The Metaverse, hole-digging, and the experiment equation

Published almost 3 years ago • 2 min read

Hi nerds -

I salute you from Barcelona, after enjoying the last few days roaming around Paris' cobblestones.

Live music, tango dancing, scooter-driving, cute bookshops, lush parks, and hipsters - European summers will always have a sweet spot in my heart.


3 brain farts

🥽 Metaverse School: I’m growing increasingly convinced the Metaverse is the next classroom.

Rather than riding the bus, a VR headset, cheaper than most laptops, will transport students to the Metaverse School every day.

Understood as a persistent virtual space where people have identity and assets, the Metaverse is where reality and cyberspace converge; it is the Virtual Reality world we design and join.

Within it, students take history classes by immersing themselves in 17th-century Roman streets. They take gym classes playing frisbee without gravity and learn business by engaging dynamically with experts from around the world.

Hardware, networking, computing, payments, behaviors, platforms, and assets - a lot is under construction to make sure this succeeds. But with VR being Facebook’s fastest-growing department and digital fashion being an industry expected to earn 50 billion dollars a year, I wouldn’t be surprised if we reach it faster than we think.

VR land

🏋🏼‍♀️ What, how, and why: Most of our life is based around us figuring out what we want to do and then doing it. Easy, right?

Interestingly enough, most of us will spend so much time figuring out the what, that we never actually get to the how - even when this is what’s taught most in our education system.

What we often miss is that this is a positive feedback loop: the less seriously we take the “figuring things out” part, the more we dare experiment, the better we become at “figuring out” what we want to do, the faster we learn why we want to do it, so the better we do it.

🧪 Experiment Equation: Experiments are usually composed of a problem, a solution, and a set of risks.

  • Problem: based on data or experiences, this is the main thesis of what we’re trying to fix by running the experiment and the reason why we do it in the first place.
  • Solution: based on what’s been historically done and the current context. This is the idea we think will solve the problem; the experiment itself.
  • Risk level: the risk associated with running the solution and failing. Consists of two parts:
    1. Depth: how bad the consequence will be if the experiment fails.
    2. Likelihood: the likelihood that the experiment fails.

Experiment's success = problem / (risk depth * risk likelihood)

2 intellectual goodies

“The most important thing to do if you find yourself in a hole is to stop digging."

~ Warren Buffet

Digging holes

"Catch yourself whenever you are about to criticize someone, and ask yourself what you are secretly jealous about."

~ Orange Book

1 funky audio

This playlist is for those of you who enjoy English indie music. I usually play it on my way to the mountains or during weekday hangouts with friends.

alt_ playlist by Juliette Chevalier

Thank you for reading.

As always, feel free to connect by hitting reply and sharing a juicy thought 💡.

We all help the curious community grow 🧠.


Jules 🤸🏻‍♂️


Learning to code is 21st century super-power. I work as a Software Engineer and teacher around the world. My purpose is to empower others by showing them what we can do with our brain, a computer and wifi.

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