When I sit down with Elliott Portnoy, it has been just over a year since he stepped down as Founding Global CEO of Dentons, the firm he scaled from a foundation in a mid-sized US firm with no global presence and ultimately became the world’s largest law firm.

12,000 lawyers, 200+ offices, 87 countries, through 61 mergers in just over ten years. Just think about this for a moment. A merger every two months. More mergers than the rest of Big Law combined.

So, how (and why) did he do it? And if he were taking on a law firm leadership role today, would he do it all again?

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Capitol Hill to the City

Elliott didn’t set out to be a lawyer. He spent years working on Capitol Hill, imagining a life in politics and policy. He eventually concluded that the law would give him what he really wanted: a practice at the intersection of politics, policy, and business. He studied as an undergraduate in the US and got his DPhil at Oxford.

His early practice was in public policy and regulatory law, and he loved it. But he’s honest that it was a different era. Washington was more bipartisan then. You could actually get things done, shape legislation, move the dial for clients. He’s grateful his practice years fell when they did. Today, he says, it’s far easier to kill things in politics than to build them.

The firm nobody expected to win

The origin story of Dentons is far more interesting than most people realise. Elliott joined Sonnenschein Nath & Rosenthal, a well-regarded US firm, but one that was, as he puts it, “absolutely indistinguishable from three or four dozen other US law firms.” It had no global presence. It had tried London once before and pulled out.

He and his team saw something others didn’t - an opening - not just to build a global practice, but to build an entirely different kind of global law firm. He calls it “a polycentric one with no dominant culture, no flag flying over the whole thing, no lawyers parachuted in from New York to do work that local partners should be doing”. The insight was radical: clients didn’t want someone who flies in from London wearing a local suit. They wanted the most elite lawyer who actually knew the market, knew the judges, knew the business community. At the time, he felt that no global law firm was genuinely “in and of the communities it served”.

The first deal, in 2010 with Denton Wilde Sapte, was not warmly received in the legal press. Elliott remembers the UK Legal Week headline vividly: it compared the combination to two drunken sailors falling into bed together. He tells me this with a smile. “It was an improbable start to what has been an extraordinarily remarkable journey.”

61 mergers in 10 years

Most law firms do a deal and then pause, sometimes for a decade, sometimes longer, while they fight out whose compensation system wins and whose culture survives. Elliott took a different view: you don’t have to choose between growth and integration. You can do both in parallel.

So they did. For most of the years he led Dentons, the firm completed more M&A than the entire rest of the legal profession combined. They built a dedicated transactions team and a separate integration team, because the skills required are genuinely different. Finding the right partner is nothing like knitting two organisations together, and conflating the two is how most firms end up stalled. At peak, they were travelling around 200 days a year. To do 60 deals, he says, “you have to kiss a lot of frogs”. There may have been 600 conversations for every 60 that completed.

What made it work was the firm’s polycentric model. Elite local firms in South Africa, India, the Philippines, across the Middle East, firms that had spent decades building client relationships and community credibility, could join Dentons and keep their identity while gaining the platform of the world’s largest law firm. Dentons became the first global law firm to combine with a leading firm in China, the first to achieve level one black economic empowerment certification in South Africa. They were the proof of concept for a genuinely different kind of global firm, and they attracted partners that no other firm could.

The three-way combination in 2013, bringing together what had become SNR Denton, Salans in Europe, and FMC in Canada, was another first. Three-way combinations simply didn’t happen in the legal profession, certainly not across continents. But Elliott and his co-architect Joe Andrew had concluded that the pace itself was part of the strategy.

There were law review articles at the time arguing you could never run a law firm with more than 5,000 lawyers. Elliott mentions this with obvious satisfaction. Those articles, he says, have had to be put in the trash heap.

Why the merger wave isn’t slowing down

The current wave of transatlantic mergers, Elliott argues, is different in character from the waves that came before. The 1990s and early 2000s were opportunistic. What’s happening now is existential.

