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. 5 days ago ·  Bonus

    AI Builds: Gmail Digest

    Most lawyers think about AI as a chat box. Ron argues that's already the old way of thinking — and the real leverage is in systems that run without you, remember what they're supposed to do, and hand you a finished result before you've had your coffee. In this episode: - Why the podcast is shifting focus from prompting skills to persistent, automated AI workflows - The "airport test" — Ron's framework for deciding whether an AI workflow is actually worth adopting - Building a fully automated AI news producer using make.com - The four-step architecture: collector, bundler (text aggregator), producer (persona prompt), and formatter - Using a Gmail label and filter to isolate newsletter content from client and personal email - Why persona prompting ("you are the executive producer") beats a plain summarization request - Why GPT-4.0, an older model, was still the right tool for this specific job - Hitting and solving the "wall of text" formatting problem with a markdown-to-HTML converter - Using Gemini as a build partner because of its familiarity with Gmail - Real examples of what the finished daily digest surfaced, including breaking legal-tech news We also discuss: - Why LinkedIn, properly configured, is a strong AI news source - Newsletter overload and why Ron started ignoring sources he used to value - The PlayStation 3 vs. PlayStation 2 analogy for why newer AI models aren't always necessary - Heather Gardner's role in introducing Ron to this kind of automated workflow thinking - Where this build actually lands on the Flintstones/Simpsons/Jetsons spectrum Key Takeaway: The most useful AI adoption in a small firm doesn't happen in the chat window — it happens when a workflow disappears into the background and just delivers. Ron's four-step build (collector, bundler, producer, formatter) is a repeatable pattern, not a one-off trick, and it didn't require the newest, most expensive model to work. This episode sits right in Simpsons territory: a lawyer who's dabbled with AI tools individually but hasn't yet connected them into something that runs itself. Ron's point isn't "go build this exact thing" — it's that the leap from Simpsons to Jetsons is smaller and less technical than most solo and small firm lawyers assume. Mentioned in This Episode: - make.com - Gmail (labels, search filters) - ChatGPT / GPT-4.0 (OpenAI) - Google Gemini - LinkedIn - Artificial Lawyer (newsletter) - The Rundown (newsletter) - Legal Tech Blogs (newsletter) - Heather Gardner - Apple / OpenAI trade secret lawsuit (Johnny Ive hardware device) - Meta AI-biased layoff algorithm lawsuit To see and download the final outputs from these tools click here. info@drescherlaw.com

  2. 5 days ago ·  Bonus

    Field Note: In Defense Of AI Notetakers

    While AI note-takers grab the headlines, the real issue at stake in this episode is one lawyers have been dodging for decades: "Is AI notetaking actually riskier than everything else already sitting in your practice?" In this episode: - Why the claim "AI note-takers turn everything into data" misses the point — meetings were already data, AI just organizes it - Ron's take on recording everything (calls, meetings, even hallway conversations) as part of the AI-forward way of managing firm information - The real question lawyers should be asking: not "do I trust AI," but "do I trust this vendor with this information under this security model" - The information governance questions that actually matter — who has access, where data lives, encryption, retention, whether the vendor can train on your data, whether recording can be disabled - How the AI adoption debate mirrors the earlier fight over moving client files to the cloud - Why treating "AI" as fundamentally different from every other cloud service is a mistake - The shift from "never put client files in the cloud" to firms running on Microsoft 365, NetDocuments, Google Workspace, and Clio We also discuss: - Confidentiality, privilege, trade secrets, and personnel discussions as legitimate concerns worth taking seriously - Everyday, non-AI examples of data risk — email, Dropbox, Google Drive, even the cleaning crew - Podcast guest Carolyn Elefant's related commentary on AI vs. other cloud tools - The Fast Company article that prompted this Field Note Key Takeaway: The mistake isn't using AI note-takers — it's treating "AI" as a special category that suspends the ordinary due diligence lawyers already owe every vendor. Strip away the letters "AI" and the questions are the same ones firms have been asking about cloud storage and email for twenty years. This lands hardest for Simpsons lawyers — the ones dabbling with AI tools but without a governance structure behind them. Flintstones lawyers will read this as one more reason to stay away; Jetsons lawyers already have these vendor questions answered. The point of this episode is to move more of the audience from reflexive fear or reflexive adoption into an actual governance conversation. Mentioned in This Episode: - Fast Company: [Why You Should Think Twice Before Letting an AI Notetaker in Your Meeting](https://www.fastcompany.com/91571498/ai-notetaker-work-meetings-privacy-data) - Carolyn Elefant - Microsoft 365 - NetDocuments - Google Workspace - Clio - Zoom - Dropbox - Google Drive info@drescherlaw.com

