How to Gain Control of Your Time

Cal Newport 0:00 I found myself recently, as the lazy quiet of summer gave way to the noisy insistence of the fall, being more irritable than normal. I would get really annoyed about the latest blown save for the Washington Nationals, or I'd walk into a cluttered room and in a frantic fit decide I had to clean that room right away because it was intolerable the way that it was currently laid out. Now, I'm familiar with this routine because it's my mind's way of telling me that now that the fall is beginning, it's time to turn back on some more serious organizational systems. I slow down for the summer, but when the fall starts, my mind begins to push back and say, "We gotta get more structured." So I did. Last week, I sat down and figured out the exact setup for my organizational systems that I'm gonna run this fall, including the specific tools I will use and the processes I will use with those tools, and this is what I wanna talk to you about today. I'm gonna put on my productivity nerd hat and walk you through the exact setup I will be using this fall to organize my life. But I'm not just gonna leave it there. I'll then step back and talk about, A, why it's important in general to periodically update or change your organizational systems, and B, give you some best practices for building a system that fits your needs for this upcoming fall. Um, and in case you're wondering, my productivity nerd hat, it features, uh, David Allen making out with a Trello board. It's, um, just pretty disturbing. All right, so we got a lot of advice and ideas to cover in this episode, so let's get right into it. [gentle music] All right, so here's my plan. We're gonna proceed in, uh, three parts. In the first part, I'll go through the details of my system for the fall of twenty-twenty-six, then we'll talk about why tweaking your systems like I do is actually a good thing, and then we'll talk about best practices when you're creating your own system for this upcoming fall. Now, a quick disclaimer before we get started. I should briefly address the meta question of why do we care about organizational systems at all? I mean, didn't Jenny Odell teach us that productivity is simply the subordination of human individuality to the industrializing logics of late stage capitalism? In other words, there's a bit of a like, "Hey, let's not talk too much about organizational system" vibe on the internet these days. But here's why I think it's important, right? My main role as a computer science... uh, as a computer scientist who studies human flourishing in a technological world. One of the things I've learned is the technological world throws a lot of distractions and a lot of work and a lot of shiny objects at you, and if you do not have an intentional plan for how to organize what you have to do and to aim intentionally your time and attention, the technology will make these plans for you. They're, they're, they're happy to hijack your day in a way that's gonna allow Mark Zuckerberg to buy the second half of Kauai. I don't know what the... what he does out there, but maybe it involves David Allen making out with Trello boards. I don't know what tech people do. Uh, so I do think it's important to talk about organization, not because... God, what's this kind of tiresome rhetoric about we're always optimizing ourselves because we're trying to, uh, we're trying to internalize late stage capitalism. No. If, if we're not organized, technology will organize our lives for us. All right, so that's my disclaimer. Um, let's get in with it. Part one, I wanna talk about my system for the fall of twenty-twenty-six. Now, I'm gonna proceed by first talking about the materials, so that is like the specific tools I'm using, and then we're gonna talk about the methods, the particular rules or systems I'll use to sort of integrate those tools into my life. I want to give some setup here. This is not a normal fall for me because I'm on sabbatical, so I'm running a more lightweight system this fall than I normally would in a typical year. However, I've been told that even my lightweight systems would be considered pretty robust for a lot of other people, but I just want you to have that, uh, that note in mind. All right. Let's start with the, the key tools, what we're calling materials, that I am using in my fall system. All right. The first material is where am I storing my tasks this fall? Well, because I'm on sabbatical, I am storing them all in a computer program called Things 3. Uh, I'll put it up on the screen here for people who are also watching. Here's the website for Things. Uh, I have a couple screenshots here. So what you can see is Things exist... You can have it on your phone, you can also have it on your computer. You buy them separately for each device, which I think is kind of cool. It's not some software service thing. Um, and, uh, it syncs up. I'll just zoom in here a little bit on the main interface. It's pretty simple, right? You have a list down here of different, um... you have different to-do lists, different categories, like family, buy a new car, throw a party for Eve. Uh, you can put dates on lists, and then you can also look at, on tasks, you can look at, like, "Hey, what's, which tasks are due today, or which ones are up, upcoming?" The nice thing about Things, what I like about it, is the interface is very easy. It tries to simplify adding things, removing things, adding dates to things. It makes it as easy as possible, so very quick to capture, um, very little actual overhead. That's what I'm using for this fall. In a more busy fall, like when I have multiple administrative or research roles at