Irish Beginnings

I grew up in Ireland as a highly curious kid that was totally obsessed with numbers. Even then, I sensed this deep fascination with how data could be used to reshape how the world works. Naturally, I was drawn to the sciences and ended up double majoring in Mathematics + Economics with a focus on Statistics at Trinity College Dublin, placing in the top 1% of double majors in my year. I was excited about being able to leverage my quantitative background in a technical finance seat.

I applied to an internship at Goldman after my first year at Trinity, excited by the prospect of joining a quantitative trading desk and apply advanced statistical methods—such as time-series modeling, regression analyses, and stochastic calculus —to forecast asset prices, backtest strategies, and implement systematic hedging strategies in real-world market conditions. Joining a trading team was a clear decision for me, as it was the only seat in Goldman where I could be responsible for capital allocation decisions within a year of joining.

Our internship at Goldman (& the first and last time I’ll wear heels to an office)

I ended up with offers to join both an equity derivatives and interest rate swaps trading desk and decided to join interest rates given it was one of the biggest revenue drivers for the division.

The Goldman era: Navigating the Public Markets at Goldman

I moved to London when I was 21 to join GS’s sterling interest rate swaps desk. I joined the team one month after Brexit, and was one of three traders holding down the fort from 2016 to 2019 when the market was filled with volatility and hedge funds speculating on what would happen to the economy and interest rates and interest rate swaps were about as pure an asset you could get for managing interest rate risk or speculating on Bank of England interest rate decisions. Navigating the Brexit-driven volatility felt like a baptism by fire, yet each day of unexpected economic data releases only strengthened my resilience under pressure. While there, I executed many $B+ dollar trades and rebuilt our risk models. I both devised and implemented a number of systematic trading strategies that contributed $10M/year to Goldman’s bottom line through predictive modelling.

During the few years I was there, FinTech was massively disrupting our day to day, with the buy side routing trades and price requests directly to traders through new software tools rather than through their sales coverage as they had done in the past. This was eroding margins and making sales people more redundant. Seeing this, alongside being a new user of Uber, Deliveroo, and Revolut having just moved to London, sparked a new obsession with how startups and new software applications could massively disrupt the world as we knew it. In particular, I was drawn to AI given I saw it as both a logical extension and highly valuable use case of the Statistics and Linear Optimization I had studied in college. The more I read about AI, the more I realized it was an extension of my passion for data, offering limitless potential to transform entire industries. After reading a book about Elon Musk in 2018, I was thrust into figuring out how to get to San Francisco so I could learn from some of the worlds best entrepreneurs and investors. I started taking online computer science and AI classes and applied to Stanford’s business school. Shortly after applying, I left Goldman to lead product strategy at an enterprise-focused startup that was building AI solutions for frontline workers. It was intimidating to leave the security of Goldman, but my drive to innovate in AI outweighed any fear of the unknown. I was extremely fortunate to get accepted to Stanford and had the opportunity to move out to the Bay Area in September 2019.

Stanford: A Journey into Tech and Entrepreneurship

First day of Stanford (& one of many beautiful blue skies over the next 2 years in Palo Alto)

Stanford was the most incredible experience for a tech nerd like me. I went from sitting in front of 8 screens on the trading floor to getting taught how to build and invest in generational tech companies that were having a huge impact in our everyday world. While there, I spent almost all of my time immersing myself in the startup world. From spending time working in product at Curated - a conversational commerce startup founded by serial entrepreneurs who had exited their last company to LinkedIn - to taking classes and hearing talks from world class VCs and entrepreneurs like Michael Moritz, Scott Kupor, Eric Schmidt and Andy Rachleff to name but a few.

In courses like ‘Startup Garage,’ I learned how to iterate quickly and validate assumptions through user testing—a methodology I’d later rely on. We also took more philosophical classes that taught us how to forget about our “limiting beliefs” and anyone who had ever dreamt big was encouraged to take the entrepreneurial risk now.

