Deep Questions with Cal Newport - Ep. 343: A Minimal Protocol for Taking Control of Your LIfe

Episode Date: March 10, 2025

One of the most commonly recurring themes on this show is the conflict between too much versus not enough productivity. In this episode, Cal attempts to find new clarity in this debate by identifying a minimal viable productivity system – that is, what are the bare minimum components needed to escape the chaos and stress of total disorganization. He then answers listener questions and dives into a A.I. themed Tech Corner segment. 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: A Minimal Protocol for Taking Control of Your Life [3:23] - Is “finding purpose” and “following your passion” the same thing? [32:38]- How can I capture key takeaways from podcasts if I’m always on the move? [37:18]- Can you elaborate on project work with your PhD students? [39:22]- How can I deal with my federal job with drastic priority changes due to political party shifts? [41:40]- Is it possible for some managers to avoid pseudo-productivity? [49:15]- CALL: Writing a book as a side hustle [51:58] CASE STUDY: An athletic trainer makes a career transition [59:19] TECH CORNER: A.G.I. versus SkyNet [1:07:30] 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?nytimes.com/2025/03/04/opinion/ezra-klein-podcast-ben-buchanan.html Thanks to our Sponsors: cozyearth.com/deepbyloftie.com (Code: DEEP20)oracle.com/deepquestionsindeed.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. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

I'm Cal Newport, and this is Deep Questions, the show about cultivating a deep life in a distracted world. I'm here in my Deep Work, HQ, joined as always by my producer, Jesse. Jesse, who just taught me something useful, complicated, I would say from a technological standpoint and useful. It turns out you can share a contact on your iPhone with another person. When you asked me how to do it, I thought you were kidding at first. And then when I realized you were serious, I was like, we need to tell the audience this that you did not share contact. I am from an era where sharing what this meant was,

you go to your Rolodex and you flip through until you get to the right letter. And you take the card out of the Rolodex. And then you go and make a Xerox copy of that card. You fax that Xerox copy to the other person. You wait for the fax confirmation. Then you're done. That's what I'm dealing with here. That's my level of technology.

So, yeah, this was useful. You could do a thing and click on a name and click on share and select your name and then like you have that information now. I also have heard rumors so my wife does this, but I'll know how she does it. You can send like locations on a map to someone as well. Yes. Like here's where. And then if you click on it, it loads up the map. Yeah.

Again, I'm calling up AAA. Can you send me a roadmap of this area? I'm in between these two signposts. between make it after mile point 341 take a right after the barn and then what I do is I put that in a a satchel and have it messengered over on a bicycle. That's how I'm still doing this stuff. Anyways, technology is now clearly, clearly I'm kind of, here's what's ironic about this, Jesse, is at the end of today's episode, I have a sort of off the rails tech corner where I, not only am I going into AI, like cutting edge AI,

I have not one, but two different, like, original theories with their own catchphrase names to understand the absolute cutting edge developments and potential of AI. And yet, I still just figured out how to share a contact on my iPhone. There's a lot of sort of, I don't know what you call it, split personality here, but I'm a theoretical computer scientist. Like, you know, some stuff I know really well and the useful stuff, I don't. A theoretical computer scientist is like if you took all of the earning potential out of a normal computer scientist, that is a theory. electrical computer scientist. We can't actually do anything useful, but we can talk about doing the sort of multivariate derivations needed for back propagation, but we can't actually build you a deep learning neural

network that would actually make money. So there we go. We do got a good show, though. We're going to dive into a concept. I've been noodling for my new book and the deep dive. It's related to the productivity and the deep life and distraction. I think it's good. We've got a bunch of questions to get into here.

And then as I mentioned, the sort of off-the-rails tech corner, I've basically combined like four tech corners in the one like 10 minute segment. So this should be interesting. But I was just feeling techy this morning. So I should all be good. All right, Jesse, we have a lot to get over cover. So let's get started with our deep dive. So one of the conflicts we've confronted here is the one between having too little

productivity and too much. We know the problem with too little productivity in your life. This could be disorganization and stress, scrambling, job insecurity. People stop counting on you when it comes to things at work. or in your personal life, and you feel like you're not making progress on any of these things that are non-urgent but important. As Emerson said, the crime which bankrupts men and nations is that of turning aside from one's main purpose to serve a job here and there.

But we also know the problem with having too much productivity in your life. Your life can become re-centered on optimization itself as you fill more and more of your time with execution for execution's sake. You can lose a sense of wonder and appreciation for anything other than just, mechanistic accomplishment. Here's Anne Helen Peterson summarizing some of these fears. This is the dystopian reality of productivity

culture. Its mandate is never you figured out how to do my task more efficiently so you got to spend less time working. It is always instead, you figured out how to do your tasks more efficiently. So now you must do more tasks. So this conflict got me thinking recently that there's a key question lurking

underneath all this conflict that we really haven't talked about enough. And it's the following. What is the minimally viable productivity system? That is, what is the minimal set of rules and tools that will allow you to escape the problems of having too little productivity, but not jump all the way into becoming a task juggling superhero? Just enough to find some breathing room, but not enough for your life to become all about execution. I think this would be useful to figure out because it would provide us with a common. in starting place where everyone should begin from, a sort of baseline minimally viable

productivity that you start from to get away from the hardship of being too disorganized, a hardship of being someone that no one can count on, the hardship of not being able to make progress on the things that you care about, but just enough that you have flexibility in there for you to figure out what fits you and your goals and your personality when it comes to how much more organized you want to be. That's what I want to try to do today. I've been thinking about this topic. I'm writing a chapter of my new book on this, so I'm beginning to bounce ideas around about this topic. And what I want to do today is start by first figuring out what are the actual problems

that we would want a minimally viable productivity system to solve. Then two, identify what are the key components, a system that solved those problems would need the feature. And then three, give some ideas about then how might you concretely implement those components. Here I think the key is there is no one right answer. once we know the minimal components of a minimally viable productivity system, I just want to talk about what might you look for in implementing these and how you actually do it can be a choose-your-own-adventure.

All right, so that's our goal. Let's get into it. I want to start by saying, what should the goals be for a minimally viable productivity system? I don't have this locked in yet, but I've been thinking about this for a couple weeks now. And there's three goals that come up most common when I think about what I really want out of this. The first is going to be stress reduction. I need a productivity system to make my life less stressful. This is sort of table stakes for trying to bring more organizations to your life in the first place.

Second, I need this system to increase people's perceived understanding of my responsibility or increase my responsibility. What I mean by this is professionally I don't want to be dropping the ball. However this system runs, I don't want to be seen as someone who may or may not get something done if you give it to me. I want to be someone you can trust. I want the same thing to happen to my life outside or if a friend or someone in my community needs me to handle something for them or ask for my help. They trust, I'm not going to forget about it. I'm not going to flake. So whatever the system does, it should give me that sense of responsibility.

I'm someone you can count on. Finally, I think whatever else the system does, it has to be able to help me make at least some progress on things that are important but non-urgent. I think that word sum there does a lot of work because depending on what circumstance or stage of life you're in, how much progress you might be able to make on an important non-urgent matter could really vary. I mean, if you're like 24 years old and your job is not that demanding and you have some sort of big idea you want to make progress on, you could be spending a lot of time

working on this. The other extreme, we can go all the way to like Victor Frankel and Mansearch for meeting, right, his memoir of his time during the Holocaust and then the, the psychotherapy field called Logotherapy did he create in its wake. And there he was pointing out just having something, matter how minor it could seem in a different context, having something that you are working on that you control because you chose to do it, is critical, not just a human flourishing, but human survival. So we got this whole spectrum of what doing some work could mean. But the key is A system should make sure that there's always some room for you to make progress on stuff that's important that no one's asking you to do it, that you have some autonomy and control in your life.

So I want those three things out of any system, but I want the minimal system that gets me those. That's my goal right now. All right. So then I started thinking, what components would a system have to have to satisfy those three things? This two is contentious, but after thinking about this for a few weeks, three things came to mind. Here's my best swing. The first is there's got to be some notion of task management. So there has to be some way of keeping track of the things that you have agreed to do that is not just in your brain.

This is going to be vital for basically all three of the goals we have for the system. You're not going to drop the ball on things. It's going to reduce distress of just trying to remember things in your brain or forgetting about things until the last minute and having deadline overload, which is like a huge source of acute stress. in people's lives. Also as a way to keep track and remember of the things you need to do to make progress on non-urgent tasks, that's kind of at the core of a lot of things. There has to be some basic way to keep track of what you've agreed to do that doesn't exist just in your brain. The second component any such system must have is some notion of workload management.