  3. 5 days ago

    Episode 021 Law Firm AI: Custom Made Or Off The Shelf?

    SHOW NOTES Most AI pitches to law firms start with a product. This one starts with an audit — and a question about whether buying software was ever the right move for a solo or small firm in the first place. Jerry Dearden of David AI joins Ron and Heather to unpack what it actually takes to build AI around a firm instead of forcing a firm into someone else's software. It's the David AI origin story, the pricing, and the pitfalls — no punches pulled. IN THIS EPISODE: - How David AI's "fitting" audit works before any code gets written — firm size, niche, workflows, tech stack - The difference between reactive AI (you prompting a chatbot one task at a time) and proactive AI (an agent that acts on its own and reports back) - Why firms keep bumping into Harvey and Legora, then walking away because the pricing and scale don't fit solo and small practices - How David AI builds agents that live wherever a lawyer already works — iMessage, Slack, Teams, or inside existing case management software - The "company brain" concept: connecting a firm's tools so AI has full context instead of starting from zero every time - Data protection, DPAs, and how David AI's own contract terms changed after a listener-style question exposed a gap - Build-versus-buy: when David AI tells a firm to keep its existing software instead of building something new - Pricing structure — audit fees, build costs, and ongoing maintenance - A real AI paralegal build for a small Utah firm, including a lawyer-avatar project still in testing - The insurance defense billing bottleneck, and how AI could translate time entries into carrier-acceptable language automatically WE ALSO DISCUSS: - Kirkland & Ellis's $500 million, multi-year investment in a proprietary AI platform, and why Jerry calls building your own LLM "frying an egg on a volcano" - Claude's connector ecosystem and what it means for firms trying to build a unified knowledge base - Staff resistance to AI and the "Iron Man suit" framing David AI uses to get buy-in - This season's ongoing FSJ knowledge-standardization exercise — this week's step is making firm documents AI-readable - A tease for Season 3: "users and builders" KEY TAKEAWAY Jerry's answer to almost every question comes back to the same place: don't buy a tool and force your firm into it, fit the tool to how you actually work. That's a different pitch than most AI vendors make, and it only works if a firm is willing to open up its internal processes to an outside audit first. This episode's FSJ moment comes from the ongoing build series Ron's been running with listeners since the start of the season. Four weeks in, the assets are identified, organized, and cleaned. This week's step is standardizing them: a Flintstones lawyer writes a plain description at the top of one form, a Simpsons lawyer turns client questions into a consistent Q&A format, a Jetsons lawyer breaks a workflow into sequential steps. It's a reminder that "AI-ready" starts with structure a human puts in place — long before any model touches the data. MENTIONED IN THIS EPISODE: - David AI - Harvey - Legora - Claude / Anthropic - ChatGPT / OpenAI - Reddit - Clio - Microsoft Teams, Slack, iMessage - Spellbook - Kirkland & Ellis - TimeSolv (billing software Ron used in practice) - Claude's connector ecosystem info@drescherlaw.com

