AI Tools for Practicing Lawyers

Ron Drescher

AI Tools for Practicing Lawyers delivers practical, no-nonsense guidance on how attorneys can use artificial intelligence tools in their law practices — right now. This podcast is for practicing lawyers who want real-world answers, not hype. Each episode focuses on clear, understandable explanations of AI tools that can help attorneys work more efficiently, communicate more effectively, and make better business decisions — without requiring technical expertise or coding knowledge. We cover topics such as: • Using AI responsibly and ethically in legal practice • Drafting, research, summarization, and document review tools • Client communication and intake automation • Practice management efficiencies • Emerging AI platforms relevant to law firms • Real examples attorneys can apply immediately Whether you are a solo practitioner, small-firm attorney, or part of a larger practice, this podcast is designed to help you understand what AI can — and cannot — do for lawyers today. No futurism. No speculation. Just practical tools for practicing lawyers. Hosted by Ron Drescher

  1. 1 day ago

    Episode 015: The Last Flintstones Lawyer

    Most conversations about AI and legal writing focus on the tools. This one focuses on the lawyers. What does a Flintstones lawyer actually do on Monday morning after they've finally decided to move? What does a Simpsons lawyer do when they discover their favorite tool isn't safe for client data? And what happens when the question isn't whether to adopt AI — but whether you'll survive professionally if you don't? Ron sits down with co-host Heather Gardner and Maryland attorney and legal educator Donna Mandl to work through the questions practicing lawyers are actually asking — the ones that never make it into the marketing decks. In this episode: Why a Flintstones lawyer's first move should be calling their Westlaw or Lexis rep — not downloading a new appWhy Heather recommends Enterprise ChatGPT as the right entry point for lawyers handling client informationThe "Claude as cleanup hitter" workflow: how to keep confidential work in a secure tool and bring the output to Claude for draftingGemini's hidden advantage — and why most lawyers are using it wrongThe hallucination problem everyone's talking about — and why fake citations aren't the real crisisThe subtler risk: cases that exist but don't say what AI claims they say, and standards of review that get quietly swappedDonna's paralegal education pivot — from policing AI use to training students to audit what AI producesRon's prediction: by end of this decade, there will be no more Flintstones-level lawyersWe also discuss: What Heather and Donna are presenting at the Maryland State Bar Association's Legal Summit panel — Ethics, Accuracy, and Efficiency: AI in Legal WritingWhy judges are getting frustrated with both pro se AI filings and inaccurate AI-assisted briefs from lawyersRon's Claude experiment: feeding Claude its own 21 hallucination types and asking how many the new model would fix (14 of 21 — 7 remain hard)The FSJ-client alignment theory: Flintstones clients are disappearing, and Flintstones lawyers will have to followFSJ-segmented follow recommendations: Dan Block (Flintstones), Ruben Hassid (Simpsons), Rich Rodgers (Jetsons)The Practice Signal segment: can AI help a burned-out workers' comp lawyer find a new career?Key Takeaway The governance question for legal AI isn't philosophical anymore — it's a billing-line decision. Whether it's a $1,400-a-year Claude Enterprise commitment or a workflow choice about which tool sees client data, the lawyers who figure out the tiers will outpace the ones still treating a free-tier tool as a research platform. Availability is not authority — and neither is a consumer account. Flintstones lawyers who hear this episode have a clear Monday-morning move. Simpsons lawyers who've fallen for Claude but balked at the enterprise price now have a workaround. And Jetsons lawyers will recognize the gap is widening faster than most of their colleagues realize. Heather said it best: prompting got us from Flintstones to Simpsons. Learning to think and collaborate with AI is what takes you to Jetsons. Mentioned in This Episode Heather Gardner — co-host, AI Tools for Practicing LawyersDonna Mandl — Maryland attorney; legal educator, Community College of Baltimore County (LinkedIn)Shaun Koenig — Maryland attorney, MSBA Legal Summit panelist (LinkedIn)Maryland State Bar Association Legal Summit — Ethics, Accuracy, and Efficiency: AI in Legal Writing panelChatGPT (OpenAI) — free tier and Enterprise tierClaude (Anthropic) — Pro tier and Enterprise tierClaude Code (Anthropic)HarveyGoogle Gemini — consumer and Enterprise ($36/month) tiersWestlaw (Thomson Reuters)LexisNexisFastcaseRich Rodgers — prior guest, Episode 014; founder, StartupTechLaw (LinkedIn)Dave Block — legal AI commentator; recommended follow for Flintstones lawyers (LinkedIn)Ruben Hassid — Claude evangelist; recommended follow for Simpsons lawyers (LinkedIn)Field Note: 21 Ways AI Can Hallucinate in Your Legal BriefField Note: Tiers of the Clown Mezu v. Mezu, Maryland Appellate Court No. 361 (2025)info@drescherlaw.com

