Version Up

About Version Up

One lawyer’s journey to transform his legal practice. Version Up (versionup.ai (https://versionup.ai)) is a podcast about deploying AI and technology in legal practice. Host Kaj Rozga — a practicing lawyer leading innovation inside a legal team at a Global 500 — talks with the practitioners, founders, and operators doing the heavy-duty work of repurposing the practice and business of law for the AI era. Each episode is a practical conversation about what’s working, what isn’t, and what’s worth paying attention to. The goal is to work towards clarity through an honest dialogue about building and deploying legal technology at law firms and corporate legal departments. For lawyers, innovation leaders, legal ops professionals, founders and investors who want the bottom-line on the state of play in legal tech. | Hosted by Kaj Rozga | Music by Brett Ryback | views my own |

Publisher

Kaj Rozga

Category

technology

Language

en

Explicit

No

First episode

28 Mar 2025

Latest episode

14 Oct 2026

Latest episodes

37 episodes in the feed.

1. 

   14 Oct 2026

   Legal Tech Unicorns: Reliable AI Agents for Legal Practice

   Denisa Kopandi returns to Version Up to discuss what happens when legal AI agents meet the uneven, iterative work of an actual transaction. Drawing on her experience testing legal AI tools and building workflows, she explains why a sequence that looks convincing in a demo can be difficult to trust in practice. We distinguish between agents working behind a chatbot’s answer and workflows intended to carry a legal matter through multiple stages. Denisa describes the gap between a neat progression from intake to analysis to drafting and the reality of documents arriving in batches, incomplete information, and clients changing the structure or timing of a deal. A central theme is the legal analysis that happens before anything gets written down. A lawyer may open an apparently routine document and notice something that changes the entire assessment. That makes it difficult to specify every task or decide in advance where an agent should stop for review. Checking the final legal analysis may not reveal that an earlier agent overlooked a document or extracted the wrong information. We explore a more manageable approach: specialized agents for narrower tasks, with lawyers deciding when to use them and how the results fit together. Examples include assessing a merger notification threshold or preparing a request for information using what is already known about the client. The question is how much useful work can be delegated without creating a verification burden that cancels out the time saved. Denisa also shares an experiment in which an agent began deleting earlier versions of a due diligence report, leaving her to transfer the analysis manually. We discuss what that experience says about reliability, alongside the difficulty of trusting a batch of contract analyses after finding an error in one. There is a training dimension too. Denisa asked interns to use AI for research and submit their full conversations, so she could review how they questioned the model. We consider whether narrower tasks and visible review can help junior lawyers develop judgment, and how quickly improving tools affect the decision to invest in building a workflow. Denisa Kopandi is a senior associate at bpv GRIGORESCU ȘTEFĂNICĂ in Romania, working across technology, competition, and commercial matters. Alongside her client work, she evaluates and implements legal AI tools and explores how they can support specific legal tasks and the development of junior lawyers. You can follow her on LinkedIn. * * * Version Up Members is a free, invitation-only community for lawyers and legal professionals putting AI to work at law firms and legal departments. Request an invitation: versionup.ai/members

2. 

   6 Oct 2026

   What Decades of Knowledge Management at Elite Law Firms Can Teach Us About Data in the AI Era

   Christopher Smith joins to discuss what it takes for law firms to turn their accumulated documents, data, and experience into knowledge that lawyers can actually use. Drawing on his previous work at Sullivan & Cromwell and Freshfields, Chris explains why many of the challenges behind today’s AI ambitions have been familiar to knowledge management teams for decades. We start with the practical problem of collecting information from busy lawyers. Chris describes why matter intake and document profiling need to fit around getting the work done, why firms should avoid asking for the same information twice, and how overly restrictive systems can push lawyers into workarounds. As collaboration spreads across email and other platforms, keeping track of authoritative documents becomes more complicated. That leads to a question I’ve often had when looking at legal AI tools: who is going to make sure they’re working from the right material? Chris sees improving tools for organizing and cleaning data, but someone still has to decide which information is correct. He shares how he brought teams at Freshfields together around shared firm data, with clear responsibility for particular decisions. We also discuss the value of a vetted collection of useful material and why lawyer attention remains a constraint on evaluating what AI finds. The incentives matter just as much. At Sullivan & Cromwell, Chris describes connecting knowledge contributions to performance evaluations and looking at whether other lawyers actually used the submitted material. We explore the tension between building a firm’s intellectual capital and lawyers’ ability to take their experience and client relationships elsewhere. Looking ahead, we consider whether broad legal AI platforms will become a common baseline, with differentiation coming from how lawyers combine tools, data, and judgment. We also discuss the apprenticeship model, emerging roles that combine legal practice and technology, and whether changing client expectations and billing arrangements will create stronger incentives to work differently. Chris closes with a candid explanation of why he is pursuing opportunities outside law firms and the limits he sees in their rewards for people who build technology. Christopher Smith is the former Chief Information Officer and Chief Data Officer at Freshfields and former Chief Knowledge Management and Innovation Officer at Sullivan & Cromwell. **Corrections: TensorFlow was released in 2015. Generative AI emerged in 2022/2023.***all views expressed our own**

3. 

   24 Sept 2026

   Why Lawyers Are Building: Beyond Off-the-Shelf Legal Tech

   Salvador Carranza, a former lawyer turned applied AI builder and adviser, joins to talk about a shift that could fundamentally change how legal technology gets made and deployed: lawyers are increasingly able to build solutions themselves. We start with the traditional build-versus-buy decision. For years, buying software was usually the obvious choice. But AI-powered coding tools are lowering the technical barrier to turning an idea into a working prototype, giving lawyers and legal teams new options when off-the-shelf products don’t quite fit their workflows, data, or needs. Salvador makes the case that building is also one of the best ways to actually learn AI. We discuss why lawyers should tinker, experiment, and iterate; how organizations can create safe environments for that experimentation; and why understanding how these systems work can make you a much more sophisticated buyer of legal technology. From there, we get into the bigger implications: the difficulty of measuring AI ROI, data ownership and vendor lock-in, whether today’s legal AI platforms can maintain their position as frontier models improve, and why legal organizations increasingly need people who can turn ideas into proofs of concept. We close by looking at what this means for the business of law. AI gives law firms new opportunities to productize legal services, rethink pricing, and capture more value from efficiency—and gives corporate legal departments the ability to build internal products that change what work they send outside in the first place. At the center of it all is a simple idea: learn AI, use AI, and build with AI—not sequentially, but all at once. Salvador is the founder of PossibLaw, where he writes and hosts a podcast focused on builders and the future of legal, and the founder of Lumen Atlas, where he works with legal teams on applied AI, training, workflow design, and technology decisions. You can follow him on LinkedIn.

Who has been a guest on Version Up

Names identified in recent episode analyses. Showing up to five guests.

• Benjamin Llinas
• Daniel Schwarz
• Thomas G Martin
• Alex Baker
• Emma Kelly

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Apple Podcasts (US)

5.0 / 5

2 ratings

Spotify

5.0 / 5

4 ratings

Contact Version Up

Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.