  4. 16 Jul

    Episode 020: Pain Points, Grok And The Homeless Summer Associate

    SHOW NOTES What if the smallest law firms are actually the best positioned to win the AI era? That's the provocation Ron opens with this week — and it comes from someone with a genuinely rare vantage point: a solo attorney who also works as a professional AI trainer for the labs building these models. In this episode: Dr. Sara Kubik's path from a gerontology-focused PhD to family law, estate planning, and now legal AI trainingInside the AI training industry — how OpenAI, Anthropic, Google, and Microsoft contract out trainer roles through staffing layers, and why it's become a multi-billion dollar businessWhy older clients are often faster and more enthusiastic AI adopters than lawyers expect, once they see it's usefulHow different AI models produced very different results on the same creative request, and what that reveals about picking the right tool for the jobVibe coding a Medicaid penalty calculator, a community spouse calculator, and a child support chatbot without a formal development backgroundThe case for solo and small firm lawyers having a structural advantage over Big Law in adopting AIUniversity of Chicago Law School's ban on electronics in 1L lectures — and why Sara thinks the policy won't survive the yearWhat lawyers consistently get wrong about how AI models work, including training cutoffs and hallucinationsWe also discuss: ChatGPT's new wave of specialized models and the ongoing comparisons to ClaudeRon's controversial take on lawyers recording everything as firm data infrastructurePractice Signals: a Reddit post from a homeless summer associate, and where AI actually helps — and where it doesn'tThis week's Season 2 AI Build segment: cleaning firm knowledge assets before teaching them to AI, including PII anonymization and "grader guidance"The difference between vibe coding and understanding what you're buildingData-focused stats on solo and small firm representation in the legal marketKey Takeaway AI adoption was never really about the tool. It's about the pain point. Sara's advice to solos is blunt: stop shopping for tools and start naming what's actually broken in your practice — then go find out what fixes it. That reframe is what makes AI usable instead of overwhelming, and it's also what makes the "solo advantage" argument real: for the first time, small firms have access to something close to the same horsepower as Big Law, without the budget Big Law required to get it. This one lands hardest for Simpsons lawyers — the ones already poking at ChatGPT on their phones but who haven't connected it to a real problem in their practice yet. It's also a reality check for anyone tempted to treat AI as a universal fix: the practice signals segment on the homeless summer associate is a reminder that some problems are human problems first, and AI is a research tool for finding help — not the help itself. Mentioned in This Episode Dr. Sara Kubik (guest)Claude, ChatGPT, Gemini, Grok, Midjourney, DaVinci ResolveCodex (ChatGPT)Power BI, SQL, ExcelClioPerplexityCooley Law SchoolPurdue UniversityUniversity of Chicago Law SchoolIndiana State Bar AssociationRedditinfo@drescherlaw.com Note: As mentioned in the episode: Is Mitch McConnell's photo real or fake? — Poynter/PolitiFact Note: This photo has been the subject of online debate regarding its authenticity. We're linking to it as referenced in the episode and take no position on that controversy.

