Try It and See

Imagine you have an idea for how to solve a problem or achieve a goal. The question I want to answer is this:

How do you know your idea is right?

Try it and see

When someone raises their hand with an idea, it’s because they’ve already imagined a future in which the idea is implemented. In an instant, their brain ran a simulation of what life is like in this new-idea-world and reported back that it liked what it saw.

Often our imagination gets it right. Say it’s lunchtime and you’re hungry. To decide where to eat, your brain will imagine your future self having lunch at different places and send back results telling you which option performed the best against a bunch of different criteria that are important to you. All of this happens so fast and so easily that we don’t notice it’s happening.

When not to trust your brain

We can trust our mind’s predictions about where to eat lunch because we’ve run the what-will-I-enjoy-eating experiment and gotten unequivocal results so many times that our mental guess-and-checks are accurate enough to rely on.

But what happens when...

• The success of your idea depends on other people’s reactions.
• Your idea involves something that’s never been done before.
• Your idea has been tried before but never in this exact way or in this exact environment?
• It’s really expensive to make the wrong choice.

In these situations our beliefs are likely to be misleading because our brain doesn’t have a reliable model of reality.

To make good decisions, we need a more accurate try-and-see simulation than our mind alone can provide.

Try it and see IRL

The answer is simple: After simulating ideas in your brain, try them out in real life. Go from an imagined future to a tangible present.

The trick is to do the IRL part quickly and with minimal risk. Our brain might not always be right, but at least it ~~jumps to~~ reaches conclusions almost instantly.

How do you do the IRL part quickly and with minimal risk?

Examine your beliefs

First figure out what you need to learn.

There is no learning without having to pose a question. And a question requires doubt.

A person’s ideas represent their beliefs about the world and how it works. By testing ideas, what we’re really doing is challenging a set of beliefs.

So ask yourself: What beliefs underpin the success of this idea?

List as many beliefs as possible and place a question mark at the end of each one. This list of questions is what you need to answer.

The value in testing ideas is not in proving ourselves right, it’s about filling gaps in our knowledge so that we have a more accurate model of how the world actually works. It’s by questioning our beliefs that we reduce the risk of being wrong and increase the chances of being right.

Place small bets that have asymmetric risk

With a list of questions in hand, the next step is to get credible answers as quickly as possible.

The fastest way to get credible answers is to build a prototype and test it a real-life situation. Prototypes are like small bets on certain ideas and beliefs. The value of what you learn from a prototype should far outweigh the time it takes to create it.

Start by building prototypes that can test the most fundamental questions on your list. If your most basic assumptions aren’t true, there’s no point testing the others. Your first prototypes should be the fastest to make and the easiest to change.

Once you’re confident in the fundamentals of your idea, you can start exploring its nuances by creating and testing more detailed prototypes.

Update your model

When you test ideas in real life, you get to see the difference between what actually happened and what you expected would happen. The gap between the outcome and your expectations is what translates into knowledge.

Ask yourself: How do I reconcile my initial assumptions with what I observed?

Look at your original list of beliefs, make note of what was challenged, and think of plausible explanations. Turn these explanations into questions and add them to the list. This annotated and expanded list is actually a slightly more complete and accurate model of reality.

Evolve your idea and try again

With a more accurate view of reality, you’re now in a position to make better predictions. Apply this newfound predictive prowess to think of even better versions of your idea.

Keep repeating this try-see-learn process until you’ve answered most of your questions and you’ve got something that’s working to solve your problem or meet your goal.

Now, what’s good for lunch?