implementation

The key to a good life is not giving a fuck about more; it’s giving a fuck about less, giving a fuck about only what is true and immediate and important.

But what are the three emails you regularly get from Uber? “It is now cheaper than it was before” (lowered inhibiting cost), “There are now more drivers on the road” (lowered inhibiting wait time), and “We can now go somewhere we couldn’t before” (lowered inhibiting range). Uber’s entire business is based on reducing inhibiting pressure.

Pilots are tightly scoped interventions that we expect not to work (remember, we have to explicitly prove efficacy as a defense against confirmation bias), so we use small populations, focus on speed to market, and do them in an operationally dirty way. Besides being fun to say, “operationally dirty” just means that we’re shooting for minimal

What are the tangible actions to take? 1. Build a durable base of specialized knowledge to understand and consistently interpret the world 2. Have the highest quality of information flow from the clearest thinkers 3. Identify all of the ways people don’t want to embrace uncertainty, chaos, imperfect knowledge, and risk. Take the bets no one else

Risk Reducers (Your Safety Net):

• The hiring manager at [Company X] could offer you a job tomorrow

• The investor who funded three companies in your space last year

• The mentor who’s navigated exactly the minefield you’re facing

• The industry veteran whose recommendation opens any door

What is the pain that you want to sustain?

We want to highlight that time-series and cross-sectional momentum are often used in a market-timing or asset-class selection context.

That’s all a potential insight really is: the recognition of some potential split and the opportunity to move closer to the utopian end of the spectrum. A potential insight expresses the distance between those two universes and, once validated, allows us to start understanding the gap and how to design interventions that bridge it.

Study after study shows that individuals who are motivated correct more naturally—and more correctly, so to speak—than those who are not.