“Deep work” by Cal Newport

The author 🖋

Cal Newport is a multiple-time bestselling author, a computer science professor at Georgetown University, a Ph.D. in computer science from MIT and publisher of over 65 peer-reviewed academic papers that have been cited more than 4,500 times.

He’s also a regular contributor to the New York Times, the New Yorker and WIRED, a frequent guest on the NPR podcast and the host of his own "Deep Questions" podcast.

Key takeaways 🎓

1. The deep work hypothesis

Deep work refers to professional activities performed in a state of distraction-free concentration that push our cognitive capabilities to their limit.

Newport believes that this type of work is becoming increasingly rare and valuable in our economy therefore people who cultivate this skill will produce higher quality work more effectively, giving them a significant competitive advantage.

2. Be okay being bored

Newport argues that we need to retrain our brains to tolerate boredom and resist the constant pull of distractions.

It's like exercise for your brain's concentration muscles.

By embracing periods of boredom and deliberately avoiding quick hits of stimulation from (mostly digital) distractions, we can improve our ability to focus deeply and produce meaningful work.

3. Turn focus into a habit

The key is being intentional about when and how we focus.

By creating a daily schedule that prioritizes deep work, we can improve the productivity and quality of our work.

Newport shares the structures/rituals that helped him turn deep work into a habit and access this productive state of mind on a regular basis much easier.

Closing thoughts 🧠

As a computer scientist who has studied the impacts of technology on our lives, Newport provides a unique, research-backed perspective on navigating the challenges of our modern distracted life.

The overall message is that the ability to focus deeply is an increasingly valuable skill that leads to a higher earning potential.

I’ve started implementing this straight away (with a bit of background noise) ✌