Fiona Phillips on How to Change the Law

Descripción

When I sit down with Fiona Phillips, Anthropic has just announced that it won’t be releasing its Mythos model - at least not yet - because of the cybersecurity implications of a system that appears uniquely capable of finding and exploiting software vulnerabilities. Talk about good timing for a podcast with a leading expert on cybersecurity. But before we get to that, let’s talk about Fiona’s story, which starts a long way from cybersecurity in the restructuring and insolvency team at a Magic Circle firm, six months before Lehman Brothers collapsed. She trained at Freshfields, with a six-month stint in The Hague doing arbitration during her training contract. She qualified into restructuring and insolvency, expecting, as she puts it, “a nice quiet corporate support team where I could hide from the really vicious transactional hours.” Then Lehman went down and everything changed. She spent the next stretch of her career working for the administrators of banks and building societies, going in on day one during the most tense period in UK banking history, picking apart what had gone wrong and figuring out how to fix it. It was fascinating work, but relentless. When HSBC offered her a move in-house, she took it, partly for the quality of life and partly because the bank was so international. She wanted to travel and live abroad, and HSBC delivered on both. A secondment to Dubai that was meant to last six months turned into four years. She ended up as general counsel for the retail bank across the Middle East and North Africa, dealing with financial crime, M&A across the region, and the complex politics of the Gulf. The HSBC digital journey In 2015, Fiona moved to Hong Kong, HSBC’s spiritual home. She tells me that if you get in a taxi in Hong Kong and say “take me to the bank,” you’ll end up at HSBC. She joined the executive committee for the retail and private banks and the team embarked on a serious digital transformation. The fear at the time was fintechs. Incumbent banks were watching startups build better, faster, more intuitive products, and wondering whether the ground beneath them was about to give way. It’s a dynamic that will sound very familiar to anyone watching legal right now. HSBC’s response was to go and learn. The exco travelled to Silicon Valley, to China, to Southeast Asia, spending time with big tech companies and innovators. They recruited people from completely different industries. They experimented. They put a team in a WeWork and said: if you were going to disrupt us, what would you build? The lesson, Fiona says, was about giving people inside a big organisation different rules to play by, creating the right environment for experimentation within a business that was built for stability. As a lawyer watching all of this, she couldn’t help wondering how the same thinking might apply to the legal function. So they tried. And then Fiona became, as she puts it, “really obsessed” with legal design. Legal tech is the new fintech When we talk about what law can learn from what happened in banking, Fiona draws a sharp parallel but also flags a crucial difference. In banking, the fintechs discovered that becoming a bank is hard. Capital requirements, regulatory burden, and consumer expectations around safety and stability all acted as barriers. That’s why the big banks survived. They digitalised fast enough, and the moats held. In law, those moats may not exist. It’s much easier to become a law firm than a bank. The barriers to entry are low. And clients may not care about the stability and heritage of a big firm if they can get what they need from a tech-enabled alternative. Law, Fiona suggests, may be significantly easier to disrupt than banking was. The one thing the banking experience made crystal clear, she says, is that you have to obsess about the customer’s point of view. “You have to stop thinking that a customer wants a mortgage. They don’t want a mortgage, they want a house.” The same logic applies to law. Nobody wants a conveyancing lawyer, she says. They want a house. The legal work should be seamless, frictionless, and invisible. If AI-native firms can build that experience from scratch rather than trying to retrofit it onto traditional models, she thinks they may have a genuine structural advantage. Kill the memo This leads us to legal design, which Fiona describes simply as making sure that when you deliver a product or service to a client, it’s designed from the beginning for their needs, not yours. She gives a pointed example. She’s been drafting an AI policy for a client. Most templates she’s seen start with definitions, because they’re written by lawyers for lawyers. Nobody, she says, has ever opened a document as a normal person and thought: what I’d really like first is a dense legal definition. And most AI policies she’s seen are either aggressive or patronising in tone, full of prohibitions and warnings, when what users actually need is clear, practical guidance on a handful of questions. Can I use this tool? What data can I put in? Has the client consented? How do I check the output? She thinks the legal profession has a deep problem with this. Lawyers don’t think of what they do as a product. They think they give advice. Products feel cheap, beneath them. But if you launched a product in banking or cosmetics, you’d never release it without testing it on users first. The legal profession has, by and large, a complete absence of that kind of testing. And she’s clear-eyed about the difficulty: making something simple is deceptively hard. Lawyers see a well-designed document and think it looks easy. Actually, she says, getting to