September 27, 2018
Law & Entropy
In 1998, I matriculated at the University of Virginia School of Law fresh out of college, bright eyed, bushy-tailed and ready to conquer the world. I wanted to be somebody. You see, in land-locked, conservative Kentucky where I was born and raised, there were three routes to prominence: (i) the old money way, the so-called genetic lottery; (ii) as a physician; or (iii) as an attorney. Finance (finánce, as they say in NY)? That was what you did at Sears when you couldn’t afford to take the thing home! Sadly, Dad had screwed me out of that lottery. One down. I flipped a coin. Turns out, law school was a great place for me. I loved being in Charlottesville, adored my classmates and the subject matter was genuinely interesting. I even managed to smooth talk my way into the venerable halls of Cravath, Swaine & Moore, where I cut my proverbial teeth and learned a great deal, least of which was what it meant to serve customers. Customer service is a critical lesson to learn early, and thankfully Cravath taught it to me well. Big law was a big disappointment for me. Prior to my move to New York City, I had imagined what my days would be like “making deals” and calling shots in the Big Apple: like Michael Douglas in Wall Street, sitting in fancy restaurants and stomping around the streets yelling about deals and pricing. Imagine my reaction when I discovered that I had spent three years of my life studying law just to spend 20 hours a day in a small, shared office sifting through documents. “Hey, Jason, go find me an example where it says ‘shall’ instead of ‘should.’” So much for the fancy restaurants. And the only yelling was from the partners telling me to read faster. My long days of stare-and-compare quickly became cold water on the hot fire that had launched my legal journey, and I didn’t have the patience to wait around for grey hair and more challenging work. But like many entrepreneurs, I let that frustration fuel my drive.
My Tech Journey
My first real foray in tech was in joining the founding team of a company called Matterhorn, whose mission was to assemble the preeminent deal database for M&A (mergers and acquisitions) lawyers and bankers. Bankers and lawyers spend hours and millions of dollars fighting with each other in order to achieve what they call “market” terms on a particular deal. Precedent is omniscient, but it’s not omnipresent. Hence the need for squadrons of high-paid young people to comb through documents in order to find the right precedent. At Matterhorn, we aimed to deliver that intelligence to users with a few clicks. It took us teams of young lawyers and several million dollars to manually construct the database. We eventually succeeded with that company, and the product still exists today inside of Lexis Nexis—not unlike Courtlink, where Matt Schiltz had been CEO. My experience with Matterhorn left me convinced to find a better way to perform some of the routine functions that were so time-consuming and costly with that product, and around contract management in general. It seemed truly crazy to me that we had to pay hundreds of dollars per hour to have someone find all the indemnity clauses in a bunch of files. So in 2014, I started tinkering. I invested a pile of my own money and eventually got to a strong enough working proof of concept that I was able to convince some great investors to get behind the idea. We launched Counselytics with the lofty objective of making legal organizations smart; that is to say, automating routinized work related to text in order to empower high-paid knowledge workers. Within six months of launch we realized that the highest and best use of our new invention, and the largest total addressable market, wasn’t in law firms; rather, it was in enterprise contract management. Finding legal clauses to accelerate due diligence is a valuable exercise, but nothing excites the C-suite and opens check books like dollars and dates. So we turned our attention away from the law firms and started focusing on applied AI in contract management.
AI - Smoke, Mirrors and, Finally, Some Straight Talk
That chapter of my tech journey obviously ended in a successful sale to Conga, where I am absolutely thrilled to be part of a large team of smart professionals singularly focused on AI solutions inside the Conga Suite. To be sure, we have more folks focused on AI than some of our competitors have in their entire engineering departments. The resources to tackle this problem the right way, and the thousands of happy Conga customers were the primary impetus for selling my company. Unfortunately, thanks in part to the media-at-large, AI is a tough field right now. You can’t pass a newsstand these days without seeing an ominous headline or magazine cover about the so-called march of the machines. Commentators from all walks incorrectly use AI, machine learning and automation interchangeably. And, unfortunately, in the CLM space many of our competitors simply exacerbate the problem—they leverage these misunderstandings to make quick sales, and then never deliver, leaving a wake of disappointed customers.
Which brings me to Dreamforce.
Foreseeably, AI was everywhere. And, sort of, nowhere. I got to surf the emotional wave this week with the AI panels. On one hand, I listened to Kai-Fu Lee’s AI panel, where he poetically waxed and waned about the threat of general AI, job displacement and the need for universal income. Scary. A few hours later over at Moscone West, a Salesforce employee droned on about Einstein, how it could manipulate salesforce data-points (yeah, guys, so can Excel...) and usually identify positive from negative sentiment. Boring. They sure do make it tough to separate the so-called wheat from the chaff!
That’s a wrap.
I’m tired and ready to go home. Before I do, I want to share the story most people won’t tell you because it doesn’t sell magazine covers, books or crappy bolt-ons to their platform. We’re nowhere close to general AI. Some jobs are going to be displaced, and some new jobs are going to be created. I worry for my future grandchildren, if anyone. Nobody has a system that can seamlessly take all your third party paper and pass it into Salesforce with complete accuracy and no human intervention. Nobody. Someday those machines are going to march, but right now it takes a helluva lot of work to make them crawl. At Conga, we already have a great business with thousands of customers and approaching one million happy users. But disappointed customers are not part of our DNA, so we have to be especially vigilant about managing expectations around AI. Almost every day of the week I will have a conversation with a customer wherein I say, “That is not possible. If anyone is telling you it is, they are lying.” I had that conversation this morning before coming over to Dreamforce. If I can impress upon readers one point, it is that you really need to work with trusted vendors when approaching AI. I’m doing that every day now at Conga—working closely with our great customers to manage their expectations and intelligently deploy our AI technology in order to accelerate time to value. We’re scoring wins and leaving people smiling. To reiterate, if I can impress anything upon those considering AI, it's this:
- Challenge the assumptions and push for clear answers
- Do your own research and homework
- Don't simply buy the AI add-on without digging into it
These approaches will make all the difference. Jason serves as the Head of AI Strategy at Conga, where he joined the company in connection with the acquisition of Counselytics. Prior to Conga, Jason was the founder and chief executive officer of Counselytics, a New York City-based technology company focused on contract discovery and intelligence. Jason is also an attorney admitted to the New York and Kentucky bar associations. Jason began his career with Cravath, Swaine & Moore in New York, where he worked on a variety of transactions, including IPOs, mergers, stock and asset acquisitions and sales, joint ventures, and debt issuances. After Cravath, Jason worked at Morgan Stanley’s MSREF private equity fund in London, where he managed a group of London-based lawyers and bankers responsible for closing billions of dollars in private equity transactions throughout Europe and Asia.