Georgetown, um, I would typically use Things for home things, and I might use Trello for my major roles because if I need to have more complicated information or I need to store files along with tasks, then I like to use Trello boards per role. But in a simpler fall like this, I think Things will be fine. All right. The next piece of material, the next tool I'm gonna use is a time block planner. I have one here. I kept the, the, the ribbon on it. Obviously, I sell my own time block planner, uh, so I have the advantage of using one that's planned by me. If you haven't seen a time block planner, I'll hold it up here. You got pages over here for time blocking, and then over here for storing tasks. You have a shut down complete, uh, checkbox and a place to put metrics. Okay, so I will be using, um, my time block planner. I get four uses out of mine. Uh, planning my day, capturing tasks when I'm away from a machine to write them down, shutdown routine, uh, justification as a shutdown box, and for tracking my metrics. The third tool I use is probably the most typical and boring, which is a calendar, but you need it obviously. That's, that's actually the one productivity tool that most people actually reliably use, is they will always check their calendar. I use a Google Calendar. Um, I actually have multiple Google Calendars, and I can put them all on the same display. Maybe the most interesting tweak I do is that I have a calendar that's called Cal Logistics, separate from the normal calendar I use for appointments, so I can put notes to myself that aren't actual appointments, but reminders about things or things like somewhere in here you need to make sure that you catch up on whatever. Um, it's a way for me to actually have information on my calendar that I see, and it's connected to days or time, but it's not looking the exact same as an appointment. Um, I share my appointment calendar with my wife so she knows when, uh, when I'm gonna be away or when I'm on calls or whatever, but I don't share the logistics because those are just points to myself. All right. The final key tool that I have is a vision document. All right? So this is something I print out and is gonna contain the sort of the core, uh, ideas for the season ahead of mine. I'll put... I, I made a sample one I'm gonna put on the screen for people who are watching here. All right. Here's a sample vision. It's, um, it's kind of jokey, but, but it has the right, the right elements you need for a vision. So what the sample vision has is at the top of it a description of like, hey, what's the big-picture vision for this season? It then has a list of, like, the major projects and practices, like what are the big things that we're hoping to get done this season outside of just a normal flow of work and small tasks? Like, what are the big, um, uh, what are the big things? Maybe optional, but the big endeavors that are gonna move me forward to bigger goals or practices I want, new practices I wanna put in place, uh, that I'm really focusing on. So you have, like, your big picture, "Hey, here's the things I'm focusing on this season." And then materials and methods, and I think this is critical. It just lists, okay, this is my system that I'll be using this, uh, I'll be using this season, right? Now think about it. Somewhere this should be written down. If you're just keeping the stuff I'm talking about today, your organizational system, if you're just keeping the system in your mind, "Here's how I'm gonna organize myself this fall," it's an open loop. It's in there, it's floating around, uh, and you don't wanna forget it. What if I forget it? What if I forget that I'm using my time block planner that I shouldn't remember to shut down? And so I like to have in my vision document just a quick summary of here's the whole system you're using. Now, this is a little bit circular because one of the things that might be in the, the, the list of your productivity systems is like, "And I keep a vision document," right? So maybe it's a little bit circular. But I wanna have that written down somewhere. This vision document then becomes your root. It becomes the root to your entire productivity system. Print it out, put it in your top drawer where your socks are because you go there every day. And you're like, "This document, from here I can get to everything else I'm doing to be organized because I have my, my goal for the, the season, the major projects I'm trying to make progress on, and the productivity systems that I'm running." Um, and if you look back at the sample one that I created... Let me go back here. Uh, under this materials and methods section where I'm kind of listing my productivity system, one of the key things I have is specific metrics, right? So if, for example, you do metric tracking, which I do and I, I recommend as a way to sort of keep up on practices you wanna do on a regular basis, you gotta write down somewhere, "These are the metrics I track every day." So that's one of the things that's there. That's where I would also say I'm using Time Block Planner, I'm using Things for my productivity. So somewhere you want one document that captures what your system's gonna be as well as your big vision for that season. That's printed out, put it in your sock drawer so you can't avoid it. That's the root for everything else that follows. All right. So those things together we'll, we'll describe as my materials. So just as a reminder, it was Things 3 for task, it was Time Block Planner for planning metric shutdowns and capture, it was my Google Calendar for keeping track of appointments and notes to myself, um, and a vision document to help orient me towards what