    38 min

  2. 5 days ago ·  Bonus

    Field Note: Tiers Of The Clown

    The question everyone is asking is wrong. When lawyers debate which AI tier is "smarter," they're arguing about a label — and labels end analysis. The better question isn't which tier is best. It's what capabilities am I actually buying, and whether those capabilities match the task in front of you. Ron's File Cabinet Test experiments proved this the hard way: Enterprise-tier AI passed tests his Plus account failed. But when it came time to brainstorm a podcast episode, he went right back to Plus. Not because it was smarter. Because it knew him. In this episode: Why "smarter" is a label that ends analysis instead of starting itThe six capability categories that actually differentiate AI tiers: context window, retrieval, usage limits, connectors, memory, and governanceHow Ron's File Cabinet Test revealed a material performance gap between Plus and Enterprise environmentsWhy the best AI tier is the one whose capabilities and accumulated context match the task — not the one with the highest price pointWhy governance and capability are different things, and why you need bothThe framework for evaluating AI tiers that survives even when pricing, features, and model names changeWe also discuss: How a Reddit thread about AI tiers triggered Ron's thinking on this episodeWhy Ron returns to his Plus account for podcast brainstorming even after seeing Enterprise outperform itThe companion handout for this episode (and why it may already be partially obsolete)How ChatGPT, Claude, and Gemini package the same core capabilities in different waysThe analogy of the context window as the size of an AI's deskKey Takeaway Stop asking which AI is smartest. Start asking which capabilities matter for the task at hand. Retrieval isn't reasoning. Governance isn't performance. Context is accumulated over time, and a tool that knows your practice may outperform a more capable tool that doesn't. The best tier is the one aligned with what you're actually trying to do. For Flintstones lawyers, this episode removes the paralysis. You don't have to figure out which AI won. For Simpsons lawyers who've already paid for something, this is the framework for deciding whether they bought the right tier — or just the most expensive one. Jetsons lawyers will recognize the capability taxonomy immediately and probably already live by it. Mentioned in This Episode ChatGPT (OpenAI)Claude (Anthropic)Gemini (Google)Heather Gardner (co-host, Enterprise environment)File Cabinet Test (Ron's benchmark framework)Folder Mania experimentsThree-Legged Stool (compliance framework — see Field Note: Building the Stool — How to Implement the AI Discovery Standards)Flintstones/Simpsons/Jetsons FrameworkCompanion handout (available at lawyeraitoolkit.com/deliverables)Redditinfo@drescherlaw.com