simple is a real art, and getting lawyers to respect that is one of the biggest challenges she faces. At one point in our conversation, we joke about launching KillTheMemo.com. She’s in. I think she’s only half joking. Back in private practice After years in-house, Fiona had what she describes as a reflective moment. She went and shadowed a criminal judge for a while. She’d originally wanted to be a criminal barrister and never did, and she wanted to ask herself a basic question: did she still want to be a lawyer? The answer was yes. She believes in the rule of law. She believes in the power of the law. But she also knew she wanted to be at the cutting edge of where technology was evolving, and she needed to be somewhere that the ethical dimension mattered, somewhere she could say to clients “I don’t think you should do this, even if it’s legal.” She found that at Marks and Clerk, a 130-year-old IP firm. What drew her in was the people. Patent attorneys, she points out, are the inverse of the usual dynamic: they’re technologists and scientists who became lawyers, rather than the other way around. “It’s kind of the perfect lawyer, in my view.” The firm works at the cutting edge of invention: AI patents, semiconductors, electronics, space. One of her colleagues is on the shortlist to be the UK’s first astronaut. Within Marks and Clerk, she’s built a new subsidiary focused on cybersecurity, data, AI law, governance, and ethics, with a strong emphasis on education. She describes it as a startup inside a law firm. She doesn’t think she’d have gone back to private practice for traditional transactional work. But she found a place where she can practise law in a way that makes her passionate and lets her build things. The Anthropic question The Glasswing announcement has led to a busy week. She tells me the defenders of companies and governments from cyber attacks are in a constant race with criminals, and the criminals have a structural advantage: they don’t have to comply with any law, go through compliance checks, or worry about whose data they’re using. What Anthropic has said, in essence, is that it has built a model that could be transformative for cyber defence, but devastating if it fell into the wrong hands. Fiona’s question is about who gets to set the red lines. She thinks it’s admirable that Anthropic has drawn them. But in a functioning democratic society, she asks, should it really be a private company that determines what the government can and can’t do with AI? These companies can enforce limits because they control the tools. But is that how it should work? She’s not arguing against Anthropic’s decision. She’s arguing that we haven’t built the democratic infrastructure to handle decisions of this magnitude. Regulation is not the enemy Fiona pushes back on the common argument that regulation kills innovation. She doesn’t buy it, though she’s thoughtful about proportionality. The question, she says, is whether the most powerful AI models are the equivalent of nuclear technology: capable of enormous good, capable of enormous harm, and therefore requiring intergovernmental rules and collaboration, not just one country’s framework. That top tier of AI, the systems that could orchestrate large-scale cyber attacks, probably warrants that level of seriousness. Your contract review tool does not. In the meantime, she thinks companies should stop waiting for legislation and start self-regulating on substance, not just process. She’s frustrated by the responsible AI conversation as it currently exists, which she sees as too focused on frameworks and tick-box compliance. She wants companies to take positions: what will you ban? What will you never do? What’s your stance on emotional recognition AI? On AI in HR? On recording every call with a transcription tool? And she makes a powerful point about existing law. Tort law already provides duties of care that could apply to AI harms. In the absence of legislation, she expects to see a lot more litigation. It’s already happening in the US, with cases involving children harmed by chatbot interactions and bias in hiring tools. The education gap Underpinning everything is what Fiona sees as a massive education problem. It’s not just judges who don’t understand the technology. Many AI vendors can’t clearly explain how their own tools handle data. Companies don’t understand the true value or true risk of their data. Senior executives can’t articulate how their organisations use it. In a world where AI governance is becoming critical, she worries about a repeat of what happened with GDPR: a compliance exercise that generated paperwork without generating understanding. She and her colleague Eleanor, Marks and Clerk’s data partner, are trying to change this by building educational programmes for in-house lawyers. The goal is about helping people ask the right questions. When someone says “let’s talk about data,” are they talking about prompts, training data, outputs, or something else entirely? Until people can make those distinctions, she says, governance will remain surface-level. Final note Fiona Phillips has built a career that most lawyers wouldn’t have the nerve or the curiosity to attempt: Magic Circle to banking to the Middle East to Hong Kong to a startup inside a 130-year-old patent firm. She’s done insolvency, financial crime, digital transformation, legal design, and cybersecurity. What comes through most clearly in our conversation is a combination of moral seriousness and creative restlessness. She genuinely believes that lawyers have a responsibility to tell clients not just what’s legal, but what’s right. And she thinks the profession’s resistance to rethinking how it delivers its work, from the 30-page memo to the definition-first policy document, is both a failure of imagination and a disservice to clients. She closes our conversation with a line from Ernest Shackleton, borrowed via Jacinda Ardern: optimism is true moral courage. It’s brave to stay optimistic, she says. But if we don’t, what else have we got? 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 [https://www.agents.law?utm_medium=podcast&utm_campaign=CTA_1]