this, what I, what progress I wanna make on big things this season and what my, my description of this whole system so I don't have to keep that in my head. All right. So now let's move on to methods. So methods are, uh, the actual rules or processes or practices that you'll use to implement your system. So you have the tools, but you also have to have your methods. Let me put up on the screen here the core methods that I am following this fall. So I have three core methods for using those tools. Number one is time blocking. Now, that means multiple things for me, right? So I wrote down right here, "Weekday plan, shutdown, and metrics," right? So on the weekdays, I time block plan the day. Uh, on the weekdays I do shutdowns. Shutdown complete, I check the check marks after I've done my shutdown ritual, and I, I keep track of metrics when I do my shutdown. So I'm putting all of that in next to, uh, time block plan in my methods, right? Um, for task, the method I'm gonna have is 20 minutes a day at least. Minimum of 20 minutes a day going through Things and trying to make progress on tasks. Now, that's a very minimal way of dealing with tasks. Like, I'll be honest about it. When I'm in a busy semester, it's much more complicated when I'm using my Trello boards and roles and capturing and processing. But for a sabbatical, this makes sure I'm not gonna forget things that need to be done because I look at my to-do list every day and I do non-trivial to-do list work every day. That really helps me with my irritability, 'cause when you're not fitting in that 20-minute minimum of just making productive process on small things, both at work and at home, is where you begin to feel like you're falling behind. And then the last thing that I am including on my methods for this fall is my weekly planning. And so I wrote this down here. So what is my weekly planning? Uh, this is where each week I look at the week ahead, see what's going on, move things around if I need to, I review my tasks, and I review my vision. I actually wrote that down here because that's key. That's when I look at my vision, why is this important? Well, often the best way to make progress on these big initiatives in your vision is when you're looking at your week ahead, block off time to make progress on them. So that is my time, like I'm gonna protect Friday morning and Wednesday afternoon to make progress on like whatever, um, big initiative I wanna make progress on, right? So weekly plans, you get your head on straight for the week. You see what's coming. You remind yourself of your vision. You make sure that your calendar reflects what you wanna do. You kinda reset, look through your things list, make sure they're organized, et cetera. You get kinda reset for the week ahead. All right? So again, this is a very stripped down organizational system because I'm on sabbatical, but again, I'm time block planning, and everything goes along with that. I'm spending 20 minutes a day as a minimum in things, and I'm weekly planning. That actually, I can tell you from experience, that is, that is a powerful system. That seems simple. Run that system with your time block planning, weekly planning, 20 minutes a day in tasks, doing a shutdown routine, keeping track of metrics. That can power a life that's gonna feel like you've got your act together. Like you're getting things done. You're not forgetting things. You're not stressed. You're making picture on big projects. You're not dropping the ball on small projects. The AC filters are getting changed. Like that is a system that I think, uh, is very flexible and powerful. Again, I would probably have something more complex if it was a more demanding semester, but that could apply to most people's situations in my opinion. All right, we're gonna take a quick break from our discussion of organizational systems to hear from some of the sponsors that makes this show possible, but stick around because coming up, I'm gonna get into the best practices for how you can create your own custom organizational system. All right, so let's talk about our friends at Superhuman here. Too much of the talk about AI these days focuses on abstract benchmark scores or attention-grabbing stunts like winning a, a gold medal or a, a hacking Agent Ana Rai. But w- do you know what, uh, I want out of AI? To reduce the time I spend on administrative and logistical efforts so that I have more time left to focus on the deep things that really move the needle. This is why I'm excited about Superhuman Go, a chat-based AI assistant that's with you wherever you're already doing your work, already aware of what you're doing, and ready to help. Now let me give you a specific example about Go that I find really exciting. Let's say you're writing an email to your boss about the status of, um, some project you're leading, and you realize that you wanna include a report based on the current state of the project in your Jira ticket management system. Well, with Go, you don't have to leave Gmail at all. You can just pop up a Go window, type in, add a quick summary from Jira at the end, and boom, off it goes, gets the information out of Jira, summarizes it, adds it to the bottom of your email, all without you having to, to go to another application or do this work yourself. All right? I like Go because it lets you focus on the things that matter without all of the brain-destroying context switching or busy work. No new tabs, no switching apps. Get what you need without losing where you are. To find out more about Superhuman Go, visit superhuman.com. That's superhuman.com for more information. I also wanna talk quickly about our friends at Monarch. Look, some