So if task management is about keeping track of what you've agreed to do, workload management is about controlling the volume of things that you agree to. It's like the gate through which obligations come. This is a piece of my thinking that I think has developed, especially in the last few years. It became a big part of my most recent book, Slow Productivity. It's probably a part that had been neglected. And so my earlier thinking about organization of productivity. But the amount of stuff that you're actively working on plays a vital role in almost all aspects of your mental health as well as your effectiveness in both your professional and personal life. So you have to have something, a minimally viable system that satisfies those goals, have to have some intentional thought about what my life.

workload is and what I am trying to do to keep it within a range that is reasonable. You don't have that there. You do everything else in productivity. You could end up executing a heck of a lot of stuff and being stressed out of your mind and not actually being able to work on the stuff you want to work on. All right. Final component, I think any viable productivity system is going to have to have is some notion of time control. some notion of like, I want to have a say in how my time is allocated on a day-to-day basis.

Maybe say, well, how would you not have a say? I mean, you're always making decisions, but not really. Actually, the default that people do is much more of a reactive mode. I am reacting to things that come towards me, maybe an email, maybe a Slack, someone calling me and saying, hey, where's this thing? I'm reacting to things that people are asking for me. and in between reacting, I sort of just drift off into a days of digital distraction

and pacification until I get stressed about something else and then I react to that stress by doing something else. Most people's days unfold haphazardly. If you pin them down

that morning and said, what do you think is going to happen today and then you see what actually happens there's going to be very little convergence between it. They are being bounced around a sort of time schedule pinball machine

and they're not the ones hitting the flipper buttons. And so we want to have at least a resistance to that. It doesn't mean be able to control your day. Like, oh, I have exact control what I'm going to go on, but you're going to have some intention that's going to be applied or at least attempted to apply.

I just think you have to have that in any viable productivity system, at least if you want to hit those three goals I talked about before. There's a lot of other stuff you might do with productivity, but first talking about a minimally viable system, those are the components. I think you have to have task management, workload management, time control, some systems for each. So I want to go through those. Let's go through those three components.

And I'm going to do two things for each. I'm going to give an idea of a bare-bones thing you could do that would put that some sort of system there in your life. And then I'll talk about more like what I do in that component, more of like a moderately advanced. You can get a sense of the options. But the key thing I want to emphasize here is these are just samples of possibility. So by giving you a bare-bones way of implementing each of these ideas

and a sort of moderately advanced way of implementing each of these ideas, what I'm trying to do is just give you a sense of there's a large landscape of possibilities here. You can choose your own adventure. You can choose your own adventure based on what the details are of your particular situation and also of your particular personality, what resonates or not. I mean, some people are going to want to go way more analog than this because they get a sort of aesthetic rush out of having something that looks beautiful. other people really love high-tech systems. And they're like, I really want an AI-powered Zetelcast and bot playing a big role in what I'm doing. And some people really enjoy that.

There's nothing wrong with that either. So you can customize this. But I want to give a couple examples so that you, the point I'm making is there's no one way to do these things. All right. So let's get specific. So let's go back to task management. What we need here, right, what are we trying to accomplish is some notion of what David Allen called a trusted system, a place where, place where the things you need to do ends up and you trust yourself to review it regularly.

Those two things is what helps prevent you from from beginning things and also reduces distress of trying to keep track of things in your mind. As soon as your mind trust, where I wrote this down is a place I won't lose it and a place I won't forget it. Then your mind releases. All right. That is a classic David Allen and David Allen himself was actually adapting that idea from Dean Atchinson.

So we can kind of follow this chain back if you want to go through productivity culture. All right. What's like a bare-bone ways of implementing this? The bare-bone way here is a text file and a calendar. You need a calendar. So stuff that is due on particular days or happens at particular times, just go straight on a calendar. It's a tool that we all use.

It's remarkably effective technology. It's probably one of the oldest productivity technologies. The oldest probably is actually what counting tablets, cuneiform tablets going back to the Sumerian days, but tracking things with time. was another one of the early applications of technology. So have a calendar. And then have a text file where you're just like,

I'm writing down things that I have to do. That's the simplest implementation. When I was in graduate school, there was a period in which I was implementing the system where I used a calendar on my computer and I had a tablet, like a legal pad. I remember it very vividly because it was a C-Sail legal pad. C-sale was the computer science

and artificial intelligence laboratory. So at the time, this was like the CS department at MIT. There's now a school of computing. It's a whole separate sort of thing. And it was swag. I don't know where I got this. It was just swag. It was like a white legal pad and it had the C-sail logo, the status center up in the corner.

And I just kept a list of there of things I needed to do. And I would cross things off as I would do them. And eventually the page would have so many things crossed off. I would copy the uncrossed off things to a new page that was clean. If you want a more modern or work-through example of that very simple way, look at writer Carol's bullet journal method. That does something similar. you write things you have to do and just copy to a clean page when it gets too messy. But that's the bare bones here.

I have a calendar for things that are time sensitive in a file or a notepad that I have everything else. That works. In a minimal viable system, that's enough. If you want to get somewhat more advanced, you can combine a calendar with a status board. This is, of course, I've talked about on the show what I do. I use Trello. One board for each of the roles in my life. A different column on each board for different statuses of things I need to do.

each card and each column is a thing I have to do. So I might have a board for my role as director of undergraduate studies for the computer science department at Georgetown. And I might have a column in there that is something like major declaration request that still need to be processed. And then I have a card for each student who has written me saying, hey, I want to declare a major. And I have kind of the information I have in there. I have another row in that that says to discuss with the chair. at the next meeting I have with the chair. I have another thing in there that says to discuss with the associate director.

And there we meet once a week and I store cards there with tasks that we're going to discuss at the next meeting. I have a waiting to hear back from column there that's very important. Oh, I had a question of this student. And now I'm waiting to hear back from him. I put a card there so I won't forget that explains. Here's the student. Here's what I asked them. I'm waiting to hear back this.

Here's the next step. So that's what I do, status boards. but as long as you have some way of putting stuff down where you're not going to forget it and you'll review regularly, you have a minimally viable task management system. What about workload management? Well, here, look, you need some way of estimating your current workload. So what is on my plate. We sometimes use the phrase on this show facing the productivity dragon, just facing directly, this is the full magnitude of what is on my plate, of things I've agreed to do. you need some way of understanding

what your personal maximum effective workload is. This is roughly how much I can do at once. That estimate may be broken down in the different types of work. And so you should be able to compare those two things and have some sense

where your actual workload is going beyond you're estimated like this is what I'm comfortably can handle. And the workload management needs some collection of rules and tools that you use to try to keep those two things balanced. That's what a workload management system. needs. Now, how you do that, there's a million different ways. If we're going to go with just

minimum simple things you could do for workload management to satisfy those properties, a couple simple ideas, and these come from my book, slow productivity. Preschedule big commitments on your calendar is a simple thing to do. All right, I'm going to agree to do this big thing. I'm going to go and actually find the time on my calendar at the point of agreement. I will go at that point and go find time on my calendar to schedule to work on this. If it takes 10 hours, I'll find three hours here, four hours here. I will find and protect that time. So now I'm actually allocating my actual hours to the agreement as opposed to just agreeing it.

And it's just abstractly added to my workload. And as it gets nearer to do this, like where am I going to find the time to do it? You get a nice little reality check from having to preschedule time for major commitments, which is if you don't have that time available in the near future, you can't avoid that reality. Because you're trying to find, hey, I got to schedule the 10. hours for this hypothetical chore. And if I can't find those 10 hours in the next two weeks, I can't do it in the next two weeks. It gives you feedback on how crowded your schedule actually is.

Or at first you're easily finding time for things, but then as your schedule fills, you have to start looking out farther into the future to schedule things. And eventually you have to tell people like, yeah, look, I'm scheduling a month out now. I've filled the next four weeks. If you're not prescheduling time and you're just saying yes to all those things, it's still going to take up that much time. You just don't know it yet. You're going to have to pay that bill, so deadlines get due, and the work is going to get done in a frenzy of stress.

It's not going to get done that well. Another very simple thing you can do is have quotas for a particular type of work. Yes, I do these type of committees, but only one per quarter. Yes, I'm willing to do peer review, but I do four per semester. Once I hit my quota, I'm done. Yeah, I do calls. I think it's important in my role as an entrepreneur that I do calls, hop on calls with young entrepreneurs who want advice, but I can only do one per week. Quotas allow you to keep things that are important, but potentially schedule strangling.

