Without Limitation

Matt Pollins

Stories from the people reshaping legal www.agents.law

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  1. What Happens Next?

    9 G. TEMU

    What Happens Next?

    Michael Bommarito ran GPT through the bar exam over Christmas 2022 to prove it wouldn’t pass. He’d been working with language models for years and had never had a moment where he thought they were really useful. Dan Katz kept asking. A little eggnog was involved. So Mike did it to shut him up. By the time they published the second paper a few months later, it had passed. That story kicked off one of the most cited moments in legal AI history. But it's just one chapter in a career that keeps moving. In this conversation, we trace the arc from that Christmas break experiment through to OpenClaw and agentic AI, the future of the Cravath pyramid, what we should be teaching our kids, and the trillion-dollar data centre buildout that's reshaping rural communities. Mike sees the same story playing out everywhere: a growing identity crisis at every level, from lawyers, to rural communities, to humanity itself. Keeping up with Mike Mike is a modern polymath and that makes him hard to keep up with. My head was spinning just trying to prepare for the interview. He started as a classics major studying Latin and Greek at Michigan before pivoting to maths and financial engineering. A PhD in political science followed, which is where he met Dan Katz in the Center for the Study of Complex Systems. He left academia for a hedge fund, then landed in legal tech in 2013. LexPredict, the company he co-founded with Katz, was doing predictive analytics and NLP for litigation years before the rest of the industry caught up. Today he splits his time across 273 Ventures and Kelvin on the commercial side, and the ALEA Institute, a nonprofit where he funds research, builds models and datasets, and runs projects like Leaky, an open source tool for detecting whether text was in a model’s training data. The real story behind “GPT Takes the Bar Exam” The first paper, GPT Takes the Bar Exam (fondly remembered as GPT Fails the Bar Exam"), showed GPT-3.5 passing some sections or coming close. But the real drama came during preparation for the second paper with OpenAI. Mike and the team discovered that the bar exam they’d tested on was in the training data. The “oh sh*t” moment wasn’t that it had passed. It was that the results might not be scientific, that they couldn’t separate memorisation from actual ability. They had to find a new exam, transform it into a format the model could process, and run it again. Only after multiple reads with clean data did they have confidence the results held. Pablo Arredondo from CaseText was involved. The second paper, GPT Passes the Bar Exam, made it onto The Late Show, the New York Times, and into conversations around the world. Agents aren’t new Mike’s latest book, Agentic AI in Law and Finance, makes the case that the word “agent” didn’t appear out of nowhere. Agent-based modelling goes back to the 1970s across economics, political science, and cognitive science. Schelling’s segregation models, Monte Carlo simulations, basic behavioural heuristics programmed into interacting routines. Mike and Dan grew up intellectually in that world during their PhDs. Then the foundation model companies picked up the term and most of that history got forgotten overnight. The book grounds the current hype in 50 years of research and asks what it means for governance in highly regulated industries. Mike’s short definition of an agent: a doer with a to-do. Beyond that, he says, it’s still a mess. And governance hasn’t kept pace. He pointed to Dario Amodei’s candid admission that nobody appointed the foundation model companies as leaders of this. The lack of governance runs all the way from the top of the AI industry down to individual firms making buying decisions, about half of which, Mike argues, are driven by FOMO rather than strategy. The pyramid is changing On law firm business models, Mike is direct: status quo is certainly not the right answer. He and Katz are writing a new book on transforming legal and financial organisations, and the working cover image is the Cravath pyramid being reshaped, its base becoming mechanical or cybernetic. He’s hearing anecdotally about firms slowing junior hiring and seeing large back-office reductions at large global firms. Mike feels the question firms need to ask themselves is what their clients are actually buying. Most buyers can’t answer that consistently, in his view. Some buy big law for insurance, some for relationships, some because they believe they get the best results. Until that’s clear, nobody can say what the new model looks like. But the old one isn’t surviving this. What should we teach our kids? Going a bit deeper than your usual legal tech podcast, we got into the question of what we should teach our kids, in a world where AI can out-perform humans in a growing number of tasks. Mike and his wife homeschool all three of his kids and says he doesn’t know whether they’ll go to college. He’s built custom AI tools for their education, and the gap between what you can deliver at home with today’s technology and what even the best schools offer is, in his words, huge. The problem runs deeper than curriculum. In the US, the cost of legal education isn’t commensurate with the expected value of the degree at most institutions. Faculty are naturally resistant to redesigning programmes in ways that might not include them. And the mismatch between what law schools will try to continue doing and what firms and clients will need is only going to widen. Mike sees some hope in states like Texas and Florida, where regulatory innovation untethered from ABA standards might allow for more practical, technical training. But the question extends well beyond law. If productised AI tools can deliver a better education than a classroom, what does that mean for public institutions where education is one of the primary services? What happens when you don’t need a teacher for every 15 to 30 students? These aren’t hypothetical questions for Mike. He’s living the answer with his own family every day. The real risk isn’t AGI The thread that ran through everything was bigger than legal. Mike’s deepest concern isn’t the terminator scenario. It’s that the global middle class expanded on the back of knowledge work that can be done over the internet by someone with basic language skills and a computer. A trillion and a half dollars is now racing to convert that exact work into “pure electricity”. If the expanding middle class is what kept the world relatively peaceful, what happens when that contraction starts? That question led us to his other new book, This is Server Country, about the physical infrastructure buildout reshaping rural communities. As we spoke, Mike was about to join a court hearing over the Oracle/OpenAI Stargate data centre project in Saline Township, Michigan, a small town of a couple thousand people where, as he put it, everything about the identity and experience they’ve had is being destroyed. Mike doesn’t hold back at this point: “We’re replacing people’s interactions with each other with tokens and audio that’s not real. We’re replacing physical landscape with something that’s not natural. We’re replacing labour in the economy with something that’s not actually labour”. Whether it’s a lawyer drawing a line around their profession, a community drawing a line around their town, or humans drawing a line between themselves and machines, Mike sees the same thing everywhere: an identity crisis, at every level, that will dominate politics for the foreseeable future. Books and links * Agentic AI in Law and Finance by Michael Bommarito and Daniel Martin Katz (2026) * This is Server Country by Michael Bommarito (2026) * Upcoming book on transforming legal and financial organizations (Bommarito and Katz, in progress) * GPT Takes the Bar Exam (2022) and GPT Passes the Bar Exam (2023), research papers by Bommarito, Katz, Shang Gao and Pablo Arredondo * 273 Ventures / Kelvin (commercial) * ALEA Institute (nonprofit research) Connect with Mike Connect with Mike on LinkedIn. He maintains inbox zero (mostly). This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.agents.law

