(How to Create a Claude Skill or Plugin for Law and Use It in Claude Cowork)

On February 3, 2026, a single product announcement from Anthropic wiped approximately $285 billion in market capitalization off the stock market in a single trading day. Thomson Reuters dropped 16%. LegalZoom cratered nearly 20%. RELX, the parent company of LexisNexis, fell 14%. Wolters Kluwer lost 13%. The London Stock Exchange Group plunged 8%. The contagion spread to Salesforce, ServiceNow, FactSet, and dozens of other enterprise software companies. Bloomberg called it a “$285 billion rout.” Analysts started calling it the “SaaSpocalypse.”

The catalyst? Anthropic released a set of open-source plugins for its Claude Cowork tool. One of them was a legal plugin that could review contracts, flag risks, triage NDAs, and track compliance. Investors took one look and decided the entire SaaS business model was cooked.

Here’s the part that still gets me: the legal skill at the core of this market panic is, at its heart, a structured markdown file. We’re talking about roughly 250 lines of well-organized pseudo-code, plain text instructions that tell Claude how to think about legal workflows. No compiled binaries. No proprietary algorithms. No infrastructure. Just markdown. And it’s included in the $20/month Claude Pro subscription. That’s less than most attorneys spend on lunch. The full Business Insider breakdown of the stock carnage is here: https://www.businessinsider.com/anthropic-cowork-legal-plugin-publishing-stocks-legalzoom-thomson-reuters-relx-2026-2

So What Are Claude Skills & Plugins, Exactly?

A Claude Skills are a set of instructions, typically written in markdown, that teaches Claude how to approach a specific domain or task in a repeatable, structured way. Think of it as giving Claude a playbook. Instead of prompting from scratch every time you need a contract reviewed or a compliance check run, you write the instructions once, and Claude follows them consistently. Skills include things like domain knowledge (“here’s how our firm handles risk assessment”), step-by-step workflows (“when reviewing an NDA, check these clauses in this order”), and output formatting (“flag issues as green/yellow/red with recommended language”). They’re stored as plain files, organized in folders, and loaded automatically when relevant.  Claude Plugins are a bundle that packages one or more skills together with slash commands, MCP connectors, and sub-agents into a single installable unit, while a skill is just a standalone markdown file that teaches Claude how to handle a specific task or domain.

The important thing to understand is that you don’t have to write these from scratch. You can work with Claude itself to build skills and plugins. Describe what you want the workflow to do, what your firm’s processes look like, what outputs you need, and Claude will help you draft, test, and refine the skill. Anthropic has also open-sourced eleven starter plugins on GitHub (https://github.com/anthropics/knowledge-work-plugins/tree/main/legal) that you can customize. The barrier to entry here is remarkably low. If you can write a clear memo, you can write a skill.

Now Let’s Talk About Claude Cowork

Claude Cowork is Anthropic’s desktop tool that takes Claude out of the chat window and puts it to work on your actual files. You point it at a folder on your computer, give it a task, and it plans, executes, and iterates through multi-step workflows on its own. It can read documents, create new files, delete files, organize folders, and coordinate multiple workstreams. If you’ve used Claude Code (the developer-facing terminal tool), Cowork is the same engine with a friendlier interface. It’s essentially Claude Code for laptop professionals who don’t want to learn code.  It is currently only available in iOS but Claude recently launched the Claude app for PC, so we’re hopeful to see them in that soon.

What makes Cowork interesting for legal professionals is that it doesn’t just respond to one prompt at a time. You set a goal, and Claude works through it like a (very fast, very thorough) junior associate. It asks for clarification when it needs it, saves outputs directly to your file system, and loops you in on its progress. The plugin system takes this further: install a legal plugin, and Cowork immediately knows your firm’s preferred tone, your risk tolerances, your clause library, and your review workflow, what files to reference as template, etc. It’s a configurable work environment; no more cutting and pasting required.

One more thing worth noting, because I think it says something profound about where we are: Cowork was built entirely by Claude Code in approximately 10 days. An AI coding agent built its own non-technical sibling, and that sibling then crashed the legal tech market. 2026 is going to be wild.

Practical Examples: Skills for Lawyers and Legal Academics

Enough theory; let’s build something. Below are four practical examples, two for practicing attorneys and two for legal academics, showing how you could combine Claude Skills and Cowork to create custom workflows. Each example includes the actual markdown you’d use to create the skill.  Markdown is still human-readable, it just gives useful formatting to the text for an LLM.  Basically, any complex prompting I do these days is in markdown.

