Resources Actionstep: actionstep.com Red Cave Law Firm Consulting: redcavelegal.com Listen: Apple Podcasts, Spotify, Amazon Music, Deezer, YouTube, RSS Keywords law firm growth, law firm growth strategies, legal tech, legal technology, practice management software, law firm workflows, law firm automation, law firm SOPs, law firm metrics, AI for lawyers, legal AI tools, small law firm, solo practitioner, scaling a law firm, continuous improvement, non-billable time, Actionstep, Actionstep Intelligence, Jared Correia, Adventures in Legal Tech Episode Highlights [00:01:00 - 00:02:00] The vexing problem: Diana Prince's firm hits 75 lawyers, and pre-bill queues, intake, and reporting start to crack. [00:03:00 - 00:05:00] Beth's first move: analyze your growth plan and map every step a matter takes before you onboard anyone new. [00:06:00 - 00:08:00] Growing capacity without headcount: make current people more effective and consider new practice areas. [00:09:00 - 00:10:00] The three assets in a law firm, and why you need an honest baseline of where you are today. [00:10:00 - 00:12:00] A Melbourne firm grows from four attorneys to 60 and hires a continuous improvement officer. [00:13:00 - 00:14:00] Non-billable work as money down the drain, and why you map workflows before you automate them. [00:14:00 - 00:15:00] Beth's case that a firm has to earn AI, and why you check your current tech stack first. [00:19:00 - 00:21:00] Actionstep Intelligence: AI built inside the platform so you don't add another tool or login. [00:22:00 - 00:24:00] Designing law firm metrics: capture your time, find the bottlenecks, and know what to do with the data. [00:25:00 - 00:26:00] Why firms should meet about their metrics, and the monthly report nobody can explain.

Chance Shifflett, head of product at Rev, joins Jared to unpack how solo and small-firm criminal attorneys can get a handle on the flood of evidence, body cam footage, jail calls, depositions, and thousands of documents, that discovery throws at them. He explains what makes an investigative platform different from a generic discovery tool, why verbatim transcription and accurate speaker diarization are non-negotiable in criminal cases, and why running privileged evidence through a generic AI tool is a real risk. He also lays out how to actually pilot legal AI before you trust it with a case. Key Takeaways An "investigative platform" is built to help you interrogate a body of evidence and find the truth, not just search a document set, and that is a different job than most discovery software does. Verbatim transcription, capturing every stutter, false start, and "mm-hmm," matters in criminal cases because a polished transcript can smooth over the details that end up mattering to the outcome. Speaker diarization is still the hardest problem in legal transcription, especially on body cam footage and jail calls, where bad mics and background noise make it worse. When you pilot an AI tool, put your skeptics on it instead of your AI enthusiasts. They are the ones who will tell you what will actually break at your firm. AI can help draft documents and process evidence faster, but it cannot read a jury's emotions or tell a case's story, so the courtroom skills that make a great trial lawyer are not going anywhere. Links and Resources Rev: rev.com Red Cave Law Firm Consulting: redcavelegal.com Listen: Apple Podcasts, Spotify, Amazon Music, YouTube Keywords legal tech, legal technology, AI for lawyers, legal AI tools, e-discovery, investigative platform, evidence review, speaker diarization, verbatim transcription, legal transcription, body cam footage, jail calls, criminal defense technology, small law firm, solo practitioner, shadow AI, AI hallucinations, Rev, Red Cave Law Firm Consulting, Jared Correia Episode Highlights [00:01:00 - 00:02:00] The vexing problem: Emma Stone's team is drowning in body cam footage, jail calls, depositions, and documents during discovery. [00:09:00 - 00:10:00] Chance calls speaker diarization the hardest problem in the market, especially on body cam and jail call audio. [00:11:00 - 00:12:00] Rev's own transcription workforce pushed back the first time the company built an AI model. [00:14:00 - 00:15:00] Rev paused all production for several weeks to rebuild its internal process around AI. [00:15:00 - 00:16:00] Why running privileged legal data through a generic AI tool is a real risk, not a shortcut. [00:21:00 - 00:22:00] Chance's pilot advice: put your AI skeptics on the test, not your true believers. [00:23:00 - 00:24:00] The adoption gap: a 25-person firm where five lawyers using AI jump from 95 cases to 130. [00:29:00 - 00:31:00] Why courtroom skills, like telling a story a jury will feel, cannot be automated.