    10 min

  3. 28 May

    Episode 014: Billable Hours and the AI Native Law Firm

    SHOW NOTES  Is the billable hour a liability you're voluntarily handing to your clients — and is AI finally giving lawyers a way out? Rich Rodgers has been building AI-native legal tools since before most lawyers knew what a large language model was. He's a practicing startup attorney, a four-time founder, and the creator of Start Legal — an AI platform designed to give founders a running start on legal work before they ever engage counsel. This episode isn't about whether AI will replace lawyers. It's about whether lawyers who refuse to adapt will replace themselves. In this episode: How Rich Rodgers built Start Legal out of 20+ custom GPTs originally created for his own clients at Startup Tech LawWhy Rich charges $10,000 to review AI-generated client contracts — and why no one has ever taken him up on itThe "Attorney Assist" model: how Start Legal pairs AI-generated documents with on-demand attorney review starting at $150 for 30 minutesWhat "AI-native law firm" actually means — and why it's harder to define than the people throwing the phrase around on LinkedIn let onThe argument for scrapping the billable hour: if AI cuts a 5-hour task to 5 minutes, does the client owe you for the hours you didn't spend?Rich's AI-generated invoicing workflow — how he wakes up on the 1st of every month with all client invoices already built and ready to sendThe Delaware ruling allowing corporations and other artificial entities to vote in certain municipal elections — and what it might mean for corporate governance documentsA concrete FSJ roadmap: what Flintstones-, Simpsons-, and Jetsons-level lawyers should actually do nextWe also discuss: The em-dash problem: how a punctuation mark became a tell for AI-generated text (and Ron's personal defense of it)Whether AI-native practice is more natural in transactional work than litigation — and where the limits actually areThe UK firm licensed to practice law as an AI — and the startup firm handling traffic tickets with no human attorneyWhether Flintstones lawyers should only try to serve Flintstones clients, or whether tech alignment between lawyer and client mattersWhy Rich thinks the next generation of clients will arrive already fluent in Claude and GPT — and what that means for practices that aren't readyKey Takeaway Availability is not authority — and it's not a business model either. Clients are already arriving with AI-drafted contracts, AI-researched questions, and AI-generated documents they believe are finished products. The lawyers who treat that as a threat are the ones charging $10,000 for a GPT contract review as a way of saying no. The lawyers who treat it as an opportunity are building the tools, setting the terms, and staying in the loop on their own conditions. The Flintstones lawyer's first move isn't to become a Jetsons lawyer overnight. It's to take whatever templates, clauses, and hard-won knowledge are sitting in a file cabinet — or a Microsoft Word folder — and start turning them into something that works for clients instead of just for the file. The Simpsons lawyer who's already prompting should be connecting those prompts to the operational infrastructure: billing, CRM, invoicing. The Jetsons lawyer is already doing what Rich is doing. The question for everyone else is how long the gap keeps widening. Mentioned in This Episode Rich Rodgers — https://www.linkedin.com/in/richrodgers360/Start Legal — https://startlegal.com/Startup Tech Law — https://www.startuptechlaw.com/Claude (Anthropic) — https://claude.ai/ChatGPT / OpenAI GPT Store — https://chatgpt.com/gptsinfo@drescherlaw.com

    40 min

  4. 26 May ·  Bonus

    Workflow Options: Claude for Legal and Strongsuit

    Workflow Options: From Prompts to Presets Every lawyer who has ever stared at a blank prompt box knows the feeling. AI promised to change how legal work gets done — but a single chatbox isn't a workflow. The legal AI world is splitting in two: enterprise ecosystems building choreographed plugin infrastructure, and vertical tools purpose-built for specific practice areas. The real question isn't which AI is smartest. It's which platform removes the most friction for your practice. In this episode: Why the AI world is moving from one-off prompting to persistent, repeatable workflow environmentsWhat connectors, APIs, MCPs, plugins, and skills actually mean — and how they differ from each otherWhat Claude for Legal launched: 22 connectors, 12 plugins, and MCP architecture designed for enterprise legal environmentsWhy Claude for Legal is largely out of reach for solo and small firm lawyers — and why that's not necessarily a problemWhat StrongSuit is, how its divorce and family law workflow presets work, and what "blank prompt box anxiety" means for practicing lawyersHow Markdown (.md) workflow files work, why they're portable across frontier AI tools, and how Ron built his ownWe also discuss: Why Consumer Claude Pro is not three-legged stool compliant for confidential client dataThe M&A demo Anthropic ran at their Claude for Legal launch — and what it signals about their actual target marketHow enterprise platforms like Harvey, Copilot, and Gemini fit into the ecosystem trackVertical specialty tools beyond StrongSuit: Litmus.ai, Glade.ai for bankruptcyThe "blank page anxiety" finding from the big law associates episode and how presets address itKey Takeaway The AI tool that wins your practice isn't the one with the most connectors or the highest benchmark scores. It's the one that eliminates the friction between where you are and where the finished work product needs to be. Presets and persistent workflows do that in a way raw prompting never could. If you're a Simpsons lawyer — aware of AI, dabbling, maybe running isolated prompts — this episode is your map. You don't have to build enterprise infrastructure. You need to identify one workflow bottleneck in your practice and find the tool that addresses it specifically. For family law lawyers, StrongSuit may already exist. For others, a Markdown workflow file built with your AI may be closer than you think. Mentioned in This Episode Claude for Legal — Anthropic's official announcement (22+ connectors, 12 plugins, MCP architecture) StrongSuit — divorce and family law AI workflow platform Model Context Protocol (MCP) — official documentation Harvey iManage NetDocuments Thomson Reuters Co-Counsel Westlaw Free Law Project DocuSign Litmas.ai Glade.ai Gemini Microsoft Copilot Ivory Mind ChatGPT / OpenAI GPTs Google GemsPrior podcast episodes: Episode 007: Folder Mania — AI Comes to You Field Note: I Wanna Hold Your Hand — Learning AI from AI How BigLaw Associates Are Actually Using AI in Legal Drafting  info@drescherlaw.com