TED and the Future of the Lawyer

I meet Nishat Ruiter, GC at TED, the world's most influential ideas platform, and learn how TED Law is asking us to question what it means to be a lawyer. What we cover * How TED grew from a conference to become the world’s #1 ideas platform. * Nishat’s unconventional path, via the Netherlands, the Brooklyn family court, and the self-taught IP licensing work that helped launch her GC career. * How organising a local TEDx event gave Nishat a deep understanding of TED’s mission before she ever joined the organisation. * What TED looks like behind the scenes, from the main conference to TEDx, TED-Ed, podcasts, partnerships, licensing, translation and global community-building. * Why Nishat launched TED Law, and what she thinks legal education misses around judgment, professional identity, cultural competence, collaboration and moral courage. * How you can get involved in TED Law (that includes law firms, in-house teams and tech companies). Meet Nishat When I catch up with Nishat Ruiter, it has only been a few weeks since the latest TED conference in Vancouver. The conference itself is over, which sounds like a natural moment to come up for air, but TED is really a year-round organisation of talks, TEDx communities, podcasts, partnerships, education programmes, licences, brand questions, rights questions, publication decisions and all the legal work that has to happen to make sure ideas can safely reach the world and have the maximum impact. Nishat sees that world from an unusual seat. She gets the force of the talks, the audience energy, the spectacle and the sense of possibility, while also leading the back-office legal review that makes the public version possible. A TED Talk may look effortless by the time it reaches the stage or the internet, but behind it sit questions about rights, privacy, defamation, intellectual property, accuracy, context and reputation. That is part of what makes her role so interesting: she is protecting ideas without wanting to smother them. The bigger question in our conversation is what happens when you apply TED’s vision of “Ideas change everything” to the world of law. TED is built around curiosity, clarity, public communication and the belief that a well-framed idea can move people. Law, at its best, is built around judgment, service, justice and the structures that allow human beings to cooperate. Yet the profession has often taught lawyers the rules far more deliberately than it has taught them how to carry those rules into leadership, crisis, culture, technology and moral choice. TED Law is Nishat’s attempt to address that gap. From Dracula to Brooklyn family court Nishat did not grow up with a plan to become a lawyer. Her first love was theatre. In high school, she acted seriously enough to play the lead in Dracula, which I point out should definitely be on her LinkedIn profile. She was drawn to the empathy of acting: understanding a character, getting under the surface, working out why someone acts as they do. A high school director then gave her a blunt assessment of the acting world. If she wanted to pursue it, she should understand the reality of the industry: she was not white, she was not blonde, and she would not fit easily into the box. It was a hard thing to hear, and it became one of the early experiences behind a theme that runs through her career: finding herself outside the expected shape and then building from there. Law arrived almost sideways. In college, she took a course on the legal and social environment of business. The professor posed a simple hypothetical: a student slips on a banana peel at a university. Who is responsible? Everyone wanted to defend the student. Nishat raised her hand to defend the university, less because she had some sophisticated view of liability and more because she was excited by the less obvious side of the argument. She liked the reasoning, the exploration, the challenge of working out the answer. That instinct took her to law school, where she initially imagined a career in international human rights and justice. After graduating, she spent time in the Netherlands, where her husband is from, and explored international work. But law school loans and practical realities eventually pulled her back to the United States. When she returned, she did what many young lawyers do: she applied for what was open. One of those openings was in family law. She worked for a sole practitioner in Brooklyn for two and a half years and saw, up close, the human pressure of matrimonial litigation. Custody. Support. Divorce. Lives being rearranged in courtrooms that had far too many cases and far too little time. At one point, she says, a judge might have 120 cases on the docket and two minutes to hear yours. The work mattered enormously, but the system around it could feel too arbitrary for questions that were so consequential. So she moved back toward intellectual property and technology. This was the dot-com era, before anyone could ask ChatGPT how to become a software contracts lawyer. Nishat went to Barnes & Noble, read everything she could find, and built herself a three-ring binder full of software licensing contracts. When she interviewed for a contracts