Raj Selvadurai, founder of Gold Street Legal Search and Lateral IQ, has spent nearly twenty years placing lateral partners the old-fashioned way: relationships, referrals, and a lot of judgment calls about who actually fits where. On this episode, Raj explains why general AI tools like ChatGPT fall short for recruiting, how he built Lateral IQ to give partners and firms verified, self-service data, and why the real signal in lateral hiring isn't who a firm hires, it's who actually stays. If you've been wondering whether AI can touch a business this relationship-driven, this conversation has the answer. KEY TAKEAWAYS Traditional lateral recruiting has always run on relationships first, and that's exactly where the risk lives: a partner's promised book of business doesn't always fully travel with them. General AI tools aren't built for a market this specific. Verification, not raw intelligence, is what recruiting actually needs, since two partners can share the same name at different firms. Real growth and churn can look identical on paper. Tracking a firm's actual hires and departures, not just its hiring announcements, is the only way to tell them apart. AI doesn't replace a recruiter's judgment, it removes the weeks of manual dossier-building so that judgment has something accurate to work from. The pandemic proved lateral moves don't need a year and a dozen in-person meetings; verified data is what lets that faster pace hold up. LINKS AND RESOURCES Lateral IQ: lateraliq.app Gold Street Legal Search: goldstreetlegal.com Red Cave Law Firm Consulting: redcavelegal.com Adventures in Legal Tech Podcast: Available on Apple Podcasts, Spotify, Amazon Music, and YouTube. KEYWORDS AI legal recruiting, lateral partner recruiting, legal recruiting software, AI hallucinations in law, Lateral IQ, Gold Street Legal Search, law firm lateral hiring, legal tech software, law firm growth, AI adoption in legal, verified AI data, law firm private equity, legal industry mergers, law practice management, Red Cave Law Firm Consulting, Raj Selvadurai, Jared Correia, AI for law firm recruiting, partner recruiting technology, Adventures in Legal Tech EPISODE HIGHLIGHTS [00:03:04 - 00:03:58] Raj lays out the core risk in lateral recruiting: partners who promise a book of business that shrinks the moment the move is final. [00:04:03 - 00:04:58] Why hallucinations and name collisions make general AI tools a poor fit for a market this specific. [00:09:04 - 00:09:32] The $10 million lateral hire that closed entirely over Zoom, with no in-person meeting except to pick up a laptop. [00:14:09 - 00:15:10] The line that reframes the whole episode: hiring 50 partners and losing 49 isn't growth. [00:17:01 - 00:17:59] Raj's own account of building Lateral IQ with zero coding background, and why owning the code mattered. [00:29:24 - 00:30:15] Raj's case for law firms building their own private equity arm instead of ceding control to outside investors.

This week's vexing problem: solo attorney Ernie DiGregorio has no IT department and no fractional vendor to help him weigh AI tools against data security and client confidentiality. Michael Santomaro, principal of Santomaro Law in Providence, walks through how he actually uses AI across his personal injury and criminal law practice, from proofreading pleadings to finding federal court rules he'd never needed before. We also get into hallucination risk, the malpractice argument for using AI at all, and how Michael turned a deeply personal passion into a growing corner of his practice. Key Takeaways Run every draft through AI before it goes out. Michael caught over twenty typos in a single complaint once he started running documents through AI, and in his book, typos in 2026 read as laziness, not just error. Using AI to rework a sentence or a closing argument isn't cheating, it's the same move as using a thesaurus or asking a colleague at the water cooler. AI can get you to an unfamiliar rule fast, but it can't replace reading the cases yourself. Hallucinated citations have already gotten lawyers sanctioned. If you've never touched AI, start small: feed ChatGPT an email you already wrote and see what it changes. Think of it as a curator, not a mystery box. Solo and small firms without in-house IT can still build real AI infrastructure with off-the-shelf add-ins for Microsoft, Adobe, and Lexis. Links and Resources Santomaro Law: https://santomarolaw.com Red Cave Law Firm Consulting: https://redcavelegal.com Keywords legal tech, legal technology, AI for lawyers, legal AI tools, solo practitioner, small law firm, law practice management, law firm technology, ChatGPT for lawyers, AI hallucinations, legal ethics AI, client confidentiality, law firm marketing, personal injury law, legal research AI, document automation, shadow AI, Jared Correia, Adventures in Legal Tech, Red Cave Law Firm Consulting, AI malpractice risk Episode Highlights [00:02:00 - 00:04:00] Michael explains Ernie DiGregorio's Providence College basketball legacy and his own family connection to him. [00:05:00 - 00:06:00] Michael shares the malpractice warning that pushed him to adopt AI: skip it, and you're falling behind opposing counsel. [00:07:00 - 00:08:00] Michael describes running a redacted complaint through AI and catching over twenty typos his staff missed. [00:08:00 - 00:09:00] Michael uses AI to find unfamiliar federal court rules on his first case removed from state court. [00:09:00 - 00:11:00] Michael pushes back on the idea that using AI to write is cheating, comparing it to a thesaurus or a colleague's input. [00:10:00 - 00:11:00] Michael flags the real risk: hallucinated case law and the sanctions lawyers have already faced for not checking it. [00:13:00 - 00:15:00] Michael's advice for AI beginners: run an email you already wrote through ChatGPT and see what changes. [00:20:00 - 00:23:00] Michael opens up about his personal connection to plant medicine and his work with the Psychedelic Bar Association. [00:26:00 - 00:30:00] Michael breaks down how referral relationships, not big ad spend, drive his caseload.