Mid-market firms are getting squeezed from both ends. The top 25 or 30 firms are pulling away, hoovering up the most profitable work and the best talent. And at the other end, small tech-enabled firms are competing for work that used to be safe mid-market territory, because the tools now allow a lean team to do what previously required a large one. The firms caught in the middle, the ones with leaders who can see the problem but are three to five years from retirement, are the ones he worries about most. He puts it plainly: “I hear from a lot of law firm leaders who are just thinking about getting to the end of their runway and letting their successor worry about it. It’s hardly a profile in courage.”

The consequences, he thinks, will be real. Some firms will go out of business. Others will find they’ve left it too long to find a merger partner worth having. The dance music will stop, and if you’ve got no one to dance with, you may not be able to combine. US firms are arriving in London in record numbers and proving to be formidable competitors. In his view, the window for a good deal is open now but it won’t stay open forever.

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If he were starting again today

I ask Elliott what he’d put on his to-do list if he were walking in as global CEO of a large law firm today. He doesn’t hesitate.

First, he’d be doubling down on global opportunity. He’s not among those who think geopolitical turbulence is a reason to retreat. He watched Bloomberg the morning we spoke covering the cascade effects of oil prices across agriculture, tech, and supply chains. There’s no going back, he says. Clients don’t retreat from global markets and they need advisors who don’t either.

Second, he’d be all-in on AI and technology - not just the narrow point solutions getting all the coverage, the plugins, the co-pilots, the contract review tools, but genuine tech enablement across the whole business. He thinks McKinsey’s estimate that 70% of legal work is automatable is probably an underestimate. The disruption, he says, is pervasive. And he suspects the billable hour will be the first major casualty, not immediately, but within a few years as the economics become impossible to ignore.

Third, he’d be shifting away from hourly billing entirely, toward alternative fee structures and success-based models that align the firm’s interests with clients.

Private equity and the AI law firm question

Elliott now spends most of his working days advising private equity firms evaluating opportunities in the legal sector, helping with everything from developing an investment thesis through to due diligence, negotiation, and board service once a deal is done. He describes it as work he loves, surrounded by smart, dynamic people who are coming at the legal industry fresh, without the assumptions (or limitations!) that insiders carry around.

He thinks the interest in law from private capital is not sudden - he reminds me that PE has been circling professional services for years, drawn by stable, recurring, profitable revenue in human capital businesses. Accountants, consultants, engineers: and law is just the next one. What changed is the regulatory environment in the US, where the MSO model now offers a workable structure. The MSO bifurcates the professional practice from the business infrastructure of the firm, allowing outside capital into the latter without touching the former. It’s a tried and tested model from healthcare and other sectors, and it’s gathering momentum fast.

By end of 2026, Elliott expects a couple of dozen US law firms to be PE-backed through this structure. By 2027 and 2028, many more. The starting point is consumer and retail-focused firms, personal injury, insurance defence, construction defect, but he expects a steady move up the value chain as investors get more comfortable with the sector and the model matures.

On the AI law firm question, he is measured. Some of the firms spinning out under that banner are genuinely embedding AI into every workflow, rethinking how legal work gets done from intake to billing. Others, he says, are doing what the dot-com era called throwing a .com on the end: branding more than transformation. The multiples being floated in bidding processes are eye-popping, he notes, though by the time due diligence is done they tend to come back to earth.

The university question

Elliott sits on the board of trustees at Syracuse University, which has forged a partnership with Anthropic to give every student and faculty member access to Claude. He sees higher education as facing exactly the same challenge as law: institutions that are leading on the front foot, and institutions that are hoping this just goes away.

It’s not going away. Faculty members, he says, may be the only group he’s encountered who are even more resistant to change than lawyers. But the institutions that embrace technology, rethink their delivery models, and position themselves as homes for lifelong learners rather than just 18 to 22 year olds, those are the ones that will thrive. The ones waiting it out are storing up a serious problem.

Law schools that don’t teach students how to use and think about AI are, he says bluntly, doing those students a disservice. They’ll arrive at law firms, public service, or wherever else they go and be fundamentally less capable of delivering value. The profession has already been disrupted. Sending people into it unprepared is a failure.

Final note

The sheer scale of his achievement at Dentons is hard to fathom, but when you meet Elliott, you can see how he did it.

He is well-prepared. He is considered and confident about where things are going and what it will take for firms to succeed. I also found him to be extremely generous with his time - before, during and after this discussion.