    52 min
  2. Why YC just backed an AI law firm

    9 LUT

    Why YC just backed an AI law firm

    What We Covered * General Legal’s founding story and its roots in Casetext * JP’s unusual career path from iOS developer to Harvard Law to Big Law (WilmerHale, Cooley) to legal tech engineer * What makes a firm “AI native” versus a traditional firm that’s adopted AI tools - and the corporate structure and reinvestment philosophy that distinguishes the two * The practical workflow: how clients engage General Legal via Slack, send contracts, and receive AI-assisted attorney-reviewed markups within a three-hour SLA * Pricing model: $250 for documents under three pages * The “attorney attention engine” concept - AI handles first-pass review and context gathering, directing lawyer focus to the provisions that actually matter * How General Legal differentiates from Atrium by targeting “run the company” work (MSAs, NDAs, DPAs) rather than “bet the company” work (priced rounds, M&A) * The competitive landscape: not directly competing with Big Law or in-house teams, but filling a gap where neither wants to operate * The YC experience, the $4.2M pre-seed, and the ambition to build the largest law firm in the world * Forward-looking topics including MCP-compatible law firms, clients pre-processing contracts with ChatGPT, and the blurring line between engineers and attorneys Key Takeaways * The defining question for an AI native firm: are you willing to reinvest virtually all profits back into efficiency rather than distributing them to partners? * Run the company legal work (routine commercial contracts) is ripe for AI disruption; bet the company work (M&A, priced rounds) still demands top-tier human strategic advice * The percentage of work done by AI versus humans isn’t fixed; it depends entirely on the matter - a DPA draft might be 90% AI, while advising on GDPR compliance is 98% human * Traditional law firms spend only 1-2% of profits on efficiency tools, which J.P. believes structurally limits their ability to compete with firms that take outside capital and reinvest aggressively * The most important hiring criterion is still excellent lawyering - you don’t need engineer-attorneys, you need client-obsessed commercial lawyers who are willing to adopt AI workflows and help shape the tools * Slack-first client communication is a meaningful efficiency gain over email, even before any AI enters the picture * The corporate structure mirrors Atrium’s model: a separate law firm entity employing attorneys alongside a partner technology company, sidestepping ABS restrictions * The long-term play is horizontal expansion across practice areas - starting with commercial contracts to earn client trust, then expanding into regulatory, litigation, and broader transactional work This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.agents.law

    48 min
  3. Should law firms encourage vibecoding?

    31 STY

    Should law firms encourage vibecoding?