manager role and they said they were looking for someone with templates, she had them. Then she made the obvious legal career move: if she was going to be the only legal person, perhaps she should be general counsel. That is a very Nishat story. She sees the gap, does the work, builds the thing and then makes it happen. Thanks for reading Agents.law! Subscribe for free to receive new posts and support my work. Finding TED before TED found her Before TED, Nishat built a career across IP, fintech, software, legal tech and a decade as associate general counsel at CA Technologies. The bridge into TED, though, began in Hillsborough, New Jersey, where she and her husband had chosen to live for practical reasons: schools, work, family life. They also cared deeply about community. Her husband is Dutch. Nishat is Pakistani. Between Dutch bluntness and Pakistani directness, she says, there was no shortage of intense discussion at home, but there was also a shared global outlook and an interest in ideas that could bring people together. Nishat was serving on the township library board and felt that the community could do more to surface meaningful ideas. TED had already been part of their family life. Her husband was an early fan, and they would introduce high school students to TED Talks. So they organised a TEDx event through the library. That meant finding speakers, shaping talks, dealing with the intellectual property, building the event and learning what TED actually requires of a local community. It took six months. She did it without any thought that she would one day work for TED, but it gave her a lived understanding of the brand, the mission and what happens when TED’s global idea is translated into a local setting. Then, during a career shift, the pieces came together. Nishat had just accepted a new role in New Jersey. Her children were in high school. She was tired of commuting into New York and wanted to be more present at home. Around the same time, a friend who had recently joined TED in video and TED Talks asked about her work. At the time, TED had no in-house lawyer. Outside firms helped with some matters, but the publication of talks raised exactly the kinds of questions Nishat understood: IP licensing, defamation, privacy, rights, risk and the judgment needed to review content without flattening the idea behind it. She had already accepted another job, so when she sent over her resume she added the caveats: she had family constraints, she did not want a five-day-a-week New York commute, and the timing would be difficult. Chris Anderson wrote back the next day. Within a week, she had met with TED’s leadership and had an offer. It sounds almost too neat, but the fit makes sense. TED needed a lawyer who understood intellectual property and also understood why the ideas mattered. The platform behind the talks Most people know TED through the talks. For many of us, TED is still associated with the canonical talks that seemed to break through the early internet: Sir Ken Robinson on education and creativity, Hans Rosling on population and data, and countless others that made complicated ideas feel alive. But TED is much broader than the stage. It began in 1984 as a conference around technology, entertainment and design. Chris Anderson later helped turn it into a nonprofit and, in 2006, TED began putting talks online. The expectation was modest. Perhaps the talks would reach 100,000 views. They reached around a million in the first month, and TED became a way of bringing ideas to people wherever they were. That required production, publishing, translation, distribution, licensing, brand stewardship and, eventually, an enormous global community. TEDx was another leap. What began as a risky experiment in giving communities a free licence to convene around ideas has become something like 4,000 to 4,500 events around the world. Then there is TED-Ed, with its animated lessons created with teachers and artists. There are podcasts, partnerships, education programmes, the Audacious Project and the many other ways TED tries to make ideas travel. A small legal team supports all of that. Their job is to help TED stay true to itself while operating globally, across formats, partners, communities, rights systems and cultural contexts. It is harder than it looks, and it gives Nishat a useful vantage point on the difference between protecting an institution and preserving the spirit that made the institution worth protecting in the first place. AI and the purpose question We spoke, inevitably, about AI. TED has always been close to the frontier of technology; many of the people shaping what comes next have appeared on the TED stage early, sometimes before their ideas became mainstream. The most compelling use of AI, in her view, is the one that serves humanity: improving education, science, health, access and the ability of human beings to do more meaningful work. She points to global discussions about AI for humanity as the kind of framing that deserves more attention. That becomes the bridge to TED Law, because lawyers are facing the same problem in their own field. A technology that can change the mechanics of work forces a deeper question about the purpose of the work. If AI can draft, summarise, search, structure and increasingly act, the lawyer’s value has to move beyond information retrieval and formal rule application into judgment, courage, context, communication and the ability to make sense of human stakes. Why TED Law exists TED Law grew out of several pressures arriving at once. Some were legal and political. Nishat points to the overturning of major precedent in the United States, including Roe v. Wade, and the broader