Robert Ambrogi Blog
When I wrote last week about BARBRI’s acquisition of Lega, I had not yet had the chance to speak with Lega founder Christian Lang, who was traveling. So I closed that post with what was admittedly conjecture on my part – that the large-language-model governance product that defined Lega when it launched in 2023 was now going away, in favor of the AI-training business that the company had developed more recently.
When I finally caught up with Lang this week, I learned that conjecture was only half right. While the governance product is not going away, exactly, it is taking on a new role, no longer focused on testing and building AI, but rather on learning and developing fluency in AI.
“Lega the platform is such a tremendous teaching tool and platform to support the workshops, to support the hackathons, to support AI innovation labs,” Lang told me. “It is the perfect infrastructure for that. So we’re using it.”
So while the company is keeping the technology, it is changing the job it does. “We’re not going to go out and try to sell the platform as the place where you build production AI solutions for your frontline teams anymore,” he said. “It’s going to be about: this is where you learn and test and try and develop the AI fluency, kind of further up the value chain.”
Repurposing the Sandbox
Lang drew a distinction between the two architectural halves of Lega. One is the “lab,” the sandbox where users bring resources together, compare models and test prompts. The other is the “gateway,” the layer through which traffic flows and where the platform builds audit trails and handles compliance scanning, observability and analytics.
In the product’s original incarnation focused on firm governance, the gateway existed largely to enforce outside-counsel guidelines and keep a record. Now, under BARBRI, the same technology becomes a measurement instrument.
“It’s actually the analytics we’re doing through the gateway – that’s exactly the feedback loop you need when you’re trying to test people and understand how well they’re doing and where are they on that fluency arc,” he said. “There’s probably not any piece of the platform that isn’t integral to what we’re doing at BARBRI, but it will be positioned slightly differently.”
Having said that, Lang added that the platform itself is not sacred and that the technology could evolve over the longer term. “If we end up two years from now running everything on top of Claude Cowork as the platform, great, that’s what we’ll do.” But for now, he said, Lega’s own infrastructure remains the better fit for what the workshops require.
‘High-End Cooking Classes for AI’
As I said in my story last week about the acquisition, although Lega launched in 2023 with a focus on LLM governance, it had evolved to increasingly focus on helping legal professionals develop AI fluency through practical, experiential learning.
The experiential side of Lega – the part, no doubt, that most interested BARBRI – predates the deal by about 18 months. Lang said the company ran its first hands-on AI workshop at the Legal AI Conference in New York roughly a year and a half ago, initially “just for fun,” on the theory that there was no reason to limit experiential learning to the firms that licensed the platform.
From there it expanded to innovation teams, partner retreats, innovation summits, law schools, and some corporate legal departments.
“These are basically almost like high-end cooking classes for AI,” Lang said, where Lega defines a realized use case, builds the materials for it, and then puts participants in a room, in teams, on machines.
He described the workshops as a three-part journey. Participants start in the model-comparison sandbox – “pick their weapon,” as he put it, choosing the model they want to build on.
They then work through what it means to build a context picture for a model, which Lang said is where the black box gets opened up: how retrieval augmentation actually works, what dials exist, what happens when you call tools and MCP servers, and where that content lands in the prompt.
In the third phase, each team builds a working prototype of an app or agent by the end of the day.
That progression, Lang argued, is what moves people past surface-level “AI literacy” and into what he calls fluency – the point at which users can reason analogically about what the technology can do in their own work.
Stop ‘Defending the Past’
I asked Lang about the Thomson Reuters Future of Professionals report I wrote about last week, which found a widening gap between how many lawyers are adopting AI and how few are extracting real value from it.
Lang’s diagnosis is that the profession is stuck in an “adoption trap.” Focusing on tool adoption, he argued, is inherently backward-looking. It is “literally defending the past,” because adoption measures how well you deploy new technology against workflows that were designed in a pre-AI era, usually framed as getting “the bottom half of our org up to speed.”
The better approach, he said, is “raising the ceiling” by identifying and empowering the trailblazers inside an organization who can reimagine what service delivery should look like in the first place.
“How do we identify that subset of users that are going to help blaze the paths to get us where we need to go to win the future as opposed to defend the past?” he said. “That, I think, is something that not a lot of people devote a lot of time to, and I think it’s existential for law firms.”
Taking it a step further, Lang suggested that the value question precedes the adoption question. Particularly on the transactional side, he said, firms sell “a very mixed bundle of services” on blended rates without always knowing where the genuine value sits.
“I genuinely believe that law firms have to find product-market fit again,” he said, “and I don’t see many firms actually doing that.”
What Comes Next
With the acquisition now completed, the near-term plan is “deeply practical,” Lang said, including running a critical mass of workshops at law firms over roughly the first 90 days, doing some law-school work, and validating the thesis about Lega’s role in building AI fluency.
He said Lega may convene thought leaders from across the ecosystem to help develop AI-fluency assessment tools, observing that the term is now widely used but poorly defined. “Right now people are using the language, but no one really knows what it means.”
Also on the roadmap is a law-student component, something Lang said both companies had been working toward independently before the deal.
He described early conversations with a law school about standing up an AI innovation lab where students could learn experientially and where firms could come in to see what the up-and-coming generation of lawyers looks like and needs.
The ambition, he said, is to use the schools as the “plain white space” for the kind of sandboxing firms can’t easily do “in the throes of service delivery against very aggressive timelines,” and to let both schools and firms learn from what happens there, forming a bridge from law school to firm, and potentially from firm to client.
There is also a possible advisory dimension, Lang noted, calling it a natural extension of the value-and-strategy work that he sees as a precondition for any of the fluency questions.
When it comes to educating the profession about AI, Lang acknowledged that there is much to be done. “It’s a hard, big, hairy problem,” he said. “But I think it’ll be fun.”