    What We Covered * The rise of vibecoding in the legal industry * Bird & Bird’s recent rollout of a vibecoding solution within the firm * Governance and compliance considerations, including how to give everyone a safe sandbox to prototype, with clear pathways to enterprise deployment with the appropriate safeguards when something proves valuable * The maintenance question * Opportunities for vendors to lean into vibecoding rather than see it as a competitive threat * The shifting training needs toward product thinking * The skills needed to sell products rather than services Key Takeaways * Velocity excites everyone, but someone has to handle sustainability, governance, and scale. * Vibecoding works, but not at scale yet. It’s brilliant for prototyping and individual problems, but no one has solved managing proliferating micro-applications. * The polarised debate misses reality. Truth sits between “I built Harvey in 30 minutes” and “vibe coding is just a hobby.” For the right use cases with proper controls, it delivers genuine value. * Recreating a feature is easy; creating a company is very hard. Weekend projects that replicate one capability shouldn’t be confused with sustainable products. * The forest of mushrooms problem. Apps sprouting everywhere, some great, some poisonous, creates fragmentation in already-fragmented law firms. * Trust must transfer to platforms before agents scale. Clients need to trust the technology enough to upload documents without a human in the middle. * Reward failure in innovation. Three days vibe coding something that goes nowhere still teaches you something. That learning has value even when the app doesn’t ship. Links Bird & Bird announces partnership with vibe-coding app development platform Betty Blocks This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.agents.law

    45 min
  4. 24 STY

    Should clients get a discount if firms use AI?

    What We Covered * Richard’s 40 years of working with law firms on pricing * His viral LinkedIn post from January 2026 that sparked debate: a fictional partner’s letter explaining why AI may not mean lower fees - we get into the arguments for and against * Richard’s view that transparency and benefit-sharing between firms and clients is the only sustainable path forward * The difference Richard has observed between what clients say they want (lowest price) and what actually drives their buying decisions * How productised legal services like Littler’s employee classification tool represent a new pricing paradigm * The “creative destruction” mindset firms need to avoid being disrupted * Richard’s journey from managing partner to pricing consultant, and the Aderant acquisition of Virtual Pricing Director Key Takeaways * Richard believes firms that have invested heavily in AI tools deserve ROI on that investment, not a race to the bottom on fees * When GCs were asked to prioritize price factors, less than 10% chose “lowest price” as most important * Richard believes the winning formula is transparent benefit-sharing: if AI reduces delivery cost from £100k to £70k, billing £85k splits the value fairly * Clients aren’t just buying legal advice. They’re buying security, reassurance, and the firm’s professional indemnity coverage * If you don’t destroy your own business model, someone else will * The legal profession’s greatest pricing limitation is lack of confidence. As one senior partner told Richard: “If you don’t think you’re worth it, why should anyone else?” * Legal work will grow, not shrink. Life and commerce are getting more complex, and AI itself creates new advisory opportunities * Technology alone won’t transform pricing. Sustainable change requires addressing people, process, and technology together This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.agents.law

    42 min
  5. Without Limitation (S1 E1): Mary Bonsor

    18 STY

    Without Limitation (S1 E1): Mary Bonsor

    What we covered * Mary’s journey from law student and litigator to founder, sparked by her own struggle to secure a training contract and the obvious disconnect between eager junior talent and firms needing support * How she made the leap into entrepreneurship, including raising external funding to create a real proof point before leaving practice * What Flex Legal is and how it evolved: from a platform focused on paralegals to a broader model supporting lawyers and in-house teams * The social mobility mission behind Flex Legal, including the impact of the SQE route and the creation of training contract pathways * The real impact of AI on junior legal careers: why Mary is optimistic, what’s changing in role requirements, and why junior lawyers still matter in an AI-enabled workflow * The skills that will define successful lawyers in 2026 and beyond: curiosity, judgment, EQ, relationship-building, and commercial awareness * The story behind the Mishcon acquisition, and why relationships and long-term networks matter more than people think * Mary’s new role as GC Relationships Director and how it reframes law firm client relationships through a “customer success” lens * The shift toward productised legal delivery: breaking work into strategic vs BAU components, combining people/process/tech, and designing pricing that works for both sides * Why client feedback and pilots are essential to successful innovation, especially when firms are building new service lines * The GC Academy: a structured programme designed to build financial literacy, leadership, legal ops and legal tech skills for in-house leaders * Lessons from 10 years of building: staying optimistic through the lows, maintaining energy, and treating startup life as a marathon Thanks for reading/listening! If this was useful, please share it. Biggest takeaways * Purpose and profit are not opposites: The best businesses can deliver real commercial outcomes while creating measurable social impact. * AI is changing job specs faster than it’s changing demand: The work juniors do will evolve, but the need for people who can operate with judgment and quality control is only increasing. * Curiosity is a career superpower: The ability to ask better questions, learn fast, and deeply understand client problems will outperform almost any technical skill. * Human skills are the long-term moat: Judgment, empathy, and trust-building remain the parts of legal work that are hardest to automate. * Networks compound over time: The acquisition story is a reminder that consistent relationship-building creates outcomes years later. * Productisation only works with real client input: Build with customers, pilot early, learn quickly, and iterate before scaling. * Founding a company requires durable optimism: You need enough energy and belief to keep going through the inevitable difficult moments. Book recommendations * Patrick Lencioni (especially The Five Dysfunctions of a Team) * Stephen R. Covey — The 7 Habits of Highly Effective People This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.agents.law

    42 min

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Stories from the people reshaping legal www.agents.law