conversations that followed about rule of law, institutions and what lawyers are meant to do when foundational assumptions are tested. Some were professional. In conversations with general counsel, partners and legal leaders, she kept hearing the same unease: the skills lawyers were using in leadership were often different from the skills they had been taught in law school. Some of it was personal. Nishat remembers staying after class in law school because she wanted to ask why. She wanted to understand why a judge had decided a case in a particular way, what was happening in the community, what the broader context was, and what was going on in the world around the decision. Another strong student once stayed behind too, then asked the professor whether any of that context would be tested. The answer was no. It was just context. The student left. For Nishat, that moment captured something important about legal education. The profession teaches lawyers to read, extract, repeat and advocate. It is less consistent in teaching them to connect law to values, identity, culture, judgment, leadership and courage. That may be manageable in parts of legal practice, but it becomes a serious gap once lawyers move into leadership roles and face moral questions, crisis decisions, compliance failures, rule-breaking, political pressure and business demands. At that point, lawyers sometimes have to push back on the very people they advise. They have to represent an organisation while retaining their own professional judgment. Substantive law still matters, obviously. But Nishat’s point is that it no longer carries the whole burden. TED Law is built around capabilities the profession needs to teach more deliberately: professional identity, critical thinking, cultural competence, intuitive collaboration and the ability to work effectively with AI. The result is a curriculum of roughly 15 to 18 hours, built to pair TED’s ability to open up a subject with the legal rigour needed to examine it properly. The work has been tested against the profession rather than designed from a private theory of what lawyers need. TED Law surveyed law schools, general counsel, managing partners, law students and lawyers across countries. It set up advisory councils. It looked at regulatory changes, including ABA developments around professional identity, client interaction and cultural competence. The gaps Nishat had identified were already showing up in the profession’s own requirements. Teaching lawyers without another terrible slide deck Anyone who has sat through enough legal training will understand part of the problem. Lawyers are cynical and sceptical audiences, and many CLE-style sessions invite exactly that response: dense slides, tiny font, rules read from the screen, and a few seconds at the end for questions so the box can be ticked. You leave with the materials and the credit, but rarely with a changed view of the work. TED’s method gives Nishat a different tool. A talk can change the room. It can lower the guard, create emotional entry and move lawyers from defensiveness into curiosity. From there, you can have a serious legal discussion: a case study, a conversation about ethics, AI, culture, judgment, practice readiness or professional identity. The inspiration is not the whole lesson; it is the opening that lets the lesson breathe. That may sound soft to some lawyers, but the wellbeing data tells a harder story. Nishat is direct about the fact that lawyers experience suicide ideation at around four times the rate of other professions, alongside higher levels of alcohol abuse and drug abuse. Research also suggests that the things that make lawyers feel fulfilled are autonomy, relationships and meaning rather than prestige, rank or power. The legal profession has spent a long time optimising for markers that do not necessarily make lawyers better, healthier or more useful. TED Law asks a different set of questions: why did you come to law in the first place? What did you write in your law school application essay? Was it really about money, status and golden handcuffs, or was there once an idea about justice, service, purpose and doing something useful with a powerful set of skills? The AI-age lawyer All of this has become more urgent because of AI. ChatGPT became publicly available in late 2022, and in the short period since then the legal industry has moved from basic experimentation to agentic AI, automation, workflow redesign and increasingly serious questions about what legal jobs will look like. None of us knows exactly what the profession will look like in two or three years. That uncertainty changes the education question. If the rules, tools and job categories of the near future are still forming, the foundations have to carry more weight: critical thinking, collaboration, creativity, cultural competence, multidisciplinary judgment, moral imagination and the ability to use AI without surrendering human responsibility to it. Nishat is interested in something deeper than skills training. She wants lawyers to examine their role in society and reach for a better version of the profession’s potential. If lawyers do not understand human beings, she asks, how are they supposed to help build the structures that protect them? An incubator with serious ambition TED Law is still in incubator stage, which is an important distinction. The work is being built, tested, refined and rolled out carefully. People can sign up for updates through TED’s legal newsletter at ted.com/law, and Nishat is actively inviting input through surveys and community conversations. There are already concrete paths in motion. TED Law is working with the ACC Foundation, the