of my proudest moments from earlier in my life was hitting key financial milestones. I still remember the day I finally paid off all of my student loans from college. But you know what I wish I had back then? Monarch, the personal finance app that goes beyond just telling you what you've spent to also help you set goals, map out big purchases, and see if you're actually on track before it's too late to adjust. For example, Monarch can send you a weekly AI recap of your spending, which makes it easy to discover if there have been major changes or other spikes in your habits that are causing problems. Monarch has taken the mental load of tracking finances off my plate. It's like having your own financial advisor in your back pocket. Any question about your finances, you can just ask the built-in AI, and it will recap and simplify it so that you aren't chasing receipts or trying to make sense of complicated spending. If I had had access to this app back when I was first starting out, I would have hit my key financial milestones much quicker. This is why you should check it out. So write your own money story with Monarch. Use code DEEP at monarch.com to get your first year of Monarch Core half off at just $50. That's 50% off your first year at monarch.com using code DEEP. All right, let's get back to our show. All right. Part two, I want to address the question of why do I keep tweaking my system? Why don't I just have the best time management organization system in the world, optimize it, and just run it every day for the rest of my life? Well, I don't believe in fixing one optimal system forever. I have two reasons why. Number one, what is it that kills systems? What is it that stops people from sticking with their organizational systems? It's almost always friction. These little bits of friction. I have to do a little bit of extra work. I gotta go into this app and transfer things and go back over to this app. I have to load this up and go into this interface and move things from here to there. Friction kills systems. Not at first. When you have a lot of time and you're excited, you do all the things. But as your life gets busier, the friction adds up and becomes intolerable, and eventually like forget this, and then you just drop having a system altogether. So friction kills systems. So to reduce friction as much as possible, um, you gotta be adaptable. So what is the reality of this upcoming season? I want the minimum possible system that still solves my problems of reducing stress and anxiety and making sure I make progress on what matters and not dropping the ball. And in the summer, you might pull this back a lot to a super simple system so you can recharge. In the fall, it might get more complicated. Maybe the winter you pull it back again. But you always wanna be adjusting to the reality of each current season to try to find, you know, places where unnecessary friction or complexity can be removed when you can The second reason why I think you should keep tweaking your systems is novelty. You will get bored of a system if you d- use it forever, and you'll get tired of it. Novelty's great because when you adjust a, a system for a given season, you get excited at first about, "Ooh, I like this new system. I feel good about it. It's exciting to try something new." That starts to wear off, and just around that time, you're creating a new s- system for the new season. So novelty will actually keep you, and I think this is critical, but novelty will actually keep you more, uh, energized about being organized in general. So I'm gonna suggest the same for you. Fall, spring, summer, at a minimum, adjust your organizational systems. You might do quarters instead, fall, winter, spring, summer. That's up to you, but that's the right way to think about it. Have novelty, have some seasons be more intense than others, and try to keep your system as minimal as possible for the demands you happen to have in the season that you're facing. All right, third part of this discussion, what are best practices for you designing your own system? Now, the one I just described to you for my fall is pretty good. That's pretty flexible. It's pretty easy. It's pretty low friction. If you're not sure what to do, do something like that. But people have different situations. They have different complexities. You know, you gotta custom-build a system to what you're facing. I wanna give you, uh, some best practices for how to do this. I have a helpful diagram here I might load up, beautifully drawn. Too bad Jesse's not here today because he would appreciate how beautifully drawn this is. All right, so if we look at my diagram here on best practices for creating your own system, at the top of the diagram are three questions: what, when, and why. All right, so what does that mean? Well, the what is... I'll put it this way. These are the three questions you have to answer when creating an organizational system. The what is, what do I have to do? This is where you keep track of your tasks. Where are your tasks? Where do you store your tasks? How do you review your tasks? How... Like, what is your way for managing all the different things you have to do? The when stands for, when am I doing it, right? So you need some sort of method for how you actually decide what to do when. Mine is built around time block planning and weekly plans. Other people have... They run their life off of, uh, task lists. Um, if you're using, like, David Allen's Getting Things Done, he suggests answering the when question with physical context, so he divides all of his tasks into context, and then when you find yourself in a given context, you just look at the list for