AI Builds: Ground Zero

AI Builds: Ground Zero

Are "build an AI agent in 20 minutes" ads lying to you?  Ron spent way more than 12 hours trying to find out. Ron set out to build the simplest possible AI legal workflow — a motion to extend time to file bankruptcy schedules — and discovered that "easy" and "AI-assisted" don't always mean the same thing. In this episode: * Why Ron decided to test AI workflow-building himself instead of buying a course * The 10-step workflow development cycle ChatGPT walked him through, from defining objectives to platform optimization * Testing the same workflow across Claude, ChatGPT, Gemini, and Copilot * Why Google Docs + Gemini unexpectedly produced the best output of any platform tested * Why Copilot's deep integration with Word actually made it harder to use, not easier * ChatGPT's pushback on regenerating an entire document — and the hospital-acquired-infection analogy Ron uses to explain AI "drift" * The lesson that mature AI users isolate and fix specific problems instead of regenerating whole documents * Why Ron avoided using Claude for this project due to a prior usage-limit experience on the Pro tier * The "airport test" from Ron's prior Field Note, Confessions of an AI Hallucinator, and how it applies to building workflows * The free "Motion to Extend Lite" workflow Ron is releasing publicly We also discuss: * How persistent AI workflows (skills, agents, StrongSuit-style systems) represent a brand-new product category * The decision points Ron had to map for an "omnibus" extension workflow covering any deadline type * Quality control checks built into the workflow — missing dates, missing deadlines, missing cause language * How Ron accidentally discovered this entire approach through his own podcast post-production process * Why bare-bones bankruptcy petitions create the exact problem this workflow solves * The risk of inconsistent details (names, dates, captions) when reusing forms across cases — and how AI reduces that risk Key Takeaway Building a workflow that actually works — across platforms, with minimal user friction, passing real-world testing — is a fundamentally different job than writing a clever prompt. The platform you choose matters as much as what you ask it to do, and the AI tool that's "supposed" to be best for the job (Copilot in Word, Claude for heavy drafting) isn't always the one that delivers. For Flintstones lawyers, this episode is proof that a usable AI workflow can exist without them building anything — Ron's free download does the work. Simpsons lawyers will recognize the platform-testing process as the real work of AI adoption. And Jetsons lawyers will appreciate the granular lesson on regeneration risk and isolating fixes rather than reprocessing entire documents. Mentioned in This Episode * ChatGPT * Claude (Pro tier) * Google Gemini (Google Docs integration, Enterprise tier) * Microsoft Copilot * StrongSuit * Confessions of an AI Hallucinator [https://lawyeraitoolkit.com/confessions-of-an-ai-hallucinator] (prior Field Note episode — airport test) * Team Accelerator [https://completebankruptcy.thrivecart.com/team-accelerator-firm/] (Ron's bankruptcy training course) * Motion to Extend Lite [https://lawyeraitoolkit.com/motion-to-extend-time-workflow] (free workflow download) > info@drescherlaw.com [info@drescherlaw.com]

Field Note: Can Apple Intelligence Pass the File Cabinet Test?

SHOW NOTES NOTE: The File Cabinet Test is used to determine whether AI can discern the contents of every file in a connected drive. The star of Apple's WWDC 2026? Apple Intelligence. Apple announced how Apple Intelligence is being incorporated into Siri. This prompts us to ask: Can Apple Intelligence finally make workflow automation accessible to ordinary lawyers? In this episode: * Why Apple's AI strategy isn't about building the smartest model — it's about removing friction * How natural language Shortcuts could lower the barrier to automation for lawyers who've never written a line of code * Whether iCloud can finally compete with Google Drive and OneDrive as an AI-connected file system * Apple's private cloud compute architecture and why privacy is not the same as privilege * Why the real story from WWDC 2026 may be the democratization of workflow automation We also discuss: * Ron's history as an Apple fanboy since the 1980s — and why this keynote actually got his attention * Steve Jobs' "best camera" line and what it means for AI adoption * Ron's existing Claude-based podcast workflow as a real-world example of what natural language Shortcuts could replicate * The fact that none of these features have shipped yet — these are observations, not a review * Siri's rebranding struggle and Apple's decision to stick with the name despite years of ridicule Key Takeaway The biggest AI story from WWDC 2026 isn't that Apple built the smartest AI. It's that Apple appears to be trying to make AI invisible — woven directly into the operating system rather than siloed in a separate app or chatbot (although there will be a stand-alone chat style Siri app). If natural language Shortcuts works the way it was demonstrated, lawyers may be able to build automation workflows simply by describing what they want in plain English. That's not a Jetsons story. That's a Simpsons story — and maybe even a Flintstones story. Prompting is useful, but workflows are transformational. If Apple pulls this off, the gap between lawyers who automate and lawyers who don't may finally start to close. Mentioned in This Episode: * Apple Intelligence * WWDC 2026 * Shortcuts (Apple) * Siri * iCloud * Finder * Gemini (Google) * Claude * ChatGPT * Google Drive * OneDrive / Microsoft * Apple Private Cloud Compute * The File Cabinet Test (from Episode 007 FolderMania) [https://lawyeraitoolkit.com/episode-007-folder-mania-ai-comes-to-you] info@drescherlaw.com [info@drescherlaw.com]