    23 min

  5. 21 May

    Episode 013 BigLaw, Privilege and an Unexpected "Wow!" Moment

    When AI becomes a privilege problem, most lawyers are still treating it like a productivity hack. Solo and small firm attorneys hear constantly that AI saves time. What they hear far less often is that the AI tool they chose — and more specifically, the tier they're using — may have just waived their client's privilege. This episode forces that conversation. If you're putting client material into any AI tool without understanding exactly how that tool handles your data, you're not just taking a risk — you're potentially handing opposing counsel a gift. In this episode: Why the tier of AI tool you're using (free, Pro, Enterprise) is a privilege and confidentiality issue, not just a performance issueThe U.S. v. Heppner case: how using Claude at the Pro tier — not Enterprise — led to a court finding that confidential materials weren't protectedThe Trembly v. OpenAI case (2024 U.S. Dist. Lexis 141362) and what it establishes about AI outputs as opinion work productWhy Harvey's architecture makes it suitable for confidential client material when Claude's public tiers do notHow to build privilege defensibility into your AI workflow: mandatory human review, output labeling, and policy documentationMatt Lafferman's framework for ensuring AI outputs qualify as opinion work product rather than discoverable fact work productRon's "record everything" hot take — and Matt's push back on where that logic breaks down in sensitive mattersHow in-house counsel faces a unique AI challenge because business and legal functions blur, and only the legal portions are privilegedAutomating law firm intake: what tools like Clio, MyCase, and PracticePanther are building, and what Dentons is already doingWe also discuss: How Dentons uses Harvey as a document vault, including running tiered relevancy scoring on large document setsThe README file as the next frontier: why tech-sector in-house counsel may need to rethink document formats entirelyKen Griffin's reversal on AI — from calling it "garbage" in January to expressing alarm at what agentic AI is doing to PhD-level workWhether AI saves time or elevates work product quality — Ron and Matt respectfully disagreeThe challenge AI poses for junior associate development and entering the legal market right nowThe FSJ closing segment: Flintstones, Simpsons, and Jetsons advice from a Big Law AI task force memberDownload: Notice of Intent to Use AI in Discovery Helps lawyers disclose AI use in litigation in a structured, defensible way. Covers:When and how to disclose AI use to opposing counselLanguage for protective orders that includes AI tools in the definition of authorized agentsHow to frame AI outputs as generated at the direction of counselAdaptable to different jurisdictions and risk profilesKey Takeaway Availability is not authority — and that principle extends to tool tiers. Using an AI tool that collects your prompts, trains on your outputs, and discloses data to third parties isn't just a privacy concern. It's a privilege waiver waiting to happen. Matt Lafferman's framework is straightforward: choose the right tool, mandate human review, mark everything as work product, and document your policy so you can show a court exactly how your AI workflow maintains privilege at every step. For Flintstones lawyers, this episode is a fire alarm — the risks are real and courts are already ruling on them. For Simpsons lawyers using Claude Pro or a free tier for anything client-adjacent, this is the moment to audit your setup. Jetsons lawyers building custom agents should be baking these privilege protections into their workflow architecture from day one, not retrofitting them after a discovery dispute. Mentioned in This Episode Matt Lafferman, Partner, Dentons (white collar, government investigations, crypto/blockchain, AI task force)Harvey (enterprise AI platform for legal)Claude (Anthropic) — Pro tier vs. Enterprise tier distinctionMicrosoft CopilotClioMyCasePracticePantherU.S. v. Heppner — Claude Pro tier, privilege, and work productTrembly v. OpenAI, 2024 U.S. Dist. Lexis 141362 — AI outputs as opinion work productKen Griffin / Citadel — remarks at Stanford Business School on agentic AIJudge Rakoff, Southern District of New YorkRule 26(f) AI Discovery Protocol AddendumNotice of Intent to Use AI in DiscoveryREADME / .md files as emerging document format for in-house counselWhatsApp communications in crypto litigationDaubert motionsRon's "record everything" CLE hot takeinfo@drescherlaw.com