For Lawyers

  1. Client Intake and Conflict Check Workflow

Continue Reading How to Crash the Legal Tech Market

A fresh Anthropic announcement set off a week of market jitters and existential questions: what happens when the big model shops ship “legal productivity” features and the public markets flinch. This week, we bring Otto von Zastrow back for a rapid-response conversation, with a front-row view from New York and a blunt take: software grows cheaper to reproduce, so value migrates. The discussion lands on a key distinction, interface versus data, and why the old guard still holds leverage even as new entrants sprint.

From there, the conversation zooms in on “systems of record” and the uneasy truth that the safest vault often loses mindshare when a new interface sits on top. Otto points to email, calendar, SharePoint, DMS platforms, and the growing power of a single chat workspace to become the place where work happens. The hosts press on a critical nuance for lawyers: legal research data is not flat, and “good law” demands hierarchy, treatment, and reliable citation context, not a pile of cases plus vibes.

Otto frames Midpage.ai as a data company first, built on continuous court ingestion plus normalization that used to demand armies of editors. He argues AI turns messy inputs into structured repositories at a scale that favors speed and breadth, yet accuracy still requires process design and verification loops. Greg sharpens the point for litigators: the bar is not clever answers, the bar is defensible citations, negative treatment, and confidence that the record matches reality. Otto agrees on the need for trust, then flips the lens: many annotation tasks look like grind work where modern models, paired with strong QA, start to outperform large manual pipelines.

The headline feature is integration via Model Context Protocol, described as a USB-C style connector for tools and models. Midpage chose distribution inside Claude and ChatGPT rather than forcing lawyers into yet another standalone site. Otto explains the wager: lawyers want fewer surfaces, and general chat platforms ship features at a pace no niche vendor matches alone, so the smart move is to meet users where daily work already lives. The demo story centers on research inside chat, with Midpage returning real case links and citations, then letting the user push deeper with uploads and follow-on tasks, while keeping verification one click away.

The back half turns to second-order effects: pricing, agent spend, and the rise of “vibe” work where professionals act more like managers of agent teams than sole authors of first drafts. Marlene raises governance and liability when internal DIY tools pop up outside formal review, and Otto predicts a pendulum toward professionalized deployment plus change management. The conversation closes on Midpage’s “holy grail” topic, citators and the case relationship graph, plus a clear-eyed forecast: standalone research websites shrink as a primary workspace, while research becomes groundwork performed by agents, with lawyers spending more time interrogating results than running searches.

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[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Midpage Goes Native: Legal Research Inside Claude and ChatGPT, with Otto von Zastrow

The promise of generative artificial intelligence (AI) in legal practice is seductive: speed up document review, contract drafting, legal research, and thereby shave down hours billed. Yet the reality for many law firms is different. A recent survey by the Association of Corporate Counsel (ACC) and Everlaw found that nearly 60% of in-house counsel reported

This week, we welcome back Tom Martin, CEO of LawDroid, to discuss his widely read “AI Law Professor” column for Thomson Reuters and his five-level roadmap for legal AI. Martin explains that the framework was inspired by a leaked OpenAI memo and aims to give legal professionals a clearer picture of AI’s trajectory. The five levels range from basic chatbots to fully AI-run organizations, with intermediate stages such as reasoners, agents, and innovators. According to Martin, while we are still in the early stages, the release of GPT-5 and its reasoning capabilities has accelerated progress toward higher levels, especially in the development of autonomous agents.

The conversation turns to the implications of GPT-5’s hybrid reasoning model, which combines inference with step-by-step reasoning to deliver more relevant answers. Martin sees this as a significant shift for the legal industry, moving beyond single-response chatbots toward sustained, goal-oriented AI. He predicts that while the technology for fully autonomous legal agents could be available within a year, widespread adoption in law firms and corporations will take closer to three years. However, with these advancements come ethical concerns. Martin outlines four principles for responsible AI agents: transparency, autonomy, reliability, and visibility, cautioning that AI’s knowledge is always bounded and potentially incomplete.

Reflecting on the legal industry’s pace of change since their last discussion, Martin notes that while some firms are sprinting to adopt AI, others may already be too late to catch up. He warns that professional services organizations must actively integrate AI to remain competitive. The discussion explores the potential for tech giants or AI companies to acquire major legal information providers, and Martin argues that the future lies in blending software, consulting, and education into a unified service model. This integrated approach, he believes, will be necessary for survival in a market where AI is capable of generating solutions without traditional software development cycles.