He’s understandably proud of what he achieved at Dentons - but what surprised me most is that he seems more energised than ever about the next chapter and his opportunity to contribute to it in both law and education.

Elliott Portnoy is just getting started.

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We discuss how he actually uses AI day to day, how he thinks about the security and privilege considerations, and what happens to the billable hour when you scale your work with AI.

Side note: for a demo of Claude on legal use cases, watch this LinkedIn Live recording I posted last week.

Introducing Zack

Zack Shapiro went to Yale Law School thinking he’d become an academic. If not law, it would have been a philosophy PhD. He eventually decided that Yale Law offered the same intellectual life with better job security and less time in training.

After law school came a year at Davis Polk, where his timing coincided with the ICO boom. He landed some of the firm’s earliest crypto work. Two federal clerkships followed, first with Judge Engelmeyer on the Southern District of New York, then Judge Lynch on the Second Circuit.

Still not sure he wanted to practise in BigLaw, he joined a friend’s e-commerce startup, BZR, as an operational co-founder. They raised money from Founders Fund, Greycroft, and Abstract Ventures, and then the business got acqui-hired in 2020. The lesson Zack took away surprised him: he never wanted to be a startup founder again. What he enjoyed was being a startup lawyer.

That year he launched a solo practice that grew into Rains. They’ve now advised over 200 clients across corporate law, venture financings, digital asset regulation, and increasingly, AI. Zack also serves as Head of Policy at the Bitcoin Policy Institute.

The post that broke legal Twitter

Before we get to how Zack uses AI, we need to talk about what brought him to most people’s attention: a post on X that hit 7.7 million views. I’m not sure a legal technology post has ever reached that level of virality?

Zack had been experimenting with X’s long-form articles feature. He’d already written two, one on the concept of the “AI centaur” borrowed from the chess world, another on what AI means for intrapreneurs inside larger organisations. Both did reasonably well - but nothing compared to the third. It laid out how he uses Claude as a practising lawyer.

He shares the moment he knew it had gone viral. At around 10,000 views, the notifications started going haywire. He describes it like a slot machine hitting the jackpot. He couldn’t do anything for the next two hours but watch the notification pings come in. Luckily, it was a Friday afternoon.

The piece generated a huge amount of debate and the comments kept rolling in on X and LinkedIn. Some praised it as a practical roadmap; others dismissed it as “productivity theatre” or questioned whether Claude has the enterprise features needed for BigLaw. Either way, it got people talking.

The lesson Zack took from it was that people want the specific, practical examples of what AI looks like in real legal work. And we got into some of that in the discussion.

Why Claude?

Zack points to two features of Claude that he thinks make the difference.

First, Claude can write code on the fly. Before this, he’d use ChatGPT to help think through contract edits, but the best it could produce was a list of redlines he’d then manually apply in Word. The formatting would invariably break. With Claude, he found a way to get it to manipulate documents directly, which he describes as XML under the hood, published as a Word doc with tracked changes.

Second, he found that Claude can create and work with local files. In his view, this addresses the context window limitation that degrades long-running conversations. Instead of relying on the model’s memory and context window, Zack also stores context in markdown files on his computer, effectively creating external memory that can be referenced as needed.

He’s also a huge fan of Skills, the open standard that I’ve written about previously and recommend that all law firms should be experimenting with. TLDR, Skills are simple, human-readable files that explain to an agent how to tackle a particular task. Zack describes it as a zip file you could send to 500 associates, your judgment encoded as a skill file that scales like software.

The Secret Sauce (public version)

Zack sees a clear split online between people who say AI has given them superpowers and people who think the whole thing is productivity theatre. He thinks the gap comes down to two things.

Disciplined input. The model is a fuzzy tool. Fuzzy input produces fuzzy output. Precise, detailed instructions produce much better results. He argues that most legal AI companies are focused on the wrong problem, training models or using variations of RAG for contract and brief templates. In his view, the training data already contains more of those than anyone could need. The bottleneck is the prompting and the context. The good news for lawyers: precision and specificity are skills the profession already selects for.

