Deep Questions with Cal Newport

Classic Episode: How Do I Learn Hard Things? | Monday Advice

Deep Questions with Cal Newport

Show Notes

In this replay of a classic episode from January 1st, 2024, Cal walks through the process of learning hard things. The good news is that most people can learn most things. The bad news is that learning is harder than we think. This advice has never been more relevant for those looking to move past the easy dopamine hits offered by their devices and find something deeper.

Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here’s the link: https://bit.ly/3U3sTvo

Video from today’s episode: youtube.com/calnewportmedia

(0:00) Learning hard things

(21:19) When it comes to taking notes, what really matters?

(27:32) Can I fit all of my hobbies into my week?

(31:12) Can YouTube teach me to be a better student?

(37:37) How do I figure out what to learn next?

(39:54) How do I learn something fast when I already have a busy schedule?-

(46:24) CALL: How does “So Good They Can’t Ignore You” relate to “Slow Productivity”?

(56:17) CASE STUDY: Slow Productivity affinity group

(1:02:23) The 5 books Cal read in December 2023

Thanks to our Sponsors:

https://www.monarch.com (Use code “DEEP”)

https://www.calderalab.com/deep

This show is brought to you by BetterHelp. Give online therapy a try at https://www.betterhelp.com/deepquestions

December 2023 Books:

Home Economics (Wendell Berry)

Panora’s Box (Peter Biskind)

Where the Deer and the Antelope Play (Nick Offerman)

Who Wrote the Bible (Richard Elliott Friedman)

The Exodus (Richard Elliott Friedman)

Thanks to Jesse Miller for production, Jay Kerstens for the intro music, Kieron Rees for slow productivity music, and Mark Miles for mastering. Learn more about your ad choices. Visit podcastchoices.com/adchoices

More from Deep Questions with Cal Newport

Oct 22, 2026

Tesla’s recent demo of a rocket-powered Roadster doing a kick-flick over a parked car touched a nerve in me. It seemed to epitomize changes to the tech sector in recent years that have been largely negative. In this short episode, I jump on the mic to explain some of my developing thoughts surrounding these ideas.

Oct 19, 2026

A lot of attention has been paid recently to examples of AI going “rogue.” What’s missing from this discussion, however, is a more detailed explanation of what specific types of systems are causing problems. Taking a closer look at this problem reveals an issue that’s much more narrow and much more avoidable than some of the frontier labs would like you to believe.

Oct 12, 2026

How do we stop from becoming so reliant on LLMs that we lose our ability to think. A new paper explores answers based on an unlikely source: rigorous mathematical models. In this episode, Cal explains the paper and its conclusions, arguing that once you cut through its complexity it yields a useful way of thinking about our current AI moment.

Oct 8, 2026

Cal Newport takes a critical look at recent AI News. Cal interviews Emile Torres who provides a stark warning about AI.

Oct 5, 2026

One of the more debilitating experiences in our current digital world is the sense of being trapped in relentless, reactive, busyness. This “whirlwind” can separate you from both ambition and presence, leaving you feeling flat and fried. In this episode, Cal discusses a simple trick he deploys when he finds himself in this state. It requires only a single sheet of paper.

See all episodes →