They keep those things in your life, but in a way that is reasonable. Another simple thing, if you're just doing bare bones here, would be project counts. You just figure out through experience, maybe through doing that pre-scheduling for a while, how many projects are the major types of projects you do in your job? How many can you usually handle before things become a little bit too stressful? And then you just have this very simple system. I only do three at a time. I'm out three.

I've got to wait until I finish something. It's this bare-bone things you can do for workload management. If you want to get more advanced, you can do, like I talked about, slow productivity, some sort of individual scale or team-scale implementation of an agile, con-bond-style work tracking system where you separate what you have agreed to work on or your team has agreed to work on

from what is actually being worked on, and you have clear WIPs or work-in-progress limits for what is actually being worked on at any one time. If you have a team, you could actually have something like a Kanban board where there is digital cards. He's used to be done with physical note cards on bulletin boards, but now there's any number of digital products for this. Of all the things your team needs to work on. And those things exist in a sort of to be worked on section of your virtual board. No one is responsible for those things until they get moved to the column for someone labeled with

someone's particular name. And then I can see, like, okay, here's the Cal column. The things under the column is what I am working on now. These are the only things you can talk to me about. The things over here, no one's working on yet. You can email me about these things. Hey, what's going on with such and such we talked about? It's not been assigned yet.

I'll talk to you when it is. Here's the two things I'm working on. And you have a clear limit. Like, here's what's reasonable. Work on two things at a time, three things on a time. You can give those things a lot of time. The fraction of your schedule dedicated to administrative over overhead is reduced to a point where you can be very effective with applying your brain to

accomplishment, the throughput with which you finish things goes up. So you could do this as a team. It really works if you have a sort of like daily stand-up style status check-in where it's like who's working on what, what do you need from each other, now let's go work. I talk about slow productivity, how you can even implement something like this for yourself, even if your team has no interest in this, where you personally differentiate on the things you've agreed to do between the things you're actively working on and the things you're waiting to work on. And you don't take meetings to do emails or really dedicate any administrative

overhead to the things you're waiting to work on and you make this whole list transparent. And when someone who gave you something to do that you're waiting to work on bothers you, you can push them to that list. You can see where your thing is. And as soon as it moves to my active status, you'll hear from me. I'll tell you right away. But until then, I'll say this nicely, you know, bug off. Of course, you won't say it that way. You'll use all sorts of fancy language, but I'm a professor, so I don't really know how to interact like a normal human in a business environment, but I'm sure you all figure that out. There's some fancy way you do that.

So yeah, you can get as complicated here as you want. But just having some sort of, at least you need some sort of minimal way of saying how much am I working on, how much is too much, and what am I doing to try to keep those two things in balance? Get to have something there. All right, the final thing is time control. What I talked about before, our goal here is to have some sort of proactive control or intention in how your day unfolds, even if you can't control it beat by beat, have some intention

embedded in your day as opposed to just reacting. So here's an example of just like a bare minimum thing you could do here. Some sort of morning review. First thing in the morning, maybe I'm keeping my tasks in a legal pad like we talked about. I have a calendar. Look at the calendar. Look at your legal pad. What's on my plate?

Maybe grab a couple things off that legal pad and say, okay, these are the things I want to try to get done today. maybe kind of figure out, here's the most important things I want to do. Why don't I do it? I see I have an open time on my calendar. Let me just start. That's when I'll do them. Make a few decisions.

It's putting minimal intention into your day. More advanced thing would be like I do multi-scale planning where I plan on multiple timescales. So in like the semester time scale, I'm thinking about my big picture goals for that semester. I look at that plan every week when I make a weekly plan. Critically, my weekly plan, I'm looking at everything scheduled on my calendar. I'm going to move things around if it's, going to really unlock my week.

If I move this or cancel this or move this to this day, it opens up big time here. So you play chess with your calendar during a weekly plan. I also schedule progress on the big rocks for my semester plan. I'll schedule them right on my calendar during the weekly plan. You know, I really am trying to make progress on finishing chapter three of my book by the end of March. I saw that in my semester plan. So now when I'm doing my weekly plan, I want to get like five hours blocked off on my calendar for writing just to make sure that time gets done. And then the final scales every day in the

morning I like to do a time block plan. Give every hour of my day a job, not reacting. I want to see the time I have and make the best possible plan for it. Yes, I'm going to get knocked off this time block plan within a couple hours and I'll have to adjust it a few times. And sometimes it'll be okay and sometimes I'll never recover. But I'm going to try to have some say on how my day unfolds. So that's a more advanced way to do it, multi-scale planning. But again, you can start with something as minimal is just like five minutes every morning. Where's the list? Where's the calendar?

What am I wanting to do today? Or what's something I want to remember to do today? Just like give it a little bit of thought before you open that email inbox before you jump in the slack. All right? So to summarize, we can go on and on about the optimal productivity systems or the best productivity systems or the most modern productivity systems. But if you want just a minimally viable productivity system, that sort of bare bones that

I think everyone in the modern knowledge economy needs to avoid stress or disillusionment or burnout. You got to have some sort of task management component. You need some sort of workload component. You need some sort of time control component. And even if they are super simple, you are going to save yourself from the worst deprivations of being not productive enough. And yet, focusing on these three things, if you're reasonable about it, that also saves

you from that sort of optimization mindset thing, right? It leaves that to the people who, like, think about productivity as a hobby. I think it puts you in a really good place. So there we go. The MVPS, minimally viable productivity system. That's my current take on this issue. I'm sure it'll evolve. But I think it's an important one to throw into the discussion.

I can't call it MVP as minimally viable product is a real Silicon Valley piece of lingo. Okay. Have you heard that lingo? Just most valuable player. Well, then there's that as well. Yeah. But in Silicon Valley, it's like rapidly developing the simplest possible like software product that like does something useful as opposed to trying to build a fully featured piece of software before you release it. Minimally viable product.

And they didn't think about MVP because Silicon Valley people not playing a lot of sports. I don't think that crossed their mind. I don't think they're, I don't think they were thinking about that. So MVPS is what we'll call it. minimal viable productivity system. All right, so we've got some good questions coming up, but first, let's hear from some sponsors. Want to talk about our friends at Cozy Earth. Cozy Earth products are designed to transform year 5 to 9, the time that matters most, into the coziest sanctuary.

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The sounds are beautiful. part nature, part orchestrated music, so it's like a calm way to wake up. I really like this. It's an all-in-one bedside sound machine, so you can also use this to play sort of like white noise sounds or nature sounds. It looks beautiful. The one that I have in one of my kids' room has like these, it's like a, I don't know what you call it like an oval. And it has these like three lights in it in the front that can light up in the morning when it's time to wake up. My son likes to make a cave out of his pillows for stuffed animals and he'll put his lofty in there.

and it like illuminates the cave and he thinks it's really cool. Like, hey, this is my illuminated cave. His is set up right now to play. We have monk bells. They're like, bong, bong, it's cool. It's a great way to wake up. So you've got to get the phone out of your bedroom, get something that's going to wake you up gently that's going to mimic your natural rhythm.

It's going to look really cool piece of engineering. I recommend Lofty. We have several, and I think you will like it as well. So join over 150,000 blissful sleepers who have upgraded their rest and mornings with Lofty. Go to buy lofty.com and use code deep 20, and you will get 20% off orders over $100. That's B-Y-L-O-F-T-I-E dot com and use that code deep 20. I'll tell you, Lofty is better than my old method for waking up, which is I used to hire Lou Gossett Jr. To hit Garbage Cam Lids.

That's a Lou Gosset Jr. reference officer. an officer and a gentleman. What's the movie? Oh, man. What is the movie where Richard Gere is in Officer Candidate School in Lou Gossett? I think it's an officer and a gentleman.

I don't know to look it up. Anyways, he's a drill sergeant. But I saw, this is kind of a tribute because I didn't realize that Lou Gossett Jr. He must have died this year because I saw him in in memoriam at the Oscars. So that's kind of my tribute to Lou Gossett Jr.

A terrible way to wake up, though. Banging garbage can lids. This is much better. Monk Bells. All right, let's move on to some questions. I didn't see by the lofty notes don't involve if possible make a reference to Lou Gossett Jr. That would be funny

if it was like, if you don't reference Lou Gossett Jr. and this ad, we're going to have to do and make good. We're graded ads, aren't we? All right, what have we got? First questions from Leer. I have a research volunteer position for a nonprofit. I found purpose in this organization, but

it doesn't really match my long-term career prospects, would this still be considered falling into the passion trap or does purpose operate under a different set of rules? Well, okay, we have a couple different things going on here. So first of all, is it a trap to have your volunteer position, your research volunteer position, get in the way of developing a meaningful paid career? There, yes, the answer is yes, that's a trap. If you're volunteering, you need to see that as a volunteer position, like helping out at your

kids school or like your local church. It could be a very important part of your life, but you see it separately than what you see is your paid profession. So it certainly shouldn't get in the way of you developing a meaningful and sustainable paid employment. But there's a secondary question here that's worth getting at more generally, which is the difference between passion and purpose. So there's a passion trap, but there is also a purpose trap.

