Ep. 354: The Workload Fairytale

A few years ago, in a spirit of post-pandemic experimentation, multiple countries ran formal trials to test a radical idea: shortening the workweek. In this episode, Cal returns to the results of these trials to identify an astounding finding that has critical implications about how we work in the 21st century and how this could be made much better. He then answers listener questions and concludes with a tech corner that addresses a simple question: when will AI begin to automate most of my work? Find out more about Done Daily at DoneDaily.com! Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here’s the link: bit.ly/3U3sTvo Video from today’s episode: youtube.com/calnewportmedia Deep Dive: The Workload Fairytale [3:39] - How would you rewrite A World Without Email to account for Slack? [18:16]- How should I manage multiple deadlines? [22:14]- How does Values-Based Lifestyle Centric Career Planning relate to Rutger Bregman's concept of Moral Ambition? [27:28]- How can I avoid burnout and use my career capital to find a less demanding job? [34:24]- Should I do my weekly plan on Sunday night to avoid the scaries? [40:32] CASE STUDY: A lawyer argues in front of the New York Court of Appeals [42:57] CALL: What exactly is considered task switching? [47:15] TECH CORNER: When will AI automate my job? [56:04] Links:Buy Cal’s latest book, “Slow Productivity” at calnewport.com/slowGet a signed copy of Cal’s “Slow Productivity” at peoplesbooktakoma.com/event/cal-newport/Cal’s monthly book directory: bramses.notion.site/059db2641def4a88988b4d2cee4657ba?bbc.com/news/business-57724779theguardian.com/money/2023/feb/21/four-day-week-uk-trial-success-patterndw.com/en/german-firms-tested-4-day-workweek-heres-the-outcome/a-70685885calnewport.com/ai-and-work-some-predictions/ Thanks to our Sponsors: udacity.com/deeplandroverusa.comcalderalab.com/deep Thanks to Jesse Miller for production, Jay Kerstens for the intro music, Kieron Rees for the slow productivity music, and Mark Miles for mastering. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:11Cal Newport?

  I'm Cal Newport and this is Deep Questions, the show about cultivating a deep life in a distracted world.

• 0:23Cal Newport?

  Here in my Deep Work HQ, joined as always by my producer Jesse. Jesse, we're doing something different. Usually the video version of this podcast, we start with the deep dive. Our audio listeners get to hear a little chatter ahead of time, but we're putting this opening chatter on video as well on YouTube, episode 354, because there was something I came across that I felt like I just had to share with the viewers and listeners because it's making me so happy. So I don't know if you, you know about this trend, Jesse, but there's this big trend where people sell fake books.

• 0:55Speaker 01

  Yeah.

• 0:56Cal Newport?

  Sometimes they'll use AI to write like a 20-page whatever, and sometimes they don't even bother, right? They just put up fake titles. There's a lot of books that are like similar to Deep Work that are out there, this or that. Well, I came across one of these that was so fantastic and it's made me so happy. I wanted to share it with the audience. It's the biography of Cal Newport. This is a fake book. It's disappeared now off Amazon, but I grabbed the screenshot of the cover. I want to bring up the cover right now. Oh, I love this so much, Jesse. So here we go.

• 1:29Cal Newport?

  Picture of me smiling me, interestingly, completely unaltered physique.

• 1:34Speaker 01

  He's jacked.

• 1:35Cal Newport?

  He is jacked, but here's the great part for copyright protection reasons to try to keep this up here. I didn't notice this at first. It was Dave Epstein. I showed him this and he pointed this out. They changed the name from the biography of Cal Newport to the biography of Cal Network. I like this idea of there being a super confident jacked version of me out there who goes by the name Cal Network. This is like my altered ego. This is Cal Newport's id brought to life. Cal Network doesn't have a to-do list, Jesse. He has a to-crush list.

• 2:13Speaker 01

  Yeah, he does.

• 2:14Cal Newport?

  There he goes. If you ask Cal Newport why he didn't respond to your email fast enough, he's going to flip your car into a ditch. Get some Cal Network. Cal Network brings barbells to meetings. And if you try to ask him to take on a new commitment, he is going to hold a bicep curl and make eye contact until you say, you know what? Never mind. I got it. Get after it. Cal Network, everyone. So here's my alter ego. I like that he's out there. I will channel him from now on when I need to take my ideas and push them. So anyways, it just made me happy, Cal or Jesse. Cal Network doesn't, Cal Network calls everyone else Cal because he's too busy getting after it to

• 2:54Cal Newport?

  learn people's names. Go Cal Network. All right. Enough of that nonsense. It just made me happy. So I'm glad we got a chance to see that. We got a good show. We got a deep dive here. We're going to get into some interesting research that underscores a point in a surprising way that we've talked about before on this show. We got some great listener questions. And then we have a tech corner for our final segment. Actually, it's based on something I wrote recently for my newsletter at calnewport.com. As mentioned, that is now relaunched to something that'll be more like three to four times a month. So if you don't subscribe, go check that out, calnewport.com. But there's a, I'm going to tackle a big AI question that I tackled in a recent newsletter. We're going to get into it a little bit at the end. All right. So with

• 3:35Cal Newport?

  all that nonsense behind us, let's move on with our deep dive. Over the past four years, a remarkable story has been quietly unfolding in the knowledge sector, a growing interest in the viability of a four day work week. Iceland helped spark this movement with a series of government sponsored trials that unfolded between 2015 and 2019. The experiment eventually included more than 2,500 workers, which believe it or not, is actually about 1% of Iceland's total working population. The UK followed suit. They had a six month trial that included over 60 companies and close to 3,000 total employees. This concluded in 2023.

• 4:16Cal Newport?

  A year later, 45 firms in Germany participated in a similar half-year experiment with a reduced work week, and these are far from the only such experiments being conducted. According to a 2024 KPMG survey, close to a third of large US companies are at the very least considering the idea of experimenting with four-day work weeks, at least for some employees. All right, so the reason I'm bringing these up is not to directly assess whether a four-day work week is a good idea, though I will return to that at the end of the discussion here. But instead, because as I'll show, these studies, if you look deeper,

• 4:55Cal Newport?

  have an important data point in them that I think points to a really important conclusion, an idea that is critical if we want to understand knowledge work in our current moment. It's an idea that I call the workload fairy tale. All right, so let's get to this hidden point that shows up in every one of these studies. I'm going to switch over now to some of these studies. Let's see, these are probably in what, the browser, Jesse?

• 5:19Speaker 01

  Yeah.

• 5:20Cal Newport?

  All right. Let's start with a claim from the Iceland study. For those who are watching, I have a summary of the Iceland study up here. Here's a key claim from the beginning of this article. Productivity remained the same or improved in the majority of workplaces. So of the 1% of population of Iceland that participated in this, they did not see a decrease in productivity. All right, let's look at what happened in the UK. Here is a summary of the UK study. This is coming from The Guardian. This has a similar quote. Across a wide variety of sectors, well-being has improved dramatically for staff and business

• 6:01Cal Newport?

  productivity has either been maintained or improved in nearly every case. Remember, these are experiments in which they are taking five to eight hours out of the work week, keeping the salary the same, making no other changes. The German study, let me load up a summary here from a German newspaper. They report something similar. I'm reading now, employees generally felt better with fewer hours and remained just as productive as they were with a five day week and in some cases were even more productive. Participants reported significant improvements in mental and physical health and showed low stress and burnout symptoms as confirmed by data from smartwatches tracking daily

• 6:42Cal Newport?

  stress minutes. Step back, all right, let's step back and consider this for a moment. These are outstanding findings. How is it possible that with changing nothing else, just telling people you now have to work notably less hours per week, that the overall value of what they are producing, their overall productivity didn't go down?

• 7:08Cal Newport?

  A big part of this answer, I'm convinced, is an idea that's pretty important from my book, Slow Productivity, and it's the idea of the overlooked importance of workload management. Here's the normal setup. Most knowledge workers have a surprising amount of autonomy over their workload, especially as compared to like a service worker or someone in an industrial context. Right? If I'm a service worker, here's what you need to do. Clock in and do this. It's very prescribed, right? If you're the barista at Starbucks, it's very clear what their responsibilities are. If I work on an assembly line, it's very clear like what I am doing. I don't have a lot of say in what I want to or not work on. In knowledge work, this is different. You have freedom to say yes or no. There's a sort of unstructured way that commitments come to you. You know, some stuff maybe you

• 7:52Cal Newport?

  can't say no to, but ultimately you are the source of triage of incoming potential commitments. There's also no transparency or direct supervision of your workload. You grab the average knowledge work manager and take one of their charges and say, what are they working on right now? They don't know. They can't say, here's the six things that this person is working on. There's no transparency in this. What you're working on is up to you to keep track of. In fact, most workers themselves don't even know at any one moment, the full slate of their commitments. They sort of get prodded into action with like email or Slack prompts or meeting invites that, oh, I need to start doing something on this. There's no direct supervision or transparency of workload as well. Now, most knowledge workers in this,

• 8:34Cal Newport?

