This post is part of a collaborative blogging effort at Startup Edition. This week’s edition is about the greatest startup hack you’ve seen.
My dad has one exemplary skill that brought him out of poverty in Taiwan and over to the U.S. with a few hundred bucks in his pocket, which he spun into a Ph.D. and eventually a full professorship at a major research university—he’s good at math.
I remember hanging out with my dad and some of his college buddies, many of whom also went on to become professors at top schools and experts in their fields. My dad’s friend told me, “If everyone worked as hard as your dad, everyone could be a professor.” That stuck with me, not as a statement of fact, but a testament to the power of hard work to shape outcomes, even in a field considered to be dominated by genius.
My dad has a simple and memorable mantra when it came to applying hard work to learn math: “Do problems without looking.” I’ve applied this basic idea to everything I’ve done from math to programming to law to startups, and it not only keys me in on deliberate improvement, it’s a source of humility and inspiration. Dad doesn’t have the best English, so let me explain.
1. Do problems
You don’t learn math by reading math. That much seems pretty obvious. You learn math by doing math and much of the point of math is to solve problems.
When I went to law school, I was surprised how many students did not grasp this basic idea. You don’t learn law by reading law, either. You learn law by doing it, and the whole point is to solve legal problems.
That’s probably because many law students were trained in the liberal arts and humanities—they were intellectually reared in an environment in which “there is no right answer” is the right answer and much of the work involves mental calisthenics on how to arrive at the point where you can talk about the shifting meaninglessness of life. That’s an exaggeration, but my point is that the first step of “do problems” is to acknowledge that it’s possible to do problems in a way that’s both right and wrong, that you can learn from.
When it comes to building a product, it becomes very easy to do what I like to call “building a bunch of random junk” without a definite problem in mind. There’s typically a deep dissatisfaction with the outcome of that process because the doing had no point in the first place. It’s not only about the “doing”—deliberate progress is made when you “do” a “problem.” The problem gives you feedback on whether the doing is going anywhere.
2. Without looking
In the math context, “without looking” means “without looking at the solutions.” It’s oddly and amazingly easy to convince yourself that you got an answer correct—or would’ve gotten it correct—after looking at the answer, even if you got the wrong answer. If you do a problem incorrectly, you should do the problem again, again without looking at the answer. That combats the brain’s incredible ability to rationalize wrong answers into right ones.
In law school, we read all the canonical cases but we were told that they were canonical. After law school, I spent one year as a law clerk for a federal appellate judge on the U.S. Court of Appeals. I was haunted by the question: if an important case came on my desk, would I know it? Without my casebook telling me that I was facing an important case, could I tell its importance from its qualities?
In law, it’s amazing and inspiring that important cases don’t show up on your desk with trumpets ringing. Just the opposite—any case could house an issue worthy of the Supreme Court without regard to how wealthy or famous the litigants are. What this breeds is a humility and meticulousness against pre-judging a case based on superficial appearances. In startups, any schlub you meet in a hoodie could be onto the next big thing. I find that to be incredibly exciting.
To me, doing problems without looking brings me back to the fundamental question that’s humiliating but absolutely vital: despite all my credentials, all my experiences, all my airs and fancy clothes, all my pronouncements and opinions, what do I actually know?