AI Tools for Practicing Lawyers

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 issue * The U.S. v. Heppner case: how using Claude at the Pro tier — not Enterprise — led to a court finding that confidential materials weren't protected * The Trembly v. OpenAI case (2024 U.S. Dist. Lexis 141362) and what it establishes about AI outputs as opinion work product * Why Harvey's architecture makes it suitable for confidential client material when Claude's public tiers do not * How to build privilege defensibility into your AI workflow: mandatory human review, output labeling, and policy documentation * Matt Lafferman's framework for ensuring AI outputs qualify as opinion work product rather than discoverable fact work product * Ron's "record everything" hot take — and Matt's push back on where that logic breaks down in sensitive matters * How in-house counsel faces a unique AI challenge because business and legal functions blur, and only the legal portions are privileged * Automating law firm intake: what tools like Clio, MyCase, and PracticePanther are building, and what Dentons is already doing We also discuss: * How Dentons uses Harvey as a document vault, including running tiered relevancy scoring on large document sets * The README file as the next frontier: why tech-sector in-house counsel may need to rethink document formats entirely * Ken Griffin's reversal on AI — from calling it "garbage" in January to expressing alarm at what agentic AI is doing to PhD-level work * Whether AI saves time or elevates work product quality — Ron and Matt respectfully disagree * The challenge AI poses for junior associate development and entering the legal market right now * The FSJ closing segment: Flintstones, Simpsons, and Jetsons advice from a Big Law AI task force member > Download: 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 counsel > * Language for protective orders that includes AI tools in the definition of authorized agents > * How to frame AI outputs as generated at the direction of counsel > * Adaptable to different jurisdictions and risk profiles Key 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) [https://www.dentons.com/en/matthew-lafferman] * Harvey (enterprise AI platform for legal) * Claude (Anthropic) — Pro tier vs. Enterprise tier distinction * Microsoft Copilot * Clio * MyCase * PracticePanther * U.S. v. Heppner — Claude Pro tier, privilege, and work product * Trembly v. OpenAI, 2024 U.S. Dist. Lexis 141362 — AI outputs as opinion work product * Ken Griffin / Citadel — remarks at Stanford Business School on agentic AI * Judge Rakoff, Southern District of New York * Rule 26(f) AI Discovery Protocol Addendum * Notice of Intent to Use AI in Discovery * README / .md files as emerging document format for in-house counsel * WhatsApp communications in crypto litigation * Daubert motions * Ron's "record everything" CLE hot take > info@drescherlaw.com [info@drescherlaw.com]

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 lawyers * The "screenshot, upload, prompt, repeat" method Ron uses to navigate new software with AI as his guide * Why AI has become an always-on tutor — and where that tutor reliably falls short * The maze-solving metaphor: how AI-guided learning gets you there eventually, but not always efficiently * Three diagnostic questions to ask any AI trainer before you spend a dollar or an hour * Why governance is no longer a procedural afterthought — it's substantive, and good training has to address it * Two new downloadable deliverables: a trainer vetting checklist and a due diligence inquiry template We 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) [https://learn.microsoft.com/en-us/training/modules/empower-workforce-microsoft-365-copilot-legal-use-case/] · Google AI Skills Hub [https://ai.google/learn-ai-skills/] · Google Workspace AI for Legal [https://workspace.google.com/resources/ai-for-legal/] * The real value of human trainers: shortcuts, judgment, accountability — things AI can't reliably replicate * A real example of a law firm that made AI training stick through scheduled, team-wide calendar commitment * Ron's earlier Field Note on taking screenshots — and why, in retrospect, that wasn't absurdly basic at all — Episode 003: Specialist AI Tools [https://lawyeraitoolkit.com/episode-003-ai-specialists] * The hallucination field note: 21 ways AI Hallucinates in your Legal Brief — download at lawyeraitoolkit.com/deliverables [https://lawyeraitoolkit.com/deliverables] > Download: 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 [https://lawyeraitoolkit.com/deliverables]. > * Three diagnostic questions to assess whether a training program fits your FSJ level > * Whether training is workflow-focused or just a feature parade > * How to assess whether the program takes hallucinations, confidentiality, and governance seriously > * A ready-to-send email/DM template for due diligence outreach to prospective trainers Key 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) [https://claude.ai] * ChatGPT (OpenAI) [https://chatgpt.com] * Google Gemini [https://gemini.google.com] * Microsoft Copilot [https://copilot.microsoft.com] * GoHighLevel [https://www.gohighlevel.com] * Cogent Marketing * Google Drive · Microsoft Word · Zoom * Heather Gardner (co-host) * FSJ Framework (Flintstones / Simpsons / Jetsons) * Ron's Field Note: Confessions of an AI Hallucinator [https://lawyeraitoolkit.com/confessions-of-an-ai-hallucinator] * 21 Ways AI Can Hallucinate in Your Legal Brief — download [https://lawyeraitoolkit.com/deliverables] * lawyeraitoolkit.com/deliverables [https://lawyeraitoolkit.com/deliverables] > info@drescherlaw.com [info@drescherlaw.com]