Executive Summary Jared sits down with Carly Savar, general counsel at Steno, to unpack what actually happens when a law firm signs up with an AI vendor. Carly explains why reading the fine print matters more than any feature list, and what separates a vendor you can trust from one that's just telling you what you want to hear. Key Takeaways Read the actual data processing agreement yourself. Don't assume a vendor's security is handled just because they signed a service level agreement. Push for a zero-day retention agreement, and ask about the LLMs your vendor is built on, not just the vendor itself. SOC 2 Type 2 certification means a company's controls held up over a full year. SOC 2 Type 1 only proves a single snapshot in time. Not all training is created equal. Aggregated usage data is usually fine. Your client's confidential content should never go into a model. New billing ethics guidance says you can only charge for the time you actually spent, not the time an AI tool saved you. About the Guest Carly Savar is general counsel at Steno, a litigation support and court reporting technology company. She spent years litigating before founding her own legal recruiting company and eventually moving in-house. Carly now negotiates AI and data agreements from both sides of the table, as counsel to a legal tech vendor and as a buyer evaluating other vendors herself. Links and Resources Steno: steno.com Red Cave Law Firm Consulting: redcavelegal.com Keywords legal tech, legal technology, AI for lawyers, AI vendor vetting, legal AI vendor contracts, data security for law firms, zero-day retention agreement, SOC 2 Type 2, SOC 2 certification, ISO 27001, shadow AI, in-house counsel, legal tech general counsel, court reporting technology, Steno, AI training data, law firm AI policy, small law firm technology, technology competence rule, Red Cave Law Firm Consulting Episode Chapters 00:00:00 Cold open and show intro 00:02:00 Meet Carly Savar and the vexing AI vendor problem 00:03:00 Zero-day retention and why training on your data is the real risk 00:06:00 What to actually ask vendors before you sign 00:08:00 SOC 2 Type 1 vs Type 2 and other certifications 00:10:00 Life as GC inside a legal tech vendor 00:13:00 Clients who want cool tech vs clients who ask the right questions 00:15:00 Not all training is created equal 00:16:00 Keeping up with shifting ethics rules and regulations 00:18:00 Tech competence and billing for time spent, not time saved 00:22:00 Advice for lawyers going in-house at startups 00:24:00 Carly's path into law and out of Big Law litigation 00:27:00 Finding Steno and the frog-in-water approach to tech adoption 00:33:00 Going to law school too soon and learning to fail 00:37:00 Women in legal tech today 00:39:00 Wrap-up and where to find Carly and Steno

Executive Summary On this episode of Adventures in Legal Tech, Jared Correia talks with Phillip Greer, CEO of Best Lawyers, about how AI is rewriting the rules of legal search and firm operations. Greer breaks down the real differences between SEO, AEO, and GEO, then explains how he turned his own company into a shop full of vibe coders. It's a practical look at getting found online and getting comfortable with AI at the same time. Key Takeaways SEO isn't dead. It's the foundation that feeds AEO and GEO, the practices that get law firms found inside AI search tools and chatbots. Quality, well-structured content and citations from reputable third-party sites matter more than backlink farming ever did. Legal consumers across every generation are shifting from typed search terms to conversations with AI tools, often without realizing it. Building an AI-literate firm starts with a safe, governed environment where non-technical staff can experiment without touching client data. Start small. Pick something fun, not a client matter, to learn how an AI tool handles data before you roll anything out firmwide. Links and Resources Red Cave Law Firm Consulting: redcavelegal.com Best Lawyers: bestlawyers.com Keywords AEO, GEO, AI search optimization, legal SEO, AI Overview, ChatGPT for lawyers, shadow AI, vibe coding, AI-literate law firm, Best Lawyers, legal directory marketing, law firm content strategy, AI governance, legal tech podcast, Jared Correia, Phillip Greer, structured data for lawyers, AI search engines, law firm AI adoption, legal marketing strategy Episode Highlights [00:02:29 - 00:04:31] Greer lays out his top SEO pitch: keep doing SEO, treat it as the foundation feeding AIO. [00:04:56 - 00:08:38] Greer defines SEO, AEO, and GEO and explains why all three belong in a firm's strategy. [00:09:32 - 00:11:59] Greer traces shadow AI from a guilty secret to standard practice at nearly every firm. [00:12:56 - 00:16:39] Greer argues authenticity beats generic AI-written content and backlink farming for standing out. [00:27:48 - 00:32:20] Greer describes building the Best Lawyers internal app store that turned employees into vibe coders. [00:32:48 - 00:36:13] Greer explains how he handled data governance and change fears before rolling AI out company-wide. [00:36:20 - 00:39:08] Greer's advice: start vibe coding with something fun and low-stakes before touching firm data.

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.

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.

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.

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.

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

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.

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?

🧾 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