Meet the Masters - Mike Arpaia, Moonfire

MIKE ARPAIA

Mike Arpaia is a Partner at Moonfire Ventures, a European pre-seed and seed-stage venture capital firm which just raised a $60m fund to support founders at the earliest stage. Pete Alexander, Director at The Up Group, talks to Mike about his transition from Machine Learning to the VC world and about early-stage technology in Europe. Mike discusses his career path to date and why now is a great time for European early-stage venture.  

Moonfire just raised $60m – tell us more about Moonfire.

Moonfire is a pre-seed and seed-stage venture capital firm, completely focused within the European region. We primarily invest in four sectors which are capital and finance, work and knowledge, gaming, community and leisure, and health and wellbeing. We are a very thesis-driven investment firm.

I would say our key differentiator is that we are a truly data-driven VC, powered by software and machine learning. l like to say that we are a technology company specialising in venture, rather than a VC firm that uses technology. Although this may seem like a subtle difference, it’s an important one, because in addition to talking about how and why we use technology, it also has implications on how we organise ourselves, how we work, how we collaborate and communicate, and how we prioritise what we focus on.

What is your background, and why did you decide to join Moonfire and move into VC?

Ok – here’s a whistle-stop tour! For the first few years of my career, I worked as a professional hacker and whilst I enjoyed breaking things, I started to progressively enjoy building products so I took a job at Etsy as a Software Engineer in the security organisation. Here I fell in love with distributed data systems and became the youngest person to ever be promoted to Senior Software Engineer (a record that still stands!).

From there I moved into a Software Engineer role at Facebook, primarily focused on infrastructure analytics and operating system monitoring. I went there with the intention of building a new capability for them in this space and built a tool called the osquery, which is now the most popular security project on GitHub. I then pursued a role as Engineering Manager at Facebook, responsible for the intrusion detection infrastructure team, which was a fun, high-stakes real-time analytics role.

After Facebook, I wanted to test myself in a start-up environment and became Co-founder and CTO at an infrastructure analytics start-up which aims to democratise osquery infrastructure for the masses. We built a lot of interesting distributed systems with a completely remote engineering team. I then wanted to focus on more of the technical machine learning aspects of the analytics that we were doing so I took a role at Workday in the US, where I was the architect responsible for a distributed search and recommendation system which used modern deep learning from natural language processing techniques.

Having moved to London for personal reasons in 2020, I was keen to explore opportunities where I could focus on machine learning in an earlier stage context. I met Mattias [Ljungman] who pitched this idea of building out a machine learning powered, data-driven, venture capital firm. Whilst a lot of VC firms talk about their origins as a technology company, that is often not the case; whereas the difference with the Moonfire opportunity was that Mattias understood it in a way that I felt may people had not in the past. And secondly, as full-time employee number one, I would really have a hands-on role in defining that.

You mention that at Facebook you went from Senior Individual Contributor to Manager. It’s a decision that lots of engineers have to decide upon, whether to step into a managerial role or to enjoy the Individual Contributor route through different seniorities. How does that thought process work and how do you decide on the route?

Companies approach this in very different ways. I was lucky insofar as at Facebook, there was a lot of support for engineers that make that transition and it’s a very well-defined path with a lot of access to educational resources, classes and learning material. I’m very grateful that I had that opportunity because I learned a lot about engineering management philosophy which is something that I’m extremely passionate about. At Facebook, when you become an Engineering Manager, you are a full-time people manager with limited hands-on engineering which is a significant context switch, and you really must love the people / management side of things to be successful.

I learned a lot about myself during the transition, one thing being that it was the first time since I was a teenager that I wasn’t coding every day. I realised that it is a fundamental part of my personality, and so after my role at Facebook, I have definitely tried to pursue roles that involve hands-on contribution, including Moonfire where there is a significant strategic aspect to my job but also an individual contributor element.

It is a challenging decision, and there are not a huge number of relevant senior engineering roles in the market at any one time, and even fewer senior engineering opportunities as individual contributors. There is also a big difference between Europe and the US on this topic, in that the archetype of a senior individual contributor does not yet exist as much in Europe as it does in the US. 

What role can data play in VC?

