· 9 min read

An Interview with Rob Saccone, Strategic Advisor to 273 Ventures

From a self-taught software engineer to a pioneering figure in legal tech

From a self-taught software engineer to a pioneering figure in legal tech

In this interview, we sit down with strategic advisor to 273 Ventures, Rob Saccone, to explore his journey and influential role in the legal technology landscape. Join us as Rob shares his insights on the evolution of legal technology, the impact of AI, and his vision for the future of the sector.

Thank you so much for taking the time to sit down with us today. Can you tell us about your career path and how it has led you to being a pioneering figure in legal technology? How have your experiences shaped your approach to leveraging technology and data in legal services?

Rob: I’m a self-taught software engineer that became a self-taught founder and software executive. I’ve learned everything I know from doing, and surrounding myself with smart colleagues, teammates, and mentors. This experience has made me pragmatic about assessing and building teams, products, and businesses. Bootstrapping from zero also taught me to approach spend and resource decisions with brutal efficiency. I’m always looking to improve, but both traits have served me well over the last 25 years in the legal vertical both in my own ventures and with my clients and partners.

My journey in legal began at Goodwin Procter in the late 90s where I built a team of developers and analysts at the beginnings of the firm’s knowledge management program. I had previously led enterprise software teams in real estate and commodities trading, but quickly learned that professional service firms offered an entirely different set of challenges and opportunities. Advancing knowledge work though applied technology and data-driven insights has been my career ever since.

I left Goodwin to start a software business called XMLAW to do just that, building on my relationships with Microsoft and their nascent SharePoint platform. In 2009 I sold XMLAW to Thomson Reuters, and quickly expanded my focus beyond KM and technology to law firm business development, finance, and management strategy. And this opened my eyes to the broader structural, cultural, and behavioral challenges that impede tech adoption in firms.

After Thomson I shifted my focus to advising firms, vendors, and tech startups on these challenges, relying on the playbooks I’ve refined over many years of trial and error, and occasionally some success! I was also fortunate to work with Seyfarth Shaw at the peak of their lean six sigma efforts as “legal operations” became front and center. As CEO of their Seyfarth Lean Consulting group I further refined my view on legal technology and operational improvement, particularly from a client perspective given our focus on law department optimization.

My career in legal has been anchored on leveraging technology and data to tackle complex issues within legal services. It’s what I’m most passionate about, especially in today’s market with all the renewed excitement around data and tech.

A lot has happened in the past year with the latest developments in generative AI and the technical world more broadly. How do you see the current state of AI and its application?

Rob: I’ve been working with ML and NLP for many years, including some fascinating but early-stage work with the data science team while at Thomson Reuters. But I admit that I was skeptical when I first reviewed large language models and generative AI. Though the early demos were mind-blowing, I felt like they represented solutions looking for problems – a classic product development misstep. But the potential for a sea change was clear, even if the specifics were not.

So, I decided to return to my roots as a product developer and engineer and jumped into the deep end. Over the last year I’ve worked hands-on with firms evaluating AI and vendors early to the game. My first glimpse into the future came with early access to CoCounsel from the brilliant team at CaseText (now TR) who have been at this longer than most, and I’ve since gone deeper by experimenting directly with a wide range of models, frameworks, and the quickly evolving patterns and practices for deploying AI in the real world.

My perspective is very different now. The remarkable improvements in performance, scale, and accuracy have been truly astonishing. But it is clear, to me anyway, that AI is as much a catalyst as it is a cure. The digital transformation we’re experiencing is still built on professional software engineering principles and thoughtful user experiences. It still requires useful and trustworthy data obtained the right way. All digital initiatives need to be stood up on a solid foundation, and there are no shortcuts or band-aids to cover over cracks. If the AI race only increases focus on these foundational elements, it’s still a win. But I do believe that those who can balance foundational improvement and transformational change will be the ultimate winners.

Currently, we are navigating a period of exploration and rapid discovery. I needed to experiment and evaluate these new tools directly to overcome my skepticism, and I would expect any business leader or decision maker to do the same. Most businesses I speak with, including law firms, face the need to evaluate these emerging tools and capabilities safely and confidently at their own pace. But the race has begun, and my advice would be to at least get off the starting line.

Comparing the early days of the internet to the current AI explosion, how do you see this shaping the future, especially in terms of adoption and application in various sectors?

