Hi, I'm Jan König 👋. I'm one of the founders of Jovo, 28 years old, and live in Berlin. < Go back to learn more.

3 things I learned at the Lean Startup Reloaded Stammtisch

This week, Kevin Gödecke and I organized the first Lean Startup Reloaded Stammtisch (a common thing in German bars: a regulars' table [Wikipedia]).

I you remember: I wrote about "What happened to Lean Startup" last week, thinking about reasons why the methodology doesn't seem to be as common (or at least present) these days

Here are 3 things I learned at the Stammtisch on Tuesday:

  • MVP: There's still big misconceptions of what a Minimum Viable Product really is.
  • Hypotheses: Coming up with quantifiable hypotheses at an early stage seems way easier in theory than it is in practice.
  • De-risk: Don't follow Lean Startup in a dogmatic way, but use elements to de-risk the riskiest assumptions about your business.

The Misconceptions of the MVP

In last week's newsletter I mentioned that the term MVP (probably the most popular concept of Lean Startup) is widely misunderstood today.

  • M for minimum: This is often confused with "ugly," but should be more about the main functionality that is needed to provide value. Customer expectations have gone up, which means in some fields a polished tool might be required (see Notion).
  • V for viable: This is also a kind of ambiguous term that can be interpreted in many ways.
  • P for product: Does product really mean product, or is a landing page enough at the beginning?

My thought was that every Build of the Build-Measure-Learn feedback loop would mean to define a new MVP. However, Maxim Lapis argued that the focus is on product, so an MVP should be the minimum version of a product that can be sold.

Apparently it can take quite a lot of iterations through the loop to define the MVP.

The Challenge of Defining the Right Hypothesis

At the beginning of his project XD2Sketch, Kevin created a landing page and spread the word at places where his target audience would hang out.

And it worked: He got many email signups that then led him to building the complete thing (which was quite a lot of effort). Learn more about his story here.

We asked him if he had a number of signups (= a quantified hypothesis) in mind when setting up the landing page (= the experiment). He responded: "I thought about this, but it was super difficult to come up with a number that didn't feel arbitrary." So instead, he decided to have the number of sign-ups inform his gut-feeling. And when the number of sign-ups felt right, he built the tool.

I've experienced this myself. Especially at the beginning it's difficult to come up with hypotheses that aren't arbitrary. This often leads people to dismiss the experiment-driven approach of Lean Startup overall.


Maxim brought something up that I had forgotten: Lean Startup and its idea of hypotheses can be a lot easier to grasp if you don't think about experiments and hypotheses. Rather, he mentioned that it's important to find a startup's riskiest assumptions and then use experiments to de-risk those.

This reminded me of a post by Ash Maurya: "The true job of an entrepreneur is to systematically de-risk their business model over time."

The riskiest assumptions can be more than just "can we build it?" or "can we sell it?" If you take a look at Maurya's Lean Canvas, any of the 9 areas of a business model can hold risks:

Any questions about these 3 thoughts? Have you had the same challenges? Hit reply!

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