Beyond the legal tech roadmap, Martin shares insights from his teaching at Suffolk University Law School and his observations from producing the “Last Week in Legal AI” news series. He sees both opportunities and risks for the next generation of lawyers, particularly in acting as translators between AI systems and legal practice. The discussion touches on generational attitudes toward AI, with younger users showing both skepticism and heavy reliance on AI for personal and professional support. Martin also addresses societal concerns, from AI in mental health applications to job displacement, and stresses the importance of curating AI outputs with human judgment.

The episode wraps with Martin’s update on the American Legal Technology Awards, set for October 15 at Suffolk University Law School in Boston, which he describes as “the Oscars of legal tech.” When asked about the biggest challenge for the next few years, Martin points to the uncertainty of where professionals will fit in a rapidly shifting world. He envisions a possible new model that combines service, education, and software to deliver legal help at scale, but stresses that no one knows exactly how the future will unfold. His hope is that the AI-driven abundance ahead will be shared broadly, without excluding people from its benefits.

Links:

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[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Tom Martin on the Five Levels of Legal AI and What GPT-5 Means for the Future of Law

This week, we welcome longtime friend and legal tech veteran Ken Crutchfield, founder of Spring Forward Consulting. Ken brings his extensive experience from major legal information vendors like Thomson Reuters, Bloomberg, and Wolters Kluwer into a timely and candid discussion about the current phase of artificial intelligence in the legal industry. Comparing today’s generative AI surge to the American Industrial Revolution, Ken describes this moment as the “Wild West” era—full of promise, hype, overinvestment, and, critically, few rules.

Drawing historical parallels to railroads, oil barons, and steel magnates, Ken illustrates how unchecked growth and technological innovation can outpace regulation until market forces or policy catch up. He notes the resurgence of large-scale infrastructure investment, now not in steel or steam, but in compute power and data centers. Just as J.P. Morgan helped stabilize chaotic markets in the 19th century, Ken suggests today’s AI frontier needs a similar recalibration, and possibly new rules of engagement.

The conversation shifts toward the practical realities of legal tech adoption. Ken emphasizes that law firms’ expectations of perfection often collide with startups’ resource limitations. Vendors need to rethink how they engage with firms by building credibility, focusing on integration, and delivering actual use-case wins. Firms, in turn, must move beyond the billable hour mindset and consider new metrics like Return on Experience. Adoption is no longer optional, it’s strategic, competitive, and increasingly client-driven.

Ken also unpacks the looming implications of content rights and data ownership in the age of AI. If firms aren’t investing in data hygiene now, they risk being left behind when more sophisticated AI tools demand clean, structured, and secure datasets. AI isn’t just about automating workflows, it’s about being ready to plug into a future where interoperability, metadata, and permissions will dictate who thrives and who gets leapfrogged.

Finally, Ken calls for scenario planning: not just reacting to what OpenAI or Anthropic might do next, but anticipating it. Firms and vendors alike should double down on what works, define success before launching new projects, and invest in meaningful adoption strategies. In a world moving this fast, it’s no longer about who gets there first, it’s about who gets there with a plan.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading The Wild West of AI: A Legal Tech Reckoning with Ken Crutchfield

In this week’s episode of The Geek in Review, Greg Lambert flies solo while co-host Marlene Gebauer enjoys some well-deserved relaxation. Greg welcomes Trevor Quick, Strategic Business Development lead at Harvey.ai, to discuss one of the most talked-about companies in legal tech today. With a staggering $300 million Series E funding round and a $5 billion valuation, Harvey is rewriting the narrative of what legal AI can be, as well as who it is for. Trevor, a longtime listener turned guest, brings an insider’s view of the company’s evolution and its ambitions for reshaping the legal services ecosystem.

Trevor provides behind-the-scenes insight into how Harvey has become such a magnet for both capital and attention. He attributes the rapid growth to the company’s structure—where legal expertise and AI engineering are in constant collaboration. From founder Winston Weinberg’s legal acumen to co-founder Gabe Pereyra’s technical leadership, Harvey’s DNA has always been rooted in practical use cases for lawyers. The company’s commitment to building with, not just for, the legal community has led to the development of a GTM team composed of practicing attorneys who work directly with law firms and corporate legal departments to customize AI solutions that align with real workflows.