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 levels * The continuing evolution of the Flintstones / Simpsons / Jetsons framework * Why some lawyers may never need to become “Jetsons-level” AI users * Patti Jefferson’s live AI demonstration using the Red Lobster bankruptcy confirmation order * The rise of agents and workflow automation beyond traditional prompting * Nancy Rapoport’s warnings about hallucinations, supervision, and professional responsibility * Why “hallucination verification” may erase much of AI’s promised time savings * A comparison between AI hallucinations in law versus medicine * Why many firms remain stuck at “sub-Flintstones” technology levels * How to identify the pain points inside your law firm before adopting AI * Why your firm should conduct a “Tech Stack Audit” We also discuss: * Dropbox and document organization for high-volume bankruptcy practices * The growing divide between consumer AI and enterprise AI * Why “ChatGPT” is no longer a meaningful description without understanding the underlying plan and governance structure * The importance of the “Three-Legged Stool” for safe legal AI deployment: * Vendor protections * Proper configuration * Human supervision Download: Tech Stack Audit Spreadsheet [https://assets.cdn.filesafe.space/LGYwVdJSqtZFXymEmecb/media/6a0643d3a97d962a35e31188.xlsx] 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 [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 * ChatGPT * Claude * Gemini * Harvey * IvoryMind * Google Workspace * Dropbox * Clio * Foundation AI Key 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.

Field Note: How BigLaw Associates Are Actually Using AI in Legal Drafting

This Field Note is a direct companion to the episode “21 Ways AI Can Hallucinate in Your Legal Brief.” If that episode showed how AI fails, this one shows how lawyers are adapting anyway. Drawing from a real-world Reddit thread with dozens of BigLaw associates, this episode breaks down the actual workflows lawyers are using today—not theory, not vendor demos, and not CLE talking points. What emerges isn’t a list of tips. It’s a set of patterns. And those patterns reveal something important: AI isn’t replacing legal drafting. It’s reshaping how drafting gets done. 🔑 Key Takeaways * AI is used for structure and volume—not judgment * Lawyers are using AI to break the blank page problem * Drafting works best when done in small, controlled sections * Strong workflows emphasize outline → structure → prose * Effective users rely on iteration, not one-shot prompting * AI is highly effective for rewriting, organizing, and clarity * Many lawyers now treat AI like a junior associate * AI is increasingly used as a thinking partner, not just a drafting tool * There is near-universal agreement: ⚠️ Do NOT trust AI for citations or legal authority ⚠️ The Core Insight Across all 12 patterns, one principle stands out: AI handles the work. The lawyer handles the responsibility. 👤 For Solo & Small Firm Lawyers BigLaw associates operate with built-in review layers. If you don’t have that safety net, these same workflows require: * Greater discipline * More deliberate verification * A clearer understanding of where AI fails 🔗 Companion Episode 🎙️ Field Note: 21 Ways AI Can Hallucinate in Your Legal Brief Use both together: * One shows you how AI breaks * This one shows you how lawyers are adapting 📥 Downloadable Companion Resource A structured breakdown of all 12 drafting patterns is available on the Deliverables page: 👉 https://lawyeraitoolkit.com/deliverables [https://lawyeraitoolkit.com/deliverables] Use it as a practical reference when building your own AI drafting workflow. 🎯 Final Thought The question isn’t whether lawyers should use AI in drafting. They already are. The real question is: Do you know exactly where AI stops being reliable?

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 letter * Two underappreciated hallucinations: * Citation drift (hybrid citation corruption) * Mutated quotations * The 3 most common AI hallucinations: * Fabricated cases * Real cases with incorrect holdings * Invented quotations * Three lesser-known (and more dangerous) hallucinations: * Subtle semantic drift * Fake multi-case consensus * Logical hallucination (broken arguments that look complete) * Why “just verify the citation” is no longer enough * A 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 correct * pass a quick check * and 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.