👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
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Last week, Data-driven VC turned 1.
Time has a peculiar way of distorting our perception; it feels as if this journey began merely last Thursday, and yet, there are moments when it seems a decade has passed. Nevertheless, there's an undeniable sense that Data-driven VC is still in its inception phase.
Zooming out, the last 12 months have, without exaggeration, been a crazy ride, and you, the Data-driven VC community, played a pivotal role. Some highlights:
Data-driven VC newsletter and my LinkedIn account surpassed 13,000 readers and 33,000 followers respectively
Writing forces me to sit down, condense my thoughts, and form way sharper perspectives than I would’ve otherwise been able to. Clarity of thought helps me to become a better investor and us at Earlybird to build a better product for our investors
I’ve been invited to a range of leading podcasts, conferences, and round table discussions to share my perspectives on AI, data, productivity, startups, and the Future of VC
I’ve met and collaborated with people I deeply respect and admire
Our community is full of some of the smartest, most thoughtful people I’ve ever met, and whom I want to be friends with IRL
Today’s piece reflects what has brought us to this point. In particular, we’ll discuss:
Origins. Why I started Data-driven VC.
Growth. How I attract new subscribers and create engagement.
Process. How I write one piece every week while working as a full-time investor.
Future. What does the next year hold?
Let’s jump right in.
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1. Origins: Why I started this newsletter
Having spent 6+ years as a researcher and investor with the question about the Future of VC and how data & AI can help us make the investment world more efficient, effective, and inclusive, I think I have had extremely lucky timing to turn my occasional Medium writing into this more structured newsletter in September last year.
Just two months later, the launch of ChatGPT - a product powered by LLMs with most likely the biggest disruption potential for any knowledge worker job we have ever seen - took this newsletter on a big wave that I did not anticipate. Suddenly, the sentiment shifted from “VC is more art than science” and “this craftsmen industry won’t be disrupted” to “how do you use LLMs” and “we can replace majority of an analyst’s job with AI”.
Trying hard to not drown but surf this wave, Data-driven VC quickly became the go-to source for investors looking for guidance, ideas, and room to exchange thoughts on their journey to leverage data & AI within their cotton industry. Moreover, it provides valuable insights for founders, operators, and everyone interested in startups.
Why did I start working on data-driven approaches in VC in the first place?
The below quote is taken from my very first episode “What to expect from this newsletter”:
When I first joined Earlybird VC as an intern in 2017, I had anything but a clue about what VC actually was. However, I had one clear - for me very obvious - expectation: Those who invest in and support the most disruptive businesses on our planet would certainly be most advanced in terms of processes, tools and tech stacks themselves. If you see and feel cutting-edge innovation day in and out, why wouldn’t you operate that way yourself? Well, to tell you I was disappointed on this one is probably a vast understatement.
In the beginning, I thought it was only Earlybird, but speaking to some peers at other firms I quickly realized that it was actually an overarching problem across the VC industry. In retrospect, having had Salesforce as a CRM system in 2017 made Earlybird actually stand out at that time. Anyways, the only “real” digitization that VC has ever seen was the transition from pen and paper to mouse and keyboard. Surprisingly, progress has stopped at the MS Office Suite (and Covid-induced video calls..) That’s (mostly) the state-of-the-art in VC.
So back to the initial question: Why this newsletter? Together with an ever-growing group of like-minded people, I made it my mission to push VC to the next level through real innovation. To overcome shortcomings from inaccessibility for underrepresented founders over biased, inefficient and manual decision-making processes to non-scalable, sometimes very limited value-add. I strongly believe that technology in general, but data more specifically, is here to disrupt VC as it did/does with any other industry.
These few lines exemplify my strong belief that VC as an industry was about to undergo a massive disruption fueled by data-driven approaches and AI. Ever since I started diving into the topic, I’ve met a diverse set of like-minded investors with similar thoughts, yet could find neither content nor a proper community to exchange thoughts more broadly.
Following my research and some interesting conversations around this topic, I decided to condense my thoughts into “The Future of VC: Augmenting Humans with AI” around three years ago. Your incredibly positive resonance proved that I hit a nerve.
Why did I start publishing my thoughts instead of keeping it to myself?
Why did I decide to share it with the world? These and many other related questions came up uncountable times. And the answer is simple. I’m a big believer in community and open-source approaches. Open source leverages the power of community to overcome individual constraints. It assumes that collective wisdom is more powerful than any one individual can ever be.
Data-driven VC is like an open-source project with an open-core model. It’s a fine line between creating a oneway all-embracing brain dump that people can just take to exactly replicate what we did at Earlybird versus publishing useful, deep-dive pieces that provide sufficient value for an audience to trigger a discussion that eventually creates more value for the community but also myself and our firm. Value and ideas that oftentimes go beyond what I had initially imagined.
How do I draw the line between what gets published and what stays part of the “secret sauce”?
There is no silver bullet but my simple line of thought is that as long as I expect someone to figure something out by spending a few weeks or months full-time on a specific topic, it’s likely no rocket science and can be published to trigger a deeper discussion.
After all, I started out without big expectations. At worst, Data-driven VC would’ve become a weekly diary to condense my thoughts and form sharper perspectives on some of the topics close to my heart. At best .. well, I had no clue ..
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