One of the most talked-about moves is Harvey’s deepening partnership with LexisNexis. Trevor explains how integrating Lexis’s data directly into Harvey’s platform removes the friction lawyers face when juggling multiple research tools. With access to Shepard’s citations and native case law lookup, attorneys can now verify and trust the results Harvey generates—turning it from a generative assistant into a full-fledged research companion. This update not only boosts confidence but also meets the rigorous standards legal professionals demand, especially those skeptical of AI’s early stumbles.

The conversation also touches on Harvey’s new functionalities like the Workflow Builder, Vault document review enhancements, and Deep Research Mode. Trevor likens these innovations to “agentic” workflows that let users build custom solutions with low or no code. Whether it’s KM teams building tailored research processes, or attorneys streamlining diligence reviews, Harvey is giving legal professionals the ability to shape how AI works with them, not around them. Trevor emphasizes that Harvey’s success comes from its honesty, adaptability, and the trust it has earned by meeting lawyers where they are—not forcing them to change how they work overnight.

In closing, Greg asks Trevor to gaze into the crystal ball, and while Trevor jokingly admits that predicting the future in AI is a fool’s errand, he offers a vision rooted in intuition, collaboration, and democratized access to justice. From expanding into tax, compliance, and marketing workflows, to becoming a central hub for legal and adjacent industries, Harvey is on a path to not only augment what lawyers do, but to enhance how they feel about the work itself. With world-class partnerships and a relentless pace of innovation, Trevor makes a compelling case that Harvey isn’t just a tool—it might just be the toolbelt.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Trevor Quick on Harvey.ai as the Utility Belt for Lawyers

In this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert sit down with Otto von Zastrow, the founder and CEO of MidPage.AI, an AI-native legal research platform. With a recent $4 million seed round and an ambitious mission to rival legacy research tools, MidPage is drawing attention across the legal industry. Otto shares his unconventional journey from AI-powered lawn robotics to transforming how litigators interact with case law. His pivot into legal tech was fueled by a combination of technical curiosity, the rise of language models, and firsthand insight from his lawyer friends overwhelmed by inefficient research workflows.

Otto walks listeners through the core of MidPage’s offering, which includes the usual suspects—case law, statutes, regulations—but with a twist: smarter search tools, intuitive UI, and features like a proprietary citator and their newly launched Proposition Search. This feature aims to solve the long-standing “needle-in-a-haystack” problem by surfacing judicial language that matches precise arguments, accompanied by contextual metadata and filters. Otto highlights that the goal isn’t just to match or mimic tools like Lexis or Westlaw, but to rethink what legal research should feel like when modern AI capabilities are built in from the ground up.

One of the more unique aspects of MidPage’s product development is their internal “kangaroo court”—a monthly teamwide challenge where employees, regardless of role, must conduct legal research using MidPage or traditional tools. Otto notes that this process not only improves product design but builds real empathy for the user experience. Engineers and designers are encouraged to think like litigators, helping identify pain points and close functionality gaps. As a result, the product continually evolves based on firsthand user scenarios, not just speculation.

The episode also delves into the data-side challenges that have historically prevented innovation in legal research. Otto explains why now—thanks to improved AI models and open access to data—is a rare inflection point for startups. He emphasizes the strategic importance of MidPage building its own case law dataset to avoid being beholden to incumbents. This independence allows them to innovate more freely, enhance precision, and lay the groundwork for broader API access that could empower the next generation of legal tech tools.

Finally, the conversation looks ahead. Otto predicts that AI will amplify the capabilities of individual lawyers, enabling them to process more data at greater depth. In a world where clients are increasingly self-educating with tools like ChatGPT, MidPage aims to provide lawyers with the means to maintain credibility and efficiency while ensuring accuracy. As AI models grow more capable and agentic, Otto sees an evolution not just in how legal research is conducted, but in how lawyers interact with knowledge, data, and ultimately their clients.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Otto von Zastrow on MidPage.AI and the Future of AI-Powered Legal Research

In this special episode of The Geek in Review, we take the new ChatGPT Advanced Voice Mode for a spin, inviting it to analyze and discuss all 23 episodes from the podcast’s 2025 season. The episode kicks off with a high-level overview of the biggest legal tech themes from the year so far. ChatGPT Voice quickly identifies a significant shift toward agentic AI tools—those that go beyond automation to become integrated partners in the legal workflow. These tools are helping firms reimagine service delivery, improve access to justice, and rethink the very structure of their businesses.