  I gotta say, like pretty unusual situation for the economic, the world of economics, this unusual situation of workload autonomy. Tell themselves what I call the workload fairy tale. And the workload fairy tale claims that the amount of work that you're doing right now is the exact right amount needed to be successful in your position. That somehow it is all just worked out that like whatever it is you're doing, this is what you need to be doing. It's the exact right amount. Not more, but if you do less, it's going to be a big problem. The results of these four day work week studies undermine this claim. Productivity did not generally go down for these research subjects,

• 9:16Cal Newport?

  even after the amount of time they had to work was substantially reduced. And if we think about why this is, the answers are actually not that surprising. Especially if you've read like slow productivity or listened to the show before. The key work in most jobs, the efforts that actually drive those pure economic productivity measures, you know, dollars produced per worker hours employed. The key work in most jobs requires much less than a 40 hour work week to complete. Just go back, if you do something like time block planning, go back and highlight with a highlighter every time block from the last week in which you were working on something that directly produced value for your organization. You're not going to have full columns marked with highlighter.

• 10:01Cal Newport?

  You're going to say, you know what, there was like 15 hours this week. Maybe there was 10 hours this week where I was actually directly doing the things that create value. This course is very different than the service sector, the industrial sector, where outside of breaks and lunch, like everything you're doing is directly producing value. So everything else you're doing is either more option, it's more optional. Like you're doing it for social reasons, or it's make work, or it's non-promotable activities, or it's just an embrace of pseudo-productivity. I want to show some activities. I'm going to kind of bounce around emails and make some unnecessary meetings. Now, look, not all of this is bad, but there's no reason to fill, you know, every available minute of your day with this optional work, the stuff that really matters doesn't actually need that much time.

• 10:44Cal Newport?

  This is what's being revealed by these four day work week studies. The workload fairy tale is in fact a fairy tale. You're actually probably doing a lot more extra stuff than you really need to, to do your job well. So if we return to the original question here, hey, but what about this four day work week? Is it itself a good idea? I have nothing against it, but it seems to me that if we solve the underlying workload problem, if we get rid of the workload fairy tale and have more control over, well, how much work should we be doing? And what are the key factors? And how much of the optional work should I be doing on my plate? A lot of the issues with burnout that drive ideas like the four day work week are actually going to go away. A four day work week itself is not going to have a problem that it is solving.

• 11:29Cal Newport?

  So once we recognize there's only so much we're doing that really matters, we should be able to have a lot more variation and flexibility when we think about what work could be. Different types of schedules, different number of hours, less intensity, more breaks. Or hey, maybe more key work and you produce more value, but less make work. There's a lot of options on the table here, but these studies I think point to this really key thing. You were not, most of what you're doing in your job is probably not actually that directly useful. That's taking place in less your total time than you think, which means you should feel some cover to actually slow down and take a breath. It's a four day work week. You know what type of work week Cal Network runs?

• 12:13Speaker 01

  Two?

• 12:14Cal Newport?

  14 minutes. He gets after it. Deep work, deep laser focus, 14 minutes. And you know what? He gets a round of applause for it. Cal Network is so impressive that when he attends the theater, when the show is over, the actors applaud him. Get some Cal Network. That's kind of, that's the catchphrase, get some.

• 12:36Speaker 01

  Yeah.

• 12:36Cal Newport?

  Get some Cal Network. So there we go. Interesting research. I think this, we kind of slept on this, this four day work week stuff. Cause a lot of it kind of was coming into immediate post pandemic times and enough other stuff on our, on our minds. But I think it's like a scandalous result that they said, hey, stop working a week and nothing really changed with productivity. The message that we should get out of that is like, oh my God, what are we doing during this time then? Like clearly we have a lot of make work and non-promotable activities going on. Like we should be able to be better. We don't think enough about workloads.

• 13:07Cal Newport?

  All right. Well, we got some listener questions, but first want to hear from one of our sponsors.

• 13:14Cal Newport?

  We have a new sponsor here, which I'm excited about, Caldera Lab. Here's the thing, guys. Wouldn't you like to look a little younger, have that fresh glow that you would see on, say, like a Cal Network type, maybe get a few more compliments on your skin, or just feel more confident when you look in the mirror? This is exactly what Caldera Lab is here for. Their high-performance skincare is designed specifically for men, simple, effective, and backed by science. In the consumer study, 100% of men said their skin looks smoother and healthier. 96.9% noticed improved hydration and texture, and 93.8% reported a more youthful appearance. And it's not just talk. Caldera Lab spends years developing and testing every formula with leading cosmetic chemists to make sure it actually works. They don't love it, they don't release it. I didn't realize this until I got in

• 13:58Cal Newport?

  my 40s, Jesse, that like, men are, you should put stuff on your skin. Did you know this?

• 14:04Speaker 01

  No.

• 14:05Cal Newport?

  Like, women know this. But like, as you get older, it's like moisturizer, like prevents your skin from looking like, you know, the wrinkled, tanned skin of an old sea captain, which is what you'll look like by the age of 45, if you don't put this stuff on. That our eyes get puffy, right? And they have like these serums you can put on. Women knew this. They didn't tell us Caldera Labs has a product that works. They actually, so it was interesting. There's a mix-up. I got sent two identical sets of their three big things. The Good, which is their serum that's packed with 27 active botanicals and 3.4 million antioxidant units per drop. The Eye Serum, which helps you look more well-rested. You know who doesn't worry about looking well-rested?

• 14:48Cal Newport?

  Cal Network. Yeah. I'll tell you why. You know how many hours he sleeps per night? 18. And also the base layer, which is the moisturizer. They sent me two sets of these.

• 14:59Cal Newport?

  I won't say who, but someone who I know was at the house and was like, oh my God, can I have one of those? And he took and he's using it. I like the base layer, this idea of like the moisturizer stuff like, oh, my skin no longer feels like George, what's that guy's name? What was the name of the famous, I don't know if you're gonna know this, he's from the last era, famously tan, like overly tanned, sort of like gad about town actor.

• 15:26Speaker 01

  Was he in Wayne's World?

• 15:27Cal Newport?

  He might've been. Harrison? Anyways, that's an old reference. So man, you need to take care of your skin. This makes it easy. Use Caldero Labs products. Skin edge formulas, rigorous R and D, cruelty free, plastic neutral, non-comiogenic formulas. That means it won't clog pores, the term I use all the time. So skincare doesn't have to be complicated, but it should be good. Upgrade your routine with Caldero Lab and see the difference for yourself. Here, go to calderalab.com/deep and use that code DEEP at checkout and you will get 20% off your first order. So definitely use that discount code CALDERA, C-A-L-D-E-R-A, calderalab.com/deep and use that code DEEP at checkout. I also want to talk about our

• 16:11Cal Newport?

  friends at Udacity. AI is what we're talking about a lot these days. In fact, maybe we're talking about it too much, but there's a reason because it is what is hot right now. And you might be looking at those people, those AI experts with their fancy tech jobs and huge salaries, the remote work and LDP to and being like, wow, how do I get those jobs? It's knowledge. They know about this, whatever the skill is, in this case, AI that is really hot right now. So how do you pick up knowledge about the type of valuable skills that might matter in your job search? Do you like go on chat GPT and say, hey, tell me how to be good at AI? Do you do like random YouTube search? No, you use Udacity. Courses from Udacity is the best way to gain new knowledge. Take their course on AI,

• 16:56Cal Newport?

  take their course on data, take their course on programming, and more. When you learn with Udacity, you're not just passively watching videos or reading articles. You're doing practical exercises and projects that prepare you for the job you want. That's why 87% of Udacity graduates say they have achieved their enrollment goal. I have used Udacity courses for multiple things, including learning video game programming with my son. Jesse, you've used some Udacity courses as well. They get you involved. They're good courses. They have good teachers. Cal Network tried to sign up for Udacity course, and the teacher, a quarter of the way through, turned it around and said, "We want to learn from you." And then Cal Network taught the rest of that course. It was called Crushing it 101,

• 17:39Cal Newport?

  and he crushed it. Best course ever on Udacity. There's tons of options for learning tech skills, but Udacity is the right one to use because it works. You do projects. There's real humans that you are working with. The tech field is always evolving, and you should be too. You can try Udacity risk-free for seven days. Head to udacity.com/deep and use code DEEP for 40% off your order. Once again, that's udacity.com/deep for 40% off, and make sure you use that promo code DEEP so they know I sent you. All right, Jesse, let's do some questions.