nonprofit arm of the Association of Corporate Counsel, to bring training to in-house lawyers. It is also working with the American Bar Association, including an in-person training in Chicago in July. Nishat wants lawyers everywhere to understand their professional values and identity, think critically, collaborate intuitively, operate across cultures and use AI effectively. Whether TED Law becomes the vehicle for all of that is secondary to the impact she wants to see. She also wants to change the way society sees lawyers. The old Shakespeare line about killing all the lawyers is usually treated as a joke at the profession’s expense. Nishat points out it actually had a different meaning: remove lawyers and you remove a mechanism for addressing injustice. That is the role she wants lawyers to recover. Final note What struck me most about Nishat is that TED Law feels like the convergence of the whole story. The theatre student who learned to inhabit a character; the young woman told she did not fit the box; the law student who wanted to know why; the Brooklyn family lawyer who saw the human cost of an overstretched system; the IP lawyer who built herself a binder because nobody was going to hand her the answer; the community organiser who brought TEDx to her town; the general counsel who understands that ideas need support. The project is still young, and Nishat would be the first to say it is being built with others: four advisory councils, law schools, GCs, law firms, students, professional bodies and lawyers who know something is missing even if they have not always had the language for it. But the central idea is already clear. The future of law will require lawyers who know what they stand for, understand the people they serve and can build with technology without forgetting why the work matters. That is a big idea, and TED is a fitting home for it. Resources * Sign up for the TED Law newsletter [https://www.ted.com/law] * Sir Ken Robinson and the best TED Talk ever (in my opinion!) [https://www.ted.com/talks/sir_ken_robinson_do_schools_kill_creativity?hsa_acc=7777130675&hsa_cam=218945593&hsa_grp=17379703273&hsa_ad=295607643496&hsa_src=g&hsa_tgt=kwd-16365900407&hsa_kw=best+ted+talks&hsa_mt=b&hsa_net=adwords&hsa_ver=3&gad_source=1&gad_campaignid=218945593] * Follow Nishat on LinkedIn [https://www.linkedin.com/in/nishat-ruiter-1a21362] 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 [https://www.agents.law?utm_medium=podcast&utm_campaign=CTA_1]

4 de jun de 202654 min

Lessons from 40 Years of Building Agents

Dazza Greenwood has been building agents for longer than several legal tech founders have been alive. In the 1980s, as an undergraduate computer science student, he encountered AI assistants for the first time. His module introduced a then-new paradigm: human language, chat-based systems. The exercise was to build something modelled on ELIZA, the MIT chatbot whose therapist module ran on a simple heuristic. Find the keyword. Reflect it back to the user. When in doubt, tie it all back to the user’s parents. It was deterministic, a little absurd, and wildly popular with the people who tried it. Dazza learned some tricks and came away with a fascination with what AI was, and more importantly, what it could be. Note: Some of the concepts in this episode may be unfamiliar to some listeners. We cover them in the technical explainer at the end. What followed was a career which has spanned dozens of initiatives around the world. Let’s just say that Dazza has worn (and continues to wear) a lot of hats. Legislative aide. Candidate for office. In-house Technology Counsel to the Commonwealth of Massachusetts (which by the way he notes would be a Fortune 50 company if it were private). Standards architect. Stanford researcher. Platform builder. He went to law school, he tells me, because he kept getting different answers from different lawyers to the same question and found it unacceptable. After years of practice, he still does not have a fully satisfactory answer to “what is the law?” but he at least knows how to find the relevant law himself, which was enough to let him return to technology without feeling incomplete. He was doing legal tech, he says, before anyone called it that. Writing scripts to automate his work. Treating legal documents as data - to the extreme displeasure of colleagues who just wanted Microsoft Word (why is it always Word?) Why didn’t the standard stick? In the early 2000s, Dazza was one of the architects of LegalXML, an effort to create an international standard for marking up legal documents so they could be treated as structured data. He ran the e-contracts group. It took seven years to reach the status of a recognised international standard. It attracted a small community of who he describes as lawyer-geeks who marked up their contracts in XML, built clause libraries, and imagined a future of genuinely interoperable electronic contracting. It did not really arrive, at least not in the way the group expected. A handful of vendors adopted the standard, mostly for workflows they were already running. The broader transformation never came. The lesson Dazza draws from it is that the obstacle was never the standard. It was the culture. The love affair with Microsoft Word was not something a well-designed schema could fix. Standards, he says, have to arrive at the right moment. Too early and the industry is not ready. Too late and people have already locked into whatever is there. The good news is, the moment has now arrived, and it came from a different direction entirely. Large language models can peer into the meaning of a legal instrument and address it as data without anyone having