Science-Driven Development

Mon 14 December 2015 in programming

Ever once in a while everything seems to fall into place and suddenly the connection between previously unconnected dots becomes obvious. During the last couple of days, I've had such a moment. In this article I describe the reasoning behind my conclusion that The Lean Start-Up, Agile Development, Specification by Example, Test-Driven Development and Elon Musk's Secret Sauce are all based on the same underlying principle: the scientific method.


The scientific method is the process by which scientists [...] construct an accurate [...] representation of the world wolfs

The representation of the world is also known as model or theory, depending on its level of acceptance and applicability. A model may describe a phenomenon accurately only within certain limitations. We use many different models in our everyday lives in order to predict the outcome of our actions and we start forming then as early as when we learn that crying will yield food and attention. When it comes to achieving your goals, the known accuracy of your model is crucial.

For example, in order to save Lois Lane, Superman can pick between at least two models

A) Catching something saves it from harm.
B) Force equals mass times acceleration.

Using the first model, he will catch her while flying horizontally and rip her apart. If he uses the second model, he will realise that since he cannot changes Lois' mass, he has to also fly downwards and minimize her de-acceleration.

Both models are "correct" - meaning they hold under certain circumstances - as dropping an egg from the kitchen counter can easily demonstrate. Proving model A wrong is a little harder and might include dropping eggs from tall buildings. Falsifying model B is even harder and would probably require accelerating an egg to a larger fraction of the speed of light. A key principle of scientific models is that you can only show where it is incorrect, never that it's correct. There is no Truth, just , less wrong".

Improving the accuracy of our models might be the most important thing in our lives. And the only way to do so is by letting them collide with reality and discard the assumptions that didn't survive the collision. With each iteration you'll have a slightly less-wrong model. This is called the scientific method.

Scientific Method


The "Secret Sauce" of Elon Musk an other highly successful people is that they're really good at going through these assumption/validation loops. And the common principle of the before mentioned software development practices is that all of them optimize going through loops on different scales.

I identified three loops, whereas the outer precedes the inner.

Software Development Loops


Assumption What we're building is valuable to somebody.

Scale Weeks to months

Validator Market

Optimization Deliver working software continuously (agile) and collect real data from users and quickly as possible (lean)


Assumption This is how the system is supposed to behave.

Scale Hours to days

Validator Customer

Optimization Have costumer close-by (agile) and specify system in common language (BDD, Specification by Example)


Assumption The behaviour is implemented correctly.

Scale Seconds to minutes

Validator Tests

Optimization Automate tests and keep them fast (TDD)

Experiment is Supreme

Using the scientific method to solve engineering problems has the pleasant side-effect that it replaces inefficient discussions consisting mostly of guessing with the design and execution of experiments. Instead of guessing if your product actually solves a problem, build a simple prototype and find out. Instead of guessing the missing specification, turn around and ask the customer. Instead of discussing which software design works better, re-factor and run the tests.

Endless discussions can be an indicator that an assumption is based on a "magical" theory which cannot be tested and require faith to be accepted. Such a theory does not qualify as a scientific theory and should not be used in a decision-making process.

What I've experienced as a main hurdle when applying these methods is to avoid the error of mistaking an hypothesis for the explanation of a phenomenon, without performing experimental tests. Sometimes "common sense" and "logic" tempt us into believing that no test is needed. wolfs These believes can go very deep and questioning them might feel like an attack on our core values.

But being able to apply the scientific method openly and rationally to your projects and your life will greatly enhance your chances of success.

Wanna talk about it? Found typo or wanna add something? Edit me