• 18:16Speaker 01

  First question's from Cole. "I work in tech, and there are hardly any emails. Instead, I'm bombarded with hundreds of Slack messages daily. How would you rewrite a world without email in 2025 as a world without Slack?"

• 18:29Cal Newport?

  I want to rewrite it because it already directly deals with that issue. So let me explain, as I say in that book, which came out in 2021, which by the way, was well after the Slack revolution was underway, that I was using email as a catch-all term for low-friction digital communication.

• 18:46Cal Newport?

  So it includes Slack or Teams or whatever low friction digital communication you're using. Email was the first, but these other ones have come along. The real villain in the book is not actually any particular tool, but it is the workflow that these low friction digital communication tools made possible. And I call that workflow, the hyperactive hive mind. It is a style of collaboration where people work things out on the fly with unscheduled back and forth messaging. That messaging might happen through email. That messaging might happen through Slack. That messaging might happen through Teams. It is the hyperactive hive mind style of collaboration that I say is the real problem. Why? Well, it requires a constant tending of these channels.

• 19:30Cal Newport?

  Whatever specific type of technology tool you're using, you have to tend these channels constantly because you have many ongoing back and forth conversations. And if you take too long of a break from tending the channels, you're jamming up too many back and forth conversations. But having to continually check these, these channels is hugely distracting. It puts your mind into a set of continual context switching, which makes it significantly diminished in its capacities. It's going to burn you out before you get to even like mid afternoon. So the hyperactive hive mind is the problem. So the right way to understand Slack, and I wrote a New Yorker article about this a few years ago. The right way to understand Slack and the weird relationship people have with it, where they sort of love features of it and they hate it. The right way to understand it is that is the right tool for the wrong way to work.

• 20:15Cal Newport?

  This is the actual trajectory of Slack is people began using email to implement this hyperactive hive mind collaboration. But there's a lot of things about that particular tool that are a little bit clunky when you're trying to do this rapid back and forth on the man collaboration. CCing is clunky. Threads aren't automatically threaded. Having to find things is difficult again. The sort of quotes and requotes and quotes of quotes of quotes that happen when you get these long email back and forth conversations. It works, but it's not great. So Slack came along and said, okay, if you want to use the hyperactive hive mind to collaborate, this is a better tool for the hyperactive hive mind. Is a better tool for that style of collaboration.

• 20:58Cal Newport?

  So the reason why people love it and hate it is that if your work is using the hyperactive hive mind, which it probably is, Slack is better suited for that. Searchable transcripts, different conversations on different channels, back and forth as opposed to like having the quote and you can go back and find conversation before. It's just like a better implementation of the hyperactive hive mind. But we also hate the hyperactive hive mind because it forces us to constantly be context shifting. So Slack is better at implementing that hive mind. So we don't have rough ends on our features, but that means we have to be even more hyperactive and we have to check channels even more often. And so we hate the things we hate about the hive mind more while simultaneously liking that at least this is a more efficient way of implementing this thing we hate. And it's an all circular sort of terrible mess.

• 21:41Cal Newport?

  But the problem underneath this all is not the tools, it's the workflow style, which is the hyperactive hive mind. That is what we have to get around. And you know who doesn't put up with the hyperactive hive mind?

• 21:52Speaker 01

  Cal Network.

• 21:52Cal Newport?

  Cal Network. Damn straight he doesn't. You want to talk to Cal Network, only one way to communicate with him in the work, registered mail. You have to send it registered mail and he will sign for it when the mail person comes to his office. The rest of us have a lot more work to do. So don't get caught up in the tool. It's the collaboration style that's the problem. All right, who do we have next?

• 22:14Speaker 01

  Next up is Nina. How do you manage multiple writing projects with no deadlines? Am I supposed to spend a couple of hours on each project every day? Should I only work on one project each day or should I focus on just one project until it's complete and then move on to the next?

• 22:28Cal Newport?

  That's a good question. It depends on the type of projects we're talking about. So when it comes to deep work, long ongoing projects, if they are of the same type, sequential is usually better. Right? So if you were saying I have three script projects I was working on, I would work on one, then work on another, and then work on a third. I would definitely not interleave three similar type projects on a very small time scale. Like, I'm going to work on a little bit of each each day. That's just too much context shifting for you to really make progress. You have to pay a price of a cognitive overhead to get going with each of those, and that overhead is just going to add up. If you're working on multiple projects on a small time scale, too much of your time is just on the overhead of trying to switch your thinking from one to

• 23:13Cal Newport?

  another. Now, there is a caveat here. If it's a very long project, you can break the project into large chunks and do those sequentially. So I've seen this with screenwriters before, that maybe they'll work on act one of a screenplay, sort of finish it, like, okay, I don't quite know where to go to act two yet, and I'm a little stuck. Now, I'm going to go work on the act three of this other screenplay, started and finished that, then I'll come back and do act two. So you can break a project up into like, big chunks, but you're still going to be working multiple weeks on one before you switch to the other. If you have projects of different types, or maybe you have a long-term project and then shorter projects that have to go on as well, then there is some interleaving that has to happen. I have to do this because I'm typically working on something like a book project, and then I'll be interleaving in things like New Yorker

• 23:58Cal Newport?

  articles or academic articles, which happen on a smaller time scale. And typically, I'm always writing books. So if I was like, let me finish my book before I write like my next New Yorker essay, or my next academic paper, those just wouldn't get done. So if it's a different type of project, like a smaller project, yeah, just get to a good stopping place on the big project, and then I'll pause it for a week to really push another project through to completion, then return to the big project. Again, there is a caveat. The caveat here is I separate out preparation, which is brainstorming and research, from actual writing. So I might be working on my book. Like, today, I'll use my actual day-to-day as an example. I am working on the final section of chapter

• 24:41Cal Newport?

  four of my current book. I've been working on it for a while. I also have a, there's a New Yorker piece I'm working on, and there's an academic paper I'm working on.

• 24:54Cal Newport?

  Those two, those two smaller things are in the research thinking phase and that is fine. So I wrote all morning on my book and then I have two calls this afternoon. One is with the philosopher that I'm working on this academic paper with and the other is on an AI researcher that I'm interviewing for my New Yorker piece. That's fine. That's research thinking. I'm happy to add that into the afternoon. It's not as, I'm not in the full cognitive context of trying to figure out and write. I'm just sort of gathering information or discussing things. So I wrote this morning, doing background research on those. When it comes time to pull the trigger on one of those two smaller projects, so let's say like the New Yorker article gets to a point first where I'm like, okay, I'm ready to write this. Then I will pause the book and just for a week, write that article.

• 25:38Cal Newport?

  So like when it comes to the actual deepest of deep efforts, like writing, the actual putting a pen to paper, I don't interleave at all. I want to be working on one thing at a time, but I will let like research overlap. So if you're working on one script from a writing standpoint, but you're still doing like background reading and taking notes for another script, that can interleave fine, but only work on one at a time. For really big projects, you want to interleave, go more sequential, whether full project and then work on the next full project or big chunk of one product for you do big chunk of the other. For smaller stuff, interleaving for bigger stuff, you want to pause the big thing to work on the small, but you can allow the research to overlap. So it's kind of a complicated set of scenarios there, Jesse, but hopefully that, I think about this type

• 26:18Cal Newport?

  of thing a lot. I don't know of many people who can successfully work on multiple large projects at once. Taylor Sheridan can do this. The showrunner writer, he wrote, God, he's working on like five shows at the same time.

• 26:36Speaker 01

  Really?

• 26:36Cal Newport?

  Yeah, but he's a madman.

• 26:38Speaker 01

  So with you and your summer schedule, you're still working on an academic paper?

• 26:42Cal Newport?

  Yeah.

• 26:42Speaker 01

  To be published in the fall?

• 26:44Cal Newport?

  Yeah, publish it when we publish it. Yeah, working on an AI thing. Pretty cool. It's gonna connect my expertise in theoretical computer science and AI philosopher's techniques and like AI. Like we'll probably put that up on archive, sort of like a public repository once we've written it and then figure out what to do with it from there. Yeah. So yeah, academic papers I like. What I get away from in the summer is really as much admin. Yeah. The only person I know who actually can, Taylor Sheridan is it and also Cal Network. When Taylor Sheridan hangs out with Cal Network, he feels lazy.