  5. 9 Jul

    Episode 019 Bankruptcy Meets The AI Revolution

    Show Notes Most bankruptcy lawyers still don't know what their own firm actually makes each month. Jenny Doling built a revenue dashboard in Claude to find out — and then kept going, building analyzer skills for pay stubs, tax returns, bank statements, and Chapter 13 objections that her staff now runs without her. If a nationally recognized bankruptcy attorney and NACBA's incoming president is running her practice this way, what's the excuse for everyone else? In this episode: Jenny Doling's path from paralegal to bankruptcy attorney to NACBA president-elect, and how she got hooked on consumer bankruptcy work back in 2004The scale of the current bankruptcy surge — commercial and individual filings both up sharply since 2022 — and what firms without systems riskWhy Jenny moved her practice from ChatGPT to Claude, and how she uses Claude skills, projects, and Cowork day to dayThe analyzer stack she built: pay stub analyzer, document renamer, bill analyzer, tax return analyzer, and bank statement analyzerHer Chapter 13 Opposition Builder skill — loaded with trustee objections, Collier on Bankruptcy material, docket reports, and key case lawConfidentiality practices: a closed Claude Team environment, a written office AI policy, and PII lockdowns before staff touch any toolWhy Jenny separates time saved from work-product elevation, and argues the second is the real benefit of AIClient-facing AI disclosures in her fee agreements, and why she avoids Zoom's built-in AI transcription specificallyA frank take on legal tech vendor Glade versus incumbents like Clio, and why responsiveness matters more than market shareThis week's Season 2 build step: organizing the firm knowledge assets identified last week, tiered by Flintstones, Simpsons, and Jetsons lawyersWe also discuss: Case law and citation practices for Chapter 13 objections, including Hamilton v. LanningRecording practices — why "team record" doesn't mean "team Zoom record"AI transcription and notetaking tools, including Whisper, Granola, and wearable recordersNACBA's upcoming AI-focused conference programming in Orlando and MauiA Practice Signal segment on a solo PI lawyer's shrinking case volume and how Jenny would advise him to diversifyKey Takeaway Jenny Doling isn't impressive because she uses AI. She's impressive because she treats her analyzer skills as infrastructure — quality control built in, confidentiality locked down before staff ever touch a tool, and her name still on every pleading that goes out the door. That's the difference between dabbling and running a practice. This one's for the Simpsons lawyer wondering how far a solo or small firm can actually take this. It gives Flintstones lawyers permission to start small, and it gives Jetsons lawyers something sharper to aim for — the difference between an old-school Jetsons practice and what Jenny calls "AI Jetsons." Mentioned in This Episode NACBA (National Association of Consumer Bankruptcy Attorneys)Claude (skills, projects, artifacts, Cowork)ChatGPTBest Case DesktopJubileeNext ChapterSharePoint / OneDriveClioGladeTara SalinasMatt McCuneinfo@drescherlaw.com

  6. 2 Jul

    Episode 018: Season 2, the $75 Consult and the Frankenstein Stack

    Show Notes Episode 018 | Season 2 Premiere | Guest: Jennifer Grondahl Lee Season 1 taught you how to use AI. Season 2 is going to be harder. The question isn't whether to adopt AI anymore — it's whether your firm's knowledge is organized enough for AI to actually use. When almost every hand in a room full of lawyers goes up to confirm they're using AI, the era of "should I?" is over. What comes next requires something most small firm lawyers haven't done: build the knowledge infrastructure that makes AI work for your practice, not just anyone's. In this episode: Ron announces the shift from Season 1 (learning AI) to Season 2 (teaching AI your firm's knowledge and systems)Why the Flintstones/Simpsons/Jetsons framework needs to evolve as AI adoption spreads across the professionJen Grondahl Lee on the trap of the Frankenstein Stack — why firms should design their workflow first, then pick the toolsThe case for charging for consultations — and why free consults are really just sales pitchesHow niching down and turning clients away can actually accelerate a bankruptcy practiceThe FSJ-level homework assignment: Flintstones find your 10 best forms, Simpsons list your 10 most common client questions, Jetsons map your 10 most important firm systemsAI court orders and the problem of courts overreacting to bad lawyering — not bad AIThe contradiction hidden in a 3-part judicial AI order: disclose AI use, verify citations — and certify the document wasn't produced by AIWe also discuss: Jen's AI-DR blog post — "copy pasta" AI content and how to train your tools to sound like you, not like everyone elseHeather naming her ChatGPT "Bosley" and why the reference fitsClaude vs. ChatGPT for brainstorming — and why power users play them off each otherThe AI hiring test: give applicants an unhappy client email and watch whether they improve the AI's draft or just paste itJen's 1,000-hours-saved estimate and how she calculated itBankruptcy Toolbox, Rebel Roundtable, and Jen's course Building a Bankruptcy Practice from Start to FinishKey Takeaway Most lawyers using AI are still using it the way they used Google — as a tool they query, not a system they've trained. The difference between a Simpsons lawyer and a Jetsons lawyer isn't which tools they use. It's whether they've done the unglamorous work of documenting what their firm actually knows. This episode is the on-ramp. The homework isn't hard — find your best forms, write down your most common client questions, name your most important systems. But most Flintstones and Simpsons lawyers haven't done any of it. That's what Season 2 is about. Mentioned in This Episode: Jen Grondahl Lee — Lawyers Success Network Bankruptcy Toolbox — membership community for bankruptcy attorneys Upcoming Events: https://lawyersuccessnetwork.com/eventsRebel Roundtable — Friday morning sessions with Jen File Bankruptcy and Get Rich — Ron's early lead magnet bookFinancial Recovery for Single Moms — Ron's targeted marketing bookJen's AI;DR blog postChatGPT (OpenAI)Claude (Anthropic)Claude CodeGemini (Google)Glade AI — bankruptcy-specific AI platformBest Case — bankruptcy case management software with AI document collector GrammarlyMaryland Legal SummitAnthropic learning resources Skilljarinfo@drescherlaw.com