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 app * Why Heather recommends Enterprise ChatGPT as the right entry point for lawyers handling client information * The "Claude as cleanup hitter" workflow: how to keep confidential work in a secure tool and bring the output to Claude for drafting * Gemini's hidden advantage — and why most lawyers are using it wrong * The hallucination problem everyone's talking about — and why fake citations aren't the real crisis * The subtler risk: cases that exist but don't say what AI claims they say, and standards of review that get quietly swapped * Donna's paralegal education pivot — from policing AI use to training students to audit what AI produces * Ron's prediction: by end of this decade, there will be no more Flintstones-level lawyers We 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 Writing * Why judges are getting frustrated with both pro se AI filings and inaccurate AI-assisted briefs from lawyers * Ron'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 follow * FSJ-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 Lawyers * Donna Mandl — Maryland attorney; legal educator, Community College of Baltimore County (LinkedIn [https://www.linkedin.com/in/donna-mandl-ab7564120/]) * Shaun Koenig — Maryland attorney, MSBA Legal Summit panelist (LinkedIn [https://www.linkedin.com/in/shaun-koenig-7b44755/]) * Maryland State Bar Association Legal Summit [https://www.msba.org] — Ethics, Accuracy, and Efficiency: AI in Legal Writing panel * ChatGPT (OpenAI) — free tier and Enterprise tier * Claude (Anthropic) — Pro tier and Enterprise tier * Claude Code (Anthropic) * Harvey * Google Gemini — consumer and Enterprise ($36/month) tiers * Westlaw (Thomson Reuters) * LexisNexis * Fastcase * Rich Rodgers — prior guest, Episode 014; founder, StartupTechLaw (LinkedIn [https://www.linkedin.com/in/richrodgers360/]) * Dave Block — legal AI commentator; recommended follow for Flintstones lawyers (LinkedIn [https://www.linkedin.com/in/daveblockatty/]) * Ruben Hassid — Claude evangelist; recommended follow for Simpsons lawyers (LinkedIn [https://www.linkedin.com/in/ruben-hassid/]) * Field Note: 21 Ways AI Can Hallucinate in Your Legal Brief [https://lawyeraitoolkit.com/21-ways-ai-can-hallucinate-in-your-legal-brief] * Field Note: Tiers of the Clown [https://lawyeraitoolkit.com/tiers-of-the-clown]  * Mezu v. Mezu, Maryland Appellate Court No. 361 (2025) [https://www.mdcourts.gov/data/opinions/cosa/2025/0361s25.pdf] > info@drescherlaw.com [info@drescherlaw.com]

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 it * The six capability categories that actually differentiate AI tiers: context window, retrieval, usage limits, connectors, memory, and governance * How Ron's File Cabinet Test revealed a material performance gap between Plus and Enterprise environments * Why the best AI tier is the one whose capabilities and accumulated context match the task — not the one with the highest price point * Why governance and capability are different things, and why you need both * The framework for evaluating AI tiers that survives even when pricing, features, and model names change We also discuss: * How a Reddit thread about AI tiers triggered Ron's thinking on this episode * Why Ron returns to his Plus account for podcast brainstorming even after seeing Enterprise outperform it * The 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 ways * The analogy of the context window as the size of an AI's desk Key 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 [https://lawyeraitoolkit.com/episode-007-folder-mania-ai-comes-to-you] experiments * Three-Legged Stool (compliance framework — see Field Note: Building the Stool — How to Implement the AI Discovery Standards [https://lawyeraitoolkit.com/building-the-discovery-stool]) * Flintstones/Simpsons/Jetsons Framework * Companion handout (available at lawyeraitoolkit.com/deliverables [http://lawyeraitoolkit.com/deliverables]) * Reddit > info@drescherlaw.com [info@drescherlaw.com]

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 Law * Why Rich charges $10,000 to review AI-generated client contracts — and why no one has ever taken him up on it * The "Attorney Assist" model: how Start Legal pairs AI-generated documents with on-demand attorney review starting at $150 for 30 minutes * What "AI-native law firm" actually means — and why it's harder to define than the people throwing the phrase around on LinkedIn let on * The 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 send * The Delaware ruling allowing corporations and other artificial entities to vote in certain municipal elections — and what it might mean for corporate governance documents * A concrete FSJ roadmap: what Flintstones-, Simpsons-, and Jetsons-level lawyers should actually do next We 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 are * The UK firm licensed to practice law as an AI — and the startup firm handling traffic tickets with no human attorney * Whether Flintstones lawyers should only try to serve Flintstones clients, or whether tech alignment between lawyer and client matters * Why Rich thinks the next generation of clients will arrive already fluent in Claude and GPT — and what that means for practices that aren't ready Key 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/ [https://www.linkedin.com/in/richrodgers360/] * Start Legal — https://startlegal.com/ [https://startlegal.com/] * Startup Tech Law — https://www.startuptechlaw.com/ [https://www.startuptechlaw.com/] * Claude (Anthropic) — https://claude.ai/ [https://claude.ai/] * ChatGPT / OpenAI GPT Store — https://chatgpt.com/gpts [https://chatgpt.com/gpts] info@drescherlaw.com [info@drescherlaw.com]