Book · recommended on 2 episodes
Slow Productivity: The Lost Art of Accomplishment Without Burnout
Cal Newport ISBN 9788410121065
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Cal Newport ISBN 9788410121065
Find it on AmazonAffiliate link — we may earn a commission at no extra cost to you.
This book by Cal Newport has come up 2 times across 2 different shows: Andrew Huberman, Tim Ferriss. The people who brought it up: Andrew Huberman, Cal Newport. The earliest mention we indexed is from 2024-02-21 and the most recent from 2024-03-11. Every occurrence below links to the episode page and to the exact second it was said on YouTube.
Our current definition of “productivity” is broken. It pushes us to treat busyness as a proxy for useful effort, leading to impossibly lengthy task lists and ceaseless meetings. We’re overwhelmed by all we have to do and on the edge of burnout, left to decide between giving into soul-sapping hustle culture or rejecting ambition altogether. But are these really our only choices? Long before the arrival of pinging inboxes and clogged schedules, history’s most creative and impactful philosophers, scientists, artists, and writers mastered the art of producing valuable work with staying power.
“Cal also has a new book out now it's one that I'm currently reading entitled slow productivity the Lost Art of accomplishment without burnout”— Andrew Huberman
The guest here is Cal Newport: A professor of computer science at Georgetown University who trained at MIT. He is the best-selling author of books on productivity and focus, including Deep Work and Slow Productivity. Cal Newport explains the neuroscience of focus and gives concrete systems to escape distraction and do deep, high-value work.
“so the new book I want to talk about this subtitle is the Lost Art of accomplishment without burnout who doesn't want that”— Cal Newport
The guest here is Cal Newport: Georgetown computer science professor, New Yorker contributor, and bestselling author of Deep Work, Digital Minimalism, and Slow Productivity. Cal Newport unpacks slow productivity, obsessing over quality, and resisting algorithm-driven attention economies in favor of long-horizon craft.
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