Throughout the episode, the trio explores consistent trends shared by legal tech leaders in recent episodes. These include the integration of AI into core legal tasks, such as contract review and litigation support; the rise of new business models like value-based pricing; and the ongoing focus on ethical AI use. Specific guests like Feargus MacDaeid and Nnamdi Emelifeonwu (Definely), Atena Reihani (ContractPodAI), and Raghu Ramanathan (Thomson Reuters) are spotlighted for their insights into embedding AI directly into lawyers’ existing toolsets to streamline and elevate legal workflows.

The conversation then turns to the importance of human oversight in maintaining trust and legality as AI becomes more embedded in legal systems. ChatGPT Voice references Garfield AI’s regulated model and various RAG-based solutions to illustrate how combining AI efficiency with human judgment creates responsible innovation. The emergence of AI-native law firms and more flexible pricing models reflects an industry on the cusp of transformation, driven by both technological advancement and client-centered thinking.

Marlene and Greg also take a moment to reflect on the human stories behind the tech. They highlight episodes featuring guests like Laura Clayton McDonald, Kenzo Toshima, Wendy Jepsen, and Gabriela Izturiz, who bring servant leadership, change management, behavioral science, and personal purpose into their work. These conversations remind us that innovation in legal tech is as much about people and values as it is about platforms and code.

To close out the episode, the hosts pose their signature “crystal ball” question. ChatGPT predicts the legal tech breakthrough of 2025 will be the mainstream adoption of agentic AI systems that proactively support legal professionals in real time. It also shares that its favorite episode was the one featuring Garfield AI and their bold vision of a fully AI-powered law firm handling small claims—a true glimpse of the future. Whether you’re curious about cutting-edge workflows or inspired by legal professionals integrating their personal passions into practice, this episode captures a compelling snapshot of where legal tech is headed.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript
Continue Reading What Does ChatGPT Think of Our 2025 Episodes? We Ask ‘Her’

In this episode of The Geek in Review, we welcome Feargus MacDaeid and Nnamdi Emelifeonwu, co-founders of Definely, to discuss how their shared experiences as practicing lawyers shaped a groundbreaking accessibility solution for contract review. Feargus, who is visually impaired, and Nnamdi, his former colleague at Freshfields, describe how their friendship and professional collaboration led to a tool designed not only for those with disabilities but for all attorneys grappling with voluminous transactional documents. Listeners learn that Definely began as a way to help Feargus navigate complex contracts more efficiently, and through iterative prototyping, evolved into a productivity suite that addresses universal pain points in the pre-execution stages of contract life cycles.

Feargus explains that his journey to co-founding Definely began with personal necessity: having gone blind from a degenerative condition by his early twenties, he pivoted from a computer science career at Microsoft to law school, relying on assistive technology and immense personal support. Once at Allen & Overy, the limitations of existing tools became starkly apparent—searching for defined terms meant losing one’s place in a 300-page agreement and juggling layers of nested definitions by reading aloud via text-to-speech. The cognitive load was immense. By collaborating with Nnamdi, who recognized that if a solution could serve Feargus, it would benefit everyone, they embraced the principle of “designing for the edge”—creating a platform that brought definitions, clauses, and cross-references into context without interrupting a lawyer’s focus.

Nnamdi takes listeners on a tour of Definely’s three core components: Vault, Draft, and Proof. Vault functions as a dynamic repository for templates, clauses, and precedent documents, enabling users to pull in the most relevant resources from connected document management systems. Draft keeps the user anchored in the current clause while instantly displaying any linked provisions or schedules in a sidebar, eliminating the need to scroll, split screens, or flip between pages. Proof automates common pre-signing checks—verifying cross-references, punctuation, and legal grammar—to ensure a polished final draft. Together, these tools exemplify how Definely streamlines contract creation by surfacing precisely the needed information in a lawyer’s line of sight, thereby maintaining context and reducing manual navigation.

The conversation shifts to quantifying Definely’s impact on law firms. Nnamdi cites a study indicating that attorneys save up to 45 minutes per day—roughly a 90 percent reduction in time spent on tedious tasks—by using Definely’s context-aware navigation. Beyond hard metrics, the founders emphasize “soft benefits” such as reduced cognitive fatigue, higher morale, and improved client value. To capture these less tangible gains, Definely’s customer success team works closely with firms to customize usage dashboards and collect feedback. Feargus and Nnamdi also reflect on the broader legal tech landscape, noting that firms are experimenting with in-house development, acquisitions, and partnerships. They believe collaboration between vendors and firms will ultimately prevail, as specialized expertise in areas like machine learning ops and user experience is hard to cultivate internally and essential for maintaining cutting-edge tools.

