Week2: Kung Fu
“I know kung fu.” — Neo from the Matrix, 1999
What we did this week and why
This week we made our first major decision–to begin building an MVP.
After a lot of thinking, reading, brainstorming, and talking with people we decided that at some point you have to dip into the desert of the real, and that point for us is now. Also, as friend and CTO of OnDeck Andi Klinger reminded me a couple days ago, there are always more reasons why a startup should fail than there are reasons it should succeed, which is true (try it yourself with any successful startup that comes to mind). Beyond a certain point, the consequences of doing nothing outweigh the marginal returns of further research. So this week we said fuck it, let’s get started.
What we didn’t discover from our research, was where we fit. It’s not ‘ed tech’ or ‘educational content.’ We’re interested in augmented learning, or using technology to get knowledge and skills wired into your brain so you can use them. That’s the DNA of the idea, even if the phenotype is unknown. As an aside, the internal name for this project is IKKF or I Know Kung Fu, from one of the coolest scenes in any movie. This scene is the vision. There’s so much to do before brain-machine interfaces, though that’s an area we will explore soon as well.
Weirdly, maybe the most important thing we learned from the process of doing the research is that we predict we’ll have the stamina to weather the downs and survive the emotional turbulence. Stamina comes from purpose and interest — it’s like the startup ketosis as opposed to the VC-hyped trend-du-jour unrefined high-glycemic-index mini-trip.
Anywho, we’ll probably fail the jump program, but you have to care enough to load it again. And again. And again. So fuck carbs.
As for what to test, we have a value hypotheses shortlist pick from:
- Anki for humans not developers
- A different paradigm of knowledge encoding (concepts instead of facts)
- Cued memory reactivation (haptic watch)
- Progressive mastery in memorisation
- Spaced ‘reading’ or combining reading and learning.
If there’s enough feedback, I’ll start a public notion page to go into what / how we’re testing and how we’re measuring in more detail.
Gratitude
I’d like to say thanks to Blazej Wieliczko, who used to work with us at Qriously and is now a machine learning and software engineer at Amazon. Few people profoundly change the way you think, even fewer do it across multiple disciplines, and even fewer still are excellent human beings. Blazej is one. Thank you.