  7. 25 Jun

    Episode 017 Training AI to Think Like Your Practice

    Show Notes What are you actually doing with AI — and does it work? Ron and Heather put their tools down long enough to talk about what they've been building with them. This isn't a roundup of tools you might try. It's an inside look at two practitioners who have spent serious hours creating AI-powered workflows for their own legal and legal-adjacent businesses — and what those projects revealed about where AI is actually useful for law firms right now. In this episode: Heather's report from the Maryland Legal Summit — how attorney AI adoption shifted dramatically in a single year, and what the fear conversation looks like nowWhy hallucination is more than a citation problem — the 21 ways AI can corrupt a legal brief, from wrong standards of proof to mutated judicial languageHeather's 11-module Bankruptcy Paralegal Course, built with AI, including a Claude Code-built floating chatbot trained on the course contentHow Heather's paralegal team uses Gemini inside Google Sheets to auto-generate and schedule weekly client status reports — eliminating a manual step entirelyRon's markdown workflow system for podcast post-production — built in Claude, portable to any AI environmentRon's Case Assessment Pack: a deep-dive workflow that turns a client intake recording into a preliminary liquidation analysis, exemption review, and client-ready deliverableThis week's Practice Signal — a 9th-year BigLaw associate terrified about making partner and how AI could be the rainmaking engine he hasn't consideredThe FSJ breakdown for capturing firm knowledge — what Flintstones, Simpsons, and Jetsons lawyers each need to do right now to prepare for the agentic AI eraWe also discuss: OWLL, the recording app Ron just downloaded — and why he thinks lawyers should be recording everythingOtter.ai as the baseline for meeting intelligence, and how Ron's workflow pack goes furtherThe difference between using AI as a Google machine versus as a strategic collaboratorWhy opposing counsel — not the filing attorney — is catching most hallucinated citations right nowHarvey and Legora showing up at the Maryland Legal Summit — and who's actually using themKey Takeaway AI doesn't magically understand your practice. It inherits whatever you've ingested into it. That's the core lesson from everything Ron and Heather describe — the tools work because they were loaded with domain knowledge, firm context, and real workflow logic. Without that, you get a very confident machine that doesn't know what it doesn't know. For Flintstones lawyers, the move is simple: start documenting. Write down what you do. Create checklists. Capture the firm knowledge that currently lives in your head. Simpsons lawyers need to organize that knowledge — standardize file names, define workflows, build taxonomies. Jetsons lawyers are ready to connect the systems, build repositories, and create governance. The future belongs to firms that treat data as infrastructure. Where you start matters less than whether you start. Mentioned in This Episode: Maryland Legal Summit / Maryland State Bar AssociationClaude (Anthropic)Claude CodeChatGPT (OpenAI)Gemini (Google) — including Google Sheets integrationMicrosoft CopilotHarveyLegoraOtter.aiOWLL (recording app)BusinessGPTBenchSimAI (Chris Ryan) Foundation AIReddit (Practice Signal source)Cromwell case — hallucinated citation example Heather's Bankruptcy Paralegal Course (Propel AI)Ron's AI Builds: Ground Zero episode with the Free Motion to Extend WorkflowGoogle Workspace (Sheets, Drive, Docs)info@drescherlaw.com

