How I Make Decisions?

A curious fact about human nature: we tend to resist validating an unrecognized pattern until it repeats.

You faced a new problem that made you wonder if it’s some sort of magic.

“To stay balanced while riding a bike, you need to keep moving.”

At first, makes no sense.

You think:

“How does moving stop me from falling?”

You live with it. Until you watch someone spinning a top.

You notice,

“The top only stays upright while it’s spinning.”

Then it clicks. Redirecting motion creates balance. You matched the pattern.

You store it under anything that looks like a circle in your brain’s filing cabinet and move on… until you face the same problem from a different angle again.

“Why doesn’t the moon ever fall? Must be because it’s spinning!”

It must be the motion again.

Well… almost.

If you dig deeper, you realize why the question itself is biased. The bike is slowly falling; it's precisely how orbital mechanics work. The moon is slowly falling; it’s in free fall around the Earth and yes, the top is slowly falling.

So all previous explanations were... not wrong. but not global facts. They were useful perceptions of being right; but never global facts.

Perception of Being Right

People tend to optimize for being right because, deep down, we know that making an absolutely correct decision is practically impossible. We can’t even prove that such a thing exists.

The irony is that the previous claim can’t be proven unless we believe that we need to factor all the data in the universe, including giraffe population density, and weigh their relevance to a desired goal.

But then, how do we really know that water boils at 100°C? we’ve ran the experiment a lot that we just trust the data we observed. It's a high-confidence guess based on stuff we deeply believe.

Making the right decision is how well you convince those around you that a particular action is likely to achieve a desired goal.

When both audience and decision makers share the same data and motivations, the relation between truth and the perception of being right follows a logarithmic pattern. It’s easier to convince someone with little data to become somewhat right than to convince someone who is somewhat right to accept the absolute truth. People will resist the truth when it conflicts with their inner beliefs. The data people have is limited compared to how complex the world is.

People are convinced that you are making the right decisions when you:

• Convince them from “I know nothing“ to becoming somewhat right enough

• They rely on your track.

• They processed all your shared data and had similar beliefs and motivations as you.

In order to be right and make the right decisions you have to prove that going from nothing to somewhat right was the right thing. And the only way to prove that you are right is making an action.

Making decisions are rarely one time events but it’s a stack of actions. if you couldn’t reach a proof it means you lacked data, therefore you collect more data and try again.

A proof is connecting points of similar patterns that the culture deeply trust, a typical VC that invests in pre-seed would look for revenue or at least attraction as a proof that your business is right. because successful startups had these patterns and now VCs deeply trust those metrics.

Does that mean if you don’t have initial attraction or revenue means you're doing it wrong? not necessarily, Shopify was founded in 2006 but their moment was around ~2014. but If you kept approaching VCs with data and claims they oppose and you execute it right, you’ll be labelled as someone who has a good proxy of judgement.

Making the Best Decisions

I think of decisions as if they are a stack of actions. when you decide to start a business, this is at least 5 years project. There might be later new decisions to modify some aspects or reverse specific actions but that doesn’t cancel your initial decision it just extend it.

Whenever you make a decision you create a new branch of the root decision, if that new decision is irrelevant to the knowledge base you have, then it’s considered a root decision.

For instance, you start a startup in the field of fintech, but later you pivot into making it a design tool or similar. your first decision is also your second one but you branched after gaining more data and that is good. because if you never branch it means you never processed the data.

Since decisions are branches based on your knowledge base there is still another factor to bring in which is: weighing the relevance of the data, mostly to revolve around the culture, the culture could be your users, business partners, personal relations or the people that is relevant in your data. Having more concrete data does bring you closer to absolute truth, but if your knowledge wasn’t weighted against what people would perceive you as right, you’d risk being too early or out of touch.

When I optimize for absolute truth, I often challenge the beliefs of those around me, which usually leads me to solutions that few resonate with. But when I prioritize fitting into the culture and resist my own thoughts, I become more of a salesman than an engineer.

Tuning between the culture and my own beliefs was the easiest way to make my best decisions, came up with new techniques or solutions that served made way easier to be adopted.

If you lived in the mid centuries and come up with a radio you'd most likely freak people out and you might even risk getting executed. because you challenged all the beliefs and basics that culture had developed and deeply trust.

If you lived in the mid centuries and were more in touch with the public (customers), you'd most likely come up with something more likely to be redundant but was called the right thing on the expense of the civilisation advancement.

Electric cars existed since the late 1800s, AI has been used in business since the 80's, blockchain fundamentals were at least since 2000. these didn't take off mostly for cultural reasons.

So how do I make the best decisions on key questions? processing the culture while keeping up with the edge of human capabilities, those two should be tuned when answering key questions, in engineering decisions you lean to modern because the knowledge base of your colleagues should be more similar, in business decisions you lean to the culture because you are a customer obsessed.