I’m very excited to announce that I’m joining Pantera as a Platform Engineer, to work alongside Joey Krug, Terence Schofield, Franklin Bi, and the rest of the Platform Team to support the missions of Pantera and the teams in which it invests. In particular, I will be working on tech and infrastructure tooling that we will make available to our portfolio projects and in-house teams that address a range of crypto-specific needs.
My background is in artificial intelligence (AI), machine learning, and data science. I have spent the last nine years working in AI R&D consultancy at Cambridge Consultants, in the UK, where my natural tendencies to think in probabilities and want to see the data behind ideas – and my love of detective work and problem solving – benefited me greatly. I’ve had the pleasure of working with extraordinarily talented teams in fields like MedTech, Communications, Robotics, Defense, and Autonomous Vehicles. I was extremely fortunate that my interests and timing allowed me to have been deeply involved in the rise of commercial deep learning; I learned so much about what’s possible with the right teams, engineering and data, and enjoyed every step of the journey.
Now, I find myself drawn to new industries breaking out and advancing rapidly around blockchain technology. I see a lot of overlap and, importantly, opportunities to apply data science and AI. I was originally attracted to Ethereum as a distributed system, powering novel financial, governance and ownership models. Learning more, the data pulled me in. Transactions all recorded; contracts, logs, and networking all totally open; a vast real-time updating dataset of connections, events and state. Add to this a community experimenting and building on each others’ ideas and protocols to form new companies and organisations.
One of my goals at Pantera will be to bring the most effective techniques from AI, machine learning and data science to the crypto and blockchain ecosystem – and specifically to our portfolio projects – to ensure our founders and teams have the tools to leverage these datasets to the fullest extent. The accessibility of data stored on public blockchains is both extraordinary and unique in its enablement of, among other things, two key features: analysis and composability.
When I worked as an R&D consultant, one of the most common wishes was that we had talked to companies years before and recommended they record their data. Better yet, record in a consistent format. In the crypto and blockchain space, we have access to exactly that for on-chain data. Not only is it recorded in a consistent format, but all companies, protocols and DAOs also record data using the same base format, adding contract-specific parameters and logs. Of course there are differences across chains, but there’s still tremendous similarity and consistency across these formats. While far from covering everything you might want to know about startups or established organisations, it’s an advantage – and potentially a tool – that I don’t think has yet fully been grasped by those building in the space, much less harnessed and optimised by proper tooling.
Not all state-of-the-art AI techniques will apply, as always, and processing power drastically limits what can be done on-chain. Still, the popularity of data explorer and visualisation products like Dune and others already demonstrates the demand for early use cases. In traditional finance and other legacy industries, for example, analytics companies, marketing and operations research projects go to great lengths and charge high fees for their insights, yet still fail to achieve the same observability as is readily available on-chain. Properly extracted and understood, on-chain data would be a critical tool to help teams understand their market, users, and performance to develop better-informed product and competitive strategies.
There remain, as always, open questions that will shape what data is available and how it is analysed. How long are transactions going to be fully observable to all? To what degree will transactions become decoupled from identifiable wallet addresses and metadata? I don’t know the answer to these questions – nor, I think, does anyone – but they will be critical to the long-term arc of on-chain privacy and the use cases crypto enables. In the meantime, I’m highly optimistic about the future of our ecosystem, and feel fortunate to be partnering with some of the best minds in crypto, at Pantera, on fascinating opportunities for research, technical developments and investment.
Despite significant macro pressures, there are crypto-specific lessons from recent events that will make the industry stronger. Combining cutting edge data science, AI and blockchain engineering with investment and platform strategy that has a track record of success through multiple crypto cycles is an extraordinarily exciting prospect. I hope many join us for the journey, and I can’t wait to see what, together, we will manage to build.