    43 min

  6. 18 May ·  Bonus

    Field Note: I WannAI Hold Your Hand: Learning AI From AI

    The AI training market for lawyers is broken. Not because there isn't enough of it — there's more than ever. The problem is almost all of it is aimed at the wrong lawyer. LinkedIn is full of Jetsons lawyers talking to other Jetsons lawyers, while the majority of practitioners are still trying to figure out how to create a PDF. So if the training doesn't meet you where you are, what do you actually do? In this episode: Why the explosion of AI training has created more confusion, not less, for solo and small firm lawyersThe "screenshot, upload, prompt, repeat" method Ron uses to navigate new software with AI as his guideWhy AI has become an always-on tutor — and where that tutor reliably falls shortThe maze-solving metaphor: how AI-guided learning gets you there eventually, but not always efficientlyThree diagnostic questions to ask any AI trainer before you spend a dollar or an hourWhy governance is no longer a procedural afterthought — it's substantive, and good training has to address itTwo new downloadable deliverables: a trainer vetting checklist and a due diligence inquiry templateWe also discuss: Why Microsoft and Google already have excellent AI training most lawyers don't know they have access to — Microsoft Copilot legal training (Microsoft Learn) · Google AI Skills Hub · Google Workspace AI for LegalThe real value of human trainers: shortcuts, judgment, accountability — things AI can't reliably replicateA real example of a law firm that made AI training stick through scheduled, team-wide calendar commitmentRon's earlier Field Note on taking screenshots — and why, in retrospect, that wasn't absurdly basic at all — Episode 003: Specialist AI ToolsThe hallucination field note: 21 ways AI Hallucinates in your Legal Brief — download at lawyeraitoolkit.com/deliverablesDownload: AI Trainer Vetting Checklist + Inquiry Template Two tools to help lawyers evaluate prospective AI trainers before investing time, money, and trust. Available free at lawyeraitoolkit.com/deliverables.Three diagnostic questions to assess whether a training program fits your FSJ levelWhether training is workflow-focused or just a feature paradeHow to assess whether the program takes hallucinations, confidentiality, and governance seriouslyA ready-to-send email/DM template for due diligence outreach to prospective trainersKey Takeaway AI is an infinitely patient tutor. It will walk you through the maze, one wall at a time, and it will eventually get you there. But it won't always get you there efficiently, and it won't always get you there correctly — especially when its training data is three years out of date. The real skill is knowing when to use the bot and when to find the human who can point you at the exit in thirty seconds. This episode speaks directly to Simpsons lawyers who are doing what Simpsons lawyers do: picking up AI tools, bumping into walls, and figuring it out one screenshot at a time. But Flintstones lawyers who haven't entered a single prompt yet will find the framework here — especially the three questions — genuinely useful before they spend anything. And Jetsons lawyers building agent workflows have likely already internalized everything Ron says. This one isn't for them. Mentioned in This Episode Claude (Anthropic)ChatGPT (OpenAI)Google GeminiMicrosoft CopilotGoHighLevelCogent MarketingGoogle Drive · Microsoft Word · ZoomHeather Gardner (co-host)FSJ Framework (Flintstones / Simpsons / Jetsons)Ron's Field Note: Confessions of an AI Hallucinator21 Ways AI Can Hallucinate in Your Legal Brief — downloadlawyeraitoolkit.com/deliverablesinfo@drescherlaw.com

    22 min

  7. 14 May

    Episode 012 – AI CLEs, Flintstones Lawyers & the Problem With Legal AI Training

    I recently participated in a live AI panel at the Maryland Bankruptcy Bar Association Spring Break Weekend — one of the major annual CLE and networking events for Maryland bankruptcy lawyers. The panel featured retired federal judge Paul Grimm as moderator, along with Patti Jefferson, Nancy Rapoport, and Ron Drescher. But this episode is not simply a replay or recap of the panel. Instead, we use the experience to explore a much bigger question: Is the legal profession actually teaching AI effectively? In this episode: Why AI CLE panels may struggle to teach lawyers at vastly different technology levelsThe continuing evolution of the Flintstones / Simpsons / Jetsons frameworkWhy some lawyers may never need to become “Jetsons-level” AI usersPatti Jefferson’s live AI demonstration using the Red Lobster bankruptcy confirmation orderThe rise of agents and workflow automation beyond traditional promptingNancy Rapoport’s warnings about hallucinations, supervision, and professional responsibilityWhy “hallucination verification” may erase much of AI’s promised time savingsA comparison between AI hallucinations in law versus medicineWhy many firms remain stuck at “sub-Flintstones” technology levelsHow to identify the pain points inside your law firm before adopting AIWhy your firm should conduct a “Tech Stack Audit”We also discuss: Dropbox and document organization for high-volume bankruptcy practicesThe growing divide between consumer AI and enterprise AIWhy “ChatGPT” is no longer a meaningful description without understanding the underlying plan and governance structureThe importance of the “Three-Legged Stool” for safe legal AI deployment:Vendor protectionsProper configurationHuman supervisionDownload: Tech Stack Audit Spreadsheet This episode includes a downloadable spreadsheet template designed to help lawyers: identify all software subscriptions,calculate monthly and annual costs,evaluate what they are actually getting from their tech stack,and determine where they fall on the Flintstones / Simpsons / Jetsons spectrum.If you complete the spreadsheet and would like us to discuss it anonymously (or publicly) on a future episode, send it to: info@drescherlaw.com We’d love to see how lawyers are actually building — or struggling to build — their AI and technology infrastructure. Mentioned in This Episode ChatGPTClaudeGeminiHarveyIvoryMindGoogle WorkspaceDropboxClioFoundation AIKey Takeaway Most legal AI education still treats lawyers as if they are all at the same level of technological fluency. But Flintstones lawyers, Simpsons lawyers, and Jetsons lawyers may not even be attending the same CLE — even if they are sitting in the same ballroom.