Reinforcement over time. Once you’ve built up enough back-and-forth with the model, you encode what works into skills. When it does something well, you reinforce it. When it does something poorly, you update the skill. The usefulness compounds. It’s a compelling idea, though it does require a level of discipline and iteration and one wonders if every practitioner will have the time or inclination for that, unless it happens automatically in the background.

A day in the life

Email is still where the work arrives. But the “substantive lawyering” now happens inside Claude.

An engagement letter used to mean opening Word, editing the scope, swapping in the client name and retainer amount. Now it’s a one-sentence instruction: engagement letter for this company, addressed to this person, here’s the retainer, standard scope. The letter comes out the other end.

He’s also built a custom tool combining Claude Code with ElevenLabs that reads long documents aloud, which is helpful as Zack has a health condition making it hard to read longer documents on screen. But for working with Claude itself, he types. Long prompts, often 2,000 words, written like essays. He finds that typing without worrying about grammar or spelling is faster than voice, and being redundant about the things that matter is a feature, not a bug.

Zack says the drudgery is gone and the work feels more joyful.

On vibecoding and the future of legal deliverables

Long-time readers will know I’m big on vibecoding. I asked Zack whether he’s started vibecoding things as a way of delivering advice. Dashboards, interactive maps, visual tools. His answer was no.

He’s sceptical of anything that intermediates between a client’s intent and the lawyer’s delivery. Take the classic 50-state regulatory review. Version one is the memo. Version two might be an interactive visual. But Zack’s thinking about version three: what if you deliver the answer in the format the client actually needs? Not a memo about sales tax rules, but the code to make their sales engine compliant across all 50 states.

It’s an interesting provocation, though it raises its own questions about where legal advice ends and software engineering begins, and who’s responsible when the code is wrong.

On security

Information security is probably the question Zack gets most in X threads.

On privilege: he thinks it’s easier than people assume. Many of the negative reactions to his article cited the Heppner case, the February 2026 ruling from Judge Rakoff in the Southern District of New York. But Zack argues that case is distinguishable. In Heppner, a criminal defendant used a consumer version of Claude, on his own initiative and not at counsel’s direction, to research legal strategy. The privacy policy allowed training on inputs. Judge Rakoff found no reasonable expectation of confidentiality and no privilege. A law firm using an enterprise AI tool with training turned off, generating attorney work product at counsel’s direction, is a different posture in Zack’s view. Whether the courts will draw that line clearly remains to be seen; Judge Rakoff himself noted that the analysis “might differ” if counsel had directed the AI use.

On data confidentiality: more nuanced, and requiring case-by-case judgment. The spectrum runs from cloud-hosted with zero data retention, through custom DPAs, local inference, and encrypted AI, to simply not putting certain data into any model.

Zack reserves his sharpest words for some legal AI vendors, who he sees as “selling fear”. He believes there are companies pushing expensive platforms with checkbox workflows that, in his view, ultimately aim to automate away the lawyers buying them. He’d rather lawyers engage with the ethical rules and the technology directly and build things themselves. Not everyone will agree; some firms will conclude that a managed platform is the most practical way to meet their compliance obligations, but Zack believes that is more fear and hype than reality.

Pricing in a post-AI world

Zack tells me that Rains charges hourly rates at roughly half the cost of Big Law, with overall service costs landing at about a quarter, the additional reduction coming from AI-driven efficiency. Most clients are on subscriptions denominated in a cap of human hours but calculated to be functionally all-you-can-eat. The long-term goal is flat subscriptions, but the technology isn’t reliable enough yet to remove the human-attention safeguard.

The tension Zack identifies is that the value of the work product is becoming untethered from the hours spent producing it, but the capacity to exercise judgment is still measured in human time. Overextending means falling into the temptation of not checking the AI’s output.

Scaling through Claude, not headcount

Rains already runs multiple Claude chat and Cowork sessions in parallel (all on screen for now!) In his opinion, one lawyer plus Claude can replace a partner plus a team of associates on certain matters.

But taking on more clients doesn’t scale the same way, because each one requires human judgment. To grow that side, he’d need to hire lawyers who use AI the way he does. That’s a small pool right now.