If ever there was one, Stanford was a safe space to start something new knowing full well you could and were likely to fail. Back in Europe, this may have been considered embarrassing, but in the Bay Area it was seriously respected to just try. I have always been a risk taker, and was grateful I’d chosen to surround myself with other people with such high aspirations and openness to doing something different, as I truly believe in the saying that “you're the average of the five people you spend the most time with”. I began working on a number of my own startup ideas, wanting to see firsthand what it might take to scale a company from inception and leave behind a lasting impact on the world as we know it.

Graduating from Stanford (w/ some lifelong friends)

I started to look for a co founder who could complement my skillsets and both shared my vision of the world and had a burning desire to build something big. In my last few months at Stanford, a friend of mine who had been on the engineering team at Airbnb recommended I meet Chirag, who soon became my co founder. His engineering prowess leading teams at Airbnb and Meta, and having worked on and exited a startup already, perfectly complemented my background and skills, and we shared a vision for building a generational company.

Retrera & YC: From Cold Emailing to Launch

We launched our first startup, Retrera, in summer 2021. The US was just going back to normal after Covid, and Chirag and I had a hypothesis about how the remote first way of working that had exploded during that time would impact the future of work. Initially, I cold-emailed 100s of founders and HR leaders, compiling feedback to refine our product before we’d even written a single line of code. A painpoint I continuously heard feedback on was how challenging it was to keep morale high in a remote first world. Startups were generally very well funded at the time given how much money had been pumped into the economy in 2020 and 2021.

Our first cofounder photoshoot

This easy money had also resulted in it being really hard to retain employees as tech companies continued to offer higher and higher salaries to poach talent. Most teams expected to need to come together in person a couple of times a year at a minimum but a lot of startups didn’t want the headache of organizing this. This had sparked the idea for Retrera, a B2B marketplace that helped remote-first teams plan in person events and improve employee engagement. The initial product would enable tech companies to browse and book hotels, activities and flights for their team events, with a view to building a suite of HR tools that helped with online events too.

We raised a preseed in July 2021 led by Bling Capital and got accepted to Y Combinator shortly thereafter. We joined the YCW22 batch in January 2022 having spent the last 6 months building Retrera. We had closed over 10 business customers, and reached $400k in annualized revenue.

Pivot Hell: The Road to Blaze 1.0

Despite the progress, we had realized that our customers didn’t just want help with the key components of their events that we could enable through a marketplace like finding accommodation, flights or activities. Rather, they wanted to outsource every last detail. In the initial months, I had done everything manually, personally handling every booking and agenda to ensure we truly understood the painpoints of remote teams. But kicking off 2022, we were starting to become dubious of how long we could “do things that didn’t scale” if we didn’t have line of sight to automating every task we were doing manually. Additionally, we foresaw challenges on the supply side of our marketplace. Existing hospitality management systems were not optimized to handle large group bookings seamlessly. Even if they were, we would have been facing an uphill battle, as many hotels and vendors were not ready to change their processes to accommodate large group bookings. Pivoting when you have made progress is even harder than pivoting when you have faced resistance every step of the way, but ultimately it was the right path forward for us. We were 2 weeks into YC when we formally took the decision to pivot and only had 8 to go before demo day. The financial markets were starting to falter as the Fed started hiking rates after the inflation from the easy money all through covid. We knew that regardless of the time crunch, we would have to maximize our chances of raising at the end of the batch in 8 weeks and couldn’t risk delaying our raise due to the pivot.

We promptly entered what the partners like to call as “Pivot Hell”. “Pivot Hell” is where you go when you spend too long exploring potential pivots and end up frustrated and without conviction in any particular direction. We were told that to avoid Pivot Hell, we should prioritize a new idea quickly and try and build traction there ASAP, then either continue with that or rule it out and pick another. But picking the best startup idea to pursue when the world was your canvas was not easy to do. We got increasingly frustrated as time went on - our batchmates were growing their MRR 20% WoW, and we didn’t know what our product did. To stay motivated, we reminded ourselves that every pivot is a chance to uncover a hidden opportunity—and we refused to stop until we found it. Eventually, we decided to focus on insights from Chirag’s time at Airbnb, where they built internal tools to analyze support tickets and prioritize product fixes that could most impact their conversion and revenue. We decided to commercialize this insight and build a platform that would automatically read support conversations from systems like Intercom and Zendesk and translate these conversations into actionable product insights for all businesses.