    35 min

  8. 5 May ·  Bonus

    Field Note: 21 Ways AI Can Hallucinate in Your Legal Brief

    In this Field Note, Ron Drescher breaks down one of the most important—and misunderstood—risks in legal AI: hallucinations. The episode begins with the recent Sullivan & Cromwell filing admitting AI-generated errors, with a close look at the now-famous Schedule A. While most commentary has focused on fake citations and misquotes, Ron highlights the more subtle—and more dangerous—types of hallucinations that appeared in that filing. From structurally corrupted citations to mutated judicial language, this episode explores how AI doesn’t just make obvious mistakes—it makes mistakes that look like law. Ron then expands the discussion to a broader framework, identifying both the most well-known hallucination risks and the lesser-known categories that are more likely to survive verification and make their way into filed briefs. ⚖️ What You’ll Learn Why the Sullivan & Cromwell Schedule A is more important than the confession letterTwo underappreciated hallucinations:Citation drift (hybrid citation corruption)Mutated quotationsThe 3 most common AI hallucinations:Fabricated casesReal cases with incorrect holdingsInvented quotationsThree lesser-known (and more dangerous) hallucinations:Subtle semantic driftFake multi-case consensusLogical hallucination (broken arguments that look complete)Why “just verify the citation” is no longer enoughA practical verification framework for AI-assisted legal writing🧠 Key Takeaway AI hallucinations are no longer edge cases—they are part of the operating environment of modern legal writing. The real risk isn’t obvious errors. It’s the errors that: look correctpass a quick checkand still make it into your brief📥 Downloadable Resource This episode includes a companion Field Note: 👉 “21 Ways AI Can Hallucinate in Your Legal Brief” Use it as a working reference during your hallucination verification process—not as a one-time read. 🔧 The New Verification Standard Before including any authority in a brief, confirm: Does the case support the proposition?Is the quote accurate and in context?Does the procedural posture match your argument?Has the legal standard shifted subtly?🔜 Coming Next Field Note: 12 Ways BigLaw Associates Are Quietly Optimizing AI in Legal Drafting A practical look at how lawyers in high-stakes environments are adapting their workflows to use AI effectively—without getting buried in verification. 🎙️ About the Show AI Tools for Practicing Lawyers delivers practical, no-nonsense guidance to help attorneys put AI to work in their practice right now. Hosted by Ron Drescher, a retired bankruptcy attorney with over 40 years of experience, the show focuses on real workflows—not hype.

    11 min
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About

AI Tools for Practicing Lawyers delivers practical, no-nonsense guidance on how attorneys can use artificial intelligence tools in their law practices — right now. This podcast is for practicing lawyers who want real-world answers, not hype. Each episode focuses on clear, understandable explanations of AI tools that can help attorneys work more efficiently, communicate more effectively, and make better business decisions — without requiring technical expertise or coding knowledge. We cover topics such as: • Using AI responsibly and ethically in legal practice • Drafting, research, summarization, and document review tools • Client communication and intake automation • Practice management efficiencies • Emerging AI platforms relevant to law firms • Real examples attorneys can apply immediately Whether you are a solo practitioner, small-firm attorney, or part of a larger practice, this podcast is designed to help you understand what AI can — and cannot — do for lawyers today. No futurism. No speculation. Just practical tools for practicing lawyers. Hosted by Ron Drescher

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