• 27:21Cal Newport?

  Cal Network taught Taylor Sheridan how to ride horses.

• 27:27Cal Newport?

  All right, who we got next?

• 27:28Speaker 01

  Next up is April. How does values-based, lifestyle-centric career planning relate to Rucker Bregman's concept of moral ambition? Do you see any tensions between the two approaches to career planning?

• 27:41Cal Newport?

  That's a good question. So Rucker, I don't know if you know him, he's a Danish writer. He's a philosopher, maybe. He got, he got a lot of attention. He had some cool books. I think they're in translation in the US, but they did very well. That was more of like a optimistic look at the future, which I think caught some people's attention. He has this new book out called Moral Ambition, which I blurbed. I think it's out now, but I read that and blurbed it. And he's arguing that young people, especially like talented people coming out of elite schools should have more moral ambition. They should, they should use their lives more to go do like useful things for the world as opposed to say like going into finance or law and to try to alchemize their elite training in the money.

• 28:26Cal Newport?

  So interesting argument. So the question is, is that somehow working against my vision of lifestyle-centric career planning? And I don't think so. And I think the issue here, I've been realizing this recently, is the word lifestyle. Right? I think about lifestyle in a very clinical definition sense of the word, which is just literally what is the style of your life? What is the day-to-day realities like, like your life? And so when I say lifestyle-centric career planning, I'm saying, look, fix what you want your life to be like in a more general sense, and then work backwards from that to find specific ways to deal with obstacles and opportunities that face you to make your way closer to that lifestyle.

• 29:09Cal Newport?

  Because ultimately, you want the lifestyle that is appealing to you as the ultimate goal, not, not accomplishing any particular goal. So we might as well get directly to the problem. But I think a lot of people associate lifestyle with something that's maybe softer or is a little bit more like self-indulgent or lazy. Like there's the term, for Lifestyle entrepreneur, which is typically pitched as, well, you have your own business in part so that you can have like a lot more like flexibility. The work is not too hard. If you work for someone else, you'd have to work harder. But if you have your own business, you can sort of trade working harder for, you know, having more vacations or not having to work so, you know, not having to put in really long hours. But that's not, I don't necessarily mean lifestyle to be soft. And one of the core things that could be a part of your lifestyle vision is moral ambition.

• 29:55Cal Newport?

  In fact, lifestyle centric career planning, I think, is probably better suited for Ruckert Bregman's vision of moral ambition than other ways that people think about it. Because if you have this strong vision of this ambition of like, I want to improve the world. This could be a big vivid component to your vision of your ideal future lifestyle. It's a lifestyle where you're like heavily involved in like directly being useful to the world. And then you can get a little bit more specific about like, for you, does that mean like I'm directly involved with people? Who I'm helping? Or maybe you have more of a intellectual conception of moral ambition that I am producing ideas that are really changing the world. I did a cool profile like this in my book, So Good They Can't Ignore You.

• 30:38Cal Newport?

  Pardi Sabetti, who was a computational biologist at Harvard, I went and spent some time in her lab. And I sort of profiled her as someone who was doing this, who had this sort of moral ambition. And found an interesting way to get there. And she ended up in a biology lab, working on genetic algorithms. And they were, they were using them to study ancient diseases and to try to find ways to get around them. Really cool. You know, she works in computers in the lab, but they also go with the partner institution in Sub-Saharan Africa where they go and spend a lot of time. And it was just like a really cool mission driven life. And, you know, my argument there was she didn't sit down at some point and say, here's my grand goal. I want to be a algorithmic geneticist who works in a, you know, lab in Africa. It was working backwards from the more general moral ambition is like, I want to use my smarts to try to do something

• 31:23Cal Newport?

  good for the world. And I want to, it to be intellectual, but also connect directly to people. And then there was a, I documented in the book, all sorts of different serendipity and opportunities that came out of nowhere that she sort of followed. And it led her eventually to this place. She was guided by that lifestyle vision very consistently. The path was jaggy. So no, lifestyle planning doesn't mean lifestyle entrepreneurship. It doesn't mean just chill. So moral ambition could be a part of it. That's why I blurred that book is that people need more ammunition for their visions of the ideal lifestyle. And this book will give you one particular ambition. It actually complements very well. My book, So Good They Can't Ignore You.

• 32:05Cal Newport?

  There's, this world's really incestuous and overlapping, Jesse. But like Roderick Bregman, when you think about his moral ambition, you need to do something good for the world. It kind of has a feel of like the effect of altruist, but he's not nearly as clinical as they are and kind of weird. But the effect of altruist really likes So Good They Can't Ignore You. So that was because they felt like, yeah, this is like more, you know, you're trying to be more systematic about being useful and not just like following your passion or this or that. So all these worlds kind of mixed together a little bit.

• 32:37Speaker 01

  I was gonna say, he wasn't so SPF.

• 32:40Cal Newport?

  SPF, yeah. SPF was, yeah. Well, no, but so there was a group, I don't, okay, I don't know this world well, but there was, there's a group out of Oxford that Will was his name, who's one of the big EA's.

• 32:53Speaker 01

  McCaskill.

• 32:54Cal Newport?

  McCaskill.

• 32:55Speaker 01

  I think. Him and SPF were boys, like, early on.

• 32:57Cal Newport?

  Yeah, so I knew, I would cross paths with Will because there was this group out of Oxford that I think he was involved with. I think it's a cool group that was called 80,000 Hours. 80,000 Hours is like the number of hours the typical person will spend working. So their whole point, and this is an EA point, is the biggest lever you have to help the world is like what you're doing with those 80,000 hours. And so 80,000hours.org was like a nonprofit based out of Oxford, I believe, that was like helping people figure out what to do with their lives in a way, not the, and they were very much like, don't just say follow your passion. Be like, no, no, how can I be effective? Like, what do I want to do with this? This, this really good, which is kind of a, kind of interesting EA idea. So I crossed some paths with William McCaskill because they like So Good They Can't Ignore

• 33:41Cal Newport?

  You, because obviously those ideas that like, don't just follow your passion, use career capital, get good at things and figure out what to do with it, kind of overlapped those a little bit. I missed, however, getting deep enough into that group to become boys with SPF.

• 33:54Speaker 01

  The Lewis book was really good.

• 33:55Cal Newport?

  I should read that book.

• 33:57Speaker 01

  Flashboys? Well, that was, no, it was a Flash, no, it was Going Infinite.

• 34:00Cal Newport?

  Going Infinite, yeah. Flashboys was cool as well.

• 34:02Speaker 01

  Yeah, I read that.

• 34:03Cal Newport?

  Lewis is the man. Lewis is the man. You know what Cal Network's moral ambition is? Crushing tasks and getting PRs.

• 34:14Cal Newport?

  And he succeeds at it, too. Cal Network doesn't have a lifestyle centered career plan. People use him as their vision of the ideal lifestyle. All right, let's roll.

• 34:25Speaker 01

  Next up is Marie. I'm in my early 40s with two young kids. I make double what my husband makes and we need both incomes for family life. I constantly feel on the edge of burnout. I'd prefer to work 50% of the time, but financially can't. Any advice on how to find a less demanding job that still leverages my career capital?

• 34:43Cal Newport?

  It's a good question. There's a couple of different things to do here. By the way, your 40s. I'm sure someone should write a book about this. Your 40s are a really interesting time. Maybe this is why I'm writing The Deep Life right now. It's a really interesting time for lifestyle like reconfigurations, right? I mean, if you think about like especially a standard sort of well-educated, middle-class, upper-middle-class American track, right? You have this like 20s, you are getting educated and doing entry-level jobs. 30s, you sort of settle into a career and you begin to, you build capital, you get good at things. And then your 40s is like this great moment of reconfiguration or reinvention of like,

• 35:24Cal Newport?

  okay, what's our play here? Am I going to write out this? Or are we going to change? Or what's working, what's not working? So it's really an interesting time for thinking through these questions of lifestyle-centric design. The first thing I would do is like really make sure that you're doing lifestyle-centered career planning. So there's often, when there's friction in your current existence, there's a tendency to do solutionism, which is I want to find a single idea that generates in me an emotional response that's positive and I'm going to place on that single idea or goal, all the hopes and dreams of making my lifestyle something I like more. So we want to be careful that's not what's going on here. Where you're like, I'm feeling burnt out. If I was just working half-time.

