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Another year, another change in legal information. The AALL Committee on Relations with Information Vendors (CRIV) did a nice write up of American Lawyer Media’s strategic changes. It is not the first legal publisher to (a) center its content exclusively on its own platform nor (b) to create all-or-nothing content
From Legal Aid to LIT Lab: Quinten Steenhuis and the Builder’s Approach to AI
Quinten Steenhuis brings a builder’s mindset to legal innovation, rooted in early Indymedia activism where scavenged hardware became community infrastructure. That scrappy origin story carries through a dozen years of eviction defense at Greater Boston Legal Services, with a steady focus on tools that help people solve problems without waiting for a savior in a suit. Along the way, Quinten also lived the unglamorous side of mission tech, keeping systems funded, supported, and usable when budgets get tight and priorities get loud.
The conversation then jumps to Suffolk Law’s approach to generative AI education, including a required learning track for first-year students. Quinten frames the track as foundational training, then points to a deeper bench of follow-on courses and the LIT Lab clinic where students build with real tools, real partners, and real stakes. The throughline stays consistent, exposure alone solves nothing, so Suffolk puts reps, projects, and practice behind the syllabus.
A standout segment tackles the “vaporware semester” problem, where student-built prototypes fade out once finals end. The LIT Lab fights that decay by narrowing tool choices, standardizing around DocAssemble, and supervising work with a clinic-style model, staff stay close, quality stays high, and maintenance stays owned. Projects ship through CourtFormsOnline, with ongoing updates, volunteer support, and a commitment to keep public-facing legal help online for the long haul.
Then the episode turns toward agentic workflows, with examples from Quinten’s consulting work in Virginia and Oregon. One project uses voice-based intake to screen for eligibility, confirm location and income, gather the story in a person’s own words, and route matters into usable categories. Another project speeds bar referral by replacing slow human triage with faster classification and better user interaction patterns, fewer walls of typing, more guided choices, more yes-or-no steps, and fewer dead ends.
In the closing stretch, Quinten shares the sources feeding his learning loop, LinkedIn, Legal Services Corporation’s Innovations conference, the LSNTAP mailing list, podcasts, and Bob Ambrogi’s LawSites, plus the occasional spicy Reddit detour. The crystal ball lands on a thorny challenge for both academia and practice, training lawyers for judgment and verification when AI outputs land near-correct most of the time, then fail in the exact moment nobody expects. Quinten’s bottom line feels blunt and optimistic at once, safe workflows matter, and the public already uses general chat tools for legal help, so the legal system needs harm-reducing alternatives that work.
Listen on mobile platforms: Apple Podcasts | Spotify | YouTube
[Special Thanks to Legal Technology Hub for their sponsoring this episode.]
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Links (as shared by Quinten):
Transcript
Combating Financial Fraud: Mid-Market CFOs Need New Mechanisms
Many CFOs continue to equate strong audit outcomes with effective fraud containment. In modern business environments, however, transactions move faster and approvals are increasingly distributed, meaning exposure is often identified only after financial scams and frauds have already occurred.
This delayed discovery is evident across organizations of all sizes. According to the 2025 Association of
From Discovery to Compliance: How AI Simplifies Legal Review
Document review plays a critical role in how legal teams assess risk, manage compliance, and support strategic decision-making. As discovery, investigation, and regulatory datasets expand in size and diversity, the quality and consistency of review outcomes carry greater organizational impact.
