You need a business co-founder | #8

It's not about having a "business co-founder" – it's about a strong commercial mindset & de-risking with the right team.


Marc who’s joining me on this newsletter has a big day today: His product Octomind 🐙 is launching on Product Hunt. They’ve developed an AI-powered testing tool for web apps that finds bugs before users do – it’s solely based on your website’s URL.1  

▶️ Here’s a link to check it out. Let’s show our fellow founder some love with an upvote if you like it (aiming for +50% click rate 💪).

Now, let’s dive into today’s topic.

It is not uncommon to hear highly talented software engineers say that they are looking for a “business co-founder” as a step on the critical founder path.

Choosing a co-founder matters a lot. No other decision has a bigger path dependency on your company. That’s why it’s worth thinking this through.

Being a business co-founder vs. having a commercial mindset

So when you’re reflecting on the responsibilities related to the business side of your company, I would break it down into:

  • Generalist mgmt. & admin tasks (incorporation, financial planning, paying taxes etc.) —> Can be done by anyone smart and determined. It’s less about a special ability and more about having the appetite for doing these things well.

  • Commercialisation —> That’s a bit more complicated.

Entrepreneurial success is in its essence about two things: (1) Building a product and (2) selling it to customers, i.e. commercialisation.

To succeed with (2), a founder – usually the CEO – has to have a strong commercial mindset. What distinguishes the researcher and the hacker from the entrepreneur is being obsessed with value creation and value capture:

What’s the maximum impact we can create for our customers? What would people hypothetically pay for this? How can we sell more to existing clients? What’s the best path to acquire new clients? Why are we not growing faster?

A strong commercial mindset does not mean that you have graduated from business school, owned P&L responsibility at a startup or worked in sales. A computer science student who turned his coding skills into a side hustle with a couple of k MRR by discovering an underserved niche strikes me as more commercial than a top business school student with top-tier internships.

The success of technical founders

Google, Microsoft, Coinbase or NVIDIA – all of these generational companies were built by teams consisting exclusively of technical founders.

No doubt, there is strong evidence to support the claim that a lot of the most successful startup success cases have CEOs with a technical background.

For his book Super Founders, Ali Tamaseb has spent four years analysing almost 200 unicorns based on 40k data points. 50% of these unicorn CEOs have a technical background while only 40% of the CEOs of the control group (startups which raised $3M, not valued $1B+).

A 2023 study from Endeavour asked the question “Where Do Unicorns Come From?

One of the conclusions:

“Science and engineering training is far more common than business. 61% of founders majored in a science or engineering field in undergrad, compared to only 19 percent who majored in business. Computer science, electrical engineering, and mathematics were popular majors among those with science or engineering degrees. Science and engineering graduate degrees outpaced MBAs among those who continued to study, and for the 10 percent of founders who completed a PhD, most chose computer science.”

Endeavour, 2023

For any ambitious technical founder, it’s good to remind yourself of these data points and case studies. It’s easier to develop an excellent commercial mindset as someone with a technical background than to become a great technologist with a business background.

De-risking the idea through your founding team

Even though – as mentioned above – the raison d’être of a company is to build and sell, it would be oversimplified to translate this into “you need the techie who builds the product and the commercial person who sells it”.

Instead, I would dissect your idea into its core risks and understand how the co-founding team de-risks them. A co-founder de-risks your business if they help you gain an unfair advantage in some important way — whether it's with a core skill set that few others possess, a valuable set of relationships, or unique knowledge/expertise relevant to your startup.

Two cases which exemplify that it’s multifaceted: (i) Leveraging AI to draft legal contracts for lawyers —> A key risk is not being able to get the contracts right from a legal perspective —> Legal domain expertise in the founding team is crucial. (ii) Building a commercial open-source LLM security tool —> A key risk is failing to balance a free open-source distribution with effective commercialisation —> A deep understanding of software eng. & developers is essential for the commercial co-founder.

Instead of thinking exclusively about the co-founders for putting your – heist movie like – AAA team together, I suggest to consider the extended founding team. Exceptional early hires (incentivised by equity) can complement effectively.

Closing thoughts

Startup ecosystems are different – in metrics and facts but also in their narratives. Views are highly influenced by previous success cases. And these views are not updated equally fast as markets and technologies develop.

“Your co-founding team needs a business guy” is one of these views.

San Francisco based Y-Combinator made a video about misconceptions related to the need for a business guy. However, it’s probably the German startup ecosystem which needs nuanced and critical thinking on this topic the most. A large chunk of startup success in Germany has been about e-commerce & marketplaces. Ideas with key risks in operations and B2C customer acquisition, therefore, ideas where an (exceptional) “business generalist” as a founder de-risks incredibly well. I think that this past still influences some of today’s thinking on the founder team.

1 Disclaimer: I’m also an angel investor in Octomind.

Founder’s view: Marc Mengler from Octomind 🐙 

Marc Mengler is a 3rd time AI founder (exited He’s the CEO & Co-Founder of Octomind (soon tba seed round), an AI-powered testing tool for web apps that finds broken functionality before your users do. The combination of his technical and business background makes him a great interview partner.

As a serial entrepreneur, you went through various cofounder constellations. How has your view on “founder-idea-fit” developed over these years?

I had the honor of working with amazing technical co founders, many of which were smarter and more technical / experienced / capable than I am. In some cases, it just wasn’t a founder-idea fit: one can usually tell after 4-5 weeks of working together, if there’s a founder-idea-fit for the founder team and if working in that constellation for the next 5-10 years is the right thing to do or not. Sometimes, I pulled the trigger, in other cases my potential cofounder. For me as a technical and product-minded founder, the idea cluster is just as important as the cofounder: I can only sell what I believe in and understand from the ground up. This means, I always do my own research and completely live in the problem and idea space. I know it’s the right idea if I lose interest in other startup ideas and if working on the idea and talking to the target customers doesn’t feel like work. If you are not motivated by solving your customers' problems or spending 10 hours every day with them, it’s not a fit.

Prior to starting, I had no expertise in autonomous driving or the automotive industry. But over time, I immersed myself into it and I think within 6 months and a lot of hard work, almost anyone can achieve founder-idea fit. That means over time, founder-idea fit becomes less relevant and founder-team fit becomes more important. I am a big believer that all founders should be technical as the goal of every founder should be to automate themselves away.

How important have technical skills & understanding been for you in the CEO roles at Octomind and previously at

I have always been a generalist interested in almost anything. But it was a road leading nowhere until I specialized in deep learning in 2014. Without insights from my own research, and octomind wouldn’t have been possible. My technical skills and understanding serve as the basis for everything I do every day. This is especially true in machine learning where progress is not always tractable and it sometimes -even to seniors- feels like alchemy. Technical understanding and knowing how to establish baselines, contrast different approaches and see patterns in graphs, their convergence behavior and team-compositions is crucial. So is the understanding that without good and scalable processes for data infrastructure, ETL, data acquisition, data balancing, quality assurance, no AI team can be productive. Only from good table stakes, good AI can evolve.

What’s one piece of advice you wish you had known earlier?

No one cares about your tech. All your customers care about is how much money it makes them or how much it saves them.

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