  8. 18 Jun

    Episode 016: Can an AI Judge Train You Better Than the Real One?

    What if you could lose your case to an AI judge tonight, so you don't lose it to a real one tomorrow? For generations, lawyers learned advocacy the hard way: draft the brief, argue the motion, get knocked down by the judge, learn why you were wrong. Litigation partner Chris Ryan built a different path. BenchSim AI lets lawyers upload their brief and opposing counsel's brief, then argue out loud in real time against an AI judge who pushes back, interrupts, and grades the performance. The question this episode keeps circling: is this the future of how lawyers get their reps in, or is the courtroom apprenticeship something AI can never actually replace? In this episode: Why COVID permanently reduced young lawyers' opportunities to argue in front of a real judge, and what that "reps problem" means for the next generation of litigatorsHow Chris built BenchSim AI as a litigation partner with no modern coding background, using "vibe coding" to go from idea to working product in about six weeksWhat vibe coding actually is, and why it's the same process as building a custom GPT, Gem, or Claude skillHow BenchSim works: upload your brief and opposing counsel's brief, choose a judge temperament (quiet, neutral, or hot bench), and argue out loudWhy BenchSim deliberately skips video rendering of the judge to avoid latency that would kill the realism of rapid-fire argumentHow the AI judge develops counterpoints from the opposing brief and is programmed to interrupt when an advocate is talking in circlesThe SOC 2 certification process BenchSim is going through before marketing to law firms, and why that matters for adoptionWhether AI will actually save lawyers time, including the "airport test" framework for evaluating whether a tool is worth the overheadUsing AI as an adversary instead of a cheerleader — prompting it to argue against your own complaint or brief before opposing counsel doesThe Flintstones/Simpsons/Jetsons breakdown of how to stress-test a brief at every level of AI adoptionWe also discuss: Chris's recent "wow moment" using AI to play defense counsel against his own drafted complaintHeather's experience having Claude Code build software overnight while she sleepsWhether AI simulation training could expand beyond litigation into bar exam prep and other legal trainingA Practice Signal segment on a deeply inappropriate mentorship moment a young associate experienced, and whether AI could have helped an older partner communicate the underlying (legitimate) concern without the inappropriate framingChris's plans for BenchSim's feature roadmap, including potential expansion into opening statements and direct examination practiceKey Takeaway Availability is not authority, and a simulation is not a verdict. BenchSim doesn't tell a lawyer whether they'll win or lose; it tells them where their argument is weak before a real judge finds out for them. That distinction matters. The value isn't in the AI replacing judgment, it's in creating reps that don't exist anymore because courtrooms don't generate them the way they used to. This episode lands differently depending on where you sit on the FSJ spectrum. A Flintstones lawyer can start by asking any AI tool to summarize their argument and flag weaknesses. A Simpsons lawyer can go further, prompting AI to act as opposing counsel and attack the brief. A Jetsons lawyer is already running full bench simulations, treating AI as an adversary that prepares them for the real fight rather than a cheerleader that tells them what they want to hear. Mentioned in This Episode: BenchSim AI (benchsimai.com)Taft (Taft Stettinius & Hollister)HarveyLegoraAnthropic Claude / Claude CodeChatGPTReddit (Practice Signal segment source)MPRE (Multistate Professional Responsibility Examination)info@drescherlaw.com

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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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