Legal teams are expected to deliver defensible results while managing compressed timelines and heightened scrutiny
Purpose Versus Task: What Nvidia CEO Jensen Huang Gets Right About the Future for Lawyers
Last week, a video clip of NVIDIA CEO Jensen Huang made the rounds on social media. In it, he’s cooking outdoors, because apparently that’s what you do when you’re running an $3 trillion company, and casually dropping one of the most important frameworks for understanding professional survival in the age of AI.“The job of a
WARNING: This Product Contains an Ingredient Not Recommended for Human Consumption …
Businesses across the country face a consequential legal and commercial crossroads as Texas Senate Bill 25, branded the Make Texas Healthy Again Act, thrusts state level food labeling regulation into uncharted constitutional and regulatory territory. The stakes are high: companies that manufacture, market, or sell food products may soon confront unprecedented warning requirements
Why technology is reshaping the secondary market pipeline in 2026
With trillions in private capital dry powder still waiting to be deployed, and limited partners (LPs) increasingly selective about where they commit, competition in the secondary market has never been more intense. Once viewed primarily as a liquidity mechanism, secondaries now play a critical role in portfolio management and capital recycling. For firms looking to
Alexi Fires Back at Fastcase Lawsuit with Counterclaims Alleging Anticompetitive Conduct Following Clio’s $1B Acquisition
Alexi Technologies has filed its answer and counterclaim against Fastcase, vLex, and Clio, accusing the newly merged legal technology giant of manufacturing breach-of-contract allegations as a pretext to eliminate a competitor in the AI legal research market. In December, Fastcase, now owned by Clio, sued Alexi in the U.S. District Court for the District of Columbia,
Check out our new Substack Page — Beyond the Model: How Legal AI Got Smart
[Ed. Note – We have launched The Geek in Review Substack page to put out content in a new way. One example of this content is a series of stories that I’ve been working on as I’ve learned more about how AI and automation tools are developed, and what works, and doesn’t work. As well as the improvements made as foundational models get better, or as the industry learns how to leverage the tools more effectively. Below is Chapter One of my “Beyond the Models” story where I start to dive in on why after two years of some pretty mediocre legal research tools, these tools are suddenly getting much, much better. We’ll still be posting here, but Substack gives us an interesting platform to work with that expands what we can do here on the blog. Including a lot more opportunities for us to hear from you! Come join us and see what all the Substack fuss is about. – Greg]
Beyond the Model: Part One – How Legal AI Got Smart
Preface
Any sufficiently advanced technology is indistinguishable from magic” – Arthur C. Clarke
For those of us in the legal industry, the past three years have created an enthusiasm around the practice and business of law that I’ve never seen before. The introduction of Generative AI created an immediate push into the legal industry, and legal research was seen as the most obvious and easiest candidate to be ‘fixed’ by AI. It has turned out to be one of the hardest.
I’ve spent the last three years trying to keep up. Change isn’t measured in quarterly updates, it is measured in weekly, and sometimes daily increments. Just understanding some of the basics can be challenging. So, I wanted to take a different approach to explaining some of the basics around why legal research seemed like an easy solution, and why it has taken a couple of really awful years of GenAI legal research tools before we started actually seeing some decent results.
Instead of going through all of the data and presenting information in a technical way, I took a page out of my friend Anusia Gillespie’s book and decided to explain it in stories. Storytelling might be a way for some of us to better wrap our heads around what it takes for AI to truly make sense of legal research.
Part one of the story introduces Cooper, Jesse, and Maya. A law firm innovator, a startup data scientist, and a law firm partner. The kind of people who I work with every day. We start off talking about how throwing LLMs at millions of documents of legal decisions doesn’t just work ‘out of the box.’ The near daily news articles of attorneys being sanctioned for “hallucinations” in their legal writings is a direct result of this misconception.
We needed a middle layer to connect the power of the LLM to the legal information, and for a couple of years the answer was Retrieval Augmented Generation (RAG). As you’ll learn from the story, it was a good first step but introduced some of its own problems.
I hope you enjoy this first of what I hope will be many stories of how innovation plays out in the legal field.
(Full article available on Substack)
Introduction
For the past couple of years, lawyers and technologists have marveled at how AI-powered legal research tools seem to be getting smarter every month. Tools like Lexis Protégé, Westlaw CoCounsel, and Vincent by Clio deliver answers that feel almost prescient. The assumption was simple: better foundational models like ChatGPT 5.2, Claude Opus 4.5, and Gemini 3.0 Pro equal better answers.
Re-engineering the B2B Narrative: Why Tech Marketers Are Ditching Campaigns for Newsrooms
Editor’s Note: Tech marketers are under pressure—and not just from competitors. Buyers have changed. They now spend months researching independently, bypassing promotional campaigns in favor of trusted, editorial-style content. In response, leading B2B technology firms are overhauling their marketing models, moving away from traditional campaign calendars toward newsroom-inspired operations that prioritize speed, consistency, and journalistic