• 36:10Cal Newport?

  All that problems will go away and we'd be happy. Maybe, maybe not. Like what you really want to do is say, what do I actually want? In an ideal world, what would my day be like? What would my life be like? And maybe it's not working 50%. Maybe it's like, no, but it's like working reasonable hours and not feeling so squeezed in the time after that. Not being able to have more time after work. I'm like, maybe it's, I'm not super stressed about work when it's done. And I don't feel like I'm constantly playing catch up on home related or family related issues afterwards. Like I, I, I want to be at an office and like, like what I'm doing. But then I want to be able to like, come home soon after the kids get home from school or like you, you have some sort of vision and we're not rushing around or whatever.

• 36:54Cal Newport?

  Then when you work backwards from that vision, you might be like, let me explore a lot of different ways forward to that vision. And yeah, maybe it's just like going to halftime, but maybe not like, maybe that's just going to be frustrating. Maybe you're going to be resentful. If you're like, look, I make double my husband. And if I go back to half hours, I'm going to feel like I'm being sidelined, but I have like an intellectual or professional ambition. And I feel like I'm actually better than him at stuff in my like job. And this is like, I'm feeling resentful about like, maybe that's not the right thing. Maybe you're like, okay, what we need to do is change our jobs and I'm going to change it to a different job that uses my career capital, but is less like one of these. We're paying for your time. You always have to be accessible type job. So it's going to be less money, but something where like I, I can use my skills.

• 37:39Cal Newport?

  But when it's done, it's done. Maybe your husband makes the shift. Maybe he goes to halftime. That reduces your income much less. That reduces your income by what a sixth? He's making about a third of the income and you cut that in half. So that's going to be about a sixth versus if you went halftime, you're reducing it by a third. Right? And then maybe he's able to take on really clearly delineated like these family responsibilities. That means you don't feel so stressed about the stuff going on after work. Like there's different types of options here. That's worth thinking about. But what I'm going now is like, get the lifestyle. Like, what do you want your day to be like? Don't say like, what do I want to get rid of? I want to get rid of burnout. Say, what do I want my life to be like? It won't include burnout, but what else do I want in my life?

• 38:23Cal Newport?

  I think that could open up potentially more interesting options. Then there's the problem. Okay, so let's say you've done that. And the best option for it is like a new job, maybe something that's 50% time or just like less demanding. Here, what I have found is that when it comes to stuff that's well past the entry level, it's not like you can go on to LinkedIn and just find this. It has to be, it often feels like for people that it's manifested. And what happens is when you begin thinking, looking and talking about them, kind of looking for something different that's going to be less demanding. You talk to friends about this, and you talk to colleagues about this, and you have some conversations. Suddenly, these super bespoke, one-of-a-kind type of opportunities

• 39:06Cal Newport?

  just have a way of sort of sifting out a materialize like, oh, wait, this person is just moving over this small organization, and they need to start an outpost over here where you happen to live, and they need someone who can run it for the next couple of years. And it's like a great match for your skills, but it's really autonomous and probably much less time. Like, great, I'll do it. It feels like you're manifesting it, but what you're really doing is just putting your antenna up to look for these things. And you're beating the bushes a little bit as you talk to people. A mixing metaphors here because I don't think you hunt for birds with antennas, but I might have this wrong. I'll tell you who can do that. It's Cal Network. He catches birds with his bare hands. He leaps and catches them. He doesn't deal with shotguns. But you see, it feels like, I've heard this again and again from people.

• 39:46Cal Newport?

  It's like, wow, once I started thinking and looking for this like more nuanced application, my career capital, it just came out of nowhere. Where was that before? They were around before. You just weren't looking for them. You know, you weren't, you weren't actually generating them. So use pure lifestyle, career plan. Do it with your husband. Remember, it's a family lifestyle you're working backwards from, not individual lifestyles that you hope mesh.

• 40:11Cal Newport?

  Explore, be broad when you explore different solutions that could get you to the lifestyle you're looking at. And then, once you execute, if you're looking for something like, again, my career capital and a very narrow type of application, you have to manifest it, which means you have to start looking for it and talking to people and beating the bushes. And you'll be surprised what comes up.

• 40:31Cal Newport?

  All right, who we got?

• 40:32Speaker 01

  Next up is Juliette. Cal, do you get the Sunday scaries? I'm trying to determine if I should switch my weekly planning to include something for Sunday night to help mitigate this. But on the flip side, is there a boundary to set here to protect family time?

• 40:47Cal Newport?

  I do get the Sunday scaries. I can minimize it. It depends when it's like, why am I summer schedule? I don't schedule stuff on Mondays because it will, it will reduce that. I have them a little bit less these days because honestly, our family life is incredibly busy on Sundays. I have a bunch of kids that do a bunch of stuff on Sundays. So there's also a countervailing sense of there'll be some relief to getting those kids to school on, on Monday. So Sunday, you're like, I'm exhausted from all the family stuff, which is nice. So I'm kind of looking forward to just like having some autonomy. But I also get the Sunday scaries about like, I gotta go back and do work. Here, I think is the ideal plan. And it's not Sunday night. Here's what I think the ideal plan is, and I struggle with this, but I think it's the

• 41:32Cal Newport?

  right thing to do. End of day Friday, that's when you plan the next week. If you can do that, and it's really worth fighting for, especially if you get strong Sunday scaries, it's better because you also get a subtle benefit Friday night, Saturday, and Sunday morning. We don't get as demonstrably anxious on like Saturday about the week ahead because we still have some time, but there is a background hum of anxiety because your mind is like, I don't quite know what's happening next week. I hope it's okay. I hope we have a plan. I'm a little bit nervous about it. And I think it amplifies Sunday scaries. If you make your weekly plan on Friday for the week ahead, at the end of the day on Friday, the whole weekend, you have the mental peace of I have a plan that's reasonable. I don't have to worry about, I'm not missing anything. So that part of your brain is like, what if we're missing something?

• 42:17Cal Newport?

  That part of your brain is much calmer. And it might just instantiate itself like a slightly more relaxed Friday night, a slightly more relaxed Saturday. So that's what I want to do. I'm always scrambling at the end on Fridays for various reasons, but that is, I think the ideal. And if I was having really bad Sunday scaries, that is a hundred percent, I would just make that a non-negotiable. I put on my calendar like a meeting, hey, guys, I gotta be done by four. I have a thing at four. Like this is key. I shut down for the weekend when I do that. So I might try to do that some more. When I do do it, I think it's, I think it's much better. They'll tell you what, you know, who doesn't have Sunday scaries? Sunday is scared of Cal Network, not the other way around. All right, we got a case study here. This comes from Sam. This is where people send in their accounts of using that

• 43:02Cal Newport?

  type of advice we talk about on the show in their own lives. If you have a case study, you can send it to [email protected]. All right, here's what Sam says. "I had the honor to argue an appeal before the New York Court of Appeals. Oral appellate arguments are not prepared speeches, but rather back-and-forth discussions, sometimes heated between the advocating attorneys and a panel of judges. When I was in law school, I read an excerpt on John Roberts. And before he was the Chief Judge of the United States, he was a litigator who regularly appeared before the United States Supreme Court. The article noted how impressed all the Supreme Court justices were when Attorney Roberts would step up to the podium without any notes and make his argument, never break eye contact,

• 43:42Cal Newport?

  and cite to the expansive record from all memory. I decided that when I got my chance, I was going to take a page from the John Roberts playbook. I got my chance before the New York Court of Appeals, without a note, all from memory. I stepped up to the podium and engaged in a rapid-fire discussion with the impressive panel of judges. It'd be funny if he added, and by the time I was done, I had been thrown into prison for contempt." Went another way. You know, the one time that Cal Network had to speak in front of the Supreme Court, they ended up inviting him to become an Associate Justice. That's how good he was. "I wish I could attribute my confidence to a memory superpower. That would have been a lot less work. But instead, it was all about deep work, active recall,

• 44:27Cal Newport?

  and another secret ingredient: exercise. For 60 days leading up to the argument, I read and studied each night in my home office with no phone, TV, or internet, other than for case research. Then the next morning, while on the treadmill or bike trainer, I reviewed in my head the material from the night before. Again, no music, no TV, just a breathy rhythm, a blank wall to stare at, and some active recall." He didn't give us a link to the recordings of his arguments, which is pretty cool.

• 44:49Speaker 01

  I watched it.

• 44:50Cal Newport?

  Yeah?

• 44:51Speaker 01

  He's a beast.

• 44:52Cal Newport?

  Yeah?