And I think it's worth trying to figure out what the difference is between these. too. So the passion trap, as I wrote about in my book, So Good They Can't Ignore You, is the assumption that the key to really liking your job is to match the content of your job to something you're really interested in. You say, I have a passion for X. So if my job involves X, I will feel passionate about my work. This was the fundamental model for career satisfaction that was taught to like Jesse Nice Generation. Follow your passion. You'll be passionate about your work. It doesn't work out that way. The factors that make a job, job meaningful and sustainable.

The factors that can help you develop a source of passion for your job are complicated and multivariate and it's much more involved than simply saying, I like this. So if my job is connected to that, I'll be happy. I really like baseball. It doesn't mean that if I take a back office job at the Nationals, then I'm going to love my job. What makes you love your job is more complicated than just the content of it. The purpose trap is interesting.

It's different. So the purpose trap is the fact that your job provides some sort of sense of purpose. So like the work you're doing feels important or is important, that that allows you to put up with lots of other factors about your job and its impact being negative. So the purpose trap is, yeah, this is kind of terrible. Like for whatever reason, like where the hours, the lack of money. money, the stress, but it's important like the field I'm in. So I'm going to put up with those other things. So it's letting purpose blind you to other elements that make a good job good.

Now, again, the reality is purpose can be a very important component in engineering your ideal lifestyle and in particular engineering what you want out of your job, but it shouldn't be the sole component. There's other things you want as well. It could be autonomy, connection to other people, since a mastery, those matter. And then there's a financial reward so it's able to fund other things that are important in your life. And also when you're doing lifestyle-centric planning, you care about how the job fits in and supports other things that are important to you in your life. All of those factors matter.

So you can't let one factor in there. Like, does this job have a sense of purpose? Stomp over everything else. You have to be more intentional about it. So what should you do? Build career capital. First and foremost, be so good they can't ignore you at whatever it is you're doing. And then leverage that capital to take control of your career.

Shape it towards things that resonate and away from things that don't make it supportive of your overall vision of your lifestyle and move away from things that to stabilize your overall ideal of your ideal lifestyle. This is complicated. It's iterative. We talked about this last week in the deep dive, the good life algorithm, the idea that you have to sort of experiment and discover what works and what does and make corrections and adjustments in your life. You're sort of navigating this multidimensional landscape of possible lives towards something that resonates more and more. but it's what ultimately works. So don't look for the one fix. If I'm passionate about this, my life will be passionate.

If I purpose of my job, my whole life will feel good. It's always going to be more complicated. You always have to be sort of solving for the complex equation here. So, I don't know, there's a lot hidden in this question, but I appreciate that because we actually got to get to a lot of interesting points. I didn't talk a lot about the purpose trap and so good they can't ignore you, but it's come up a lot since that book came out. People are like, no, I mean, I'm not passionate about this, but this is an important

cause. So because of that, I'm putting up with a lot of other negative things in my life. That's a real common trap that people get in. All right. Here we got next. Next is from charity. I'm always on the go when listening to a podcast, so it's hard for me to stop and write stuff down. How can I capture these discovered tactics and tips? Well, I think it depends on the podcast. I think for most podcasts, it doesn't matter. For this podcast, I think what Jesse and I recommend is probably you have a dedicated space, for listening to it in.

I would have this built custom if possible. Your inspiration, and clearly doesn't have to be this large, but your inspiration when thinking about like a space that's appropriate for listening to our podcast, I'm thinking like the cathedral and charts. Maybe not you're dumb. Smaller, but something in a similar level of contemplation, and you really should be sitting in there,

dedicating, I would say, easy four or five hours to kind of go slowly and to re-listen and to take your notes. So, okay, ideas from podcast. I don't know. Here's the two things I do. I will jot down time stamps in the notes on my phone. If there's something like, ooh, I want to remember that.

It only comes up so often, right? I mean, some interviews are rich with these. If you're watching an interview show, some have none. But I put timestamps down temporarily in Apple notes. And then you can go later and write those down somewhere else. The other thing I sometimes do, this will happen a lot if I'm working out and I listen to a podcast. and then I get an idea, like, oh, that, like, gives me an idea what they're just talking about.

I voice dictate into Gmail, email to myself. So I'll just like, and they're weird because I have no punctuation and, you know, there's a lot of typos. But I'll just voice translate a bunch of ideas, send. And then after my workout, I have a couple of those emails in there I might want to deal with as well. So you can kind of develop your tricks. The third thing you could do is if you have a single purpose notebook, you could dedicate this, like a field notes notebook and a pin. just have that with you in a pocket. You could just jot in there

timestamps as things come up and you could deal with that as well. So whatever works, but I typically am doing the notes and the emails to myself. All right, who do we got? Next question is from Andrew. In a world without email

and in the podcast, you talk about communication protocols and office hours. Is there anything else? As a professor, I'd love to know how you work on projects with your PhD students. You know, in a world without email,

I talk about a cool study. It was done, I think it was University in Maryland, and they're looking at models for managing, for professors managing doctoral students. And the model they tried that worked really well was borrowing ideas from agile software development. So in particular, they worked on, okay, we keep track of clearly what each of the students is working on, right? So there's no question about that. And we have, like they have in the agile methodology, these daily stand-ups that are like 10 minutes long. And this was actually hard to dial this in just right.

This is not let's all talk for a half hour about what's going on. It is 10 minutes of like, okay, I see you're working on this, whatever it is, writing up the data from this experiment, trying to understand this proof from this paper, working on correcting this mistake and this proof. How's it going? What do you need? What progress did you make progress going forward? And it's quick. And you go through. And in this way, students always know what they're working on and they can't get stuck that long.

This actually worked really well. And it worked well in contrast to what standard, this is the way I was trained, was you have a weekly check-in with each year's students. And you have this meeting and it's an hour long and it feels sometimes it's packed because you have things you really have to work on, but sometimes it feels performative. And students can be stuck for a whole week until they actually get to this meeting. And you might not have the right energy or time to help them make progress or not.

They found this daily stand-up worked much better. So students really know what they were working on. and then you set up additional one-on-one meetings as there's very focused work to be done. Oh, now you're really stuck on a proof. Let's put aside time now for you and I to work on this proof and I'll help you get unstuck. So like the longer meetings are being dedicated for actual, we've identified an actual problem where we can make real progress. But the daily check-in is really quick and the keeping track of who's working on what keeps people from getting stuck. So that feels like a good idea.

I don't, I'm a theoretician. I also work on digital ethics. I don't have large research teams, but I've heard this works pretty well. All right. What we got next? From Chris, I'm a federal worker with recent concerns over incompatible values pitched by leadership. Do I just focus on surviving the day to day despite a values gap? Well, it's a timely question, but it's a complicated one.

So in your lifestyle-centric planning, I took some notes on this, your job is probably supporting many aspects of your ideal lifestyle. I mean, even just having a job, the income, where you live, like what it's supporting, the hours, etc. So what you were working on and how you value what you're working on is one aspect of the ideal lifestyle that your job is supporting,

but it's not everything. So we want to be careful here about making an immediate drastic change because what could happen is you could be saying, there's something I don't like about currently how my job is set up, and so I'm going to leave that job because it's important to me that I like the people I'm working for the mission, but then there's like six or seven other things that are important to you in your life to take a hit, and you're thinking like maybe that wasn't a fair trade, right? So we want to go with some care.

So let's talk about how to be, how to be more discerning here. In my book so good they can't ignore you. I talk about working towards working on things that are directly against your values. I say that's a disqualifier for a job being something that you can get long-term value out of. So what we want to be, if we're going to get more fine-grained about that here, so does this apply or not? You want to be careful here, especially in this government context, about there's a difference between what my job is directly is pushing something that's against my values versus there are things in my job or the place I work for that I value that are being like blocked or stopped. It's like this is really relevant in the government right now where it might be like maybe, you know, you're working on clean water or something like this. And it's not that someone is coming in and saying you have to like actively work on something that's going to make water less clean.