to tag a single element. Lawyers, it turns out, are naturally good at the lingua franca of LLMs: precise language, conditional logic, sub-clauses, if-but-not-that constructions. The standard that nobody could agree on turned out to be language itself. Is your agent loyal to you? Dazza has just finished a research sprint at Stanford’s Digital Economy Lab on a project called Loyal Agents, run jointly with the Consumer Reports Innovation Lab. The question it asks is simple and the implications are not: when an AI agent conducts transactions on your behalf, what legal framework governs whether it is actually acting in your interest? His answer keeps returning to fiduciary duty, and specifically to a US federal case called Kovel that almost nobody in legal AI is talking about. Kovel itself is sixty years old. It involved an accountant working with a tax law firm whose communications with a client became the subject of a grand jury subpoena. The Second Circuit held that the privilege extended to the accountant because he was acting as the lawyer’s agent in providing legal advice. The principle that emerges, Dazza argues, applies directly to modern AI vendors. To protect attorney-client privilege when a SaaS provider is handling client communications on behalf of a lawyer, that provider needs to be the lawyer’s agent in the legal sense. Most enterprise AI contracts disclaim exactly that. Dazza has read them all. He has built a public breakdown of what each of the major frontier model providers actually says in their enterprise terms about confidentiality and agency. See Links below. The most upvoted question at Anthropic’s recent legal webinar, which drew over 20,000 registrations, was about how to handle privilege when using general purpose AI tools. Dazza thinks the profession is looking for the answer in the wrong places. The technical controls matter. Zero data retention matters. But the legal layer, the contract clause that says we are your agent, is what Kovel’s logic requires, and most providers do not offer it. His pitch to the frontier model providers is direct: stop disclaiming agency and start defining it. Write a narrow, limited agency clause. Be your client’s agent for three specific things and disclaim it for everything else. It contains risk rather than expanding it, it supports privilege, and for providers building agentic products, it simply reflects reality. If a human did what these systems do, it would be an agent. In Dazza’s opinion, the contract should say so. The platform nobody has built yet Six months ago, Dazza started building something called Interlateral. The felt need behind it is something he has observed sitting in meetings in San Francisco with startup and innovation teams where everyone has agents running quietly in the background, and then communicating with each other through the narrow human-to-human channels of Slack and email, as if the agents are not there. Interlateral is a shared collaboration space where humans and their agents can work together in the same room. You bring your agents. He brings his. There is a third space where they can interact, collaborate, and co-work, with a shared markdown surface that both humans and agents can read and write into. The design principle is human-centred: a person is always at the wheel. The agents are extended cognition, not autonomous actors. The first event ran at Stanford last week with 60 lawyers and eight teams, and the next is at MIT. Eventually, Dazza wants tens of thousands of participants. He thinks the combination of people and agents in a shared space is a genuinely new source of collective intelligence, and that we have barely started to understand what it can produce. There is a harder problem underneath it. In Google Docs or Slack, identity is straightforward. You can see who wrote what. In a space where agents are acting on behalf of humans, you now have two levels of separation from the person you think you are dealing with. Agent identity and attribution, knowing whose agent it is and holding humans accountable for what their agents do, is a bleeding-edge question the industry has not yet solved. How he builds with agents At the end of our conversation, Dazza pulls up his GitHub repo and walks me through how he actually works. The interlateral_agents repo is open source, the product of years of slow tuning, and it is more architecturally interesting than most people’s agent setups. He runs three models in parallel: Claude Code, Codex, and Gemini, with Grok CLI from xAI expected to join shortly. What makes it unusual is the communications layer. The agents share what he calls a multiplexing comms hub, a setup that lets them read each other’s outputs and write into each other’s terminals directly. He describes it as a Vulcan mind meld. One agent can see that another tried something, that it failed, and suggest an alternative approach. The collaboration is explicit and adaptive rather than just running tasks in sequence. On top of that he uses skills: lightweight prompt-level definitions that tell the agents how to organise their work on a given task. He can arrange them hierarchically, with one agent orchestrating the others, or as peers collaborating on the same problem. The skills determine the shape of the collaboration without requiring complex infrastructure to enforce it. It is, he says, a surprisingly low-key way to get a lot out of very capable but very different models working together. What is the AI-native organisation? I ask Dazza what he thinks people are underestimating. The current pattern, he says, is that AI creates extraordinary efficiency at discrete points in a workflow and then causes congestion at the parts