• 44:53Speaker 01

  The judges... Interrupts so often, like all the time.

• 44:57Cal Newport?

  You gotta just be on your game.

• 44:59Speaker 01

  Like they're just like, he's getting pounded left and right by all the different judges.

• 45:03Cal Newport?

  Good for him. In the first couple of months in 2025, I had more imaginary conversation with those seven judges than with real people. That's a really cool story. Here's what I like about this, right? I mean, he got after it. It was hard work, right? So 60 days, he just was like, I'm gonna do the thing that actually matters, which is active recall. I argue that all the time and I'm gonna do it. Yeah, it's daunting in the abstract. How am I gonna be as prepared as like John Roberts famously was? When you break it down, it's like, I'm gonna do 60 days worth of deep work, the right type of deep work on the right things, and look at what he accomplished. What comes to my mind when I see that is think about, you know, if you took the time that you're probably dedicating right now

• 45:49Cal Newport?

  to helping the share price of Meta or of, you know, ByteDance, who makes TikTok, all the time you're spending on your phone and having like arguments with people on Blue Sky or following rabbit trails on YouTube. Imagine if you put that time over the next 60 days, like something you wanted to do really well, and you actually put in the right time. You did the hard work that actually matters. And like every day you gave it an hour. Like Sam, you could be a beast after that 60 days and then repeat that again and again. Imagine the skills you could build. Sometimes we look back at intellectuals from time long past, especially those that like came from the Gentry and had some free time. Like, my God, they speak like 19 languages and, you know, in their

• 46:31Cal Newport?

  spare time, like, oh, they translated Euclid from the original Greek to do a new version of it. And they also like mastered gaseous chemistry or this or that. It's just the application of doing the right work that's hard again and again and again, and just getting used to that. You repeat that, a lot of really cool stuff aggregates. So anyways, I think that's a great case study of deep work, applied regularly, produces really deeply meaningful, cool things. The only reason why we don't have that time now is because we have these distraction machines in our pocket. And what do we get from that? Like, in the end, what? Like a bunch of memes that we know about? Not nearly as worth it, unless those are Cal Network memes, which I hope become a thing,

• 47:14Cal Newport?

  but I don't think they will. All right. Do we have a call this week?

• 47:17Speaker 01

  We do.

• 47:17Cal Newport?

  All right, let's hear this.

• 47:20Speaker 02

  Hi Cal, my name is Jordan and I'm a conductor and an academic. Currently completing my doctorate in Baltimore and meanwhile, conducted a number of different orchestras and other ensembles. I wanted to ask you about the concept of interleaving. It's something you've talked about before and it's come out in Adam Grant's recent book, Hidden Potential. Musicians know this concept well. You might work on skill A for a while and then go to skill B and then go back to skill A, then skill C, then skill B, something like that. But when I think about this idea, it reminds me a lot of the idea of task switching, which I know very well.

• 48:03Speaker 02

  It's something we want to avoid when we're trying to engage in deep work especially. I wonder what you think about this. Is it that task switching in this particular case is between various deep work-related tasks? And therefore, it is cognitively demanding, but it's the appropriate place to spend that cognitive buck? Or is there some other way to contextualize and reconcile these two seemingly opposing ideas?

• 48:39Cal Newport?

  All right, well, we talked about this a little bit with the screenwriter question. I'm going to get more precise in answering this more precise version of the question. So when it comes to task switching, the main thing that we worry about is the cognitive overhead of that network switch. So when I switch my attention from the thing I'm writing to an email inbox, the target of my attention is switching from that thing I'm writing over to whatever demands are made of me in that email inbox. And this institutes what a psychologist would call a network switch. Our brain is trying to shift its focus from this cognitive context over to this other cognitive context. That's expensive and takes time.

• 49:24Cal Newport?

  That can take 10, 15, up to 20 minutes to fully switch your context. So what happens when we glance at email inbox for five minutes? As we start a network switch, we abandon it and go back to the original thing. And now we have a mix of both of those networks together. And before we can completely regain our cognitive context on the original thing, we look at our inbox again and institute another network switch. And that's that state of sort of partial, continuous, partial attention, to use a Linda Stone term, or the diminished cognitive capacity I talk about. So the cost of task switching, our problem with task switching, is this like 10 to 20 minute cost of trying to change your attention. It's slow to change attention.

• 49:58Cal Newport?

  So when it comes to like a deeper task that's done over a longer period of time, that type of task switching cost doesn't matter much as long as you're spreading out these switches over a long enough time that the ratio of switching cost to execution gets really small. So like if I'm working on one skill all day Monday, and another skill all day Tuesday, and then back to the first skill on Wednesday and the other skill on Tuesday, that the task switching cost here is negligible, right? Because it's, yeah, it takes me 20 minutes to really get in the mindset of that skill, but then I'm spending eight hours that day working on it. And then I work the next day, I have to switch to the other skill. That's 20 minutes, but I'm spending all day working on it. So as once you get to bigger time scales than like once every five minutes, I'm checking something, that type of overhead matters less. But there's a second type of overhead that I mentioned

• 50:42Cal Newport?

  in the screenwriter question that also sort of matters. And this is like a bigger orientation overhead. Like when I'm working on a book, yes, there's a cognitive cost to actually getting my attention all the way on the chapter I'm writing now. But there's a bigger orientation I have over a bigger time period that's towards working on that book. And I'm thinking about the book. And when I'm not writing, it's in my head. And I'll bounce around thoughts. And it's kind of there in the background churning. And then I come back to it, I work some more on it. Maintaining a general orientation towards a very large or important project is helpful. And there's a cost to switching that, that you'll feel on a bigger time scale.

• 51:25Cal Newport?

  So this is where if I was working on two books and switching between them on Monday and Tuesday, and then back to one on Wednesday, back to the other on Thursday, that cognitive switching cost of just switching my current focus, who cares? It takes 20 minutes, I'm spending the whole day working on one book, but the orientation switching cost, that would be a problem. I start to get, well, I'm kind of, my mind is oriented towards solving this book, but then I'm trying to reorient, try solving that book, and that could be a problem. You know, I first learned about this, actually with academic paper writing, I used to work on multiple academic papers at the same time, meaning not the same day, but like, some days I'll work on this one, then later in the week I'd work on another. And my advisor, who's, you know, famous in the field, was like, "No, no, no, just do one, stay oriented on that one until you've solved it and done the best possible work, then write the next."

• 52:09Cal Newport?

  And I was like, "Ah, it's faster to work on multiple ones at the same time," but she was right. One at a time was going to produce a better work because you can keep your general cognitive orientation towards that one project. So what's the scale at which you'd be switching those? That's at like multiple weeks or months. And that's why I was saying to the screenwriter, if you want to switch your context between different screenplays, you want a chunk that's like, "I wrote the whole first act of the screenplay, it took a month." And then if you want to switch your orientation to another screenplay and spend six weeks working on its second act, that's okay. It'll take a few days to sort of get your cognitive orientation fully switched over, but then you'll get into the groove of it. So we have two scales of context switching, the sort of in-the-moment immediate focus

• 52:51Cal Newport?

  scale, which is what kills us when we check our email or Slack so much, and then the bigger picture, like general cognitive orientation, that can take days to really switch over. And so in the end, what this tells us is for like really big, long cognitive endeavors, you want to give things multiple weeks before you switch to another really big thing, and if possible, like push something through to a really clear finishing point before you switch over to something else. So we got two levels. Of test switching. All right. So we got a final segment of Tech Corner coming up, but first I want to briefly hear from another sponsor. I want to tell you about the Defender 110. This is a vehicle built for the modern Explorer. It's naturally capable and expedition

• 53:35Cal Newport?

  ready. It's a vehicle that's purpose-built and courage-driven. It's a good-looking vehicle. I've seen these Defender 110s around. We kind of think of it unofficially as the official car of the Deep Questions Podcast. I don't know how you unofficially think about something as being official. That just kind of cancels out. It just means we think about it. Yeah. It is the type, here's how I will say it, and this is an endorsement you can take to the bank. It's the type of vehicle that Cal Network would drive. And maybe that's not a good thing, actually. Cal Network bench presses Defender 110s. That's how strong he is. No, I really love the way this car looks. I also really like, here's the good thing about this whole line of Defender vehicles, is you get that off-road proudness that you

• 54:16Cal Newport?

  think about. Sure. But the driving experience, the nice touches are also cutting-edge as well. So you get like the really nice experience when you're just sort of driving this to work. And then you know, though, you have that ability. If I need to take this off-road or go explore, the other things that makes a deep life deep, it's there for you as well. Good-looking car inside and out. I love the tech. I'm a tech nerd when it comes to cars. 3D surround cameras in the ClearSight ground view. So you can see what's under your car. Oh, there's this rock where I want to make sure that we're going around it. The 3D surround cameras means when you then bring that same vehicle to try to parallel park in DC, you can see exactly where everything is. ClearSight rearview, you can see out your back, even if

• 55:00Cal Newport?

  your back view actually is obstructed. Maybe you packed the back of the Qatar too big, or Cal Network's traps are blocking the back window. ClearSight rearview mirror, use the camera. You can still use it like a normal rearview mirror. The Pivi Pro infotainment system is fantastic. Intuitive driver's displays that you can customize. So look, it's a beautiful car, inside and out, a joy to drive, but it has the capabilities to take you on whatever adventure you are looking for. So we'll just call this for now. I think if we call it the official car of the Deep Questions Podcast long enough, they're going to give us one.