He’s thinking about what comes next: training for larger firms, forward deployment into in-house teams, possibly selling his agentic workflow to a tech company. He sees two possible futures for the profession. One where everyone ends up inside opinionated platforms and everything becomes a process. Another where lawyers use AI directly and the profession opens up.

On venture capital and AI law firms

Y Combinator’s latest batch included two AI-native law firms: General Legal, and LegalOS, and another legal service platform, Arcline. VC money is flowing into the space more broadly. (Take a look at my list of AI law firms here.) For now at least, Zack isn’t rushing to take any.

His concern is that the incentives of a venture-backed AI law firm push towards automating everything, including the judgment, and delivering what he bluntly believes is slop. In his view, you need good lawyers doing the lawyering, with automation built around that. He points to Atrium, the hybrid law firm and legal tech company that raised $75 million before imploding in 2020, as a cautionary tale.

The tools are already here, he argues. He doesn’t need $60 million to keep building skills. But he’s open to conversations.

How to get involved

Zack is open to conversations with Big Law managing partners, in-house leaders, and tech companies thinking about the future of legal work. Reach him on X at @ZackBShapiro or email [email protected].

For a live demo of Claude on legal use cases, watch this LinkedIn Live recording I posted last week.

Links

* Rains (rains.law)

* Zack Shapiro on X (@ZackBShapiro)

* “The Claude-Native Law Firm” (original post on X)

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

In this episode, I meet Dr. Sarah Stephens and learn how an AI Assistant in WhatsApp is solving real problems for women in Tanzania

Introducing Dr. Sarah Stephens

Dr. Sarah Stephens isn’t your typical legal technologist.

She started her career on a traditional path, training at the global law firm, Linklaters.

But a summer volunteering on grassroots access to justice projects in Kenya, working with children and widows navigating life-limiting legal situations, set her on a very different path.

Nearly two decades later, she’s running an AI-powered legal empowerment platform in Tanzania, sitting on the UK’s Online Procedure Rules Committee, leading the Sussex Centre for Law and Technology, and launching a new AI law lab.

I’ll confess, I have struggled with the term “access to justice”. It feels like one of those terms that mean different things to different people and it can sometimes feel abstract. This conversation and Sarah’s work helped me think about it differently.

Meet Dada Wakili

After Linklaters, Sarah moved through Kennedy’s, picked up a master’s in human rights law, and took a case to the Human Rights Court with Coram Children’s Legal Centre and won.

Then came the opportunity to relocate to East Africa, where she went in-house with KPMG in Tanzania. That’s where it all clicked.

In Tanzania in 2015, Sarah watched M-Pesa, the mobile money platform, transform financial inclusion through mobile phones and asked herself: why can’t we do the same for legal services?

That question ultimately became Dada Wakili - dada meaning sister, wakili meaning lawyer.

It’s an AI-powered chatbot on mobile phones, integrated with WhatsApp, that guides women through the justice issues they encounter in daily life.

The focus on women came from the field research. Tanzania has a pluralistic legal system, with statutory, religious, and customary law all interplaying, and the gaps fall hardest on women. A husband dies, the family invokes customary rights, and the widow and children lose their home. It’s unconstitutional. But nobody tells them that. That’s where Dada Wakili comes in.

The design challenges are real: laws still written in English from the colonial era, training data split across two languages, feature phones in rural areas with no smartphone access. The team is Tanzanian-led, engineers, lawyers, partners, and the whole thing is free to users. It’s currently grant-funded by Irish Aid and the FCDO, but finding sustainable financing remains the hardest problem to crack.

How to get involved

Sarah is actively looking for law firms, legal tech companies, and organisations interested in supporting Dada Wakili or collaborating on the Sussex AI Law Lab. Connect with her on LinkedIn.

What “Access to Justice” really means

Sarah pushes back, gently, on the phrase. Access to what, exactly? In the UK we tend to think courts, advice, enforceable remedies. In Tanzania, justice might mean resolution within a customary system. She prefers the frame of legal empowerment: building someone’s individual capability to act on information they’ve received. And she’s clear that AI won’t solve the access to justice crisis, because the crisis isn’t one thing. It’s a web of policy failures, funding gaps, and poverty.