But that like funding's being taken away from clean water. And so there's a bit of a difference there. Or the boss of my boss is someone who doesn't care about. I'm in, you know, regulatory oversight and, like, has a different way of thinking about it. But it's not actually changing what I'm doing day to day yet. So there is a difference between I'm selling cigarettes and I really don't want to be selling cigarettes versus I am helping people quit smoking. And the amount of programs we're working on this has been cut in half. There's a difference between those two things.

It's frustrating to have resources. or projects towards what you care about be reduced, but it's sole deadening to be actively working on the opposite of what you care about. So that I think that is an important distinction. A lot of what happens or what's happening now in the government or when new administrations take over, it often tends to be more of the resources or focus as being reduced on the things I care about versus I am actively being forced to work on something that I directly dislike. That happens as well, but make that distinction.

going to be a key distinction in figuring out how to act here. You also want to be careful not to personalize. This is very common. And jobs in general, this is not just for this government scenario, where you personalize, like you can, because our mind is good at this. We're used to dealing with individuals. So you personalize this individual, this person who's coming in and messing with, maybe my organization is 20,000 people, but this person who's coming in and messing with

it, I hate that person. I could just imagine that person. I dislike them. And I, this is about a battle between me and them. And I'm not going to let them win. You know how they're not going to win? I am going to, you know, I am going to quit. And in your mind, you imagine it like in the Paleolithic tribe where there's 12 of you

and you're making the big display in the group of 12 and the new person who's trying to take over the tribe, can ignore what you did in this big showy thing. But what really happens in a large organization is no one notices. Or that's what they're hoping. They're like, yeah, we want people to quit anyways. They don't care. notice. You can't personalize. You have to see it abstractly. What am I getting from the job? How's it fit into my ideal lifestyle? And then you can take, it just gives you some breathing room,

then you can take your time to figure out what to do. And the answer might very well be, no, no, no, we've changed our mission, like in my government position. I'm now doing something actively just like I need to get out of there. And we've seen this actually happened recently in the government where people are saying, I'm being asked, I'm literally being asked to do something that I don't want to do and they're leaving and they're being asked to leave. But if it's not that, now you can take your time.

Hey, am I still able to make progress admits to hardship, make progress on things I care about to the best that I can? Oh, it's super frustrating, but it's important that the work goes on. Maybe that's the answer. Or maybe it's this whole thing

has been gutted and there's no reason to be here anymore. But my job and its benefits and its flexibility is, you know, it's supporting my family. It allows the hours are reasonable. I can go coach to my kids' little league team or heavily. There's these other things this is making possible that's very important in my life. So I don't want to throw that away. So yeah, I'm going to explore.

I probably need to make a change. But I'm going to take my time finding this. And maybe I'm going to be very checked out mentally and, you know, phantom part-time job and in all this sort of situations. But I'm going to take my time finding this. Because no one's going to notice if I make a big showy thing unless I'm, you know, already famous or something like this as well. So I guess what I'm really pushing here is some is caution in this scenario. Understand the way your job fits into your larger lifestyle-centric vision.

Separate actually working against your values versus working in a place where someone against your values is munking around with it. Frustrating you can't do more is different than frustrating at what you are doing. And then if you do make a change, take your time to make that change right in a way that's going to support your full lifestyle. don't get caught in the trap that, you know, Elon Musk or Big Balls is going to notice and be like, oh my God, I'm going to change my waist.

They quit and they sent this email to their boss and like this is, you know. So you're kind of winning if you're staying in control of your own life. I guess that's the way I would think about it. All right. What do we have next, Jesse? We might have our final corner. Oh, slow productivity corner. Today is we're recording this on the fourth.

Yeah. in the fifth of March is the one year anniversary of my book slow productivity. So over the last year in every episode we've had one question dedicated to ideas

for my book slow productivity which was just our excuse to play theme music. We should have people write in. When we have people ride in the Jesse atkellnewport.com is this the end of the corner should we find another way

to use the theme music or should we just like clean break and move on from the segment? Right now our default is to move on but send your vote if you have one, the Jesse at Calhneuport.com. But either way, we know for sure right now, we can hear that theme music at least one more time.

No, it's just hitting me what the theme music sounds like. What's that? The more you know. Remember the NBC? The more you know. That's why it's hitting our like millennial memory banks right there. All right, what's our question of the week? It's from Daniel.

In your episode, Let Brandon Cook, you argued that letting the brandons of your organization cook will help move the rest of the work culture away from pseudo productivity. What if your organization has a fairly entrenched pseudo product productive managerial work culture that trickles down to knowledge workers? Are there specific recommendations you'd make for moving managerial work culture in a deeper direction? Well, the Let Brandon Cook idea, who I have in mind this beginning to affect is to managerial class. Right.

So the idea from that episode titled Let Brandon Cook. cook was if an organization starts deciding, okay, at least we have some people you have a highly specialized skill. And we're going to prioritize them applying that skill, right? We're not going to, even if it's like less convenient for us or other people, it's not going to be about responsiveness or having the most low friction back and forth conversations or what's going to make our lives easier. It's like, let that person do what they do best because it moves the bottom line.

And I said, if you have a few people doing that, that'll put cracks into, the pseudo-productivity firmament. So this idea that busyness is what matters, that idea itself is destabilized when you have some people who are mattering, not for being busy. And who do I think that's going to really affect psychologically? I think managers. You're a manager and you realize, well, some of these people, they're helping our bottom line more, not by answering my emails really quickly, but because, like, we're letting

them actually spend time doing what they do really well, makes it. hard for you to remain fully committed to the pseudo-productivity ideal that activity is all that matters. So actually, it's the managerial class itself where I want to start affecting some changes. And I think that is where letting Brandon Cook can begin to help make progress. Because once you start thinking another way of measuring productivity is how much actual valuable stuff did you produce, that sounds so obvious because every other measure of productivity and every other sector does that. But we don't do that in knowledge work. So as soon as you're you bring that in the knowledge work.

This many lines a good code. This article's that got this many, you know, readers or won these many awards. When you're thinking about results, suddenly email response time doesn't matter. Suddenly being on Slack doesn't matter. Suddenly, like, what's really important that we need to know exactly what days you're in the office doesn't matter because, like, results can, results for what moves the deal. So I don't know. I think the let Brandon Cook idea starts with superstar performers, but begins to

change the mindset of managers, and now you're going to get over time more flexibility for a lot of other people as well. All right, do you have a call this week? We do. All right. Let's hear it. Hi, Cal. My name's Danny, longtime reader, big fan.

I am a programmer full-time. I also have a part-time gig teaching math. The programming relates to math education as well. And although I don't want to, quote, be. become a writer. I have a book in me about math education, and I kind of wanted to ask you how one goes about sort of writing a book on the side. I've read little things about the king who wrote a book while he waited for his wife to come to dinner in just those little bits of time. So I'm just curious if you had any thoughts or tips or had heard things about how people

manage the process of just sort of kind of putting a book together, not to make a living at it and not on any really strict schedule, but just wanting to, you know, get a book together. Thanks, Cal. Appreciate everything. Well, it's a good question. And when it comes to nonfiction, Danny, people want the picture you're painting there. They want that to be true. Like, what's interesting to people is this idea of, like, I have this habit.

it where I'm kind of writing a little bit every day or in these certain types of little windows of time and over time this book comes together and then like, hey, this book's pretty cool and then it gets published and kind of finds an audience. It's actually not how nonfiction is written. There's a reality to how nonfiction is written and there's that story that people like to tell because it's fun. Low stakes writing when you get time is like fun, but it's not how nonfiction gets written. In nonfiction, you sell the book first. You sell the book based off a proposal first. There's a little bit of exceptions.

If you're talking about an academic press, it's a little bit different, right? You might have the book together for, like it gets a little bit more complicated. But for the most part of nonfiction, you're selling the book first and then you're writing it. So actually, in nonfiction,

unlike fiction, the motivation to write is not a problem. The motivation is I have a contract. They've already given me the first half of the advance. I'm going to have to give it back. If I don't deliver my book by this date, it's due in eight months. it's not fun like I'm just kind of like writing when I get a chance in the shed.

This is a job now. I've been paid to do a job. I've got to execute it. It actually feels much more commercial and workman-like than you would imagine. So writing nonfiction is not something where motivation really matters because you sell the book first. So how do you sell the book? Well, first you get an agent. And here, the process of getting an agent is not, there's not a lot of hoops you're jumping through, right?

I mean, there's something called a querying process where you're sending letters of a certain format, you're emailing them these days, two agents who are saying I want to find authors, query me here. Here's the type of authors I support. And you're sending them, and it's a page long, there's a format to it, and if they're interested, they're like, let's talk.