Rob: The trajectory AI is taking mirrors the early internet era, marking the dawn of a new paradigm for value exchange and innovation. For some it’s a land grab, a race to make money before the dust settles. This is fine, but we all saw how the bubble popped before.

But this time, I think AI introduces unique challenges and opportunities specifically for professional services and knowledge workers. Most of this knowledge is captured and communicated in written words, and we are discovering whole new ways to create and consume this knowledge. While previous attempts at efficiency and scale in professional services were incremental at best, we’re now on the cusp of unlocking massive scalability at a fraction of the cost. That is, assuming we can solve for quality and reliability, but all signs indicate that these are solvable - thanks not only to advanced models, but to the advanced software engineering required to put them to use.

As I said, now is the time to get ahead of these challenges and opportunities. But I wouldn’t go so far to say now is the time to broadly adopt or deeply invest in one tool or approach. It’s too soon to pick a winner, but it’s not too late to join the race.

With AI redefining roles, especially in professional services, what does this mean for the future of work within these sectors?

Rob: Throughout my work with professional services, I’ve consistently observed two primary challenges to business growth and stability: scale and sales. Scalability is straightforward: firms are inherently limited by the number of humans and hours in a day. Sales is more of a structural challenge, as professionals are expected to wear multiple hats and be great in all roles. It is rare to find a true rainmaker who can sell and manage relationships while managing teams while maintaining their own level of domain expertise.

AI’s impact will primarily be measured by increased scalability, and if done correctly will free firms from the limitations I mention. In other words, fewer people can deliver more, and possibly better, results at the same or less cost. Clients love this thinking, but most firms are terrified by it. Particularly those who only know how to price and bill by the human/hour. This brings us back to the prerequisite foundational improvements I mentioned. Optimizing a practice for max scalability at lower cost without repackaging and repricing is a fool’s errand.

Based on results so far, we can assume that AI will primarily impact the work currently delivered by less experienced professionals – junior associates, paralegals, or support staff. Today the work they are assigned often serves as training and experience-building, but if clients won’t pay for it and there are digital alternatives to get it done faster and better, firms must reconsider staffing and professional development as well.

It has been said that AI will replace tasks, not jobs, and I believe this holds true in legal services. But the nature of the jobs will clearly change. We’ll need to shift from doing to managing and allocating resources, including digital assistants as part of our teams. This requires new ways of interacting with others and delegating work.

Given your advisory role with our company and considering our focus on AI in the legal space, what aspects of our approach and technology excite you the most?

Rob: What stands out to me about the team at 273 Ventures is your comprehensive understanding of both the practice and business of law combined with how technology, specifically AI, can be integrated realistically and effectively. This blend of expertise is rare and invaluable for addressing the challenges and opportunities in the legal sector. Lateral thinking across these areas and proven experience and credibility are the keys to putting tech to use and having it stick.

This is not just about revisiting old problems with new solutions; it’s about shedding new light on these issues, bringing a refreshing perspective to the table. We have a responsibility to educate the market on these advancements, to cut through the hype and help point firms in the right direction while considering their unique market position, direction, and ability to adapt. 273’s credibility, trustworthiness, and the depth of your expertise are fundamental to leading this change.

With this technology it’s difficult to predict where things will be in 3-5 months, let alone 3-5 years. Having taken a close look at Kelvin and your overall technology stack it’s clear that there are foundational investments and strategic decisions being made that prioritize solving meaningful problems efficiently while keeping an eye on the horizon. I’m honored to be part of 273’s journey!


The 273 Ventures team has developed the Kelvin Legal Data OS to organize and connect data from various structured and unstructured sources, including documents like contracts and briefs, timekeeping entries, and laws and rules. Kelvin ships with automation for legal-specific use cases, like due diligence and regulatory monitoring, as well as connectors for common systems like Aderant and TeamConnect. Kelvin is LLM-agnostic, with support for practically all commercially available large language models, including GPT-4, Claude, and Llama 2. Kelvin is a modern purpose-built platform specifically designed for the legal industry, with an emphasis on compliance with information security standards and data protection laws. Kelvin can run on your own physical server or private cloud, on a developer’s laptop, or in any public or hybrid cloud environment.

For press inquiries: hello@273ventures.com

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