When I first met Mattias, he told me that he wanted to build the most quantitative venture capital firm in Europe. Equipped with data, algorithms, and custom-made software, Moonfire would set the standard for a new paradigm in sourcing, evaluating, and managing investments. The vision was to establish a new form of venture capital where a team powered by software enhances its ability to execute with better knowledge and greater velocity than anyone else in the industry.

VC firms talk about being data-driven all the time. What they mean is they use data to inform and accelerate various decision-making processes in venture capital. We’re not just creating a single model and integrating it into a traditional pipeline. We’re building out operations from the ground up and approaching the problem like a software development project.

Our sourcing, screening, and evaluation process is a production-grade data pipeline. Throughout this pipeline, we make a series of decisions. Whenever we have an opportunity to use a learned model to facilitate better decision-making, we do so. When we have a series of companies or founders to filter through, we reason about the problem as if we are building a modern search and recommendation system.

All of this is to say that we use data throughout the entire venture capital lifecycle, at every stage of the process.

As an American who moved to the UK in the last 18 months, what are you most excited about in the European tech scene?

It is such an interesting time in Europe. The tech industry is just a bit smaller than the US in terms of the number of scaled companies, but we are at this interesting inflection point where things are starting to pick up rapidly. The number of unicorns in Europe are starting to increase at a very significant rate. I think the US market is saturated right now, and Europe has so much opportunity with enough capacity and established expertise for it to be really taking off. It has the core infrastructure and enough established processes of existing unicorns for it to be a high-growth region. For me, it is still a golden age of European technology, with an untapped market full of opportunity, a bunch of entrepreneurs who hold diverse perspectives and who are all eager now they have access to capital. It’s exciting and I think we’re at a great point for European early-stage venture. I’m so happy to be involved in this ecosystem.

In your view, how has the pandemic changed hiring practices?

At Moonfire, we are seeing a systemic breakdown of geography, talking to European Founders and how they are going about hiring. Companies and investors don’t care as much about where people are based. Companies such as Omnipresent and Deel are making it much easier and more sustainable to hire people across various geographical regions, whereas before it was relatively prohibitive. The deconstruction of the office space has made it such that most companies are open to hiring people across the continent and across the world in general.

This is helping companies because they can tap into a much larger market of talent, finding the optimal talent for them, and often they can find talent in markets where the cost of living is not as expensive, which in turn makes the talent less expensive. The removal of massive office space as a line item is also allowing companies to operate much more economically, which is beneficial to early-stage Founders because you can get so much further for less.

Before moving into VC, you were a Founder CTO and a machine learning software engineer - in your view, how do you create a high-performance culture?

I think it comes down to establishing a culture that emphasises a combination of both velocity and quality. In sufficiently early-stage companies, velocity is everything; you have less funding and fewer resources than the incumbents, you have fewer people and less marketing power. The key difference is that you can move more quickly than your competition. Velocity, however, is not sustainable long term if you don’t have the quality to back it up. Quality from an engineering perspective is key and without it, you are not going to be able to scale your infrastructure as you try to onboard more customers.

As a Founder, I think the key to building a high-performance engineering organisation is establishing that line between velocity and quality and being true to yourself about where your team indexes along that line, focusing on any weaknesses on either side.

What is your career highlight to date?

If I had to pick one, it would be building osquery at Facebook and being part of that project. Every security practitioner’s objective should be to make the internet a safer place and for me, there was no better way to do that than create a piece of software, open source it and have it become a very foundational piece of infrastructure that now the entire industry uses to stay secure. Thousands of companies use osquery every day and whilst I no longer actively work in information security anymore, I know that the fruits of my labour are still adding value and protecting people.

Are there any books that have influenced your career or leadership style that you would recommend? 

One book that fundamentally changed the way I reason about technology – and everything really! – is a book called The Field Guide to Understanding Human Error by Sidney Dekker. Assuming good intent and that people want to come to work to do their best, how do outages or errors occur? People are quick to highlight things as human error but, by doing so, you are fundamentally eliminating the ability to find the deeper issue. The book delves into the missed opportunities by labelling human error as the cause and gets you to question why decisions were made at the time and how to learn from the mistakes.

The Moonfire team.