If you get an agent, they'll help you write a proposal. They'll be the ones to sell it to a publisher, then you'll go write the book. So that's how that actually works. People don't like that story because it front loads the evaluation. You're like, shoot, I like the idea of writing this book. But the reality of the story is that,

I could start querying agents this week and by next week know that none of them are interested and that could be the end of that dream. Right? Because your mind kind of knows like, I don't know if we really have this fully worked out. Like are we the right people to write this book? It's a topic, something that people really need to see.

I'm not quite ready yet for someone to like evaluate this. But that's really how nonfiction actually starts. So it's like good news, bad news. Good news is you don't have to worry about tricking yourself to write or motivation or willpower or procrastination. The bad news is getting to step two of nonfiction book writing is like really hard. Step one is actually selling the book first. But don't run away from the reality, right?

Confront the reality. If you can't get an agent for your book idea, then use that as a forcing function to figure out, well, why not? And that could help you find a better idea. I wrote like a kind of a well-known blog post about this years ago, back when I was still writing my student books. And if you go to search for like Calnewport.com and, you know, how to get a non-fiction. book deal. I wrote about everything I learned selling my first three books, which are just like straight up student focused nonfiction advice books. I lay out all these ideas. Here is how it works. Here's what I learned to do. It's funny, Jesse, I talked about in that article. I reread it

recently. I'm like, well, look, I'm not like a New York Times bestselling author who has sold millions of books, but I've still had a pretty good run. And now you fast forward, you know, 10 years after that, I have done all those things. But back when I wrote that post, that was like this impossible future that I had not achieve and I was never going to achieve. So I didn't really believe in myself back then. But that post gets, I mean, I was right in the thick of like just starting out as a writer. It's right after I sold my third book. So go find that article and don't ignore the reality.

And the thing that trips up most people with this reality is I identify early on in that article. To sell a book, is what I learned from my agent 20 years ago. You got to have an idea that people are going to feel like they have to read. there's got to be a sizable audience that's going to feel that way and you have to be the right person to write it. It's actually really hard to find something that satisfies all three. Like you can come up with a killer idea, but like if you're not a writer with any sort of connection to that idea,

then like you're not the right person to write it. Or you could have an idea that you were the right person to write, but it's so niche that no one cares. It's not a big enough audience. Or you have an idea that like in theory a lot of people would be interested in this. Like it's relevant to a lot of people and you're the right person to write it, but no one is going to feel like, oh, I have to read that book. It's not motivating me like, ooh, I got to see that. It's hard to get all three. But if you get all

three, it's hard not to sell it because, again, agents are desperate for clients, publishers are desperate for books. They just have to be viable ideas being written by viable people. But it is not a world of people trying to reject stuff that you're trying to slip past. It's a world where people want to accept stuff. So your job is to get rid of the rough edges that makes it impossible for them to accept what you're doing. So read that article, confront the reality of how the industry works instead of the story you want to be true. Or you can write for fun.

But if you really want to publish a book, you've got to confront the reality of how that industry actually works. And if he takes the approach by writing for fun, you can just self-publish and essentially nobody's ever going to read the book, though, right? Yeah. Probably no one will read it. But you could write for fun. You could write on like medium.

No one will read it. You could have a substack. But again, if you don't already have an established reputation, no one's going to read that either, but you could do that, or you could write for family or friends. Like, that would be fun as well. Fiction is better for this because in fiction, you're supposed to write the book first. So, like, you can just write fiction because in theory, you're doing the same thing as Brandon Sanderson, right? You're like, yeah, we all just write the thing first and see if it works.

So it's a little bit more fulfilling. Nonfiction, though, you shouldn't delude yourself. If you're, you know, 300 pages into your self-help manifesto that you think it's going to be brilliant, you're not really... following the path or in the world of professional writers. That's just not the way that typically works. All right, so we got a case study here where people write in the share their personal experiences implementing the type of advice we talk about on this show. This week's case study comes from Kelly.

Kelly says, I am 26 years old and an athletic trainer by trade. I recently transitioned away from working in collegiate athletics and into a new pursuit of K to 12 substitute teaching. At my old job, I became burned out after dealing with high administrative over overhead expectations for having an online presence outside of working hours and limited free time to explore deep pursuits. I had trouble finding meeting outside of work. Despite your prudent advice, I resigned from my old position with absolutely no plan

for my next move. I did some lifestyle-centric career planning, however, and found that substitute teaching could help me build career capital in the educational realm, provide enough consistent structure around which I could time block, give me enough time off to explore new hobbies and pursue deep, meaningful things. So I took your advice to make my phone less appealing, bring a book everywhere I go, and limit my consumption of algorithmically curated articles,

posting content. I was doing great with my more analog lifestyle until a medical crisis happened in my family last week. And then Kelly goes on about how, like, a lot of this stuff got difficult over this last week. But I want to pause there, the focus on the things that Kelly did do that I really want to emphasize here.

And then I'll talk about briefly how to make sense of what's going on with her, like right now, with this medical issue. So what I like about this, lifestyle-centric planning for the win. No, I would have done, as she pointed out, I would have done the lifestyle-centered career planning before I left the old job, but okay, it's still worked out. Substitute teaching, it's not the thing that pops to your mind necessarily as like, oh, God, that's the dream job. That's what I want to do.

But it's the type of thing that can come up when you're doing lifestyle-centric career playing. What do I want my life to be like day-to-day? what are the things that matter, doing that analysis, and then looking at your specific opportunities and obstacles, led Kelly to, like, if I did substitute teaching, I'm working on this capital here, and I feel the structure I need.

I don't have this extra stuff I have to do outside of my work, and I can pursue these other things that are important to me. And I like how then Kelly also did a rebuilding of her digital life. I'm going to bring books. I'm going to make my phone less interesting and how that freed up a lot more time and focus and contemplation for pursuing things that are interesting and probably reconnecting with herself more.

That's a fantastic example of the way I talk about transforming your life, which is not as exciting as like I just got this giant goal and I pursued it and everything was better, but it made a real difference. Then Kelly talks about, we'll mention this briefly, hey, things got tough recently. There's like a big medical emergency of my family,

and I won't read all the details, but basically she's saying that put her on her phone all the time, first to be in contact for obvious reasons with family members, but then once she was on her phone all the things, time she began using it more, again, understandably, as digital pacification because it was very stressful what was happening in her family. And as I talked about this, I've learned this like during my own medical things recently. There's like a numbing effect, a distracting effect of just algorithmically curated content. So the question she's asking finally is like, well,

how do I deal with that? I say, well, you're going through an emergency. Like now it's not the time to nitpick about like your digital habits. Now is also not the time to hold yourself to the same standards that you were holding yourself to the day before the emergency happened. You will get back to that. But like what you're doing now basically is think about this as crisis lifestyle-centric career planning. What do I want during this crisis period? What is my ideal of how I want to look back and say I got through this? And it's going to be less about I spend four hours a day on self-improvement, right?

Because no, this is not, your headspace is not there and your time is distracted. It's going to be more like I want to be the person people count on. I want to be the person that people look back afterwards and say like Kelly was a rock. during this and it was really useful. It's going to be about leadership. You're going to have to have a lot more self-care. Maybe you want to start replacing phone self-care with other self-care, but you're not replacing it with like, I want to go be productive, but maybe I'm going to spend more time, whatever, going for like long runs or hot baths or going to like movies, like stuff that you feel like is maybe a little bit more uplifting or less numbing that still helps distract

you. But it's like you have to do a whole separate lifestyle career planning for this period that's based on like how do I get through this in a way that I'm proud of. And then when this crisis is over and it will be over, go back to what you're doing before because it sounds great. You're envisioning what matters to you and you're pursuing that and you're building your own idiosyncratic path to a life that is in the moment something that you're proud of and in long term is opening up cool options. So you're doing the right things, Kelly. Don't be so worried about what's happening now. Keep focusing on who you want to be and then get back to your bigger vision when the emergency is over. All right, we got a off the rails tech corner coming up, all things AI.

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See if your company qualifies for this special offer at Oracle.com slash deep questions. That's Oracle.com slash deep questions. Speaking of deep questions and AI, Jesse, let's move on to our final segment. All right, so I want to talk a little bit about AI here and jam way too many ideas into a short segment. The thing I want to react to to kick things off is Ezra Klein's recent podcast. I have this up here on the screen for those who are watching instead of just listening. This is Ezra and he is talking here with Ben Buchanan, Biden administration AI-related official. There's a quote from this podcast I want to read and then I want to use that.

to riff off of. All right. So here is the quote. This is Ezra talking at the beginning of this recent episode of his podcast. He said,

for the last couple of months, I have had this strange experience. Person after person from artificial intelligence labs from governments have been coming up to me and saying, it's really about to happen.