that context, like computer admin work. I'm at my computer doing admin work on the internet. You have a list of computer admin work where you've moved tasks just in that list. You just load up that list and choose things off of it. Like, that's the David Allen answer to that question. If you go back to, like, the 1970s, 1980s, you're gonna get priority systems, A, B, C rankings for my task. I do all the A tasks, most of the B tasks, and only the C tasks if I have time, right? So there's different ways to answer this question of when do I do tasks? How do I decide what I'm doing next? But you need an answer for that in any reasonable organizational system. And the why stands for why am I doing that, which means you need an explicit way of managing your workload, what you say yes to, how, what you say no to, how many things you work on concurrently, when you work on them, et cetera, right? So these are the base questions that any reasonable organizational system needs to ask is what, when, and why. Okay, now once you've, uh... Those are the questions. How do you answer them? Like, what form do your answers take? Well, the form that we just saw, you need materials and methods, right? So then you're like, "Okay, well, what tools am I gonna use to implement my answers to those questions, and what rules do I have about using those tools?" And so those are your materials and methods. That's a good way of breaking up the way you think about your organizational system, and all of this should be built on a foundation of a vision. What am I trying to do? What's important to me? What are the things I wanna move forward on? So you have a foundation of, like, a vision for your life, but more specifically a vision for the, the season that you're currently facing. So to me, I think that's really important that you're able to ground your organizational system for a vision for, like, what it is you want, that what, what is that season gonna be like? And it's not, this is not just accomplishments, like here's my goals. It might be like, "I want this to be a quiet season. I want this to be a season, you know, it's summer, and it's about family," or like, "The fall really should be about Halloween decorations. I wanna kinda build my life around it." You need some sort of organizing vision that you're trying to actually move towards. Otherwise, you're just gonna become a task executor. "Hey, I got a great system. I execute all these tasks, and I'm sort of, uh, in drift and drowning in ennui." All right, so let's just look at this one more time. Your organizational system has to answer the questions what, when, and why. Those answers should take the form of a description of what materials you use and what methods you deploy around those materials. Everything should be grounded in a vision that's custom fit to the season that you are currently facing. All right, so there we go. Those are the big issues about the fall, right? I told you what my, my stripped-down organizational system's gonna be for this fall. I told you why you should keep changing your organizational systems per season, and then I gave you some best practices for how do you create your very own organizational system. Uh, what are the best practices for creating one that's gonna work for you but covers the thing that these systems should cover? I would like to hear what you end up with. If you wanna share whatever organizational system you're using this, uh, this fall, you can send it to podcast@calnewport.com. How do you answer what, when, why, what material, but in terms of what materials and methods you use? And if you wanna share your vision, you can, um, and maybe in a later episode, I will share some of these on the air. All right, so that's enough about what I'm interested in. Now I wanna know what you're interested in. It's time, as I often like to do on Monday, to open up the inbox. Uh, if you have a question or something you wanna share or feedback on a past episode, send it to podcast@calnewport.com, and maybe we will deal with it on the air. And we don't have Jesse today. Um, he's dealing with some family health issues. We wish him our best, but it means I will have to, uh, I'll have to handle all the questions today. So you, you will have to, you will have to bear with me. All right, message number one. Message number one comes from Catherine, and Catherine

Cal Newport 24:36 says, "I thought you would find a comment below from Dervla McTiernan, an Irish novelist in Australia, about her use of AI interesting." All right. So Catherine sent a link to a newsletter from, uh, Dervla McTiernan, an Australian Irish novelist living in Australia. All right, so I read that newsletter, and I pulled out here the key quote, in my opinion, from this newsletter that Catherine sent me. So here's the key quote from this novelist newsletter. "I don't use AI at all for my writing, but I do use it for a lot of the business that surrounds writing, and it feels like I suddenly have the ability to do a lot of things that I could only half do in the past. Which means, of course, that I feel like I should do all of it. I've been frustrated for years by some of the constraints that I've felt in my work: access to information, the ability to use certain systems really well, like Canva Design or Meta Ads, or the intricacies of the Mailchimp backend. And now that those constraints have largely been removed, it's incredibly tempting to spend all of my time working." All right, I think this is a really good point because it actually dovetails with something I've talked about for years here on this podcast that AI is making worse. All right, so stay with me here. The con- there's a concept