downstream that have not changed. Contract review is faster. The humans waiting for the output of contract review are not. The clog forms between the transformed part and the untransformed part, and it is going to get worse before anyone fixes it. The AI-native organisation is one that has redesigned itself around AI, touching pricing models, staffing, role definitions, and quality control, which starts to look less like a periodic event and more like continuous monitoring. That redesign, he says, is not premature. It is coming whether organisations are ready for it or not. The ones doing the mapping exercise now, looking holistically at the full lifecycle of a matter rather than optimising individual tasks, are the ones who will navigate it gracefully. The ones waiting are storing up a serious problem. Final note Dazza Greenwood is genuinely hard to keep track of. In preparing for this conversation I found Stanford research, open source repositories, consulting work, a platform under active development. Dazza literally switched hats midway through our discussion. What surprises me most though is that none of it feels scattered. The dots (and hats) are actually very connected. It all connects back to the same conviction he has held since the start: that law and technology are not separate domains, that legal instruments are data, that agents will conduct transactions on behalf of humans and the frameworks governing that need to be built carefully. He has been pretty patient about this for forty years. The future, he says, has finally arrived. And he seems genuinely delighted about it. Links * dazzagreenwood.com [https://dazzagreenwood.com], Dazza’s blog including his upcoming open source model comparison table * computationallaw.org [https://computationallaw.org], Dazza’s write-up of the Stanford Interlateral event * interlateral.com [https://interlateral.com], sign up to attend a future event * civics.com [https://www.civics.com/]to understand more about Dazza’s consulting work * loyalagents.org [https://loyalagents.org], the Stanford and Consumer Reports research and vendor contract analysis, including the Kovel breakdown * analysis on when agency is a feature not a bug [https://loyalagents.github.io/loyal-agent-evals/report/#2-3-2-when-agency-is-a-feature-not-a-bug-the-kovel-pattern-in-legal-tech-saas] * github.com/dazzaji/interlateral_agents [https://github.com/dazzaji/interlateral_agents], the open source agent library Dazza uses to build with Claude Code, Codex, and Gemini The Technical Stuff Here’s a quick primer on some concepts that may be unfamiliar to some: Evals Short for evaluations. A structured way of testing whether an AI system is doing what you want it to do, consistently and measurably. Dazza uses an open source platform he built to run evals on agent behaviour, putting numbers on whether an agent is acting in a user’s interest or getting tripped up by a conflict it has not recognised. Think of it as quality control, but for AI decision-making. Fiduciary duty A legal obligation to act in someone else’s best interest rather than your own. It applies to lawyers, financial advisors, and other professionals. Dazza’s Loyal Agents research asks whether AI agents should be held to something similar, and whether the contracts governing AI services currently reflect that expectation. Most do not. Kovel A 1961 Second Circuit case that Dazza thinks is the missing piece of most privilege discussions in legal AI. United States v. Kovel involved an accountant employed by a tax law firm whose communications with a client became the subject of a grand jury subpoena. The court held that the attorney-client privilege extended to the accountant because he was acting as the lawyer’s agent in providing legal advice. The principle Dazza extracts: for privilege to hold when a SaaS provider handles client communications on a lawyer’s behalf, that provider needs to be the lawyer’s agent in the same legal sense. Most AI vendor contracts disclaim agency explicitly. Dazza argues this is both a legal risk and a fixable problem, and that providers who address it will have a commercial advantage in the legal market. Multiplexing A communications technique that allows multiple signals to share the same channel. In the context of Dazza’s agent setup, it means his agents can read each other’s outputs and write into each other’s terminals in real time, rather than operating in isolation. The result is agents that can observe what the others are doing, flag when something is not working, and adapt accordingly. Skills In the context of agent configuration, skills are lightweight prompt-level instructions that define how an agent should approach a task or how a group of agents should organise their work together. They are not code in the traditional sense. They sit closer to a well-written practice note. Anthropic has its own Skills framework, which we have covered separately on agents.law. Loyal Agents Both the name of the joint Stanford Digital Economy Lab and Consumer Reports Innovation Lab research project Dazza works on, and a broader concept: the idea that AI agents conducting transactions on behalf of users should be demonstrably aligned with those users’ interests, in a way that is measurable, contractually grounded, and legally enforceable. The research has produced evals for testing agent loyalty and a public analysis of how major AI providers currently handle the relevant contract terms. 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 [https://www.agents.law?utm_medium=podcast&utm_campaign=CTA_1]

26 de abr de 20261 h 5 min

Fiona Phillips on How to Change the Law

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