Smarter Faster Better

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Mental models

If you have robust mental models, you can grasp the world on a deeper level and notice things instinctively. You can match your experiences to the right lens and interpret them instantly.

A study of productive executives at large companies. The superstars:

Narrate your life to yourself. Tell yourself what it is you’re about to do. Explain your experiences. Come up with theories about the structure of reality and challange others to disprove them. In other words: build lots of mental models and refine them.


Cognitive tunneling — it’s when you go from light focus to a spotlight instantly in a moment of panic, and you don’t know where to focus it. And so get super confused and overwhelmed.

(This is the danger of automation, a cause of many plane crashes. The plane mostly flies itself, and your focus is light. But when shit hits the fan, you’re forced to focus your attention too fast, and you don’t know what to do.)

The antidote for that is better mental models. When you have lots of mental models, you’re constantly scanning your environment for matches, and when something happens, you can find the right lens instantly.

Goal setting

Need for cognitive closure is the desire for firm answers and the aversion for ambiguity. Successful people tend to have high NFC, their lives are organized, and they know what they’re doing.

The need for closure is highly desirable… until it’s not. (Yom Kippur War)

When not in check, it makes you close-minded, unwilling to change your opinion. It makes you over-decisive, too focused on the specific and measurable.

GE’s SMART goals: in this system, the need for closure is so strong, it caused people to expend energy on inconsequential goals. If you’re only taught to make specific goals, you’ll only pursue specific (but small-minded) goals, and never dream big.

Stretch goals matter — ambitious goals you can’t yet explain how to achieve.

What you need is the combination of both. Too many specific/measurable goals, and you won’t achieve anything that matters. Too many vague stretch goals, and you’ll get stuck, overwhelmed by them. Instead, shoot for the stretch goals, but then break them down into more and more concrete tasks.

Think probalistically

Life can be a lot like the poker table — there are no certainties, only a set of possible futures, that you can weigh and judge, to make choices that have the greatest probability of success.

Human brains are very good at Bayesian inference. We instinctively weigh different options to choose the most likely outcome. We intuitively select the appropriate distribution model in different situations (random, power law, Erlang, normal curve).

But you have to seed your Bayesian base rate to avoid biases. Survivorship bias is a big danger. To avoid it, expose yourself to the full spectrum of experiences. Don’t just read and think about success. Read about companies that fail, think about the small and big mistakes you’ve made after a workday, etc… Calibrate your brain to reality, and then, you can let your brain make intuitive probalistic decision much better.

And sometimes, do it explicitly. Imagine different possible outcomes and their results. Then seek information to weigh the probabilities of these outcomes. And average to get the expected value.

Dealing with information

We get overwhelmed with information when there’s too much of it, and we can’t easily split it into manageable pieces.

You can help with this by creating disfluency. By making information slower and harder to process, we’re forcing ourselves to slow down, engage with data, and think it through.

Counterintuitively, disfluency makes it easier to make decisions based on data.

Decision making also becomes hard when we put on one frame of mind, and then we become stuck and can’t see the alternatives. (Example with how first asking about listing advantages or disadvantages changes behavior of people asked about VCRs).

Formal processes can help us by breaking down the problem into a set of steps that force us to consider multiple frames of mind.

Team collaboration

Google’s research group analyzed hundreds of teams across the company to figure out what makes them successful or not.

The “who” of teams doesn’t seem to matter much. No pattern was found between composition of teams and their success. (Some had all stars, others just a strong leader; some were diverse, others all alike…)

What makes the big difference are the norms — the behavior of the team, its dynamics, its unspoken rules. Most importantly:

  1. Psychological safety of each member. You have to feel safe expressing your opinion, while everyone respects everybody else.
  2. Empathy. Everyone needs to be sensitive about how others on the team feel.

Team cohesion by itself is not the point. You need to strike the right balance. If team cohesion keep you from expressing your opinion (because you’re doing something “for the team”), that’s not good.

Responsibility and commitment

Push responsibility down to people who have the most direct contact with a problem.

Toyota Production System/Lean manufacturing: Any worker can stop the assembly line, and their manager will take commands from them to help them resolve a problem on the spot.

The person closest to a problem has the greatest expertise about that particular problem, and therefore it would be wasteful not to give them authority to act on it.

5 types of companies (15-year study of Silicon Valley): star-led, engineer-ed, bureaucracies, autocracies, and commitment firms. (Also mentioned by Originals)

Commitment firms outperformed them all. They might grow steady and organic, but their employees stick around for long. They thus dodge one of the biggest hidden costs of companies: the profit lost when an employee takes their clients or insights to another company.

Creativity and innovation

Everything is a remix. Most creative, innovative, important works are made by combining existing (even conventional) ideas in new and unexpected ways. (The combination, not the ingredients is the innovative part.)

(Example: analysis of scientific papers. Many of the most influential ones cited very unconventional combinations of existing papers.)

Diversity in ecosystems is greatset when there’s a level of change and disruption present. Not too litle, not too much. In a stable system, one or a few species have the tendency to dominate and drown out all other species. But disrupt the system occasionally (a fire, a flood, a dead tree), and space is created for more species to compete.

The mechanism might as well work in a creative context. Once you find a survivable idea (but one that’s still not right), you might get stuck. You start spinning, because you stop seeing different possibilities. Sometimes you need to give a jolt to the project, mix things up, to allow for novel ideas to emerge.

Creative desperation, therefore, can be a necessary disruptor for seeing solutions, and not a bad thing.

Innovation brokers are crucial. Those are people who have a treasure trove of problems already seen and solved — a great diversity of patterns that can be matched together to create something novel.

To distinguish between creative and cliche, become sensitive to your own feelings — the way you respond to different ideas and solutions.

Ed Catmull: Creativity is just problem solving (See: How to fly a horse)

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