Finally, the episode zeroes in on technical and operational safeguards to ensure accuracy and maintain the “human in the loop.” Feargus describes how Definely uses a retrieval-augmented generation (RAG) approach, chunking and embedding each contract so that any language model query is strictly grounded in the document’s own text. By setting the model’s temperature to zero and building guardrails at every step, they contain hallucinations and ensure that the attorney remains the arbiter of correctness. Looking ahead, both founders predict a rise in agentic workflows—small, task-specific language models that plug into a suite of specialized tools—and a greater emphasis on UX design as software shifts from simple point-and-click interactions to more dynamic agent-driven processes. As the hosts close the interview, Definely’s mission emerges clearly: empower lawyers to work smarter by bringing critical contract information into focus, while preserving the essential human judgment at the core of legal practice.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Continue Reading Designing for the Edge: Feargus MacDaeid and Nnamdi Emelifeonwu on Definely’s AI-Powered Contract Navigation

On this episode of The Geek in Review, we welcome Philip Young, co-founder and CEO of Garfield AI, the first AI-powered law firm approved for practice by the UK’s Solicitors Regulation Authority (SRA). The episode kicks off with a discussion of recent stories that explore AI’s evolving role in legal proceedings, such as avatars testifying in court and the ethical challenges that arise when deepfakes and synthetic personas enter the legal process. Philip, a seasoned litigator and technologist, draws from his 25 years of legal experience to weigh in on the potential and perils of AI-driven courtrooms, emphasizing the importance of authenticity and trust in legal proceedings.

Young shares the backstory behind Garfield AI, which was inspired by a real-world problem faced by his brother-in-law, a plumber who struggled to recover small debts from non-paying clients. Seeing an opportunity to help small businesses navigate the small claims process efficiently, affordably, and with minimal friction, Philip set out to build a system that mirrors what a traditional law firm would do—without the high cost or time burden. Garfield reads invoices and contracts, verifies the legitimacy of claims, guides users through pre-action letters, claim filings, and even court preparation, all while remaining compliant with UK legal standards.

One of the most unique features of Garfield AI is its dual design: it serves both pro se claimants and can be white-labeled for use by traditional law firms. Young explains how legal professionals can integrate Garfield into their workflows, using it to generate documents under their own branding while Garfield handles the backend. This hybrid approach provides flexibility for users, whether they prefer a self-service platform or seek a human-in-the-loop experience. Garfield’s early success has sparked interest across the legal spectrum—from solo practitioners to regulatory bodies—demonstrating that AI can support, rather than displace, the legal profession.

The conversation also delves into Garfield’s journey to regulatory approval. Young describes the rigorous process of working with the SRA, ensuring the platform aligned with legal duties to clients and the courts. He highlights the importance of maintaining accountability and explains how Garfield was rolled out cautiously, with layers of human oversight and a roadmap toward data-driven, risk-based review. With increasing inquiries from international regulators and courts, Young sees the platform as a potential blueprint for improving access to justice beyond the UK, although he notes that success depends on a supportive regulatory environment, judicial openness, and sufficient technological infrastructure.

Beyond the tech, the episode emphasizes the human element of law. Young passionately advocates for AI as a tool that enhances legal practice rather than replaces it—freeing lawyers from mundane tasks and enabling them to focus on strategy, advocacy, and client care. He shares his hope that Garfield AI and similar innovations will close the access-to-justice gap by enabling small-value claims to be pursued cost-effectively and fairly. As he notes, AI may never replace the human lawyer’s emotional intelligence and presence in court, but it can certainly help more people get there.

To learn more about Garfield AI and its innovative approach to legal automation, listeners can visit www.garfield.law. This episode is a must-listen for anyone interested in the intersection of law, technology, and the future of justice. As always, the podcast ends on a warm note with music by Jerry David DeCicca, underscoring a thought-provoking conversation that blends legal tradition with the tech of tomorrow.

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[Special Thanks to Legal Technology Hub for their sponsoring this episode.]

Blue Sky: ⁠@geeklawblog.com⁠ ⁠@marlgeb⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Continue Reading Philip Young of Garfield AI: The World’s First AI Law Firm Gets the Green Light