New rules for online courts

Appointed by the Lord Chancellor, Sarah sits on the committee writing the rules for England’s online court system. The inclusion framework she’s been working on provides principles for legal tech builders across the digital justice ecosystem, covering pre-action advice tools, online dispute resolution, and self-help tools, with the vision of end-to-end data flow from early advice through to court. The rules are deliberately short and plain. No white book.

Sussex, students, and the skills question

The Sussex Centre for Law and Technology teaches AI literacy, innovation, and building. Sarah’s view is that lawyers need wider life experience and tech fluency more than ever, but also that AI critical literacy matters as much as AI enthusiasm.

Her students are asking hard questions about bias, data, and environmental cost. Some refuse to use generative AI because of its water consumption. Every tool, she feels, should carry an environmental statement.

The new Sussex AI Law Lab (SAILL) will run real use cases from the university’s legal clinics and partnerships with organisations like Citizens Advice, and get students actually building. (I’m hoping to support by providing a course of vibecoding!)

Where next for Dada Wakili?

After a big week at the Legal Tech for Access to Justice East Africa conference and a national TV appearance (far more challenging than my podcast I’m sure!), Dada Wakili is expanding from smartphones to feature phones via USSD and SMS, reaching more remote communities across Tanzania.

Partners from other countries are already asking when it’s coming to them.

If you’re inspired by her work, please reach out to Sarah directly on LinkedIn.

Links

* Dada Wakili

* Sussex Centre for Law and Technology

* Access to Justice Foundation

* Online Procedure Rules Committee

* Sarah Stephens on LinkedIn

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

When I sit down with Richard Tromans, he has just published a piece on the Anthropic legal plugin, along with a flurry of other updates on the day’s legal tech developments - another busy morning in the world of Artificial Lawyer.

He started the business in 2016 after a career in journalism and consulting - inspired by the change he saw coming and wanted to be a part of shaping.

Nearly a decade later, he says things are finally moving.

In this conversation, we cover his diverse background (he’s done more jobs than most people you know!) and how that informs his writing. We cover what is different about the latest developments in legal tech, whether the law firm pyramid is about to be replaced by something else, and whether AI risks making us all a bit dumber.

A decade of travel that still shapes his work today

Richard left university with one goal: never have a proper job. While his peers were lining up training contracts and summer placements, he went in the opposite direction. A decade of travel, factory shifts, bar work, cinema tickets, salad prep, and even a stint as a telephone tarot card reader (yes really), which he quit once he realised the callers were people who couldn’t afford a therapist.

He doesn’t see those years as squandered. Working in factories taught him how different parts of the economy actually operate and the assembly line gave him a perspective on the economics of law firms. Growing up in the Black Country, the historic heartland of the Industrial Revolution, shaped everything. His school history teacher skipped Waterloo and the Napoleonic Wars and spent years teaching the Industrial Revolution instead, in a town where it had literally happened a few doors down.

By the time Richard eventually landed in the City and then legal tech, he had a completely different lens.

From journalist to consultant

Richard’s first real job in law was as the world’s first international legal reporter at Legal Week magazine, starting in 1999. His beat was everything happening outside London: globalisation, the expansion of the magic circle firms, the BRICs coming online, the EU taking shape.

The job meant sitting down with managing partners of enormous firms and asking them to explain their strategy. He says the first couple of years he probably didn’t understand what they were saying and his articles probably weren’t much good either. But he got deeper and deeper into the business of law. About seven years in, a managing partner stopped their interview mid-conversation because he said Richard now knew more about the subject than he did. That was his first consultation. It was free, because he was still a journalist.

He spent the next decade or so as a strategy consultant in the City. By 2015 he was running his own practice, strangely dissatisfied, and increasingly intrigued by AI - which, he admits, he initially mocked. He says the scepticism masked a deep-seated interest. He just wasn’t getting good answers.

Then someone invited him to see it work. A company called RAVN (later acquired by iManage) showed him their contract analysis tool in action. He watched it zip through real estate documents and pull out key clauses. And he thought: this is the industrial revolution of the legal world. He changed his LinkedIn title to “legal industrialist” in homage to his Black Country forefathers, and launched Artificial Lawyer.

