Preface

These days, I wear many hats. I anticipated this when I decided to start a startup, but I've taken on even more roles than I expected. I expected to be an engineer, I never anticipated being a cookie delivery boy; I expected to be a salesman, never a janitor. You get the gist. 

One of my roles is to understand the nature of new technology like Artificial Intelligence and how it will change financial compliance. I feel fortunate that I get to work on this part of my job because it’s something that I have been interested in for a while. 

My first job out of college was consulting at Google, where I got to see the inner workings of the AdWords data science machine and then worked on establishing analytics for Google's recently launched smart speaker line, Google Home. AdWords made a ton of money but was a crummy product; Google Home was a good product that lost money. I was living in San Francisco, reverse commuting to the suburbs, and I met the author of my Johns Hopkins macroeconomics textbook in a restroom after a presentation.

None of this really made sense to me. So, in a fit of reckless ambition—or boredom, you tell me — I decided to join a company that was in an interesting position and thus was recruiting people with inadequate credentials into important positions. When I joined Castle Global, Inc. (now known as Hive), they had just decided — with $10M+ in venture funding from General Catalyst — to pivot away from mobile phone applications to become an enterprise AI company.

Back in those days, there weren't many enterprise AI companies. The Hive founders immediately foresaw many of the AI innovations of today. The projects I worked on included building what was — for a brief time — a market-leading data labeling solution (now a $10B+ business), an analytics business centered on using AI to measure TV trends using device data (now a $2B+ business), and one of the first systems — which I personally coded — to extract information from complex insurance documents at a top global reinsurer.

The document tech never made it out of pilot. It was too early — AI technology wasn't where it needed to be for the product to be viable with adequate accuracy. Always a pivot away from a unicorn valuation, Hive found success by moving into a different market and built the content moderation company that it is today. I changed jobs when I left San Francisco for a change of pace during the pandemic and built fintech systems used for things like Form 5500 filings and recordkeeping 401(k) plans at Guideline for a few years.

In 2023, Ed and I — friends since our 18th birthdays — drank too many mojitos while visiting Miami and decided to start a business together. Oddly enough, we noticed that if we started an AI financial compliance company, we would have a clear expertise advantage about the application of AI and, possibly, enough knowledge about compliance to be dangerous. We started Y Combinator in January of 2024. I panicked and enrolled in the NSCP law school course to become a Certified Securities Compliance Professional during the YC batch, and we were off to the races.