We're going to get artificial general intelligence. What they mean is that they have believed for a long time that we are on a path to creating transformational

artificial intelligence capable of doing basically anything a human being could do behind a computer, but better. They thought it would take somewhere from five to 15 years to develop, but now they believe it's coming in two to three years during Donald Trump's second term. They believe it because of the products they're releasing right now and what they're seeing inside the places they work, and I think they're right. So not surprisingly, this podcast has many of my New York Times reading coastal friends

worried about AI. Like if you just kind of hear this wording casually and you're not in the AI industry and you're not a computer scientist, this does kind of sound like we're a couple years away from SkyNet, right? Machines getting out of control, machines making us unnerved about turning them off, machines that are causing consequences that we didn't anticipate. So existential challenges. But are we? Well, no. And I want to start by saying there is a meaningful decision. distinction between AGI and that other scenario, which we should better call superintelligence.

And I think it is worth reviewing this distinction. If for anything, so you'll have a more accurate view of what's coming and also have a more accurate view of other things that maybe are farther in the future, that's worth keeping an eye on. All right. So AGI in the way Ezra is talking about here is actually, you know, it sounds like a big thing. We achieve AGI. Something has happened. When that happens, we cross that threshold, something is worrisome.

is really you can think of it as an arbitrary quality threshold for the things that these language models are already doing. This is actually what experts mean when they talk about AGI right now. It's like right now I can ask ChatGPT that create a memo of summarizing whatever, historical factors relating to like the adoption of a certain type of technology. And it will do this like pretty well. It'll like pull on information.

It'll be written properly. It'll be on the topic. probably not as good as like having a researcher do it, but it would do it pretty well. It's going to get better at this. And at some point, it'll get good enough at writing this memos. We'll say, like, that's crossed the AGI threshold. Like, that's as good as, like, a good researcher would do.

It's like this arbitrary threshold. So it's not that when we cross that threshold, there'll be suddenly new things that artificial intelligence can do that it has been able to do before. It's the things you already know it can do have gotten past a sort of arbitrary, subjective threshold of, like, that seems as good as, like, humans are doing it. It's like kind of around there right now. Like it can write a pretty good memo.

It can write a pretty good joke. It can write pretty good computer code, but not quite as good as a person. Like soon it will be as good as a person. That's AGI. Now, this has real economic and security consequences. The better these models get at these things, there are these real-world consequences that get worse. And Ezra and Ben get into these. In the interview, it really is about both security and economic consequences of this.

But when you recognize what AGI is as like an arbitrage, quality threshold and stuff AI is already doing pretty well and not some sort of new capabilities. We realize it is serious, but it's not the type of thing that James Cameron's going to make a movie about. Let's talk, though, about the things that James Cameron did make a movie about, and that is this idea of superintelligence, of AI getting increasingly autonomous and smart until it's smarter than us as designers, and then all sorts of sci-fi chaos happens. this is something that people are also worried about. It is separate as we just established from AGI,

but it's not impossible. So why don't we talk about that? So here's the conversation Ezra did not have, which is like what would be needed for superintelligence and are we on track of that or not? So let's have that conversation now. I begin to wrap up my conversation or consolidate my conversation of like what would be needed

to create, to quote, like an original article from the 50s about Rosenblatt's very first self-learning machine learning model the perceptron

electromagnetic perceptron was called a Frankenstein machine what would be needed for AI to become something that was

James Cameron ask like ooh either I feel uncomfortable turning it off or it's doing stuff

I didn't intend for it and it's scary there's four things you need and I call these to Frankenstein

factors One, understanding. The machine has to be able to understand complex concepts, know the reasoning behind them, be able to like apply these understandings to create new information, just have like an understanding of stuff and ideas and concepts. Number two is world modeling. A system needs some sort of, to do this,

some sort of model of the world around it and that it's in. Three, it needs some sort of incentive system. Like here's what matters. matters to me and what doesn't, and for it needs some sort of actuation. All of these things, a way of actually impacting the world around it. And so then what you need then is a system that has a state of the world, using its understanding and its incentives can explore actions it can take through actuation that will change its world state to something that is better in its incentive, whatever its

incentives are, the things and values. and that is like the action loop that makes things interesting. So if you don't have a world, like an updated understanding of yourself and the world around you, where you are and what's happened to you, there's no way for you to have any sort of like,

scintience because there's no memory, there's no state, nothing changes, right? And if you don't have incentives, then your model's not, your system's not doing anything. If you don't have actuation, there's no way for you to act on your incentives. But you put those four Frankenstein factors together,

now you have the possibility of a system that goes awry. And I think this is, actually what people, the lay person has in mind when they get worried about artificial intelligence, not the economic or security consequences of machines continuing to get better

at things are already doing, even though that's really where the practical attention is right now. So I have some good news about it, and then a piece of bad news. So there's some good news about these Frankenstein factors. One, all of the energy is just

focused on one of those, which is building models with understanding, that's what these language models are right now, is they have complicated understanding of concepts built through training. World modeling, incentives, actuation, like most of this right now is just left to the people using the models because there isn't any real direct, immediate economic incentive to building those type of machines.

Like, having a model with lots of understanding that a human with their own incentives is a model of the world, and here's what I want to do, and I can take the results and apply them over here, This is actually like the most efficient use of this technology right now. So there is no push to build systems with complicated versions of the Frankenstein factors. All of the focus right now is just on understanding. Modulo is some sort of like relatively minor scripted agent systems.

Another thing that should make us feel better is that the Frankenstein factors two for four, world modeling incentives and actuation, these aren't trained. They're engineered. I think it's a really important point I mentioned before, but I just want to underscore it here. The language models we're building for understanding are trained, meaning that we have these large transformer-based neural networks. We give them a lot of training data, and they somehow adjust their internal wiring until they do what we ask them to do really well,

and we don't really know how they're doing it. So they have this sense of an alien mind, as I talked about in my New Yorker piece from a couple years ago, or sort of like emergent abilities that can catch us off guard or surprise us. That's very unsettling. We don't know how this thing works, but it just starts working and we kind of watch what it can do.

These other factors, world modeling incentives actuation, any reasonable way we have thinking about building these, these aren't systems we train and don't know how they operate. They're just going to be hand engineered by people. So we choose the incentives. That gives us a lot of power

about what these machines can do. We choose like how the actuation works, what actuation it can and can't do. That gives us a lot of control over what these things can do. Remember, the understanding that we have encoded in language models. Language models are inert. They're giant matrices full of numbers that we can run

through GPUs to create probability distribution tables on tokens or token sequences. They have no state, no recurrence, no loops, no ability to, no autonomy, right? It's just a large plato machine we turn to crank and out of the other side comes tokens. So a language model

has no ideas. Has no memory, has no state, can't do anything. It is these other engineered systems that could work with a language model if you wanted to have a full autonomous sort of digital intelligence. And those are hand-engineered, and they can be what we want to be. And I point to the example often here of Cicero, the multi-model system that played the game, board game diplomacy very well. Noam Brown worked on this before he got hired away to Open AI.

This is probably one of the closest systems we've seen to having all the Frankenstein factors. It used language models, and it had incentives, and it had actuation. It could actually, like, communicate with people over the internet to play this game. but because everything was engineered except for the model that like evaluated moves and created language, they could say, for example, we don't want you to lie. And because they could control the actuation and the incentives and the simulation of the world,

they could just program in, don't consider options with lies. So there's this kind of nice, the Frankenstein factors have a lot of control outside of the understanding component. I call this IAI or intentional AI, the idea that if we're going to build an autonomous type of system, if and when we get to that. We'll have more control over that than we imagine when we think about

the unsupervised training of language models. The other thing we should feel good about is another idea. I'm actually writing a paper about this right now. We don't have any reason to believe that our colloquial notion of superintelligence is actually computationally tractable. So we just have this idea of like, well, computers are doing these things pretty well. So we can just imagine a sufficiently powerful computer doing thinking at a level that is sufficiently more complicated than what humans could ever do. And then that computer would have power over us.

But this sort of cognition that computers are doing, these are actual, you can think of these like actual problems being solved by computers. And here's something that every theoretical computer scientist knows, right? This is just ingrained into us in like every theory class we ever take. And this goes back to Turing. Most things can't be done by computers. Most problems are unsolvable. or if they're solvable, they're computationally intractable. So we don't actually know

that it is possible for there to be a computer program that is somehow representing something like a supercharged human intelligence. That is like a fallacy of, it's a common philosophical fallacy to imagine we can make computers more powerful so the things computers can do, they'll be able to do increasingly more sophisticated. Complexity theorists know, like our main frustration is like most things can't be solved. Both problems are just impossible.

