👋 Hi, I’m Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with Data & AI. ICYMI, check out some of our most read episodes:

Brought to you by Affinity - Campfire 2025 is coming to London!

Private capital teams are drowning in emails, data, and shifting markets—just as competition for the best deals reaches new heights. On October 28, 2025, Affinity Campfire London will bring together leading investors, dealmakers, and operators to turn that noise into actionable insight.

Join peers for an afternoon of networking and hands-on learning. From smarter sourcing and fundraising to practical AI integration, you’ll take home proven tactics, hands-on demos, and real-world success stories you can deploy immediately.

Following last week’s episode on why now is the best time to start leveraging AI for investing, I’d like to share my personal retro after 8 years of pushing AI & automation into VC and the honest truth about what I would do differently if I’d need to start all over again today. No fluff - promise.

Let’s jump in!

Don’t reinvent the wheel: Learn from peers!

One of the most surprising patterns I keep noticing is how many people try to solve a problem entirely on their own—despite the fact that it has already been solved before. Peer exchange? Community? Internet? Seems like untapped land for too many people. Specifically when it comes to tech for VC.

Over the past years, I’ve seen majority of VC firms operate in the dark. Because it’s “their secret sauce”. Sure, dream one. Your web scrapers, entity matching, and access to highly innovative sources like Crunchbase and Harmonic is really cutting edge.

In all honesty, 95% of what I see investors, product leads or engineers at VC firms trying to solve for has already been solved, and it’s really not a differentiator at all. The ones who have solved it, oftentimes openly speak about is as they know it’s far from secret sauce.

To foster peer learning and community exchange, I’ve had various thought leaders from our community share their learnings and what they’d do differently today. For example, we had Alex Patow from Inflection VC (and ex EQT) share his learnings of building tech with limited resources for a micro VC fund or Ali Almufti from BlackRock writing about forecasting for private market companies. We also had more than 100 speakers from firms like Accel, Atomico, Index, Moonfire, Seedcamp, and more share their learnings and behind-the-scenes at our virtual and physical summits & roundtables - most of them recorded and available here.

10 do’s and don’ts to bring AI & automation into VC

Condensing all the valuable learnings from our DDVC community and pairing it with my own journey across the last 8 years of transformation Earlybird VC with AI & automation (with significant resources and a dedicated engineering team), here’s the brutally honest truth, lessons learned, and how I would start if I’d need to do it all over again today - all packaged into 10 items:

1. Community: Join like-minded peers. You’re not alone.

When I embarked on my tech for VC journey in 2017, I felt lonely. Everyone told me “it’s not possible” and “others have tried” but nobody - except my partners - encouraged me to push for change. The industry was just not ready.

Fortunately, I trusted my instincts, similar to a few other lonely soles I met during my PhD and first years as an investor. We began connecting, exchanging our struggles, brainstorming, and contemplating the future of venture capital through one-on-one discussions. Gradually, these conversations evolved into small WhatsApp and Slack groups, which have been expanding steadily over time.

These groups still exist and are great, but it’s super fragmented and thus we decided to launch The Lab last year as a dedicated resource hub and community for like-minded peers. With 150+ members ranging from micro & solo GPs to early-stage, growth, and multi-stage firms, the community keeps growing fast and hopefully establishes itself as the central point to co-innovate when it comes to tech for private market investing.

2. Sponsors: Get top-down support from your GPs.

Once you surround yourself with like-minded peers, you will quickly understand where the industry is heading and what you can do to not miss the train. Once the direction is clear, you need buy-in from your GPs as every investment in tools and engineering HR will cut from their profits.

So better have a convincing story as the lack of top-down buy-in makes it a no-starter. Make sure you’re all on the same page. How much are you willing to spend? What are the expectations?

3. Focus: Define what you actually want.

Many funds don’t take the time to craft a plan and out of a perceived pressure rush into doing something for the sake of doing something. They start buying datasets and comparing CRMs without actually knowing what they want. Don’t be one of them.

Take a step back and define your firm’s strengths and weaknesses. What works well and what can be improved? Thereafter, define where you want to go. What is your north star? Once you know where you are and where you want to go, ask yourself on how you can close the gap.

While for some the north star is increased deal flow and coverage, it’s better prioritization and access for others. Define your goals and be critical about which initiatives contribute to your ultimate goal. Don’t get lost in the noise and just try to copy what others have done. Even worse, don’t be reactive to the masses of tool providers reaching out. Be proactive, do your home work, know what you want. Ignore the rest. Focus. Focus. Focus.

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