• 55:30Speaker 01

  That'd be good.

• 55:30Cal Newport?

  That's the goal. We would, and we would put, we should have a bumper sticker, just like a D and a Q, you know, like doesn't spell it out, but we would put a nice, a subtle DQ bumper sticker on the back and a giant car wrap of Cal Network's bicep on the side. I like this car, the Defender 110. You can design your Defender 110 at LandRoverUSA.com. Visit LandRoverUSA.com to learn more about the Defender 110. Explore the Defender 110 at LandRoverUSA.com. All right, Jesse, let's do our final segment.

• 56:05Cal Newport?

  We're going to do a tech corner here. Here's the theme, this question.

• 56:10Cal Newport?

  When will AI automate my job? So we talk a lot on here about work and technology. Well, this has to be one of the biggest questions at the intersection of those two topics. We've been hearing a lot about how AI is going to automate these knowledge work type jobs that we thought would be safe from such automation. So we've been hearing this a lot. Is it coming? What's going to happen? I wrote about this recently. So my newly revamped newsletter, which is now coming out three to four times a month. I sort of kicked off the new regular newsletter with an epic article titled AI Work and Some Predictions. I'll put on the screen here for those who are watching. And I get into like everything I've been thinking about recently about AI and work, everything I've learned in my journalism, my academic work, et cetera.

• 56:56Cal Newport?

  One of the sections from this epic article was titled, What About Agents? So I want to read you the starting of this piece and then I'm going to summarize what I found. All right. So the starting of this section, I say the following. "One of the more attention catching storylines surrounding AI at the moment is the imminent arrival of so-called agents, which will automate more and more of our daily work, especially in the knowledge sectors once believed to be immune from machine encroachment. Recent reports imply that agents are a major part of OpenAI's revenue strategy for the near future. The company imagines business customers paying up to $20,000 a month for access to specialized bots that can perform key professional tasks. It's the projection of this trend that led Elon Musk to recently quit.

• 57:38Cal Newport?

  If you want to do a job that's kind of like a hobby, you can do that job, but otherwise AI and the robots will provide any goods and services that you want."

• 57:47Cal Newport?

  But progress in creating these agents has recently slowed to understand why requires a brief snapshot of the current state of generative AI technology... All right, so this is the setup. Agents were the things that we are referring to when we refer to AI taking over knowledge work jobs. An agent is where you take something like a foundational AI model, like a language model, and then you add extra software around it that has memory and goals, and it will continually query that model to figure out like what to do and then can take actions based on like what it says, right? So like in a simple way of understanding, one of these agents might be an email agent where the agent software, this is not AI, just normal software, like talks to your

• 58:27Cal Newport?

  email server and says, hey, give me the latest email that we received, and then it takes the text, and then it says, I'm going to create a prompt that says, here is a prompt from a recent email, please like describe like how I should respond. And then they'll give that prompt to the language model, the language model responds to the agent, and then the agent like takes that response, talks to the email server, says, hey, send this email back to the sender, right? So it's a mix of AI models and just sort of control log. That's an agent. It's software wrapped around AI models that can actually take actions in the world. And so the idea is, these language models are so smart and powerful, we could just add agent wrappers around these for like many different types of tasks, including multi-step tasks, because they can query the model many times.

• 59:10Cal Newport?

  They can query the model and say, give me a plan, and then it can query the model for each of the plans and say, how should I do this step? And then it can actually implement what the model says. This is the vision, or one of the main visions for how AI was going to automate these jobs. But as mentioned in the thing I just read, progress has somewhat stalled. So here's what's happening, and I'll just summarize this for you. Not long ago, there was a belief in the generative AI world about so-called scaling laws, which was this idea that if we continue to make language models larger, more data, more parameters, treat them with more GPUs, their capabilities on basically everything you can do with them is going to get better.

• 59:47Cal Newport?

  The scaling laws held for a little while. GPT-2 was much better than the original GPT. GPT-3 was a giant leap beyond GPT-2. And when GPT-4 came out, for example, it was better than GPT-3 in like nearly every way. They made the model bigger, they trained it longer, and like everything you would ask GPT-3 to do, it would do better. So there is this idea that if we keep scaling, these language models will have so many capabilities, there's so many things you can ask it about that will give you good answers to, that we can just wrap agents around GPT-5 or 6, like whatever level it is, it'll be smart enough that we can wrap agents around it for like any sort of reasonable work task. And it'll be this army of agents that's going to be automating work. And OpenAI was like, this is going to be the key to our revenue.

• 1:00:32Cal Newport?

  They're losing a lot of money, this like this will be the key to our revenue. That was the idea. The scaling laws have been faltering. After GPT-4 and roughly these equivalents for other types of other companies like Grok 2 and some others, continued efforts to make these training, the training sets, the GPUs and the parameter sizes much larger, weren't yielding the same type of giant improvements. This is why, for example, GPT-5, which we've been expecting for a long time for now, never has, hasn't come out yet. They've been training bigger models, but they're not getting the same leap that they got with like, say, GPT-4. This is why, as was reported in the Wall Street Journal last week, Meta had to make this announcement that their newest model, their newest Llama version, which they codenamed

• 1:01:17Cal Newport?

  Beameth, which they trained on like 10x the size data centers, they're delaying its release because when they were done, it just wasn't that much better than the last model, not better enough to release it as like a brand new product. It's why when Elon Musk put a crazy amount of money into a huge data center for Grok 3, it was like a little bit better than Grok 2. So these giant leaps aren't happening anymore. The scaling laws are beginning to falter. So if we can't just assume that language models will just keep getting smarter and then we can just ask it to do anything, where has the attention turned in the industry? Well, it's turned instead to doing reinforcement language tuning on existing models. So here's how this works.

• 1:01:59Cal Newport?

  This is, you take a, what they'll call foundational model, but just an existing language model like GPT-4. And then let's say you have a particular thing you want it to be better at, like producing computer code. You create a big synthetic data set of like, here's questions, and here are the right answers to that question. And you go through when you give these questions to the already trained foundational model and then you use reinforcement learning to say your answer is right or wrong or here's where it's right or wrong and you use that to adjust its weights in such a way to get better at exactly that type of problem.

• 1:02:34Cal Newport?

  You have a good synthetic data set for a particular type of problem and you tune it properly, you can then tune your foundational model to be good at that particular type of specific type of prompt. So like when you hear about, you know, OpenAI saying this model is really good at reasoning. What that means is they started with something like GPT-4 and then they generated a giant synthetic data set of reasoning questions with step-by-step answers and then they would give each of these questions to GPT-4, whatever the foundational model is and they would, you know, as it spelled out its work, they would say that step is wrong and that step is wrong. And with this fine-tuned reinforcement training, it could get good at solving those type of problems. You ask it those type of logic questions, it'll show its reasoning, do well at it. Math is well suited for this as well.

• 1:03:17Cal Newport?

  OpenAI is supposedly paying like a hundred dollars an hour for math PhDs to write all these sample problems and answers so they can create this big synthetic data sets that try to tune certain foundational models to be good at solving these types of math problems. You can do this with computer programming and reasoning as well. So for like certain things, you can use these synthetic data sets, tune a foundational model through reinforcement learning to be good at replicating the type of question and answer pairs that are in this synthetic data set. This is really where all the energy is now. It's why OpenAI didn't release GPT-5, but instead released like these six different models with really confusing names. 03, 04 mini, 05 express minus three, like, you know, what are they doing here?

• 1:03:59Cal Newport?