Or if it's possible, it's computationally infeasible. It's actually the rare problem that a computer can efficiently solve. So we have no reason to believe that superintelligence is actually computationally feasible. Like, we might be hitting the limits of, like, what cognition a computer can do in any sort of, like, reasonable computational efficiency. Like, right? I mean, think about it. It might be true. We're building the biggest possible computer systems that are feasible.

right now. They might have tens of thousands of GPUs and these giant custom-built data centers. Like we can't really build these systems any larger. We just could be pretty close to some limit of like this is it. Right? So it's a logical fallacy to extend a curve. Things got smarter.

They'll keep getting smarter. We don't know that's the case. Most problems are unsolvable. Now I'll throw in my final thing which is like, yeah, but you don't need a superintelligence for one of these autonomous systems built on the four Frankenstein factors to create a lot of problems.

In fact, some of like the common scenarios we imagine of these things create a lot of problems is more about like recurrent spiraled out of control. I have some understanding, which means I can do a lot of stuff. So I'm a system that has a language model I can use, which means like, for example, I can analyze code and produce computer code and I'm pretty good at producing computer code. And I have an incentive over here that says like, I want to spread somehow. thinks that's what I want to do. And I have a world model that's like trying to figure out, it's evaluating different things we could do against those incentives. And then like that model

might simulate and figure out like, oh, the right thing to do is to like try to break through the security of this network and copy myself over here. And then the program's going to do the same thing. And then we have actuation. I can actually like communicate on a network and copy code. And it might not be anything super intelligent, but you turn this thing on, you come back the next day. And there's 100,000 copies of this bringing down computer networks around the world. So, like, actually, the real first concern with an autonomous style, I think AI system is not going to be, we get something alive, we feel bad about turning off.

It's not going to be SkyNet superintelligence. It's going to be like a supercharged power of a computer virus. It's going to be like the Morris Worm from Hell. And that's a reference, Jesse, is Robert Morris in the early days of the internet when it was still really just something among universities, a young graduate student at Carnegie Mel and Robert Morris. wrote this very simple program and he was like

oh it's going to spread itself by exploiting I think it was a flaw on the Unix Sendmail program like an early email program it could use to copy itself on the other computers and it's kind of just like an experiment

and it ended up like taking over and crashing half the internet that was the Morris Swarm interestingly I ended up taking distributed systems with Robert Morris at MIT during my graduate days and they always had this story that he wasn't allowed

to do there's a big pistol shooting team at MIT. They have a world class team. And it was always like Robert Morris tried to sign up to do pistol shooting and couldn't it because he has a federal record from the Morris worm. The story doesn't check out. If you really think, these pieces don't check out, but it was like a big story.

His class was hard too. Distributes isn't through Robert Morris. Anyways, that type of thing can happen. So this is where I think the Frankenstein factors get out of control. But okay, now I'm going to Judah flip that again into a positive, which is that's not a bad way to bring attention.

to the potential danger of the Frankenstein factors all coming together is like you have some supercharged Morris worm type things happen. That catches everyone attention. Like, whoa, whoa, we got to be much more careful about when we attach a world model and actuation to understanding, maybe actuation needs to remain under human control. And, you know, this is going to be some of the really interesting sort of AI safety talks of a few years from now. Right now, the focus is on AGI, which, again, that's a scary term. We should really just think about a quality threshold for stuff that language models already do past which their potential economic and security impacts become harder to ignore.

That's what we're focusing on now. I think that's hard for a lot of people in their day-to-day life to get their arms around. But if we want to talk about autonomous AIs doing stuff, it's the Frankenstein factors that'll matter. And that's a whole other complicated story. But it's one that I don't think is as scary because, again, that like I don't want to turn this off or it's SkyNet. There's so many things between us and that and so many other things are going to happen first. So basically, Jesse, I'm just ranting on AI here. I'm covering a lot of ground.

This is like multiple different papers I could write right now. But I just, I listened to Ezra's podcast and figured, let's rock and roll. So is the paper for Georgetown? Oh, I don't know. I'd write it for an academic journal. Yeah. Yeah, it'd be a Georgetown thing. By the way, I'm looking at this video from Ezra's podcast.

He now wears like a blazer. I didn't even know that was him. Well, that's not him. That's Ben Buchanan. Yeah, he has a beard now. I've done a show a couple times. It used to be more casual. Yeah, look at that.

He's got like, I should wear a blazer. Look, they have a fireplace. Oh, man, we got to up our game. New York Times is up our game. When I first did Ezra show back when he was still at Vox, they used Slate Studios here in downtown D.C. And it was just like a nondescript, just studio with sound acrates. And there's no video back then.

So we just in a T-shirt or whatever. And then during the pandemic, I did a show. just at his house and he would just like zoom in or whatever. So he's up to his game. So what's an example of a problem that can't be solved? Like is there a god? No. So, okay, you have to formalize, not to go down this rabbit hole too much, but you have to

formalize what we mean by a problem. So like one way you can formalize a problem is you can imagine like your abstract computer algorithm is given an input, like some sort of data or like a string. And all you have to do is accepted or rejected. Is this good or bad? And so in this formulation, this is like Mike Sipser's formulation of computability from his famous textbook. I also studied with Mike Sipser. In this formulation, a problem is just a collection of inputs that you should accept.

So to solve a problem in this particular formulation, it's just you have the ability of accepting any input that's from that set and reject anything that's not. And because these sets can be infinite, like you can't just. have it all hard-coded, right? If you just think of a problem that way, the number of problems is what's known as uncountably infinite, whereas the number of programs as countably infinite. And these are two different

sizes of infinity. They're vastly different. It's the difference between whole numbers and numbers with like infinite decimal places. Then, and Turing did all this, by the way, in his original paper, uncomputable numbers in their application to the enchiltern theory. So it's like famous 1930s paper that like laid out all these issues pre-computer.

He then said, look, we can look at we can identify specific problems that can't be solved. So, like, here is the very first problem he identified that can't be solved that, like, actually is a problem. Of these, like, uncannibly infinite problems, most of them don't have, like, a short summary. They're just abstract problems. But there's a lot you can identify that are specific problems that can't be solved. The very first unsolvable problem identified by Turing was the halting problem. So he said, like, imagine here's your challenge.

You have a program, and the input we're going to give your program is two things. another program and an input to that other program. Right? So, like, here's some source code, and here's, like, a file you're going to run the program on. And your job as the program is to say, if I run this input program on this input, will it halt or will it loop forever? Like, if I run this on this, will it eventually halt or will it loop forever? That's called the halting problem. This turns out to be, like, a really...

This is a mathematically significant problem because they were trying to understand this problem of does there exist a machine that can tell if there's a proof for every... There's this whole thing about mechanically computing proofs for math problems. Because it's before computers. So put that aside. He pretty easily proved that can't be solved. And he did it by contradiction. He said, like, let's assume you had a program that could always solve that.

I'm going to use that as a subroutine in another program that contradicts itself. So, like, that was the very first problem we identified that couldn't be solved. There is no unified, does this program halt program? program. And now, you know, there's whole textbooks on this or this or that. But most problems can't be solved. So we don't know where superintelligent falls into this universal problems. So, and then of the problems that can be solved, most can't be solved computationally efficiently. So there might be problems like, in theory, yes, you can solve this problem. But if we can't solve it in a number of like computing steps that can be expressed as a polynomial de-input size, it's something that the most powerful computers in the world will run until the heat death of the universe will never solve. So like most, most problems that can be solved are computationally intractable. So like what we're really talking about, when we talk about solving problems, is problems that can be solved and can happen to be solved in like a relatively small amount of time. And that's like a pretty small collection of things.

And those are the things we do with computers. But super intelligence, I don't know. It's all of me. It's not. I took theory with Mike Sipser. He was the chair of the math department. MIT's a cool guy. All right.

Well, anyways, that's enough geeking out. I don't know what's going to. what's losing more viewers? All the basketball references from the in-depth last week or the Mike Sipser references about computability and complexity theory this week. But between those two, I think we're down to like three listeners, and they are like MIT graduates who love basketball. So there we go.

So we're back next week with another episode. Thank you for listening. And until then, as always, stay deep. 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.

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've got to sign up for my newsletter at calnewport.com and get some deep wisdom delivered to your inbox each week.