The billable hour problem that never went away

Richard tells a story from early in Artificial Lawyer’s life. He was giving a speech to hundreds of people at a law firm network event in Berlin, right next to the Brandenburg Gate. It had gone well. Then a woman at the back raised her hand and said: there’s one problem. I sell time for a living, and this will destroy my business.

Every head in the room turned. Richard admits he hadn’t thought deeply enough about the billing question at that point. He was more amazed by the technology. But she was right. She owned a private business, she wasn’t a charity, and this thing was not going to help her.

That was nearly a decade ago, and the problem hasn’t gone away. Almost every issue anyone ever raised about AI in law — training juniors, the billable hour, time to value — still exists. The base technology has changed dramatically, but the structural environment hasn’t.

Why firms aren’t rushing to change

On whether big law is productising its work, Richard is blunt: no, and we shouldn’t expect it. Even Big Law, he points out, contains about twenty different constituencies. Shipping firms in London are nothing like private equity firms in Manhattan. They share a pyramid structure, but they’re radically different businesses.

The economics are too compelling. An equity partner can work out on the back of a napkin what a workstream will produce in billable hours, at what rates, for what profit. It must be incredibly reassuring, Richard says, to know at the end of each quarter that you and your team have made millions doing essentially what you did last year. Without much client pushback, without much threat from new entrants.

He’s not surprised they’re not queuing up to disrupt themselves. Some firms are doing interesting things at the edges. If you went to an equity partners’ annual meeting and proposed a radical redesign of the business, why would they vote for it? There’s no need yet. They don’t feel it yet.

Richard thinks we’re waiting for a Cravath moment: a leading firm or small group of firms that seize the moment, change the model, and everyone else lines up behind them. He doesn’t know whether it will come from the US, the UK, or somewhere else. But he thinks it will take three or four years before partners start truly feeling it — losing clients, being told by buyers that they won’t pay for anyone below eight years’ PQE.

The pyramid is eternal, but it will operate differently

Richard pushes back on the idea that the pyramid is going away. The pyramid, he says, is the eternal structure of all human labour and organisation. Even organisations that say they’re flat are kidding themselves.

But the way it operates is going to change. He makes an interesting historical point: law firms were one-to-one for hundreds of years. A partner and an apprentice. It was technology - Word, email, the internet - that allowed leverage to scale. The question now is whether technology shrinks it back down again.

What won’t change is that equity partners are owners with client followings or irreplaceable niche skills. How they design their businesses around that is up to them. He wonders how many partners are actually having that conversation, versus how many are simply behaving as if this is the way it always was.

Cognitive surrender and the risk of getting dumber

Richard raises a concern he calls cognitive outsourcing. He shares a recent experience where ChatGPT confidently told him that a type of AI plugin didn’t exist - and nearly convinced him, until he pushed back and the model admitted it was wrong. He’s seen it with health questions too: the model assured him an edge case was extremely unlikely, and it turned out to be the correct diagnosis.

The danger, he says, isn’t just hallucination. It’s that when AI tries to be clever, it leads you down the wrong street entirely. And if people - or governments - outsource their thinking to systems that aren’t good enough yet, the consequences could be severe.

What’s next

Richard plans to keep Artificial Lawyer going for at least another twenty years. He can’t wait to see what legal tech looks like then. The Legal Innovators events are expanding - London, Paris, New York, California, which he calls the perfume bottle lineup. And he’s quietly launched The Robot Times, covering the intersection of robotics, business, and law, because he believes the robotics industry will become huge in the next decade and will need its own specialist legal ecosystem.

Through it all, the thread is the same one that started in the Black Country: how do complex systems change? He’s been watching this one for a decade, and he thinks we’re finally passing through a gate into something new.

Final Note: Turing & Partners, an AI Law Firm (in 2016)

In preparing for this discussion, I stumbled upon this post from 2016 about an AI law firm. I did a double-take when I saw the date!

Turing & Partners, an AI Law Firm

* Driverless cars

* AI-powered law firms (heard that term recently)

* New leverage models

* Big data centre developments

Links

* Artificial Lawyer

* The Robot Times

* Legal Innovators events (London, Paris, New York, California)

* Follow Richard on LinkedIn

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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

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

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

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

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