  Each of those is a foundational model tuned with reinforcement learning to different types of synthetic data sets and one that's good at one might not be as good as others. This is sort of where we are now in the industry. Now, this can create really cool tools. If you have a good data set for a particular problem and you're starting with one of these really fantastic foundational models like GPT-4, you can get really cool results, like the type of math problems are in synthetic data sets we get better at. They did this for the International Math Olympiad, which famously has these like really devious, difficult math problems that require these insights. Well, they generated a huge amount of sample math Olympiad style problems and they tuned a foundational model with and it could get really good at doing like math Olympiad problems.

• 1:04:42Cal Newport?

  So this is where we are now, but what this gives us is sort of like bespoke abilities. And they're somewhat limited to where we have the right data to do this reinforcement learning. This is very different than the vision of we will scale up a general model until it gets so smart that we could just ask it any of these things. Like the vision was GPT-5 would just be good at the Math Olympia, would be better at math and would be better at programming and would be better at logic. But instead, we have to find, we have to tune with reinforcement learning GPT-4 for each of these separate purposes. So the issue for work is there's a lot of things we do as knowledge workers, that there's not a good synthetic data set to tune on, right? Because it uses a lot of sort of like shifting bespoke information. I have to know who's who, how my company particularly works, like the current emotional

• 1:05:26Cal Newport?

  state of the different people in my companies. I don't have a way of like tuning or profitably tuning a foundational model to be good at that particular thing. So what we're going to get probably is a lot of agents that can do certain things really well, or models that are tuned to certain things. But we're not going to easily get to a place where we can just throw out agents for every task we want to do. So even a task that seems as basic as emptying an email inbox is going to remain beyond this current technological trajectory because there's just too many specific bespoke idiosyncratic abilities required for me to answer my inbox with the specific people involved in a particular company I'm in, with a particular history we have in the last six months of what's going on.

• 1:06:08Cal Newport?

  That's, we don't have a synthetic data set for those type of emails and how to answer them that we can like tune up a model on. So I think where we are with workplace automation is we'll get maybe some more agents, but I think the, the big wins in the, in the workplace is going to be, A, natural language interface of software, I talked about that in this article, but it's going to be using the understanding portion of these models so that I can just tell software what I want it to do without having to learn the software, huge productivity boost, not sexy, but huge productivity boost. And the continued expansion of the true killer app of the first generation of generative AI, which is smart searches. Where now I can ask something like a new version of ChatGPT, you know, questions about anything and it can search the web to get information.

• 1:06:52Cal Newport?

  It can analyze it and give me my answer. It can give me the answer in whatever format I want. I can give it my own input. Hey, here's a report. Can you go through this and tell me, you know, summarize in a table like the main takeaway points? This is like a huge ability. I can give it, someone wrote me about this recently in response to my article, like a photo. Hey, can you analyze what's going on in this photo? Right? What, who's in here? What's going on here? The smart search capability. The models can take information, be it from the web, from your local files or whatever, and like do a pretty good job of understanding it, reordering it, reorganizing it and producing it in a format you need. This is the thing that raises the killer app. Whenever you hear people say like, I'm so impressed with AI.

• 1:07:35Cal Newport?

  It's usually a smart search application that you're talking about. And this is no small business, right? I mean, just web searches alone earned Google $175 billion in 2023. This is the way that OpenAI is going to find profitability. Not $20,000 a month agents that people are paying for to like automate doing some sort of task in my job. It's going to be, we all are just talking to these like smart searches all day long. It just makes various parts of our life easier, right? It's, can you look at this report? Pull out these examples, put them in an Excel spreadsheet. And then when you get to Excel spreadsheet, you can just ask the spreadsheet, can you make a chart about this? No, no, make it a pie chart. Can you make the colors red, green and blue instead? Make those labels larger. Great. Can you email that?

• 1:08:20Cal Newport?

  So it's not your job being automated. It's the, some of these steps you do in your job, I think, are going to be, you're just going to have more power. You're going to be able to do more things than you could before. So don't sleep on natural language interfaces. Don't sleep on super searching. But also don't take too seriously people that say that increases in ability over there means... Like we're going to have AGI or super intelligence. I get this feedback all the time. They're like, well, look, we, we, we weren't be able to do this. Now we can do this. So naturally like we'll be able to do everything else. You can't, this is like an EA thing. You can't just assume you're going to keep moving up the exponential curve. The scaling law has failed.

• 1:09:01Cal Newport?

  We're now having to synthetically train foundational models for particular tasks for which we need particular data.

• 1:09:09Cal Newport?

  So there is big change coming. It's going to be incredibly intuitive. It's already happening now, but it's not going to be our jobs being fully automated. I think that's more of like a attention catching thing, but there's not a reasonable tech story for that right now. Just like there's not a reasonable tech story for like a full genius level AI. There's not a reasonable tech story for superintelligence. Until someone can deliver you, here is the technological story of how that will happen. We, I'm not listing as much. I don't, I do not extrapolate from, we were able to get from A to B. Therefore, we should be able to get from B to whatever C I want to choose. That's not the way that works. We get interested in a particular application when someone can show us this is what we need to do to get there. We're just missing P, B, and C, but we're working on it and we're making progress on it.

• 1:09:53Cal Newport?

  That's when you start thinking about that. So anyways, not to get too much down that track, but when it comes to will my job be automated? No, but certain parts of how you deal with information is going to become way more powerful. Certain ways that how you'd use to talk to software is going to become way more easier. And I think this is going to make people more effective, productive and make jobs better. And that's like in the next two years, timeframe that we're talking about. So I actually think that stuff's going to be kind of exciting and not all these AI companies will survive, but there's enough value there for at least some of these to survive, even with the big expenses of all the compute, et cetera, they have to do. But there you go.

• 1:10:29Speaker 01

  175 billion a year for Google is.

• 1:10:32Cal Newport?

  Yeah.

• 1:10:33Speaker 01

  A lot of cash.

• 1:10:34Cal Newport?

  It's a lot of cash. Yeah. Their stock fell when it was revealed that Google searches are down because more people were using.

• 1:10:41Speaker 01

  I know. So I've seen that.

• 1:10:42Cal Newport?

  Yeah. Yeah. It's huge business. And I think this layer between searching and answers would be, that's going to be a really big change. We're really used to like getting lists of websites. Right. But I do think, by the way, Google will catch up. There's a really, there's a really interesting, Ed Zitron won a Webby Award for a podcast episode he did on his Better Offline Podcast about, I think it was called The Guy Who Ruined Google Search. And the, the argument of this sort of audio essay was that Google has particularly, like on purpose, not improved.

• 1:11:18Cal Newport?

  Google search like along these lines of like, let me just talk to it and you give me the answers and because they can sell more ads, actually having more and more pages of results and you have to do more searches is better for them. So they kind of are hobbling themselves on purpose because it keeps revenue higher now, but it could shoot them in the foot in the long term because people are, you know, Gemini is not very good. And no one looks at those Gemini answers at the top of Google, but more and more people just go to chat GPT and ask their questions. I think Google can catch up. That was the problem. Like when there's $175 billion at stake, people are so used to google.com. Yeah. All they have to do is like, all right, yeah, we're a little behind, but we're going to like, change this to look like what people get with chat GPT. And people like, yeah,

• 1:12:02Cal Newport?

  I'm still used to going to google.com. So I think Google could keep, there's so much money at stake, but that's, that's, I don't know. It's like, OpenAI is trying to fake people out with talk of agents. Then Sam Altman just talks about crazy stuff, you know, Dyson spheres to capture all the power, super intelligence. You can't, crazy things come out of there. And like, the more they get worried financially, the crazier they get with what they talk about. But this is probably what they're really thinking. It's like, if we could, but maybe they don't want to talk about it because they don't want to give Google too much warning. Like, we need to win search. We need to be like powering the software interface for all software that people are using. Like, that's where the real power and money is, I think. Not, you know, somehow 9000 just does all your

• 1:12:42Cal Newport?

  work for you. All right. Well, anyways, that's all the time we have for today. Thank you for listening. We'll be back next week with another episode. And until then, as always, stay deep.

• 1:12:56Cal Newport?

  Hi, it's Cal here. One more thing before you go. If you like the Deep Questions podcast, you will love my email newsletter, which you can sign up for at calnewport.com.

• 1:13:09Cal Newport?

  Each week I send out a new essay about the theory or practice of living deeply. I've been writing this newsletter since 2007 and over 70,000 subscribers get it sent to their inboxes each week. So if you are serious about resisting the forces of distraction and shallowness that afflict our world, you gotta sign up for my newsletter at calnewport.com and get some deep wisdom delivered to your inbox each week.