that I've always been wary of that I call checklist productivity. And it's this idea that when it comes to some sort of important endeavor in your life, that there's a way to, I'm not gonna say hack it, but the checklist productivity mindset is if you can get the right information about the steps that really matter and execute these, like checking items off of a checklist, then you will find great success in this really important endeavor. And what's compelling about the checklist productivity concept is that it moves the necessary action for success away from deep effort on something hard that's competitive and that you might not succeed with to information scarcity. No, no, no, you can... If you get the right information, these are the right things to do. You could just execute those, and you will have success. And this is really appealing because executing the items in checklist productivity is not competitive. It doesn't typically require deep work. It's more mechanical, and it's often much more fulfilling. You're setting things up. You're moving things. You're seeing immediate results. And so we want this to be true. We want it to be true that we can find a secret list of things to do, and if we just do these right things, we'll be a successful author. We'll be a successful professor. We're going to suddenly have promotions at work. So checklist productivity, um, it's very infectious. It was really big in, like, West Coast productivity type literature in the 2000s. Hey, just get the right information. You can optimize. Like, think about some pieces of, like, uh, 4-Hour Workweek had a real checklist productivity vibe. Here's the secret information. Do these things, each of which is e- like completely accomplishable and predictable. Do these things and success... it'll add up to success. Um, a- I'm not a big believer in checklist productivity 'cause it doesn't work. For hard things, it's the hard things that matter. It's the creation of the art. It's the rare and valuable thing. There's no way to avoid deliberate practice and deep work and grinding and straining, and it's uncomfortable, and you get better, and a long, winding road to the pride of competent accomplishment that's hard-won. That's almost always what's, what matters. There's no magical list of to-dos that you can execute that's going to s- get you the same level of success of just doing the hard work of becoming too good to be ignored at something that va- that you value. So checklist productivity, I feel like, is a little bit dangerous. Well, AI supercharges checklist productivity because it puts at your fingertips, like Dervla's talking about in this newsletter, the ability to execute all sorts of checklist productivity style things, which... Like, let me read the examples from her newsletter. These are perfect examples of checklist productivity. Um, you know, using Canvas Design better or using Meta Ads better or, or, uh, using your Mailchimp newsletter software better. All of these sort of, like, technical things. You're like, "Wow, um, I've optimized my setup on Instagram. I have tags now for incoming subscribers in my newsletter management software so that I can segment different types of messages to them. Um, I'm using Canva in a more advanced way, so I can have really cool-looking memes that I put up in my TikTok post." Like, whatever it is, right? All these type of things. You feel super productive. I'm doing all these things. But they don't add up typically to real success. That almost always requires you doing the thing that's, uh, really hard, and you have to be too good to be ignored. So AI vastly opens up access to checklist productivity style, um, activities and makes them very fun and fulfilling to do because you're getting, like, step-by-step instructions from a chatbot, or if you're using an agent, it'll even do some of this for you. It's addicting, but it's not gonna make you a successful novelist, and it's not gonna make, uh, it's not gonna give you a promotion at work. It's not gonna make you, you know, your newsletter, uh, suddenly take off. Ultimately, you still have to be doing something hard that's rare and valuable. If checklist product-- If it worked, we would just automate it, and immediately we would have 100,000 people doing that same thing, and the value would disappear. So my advice is constrain checklist productivity time. It's not that those activities aren't useful, but they're not the solution. And so you wanna constrain that time, maybe have one checklist productivity style initiative per week that you're working on, and still keep the, the main thing the main thing. The core of your day is doing the hard work on the thing that ultimately produces value that you're getting better at and is becoming more rare and valuable. Do not drown in checklist productivity actions just because AI makes it possible. All right, message number two comes from longtime reader.

Cal Newport 30:11 I felt like during law school I kind of lost my way a little bit with my relationship with technology, maybe even as a way to cope with the struggle of being in university. I ended up f- uh, falling into a pretty bad social media addiction. With all the professional networking opportunities, I found it overwhelming to say the least, having 24/7 access to a variety of different professionals I could reach out to, reading up-to-date articles in a variety of different legal landscapes. Overall, it was just a huge waste of time. Anyway, I recently started studying for the bar exam. I found myself over the time between graduating from law school and starting working on the bar, um, rekindling my relationship with the deep life. I've gotten back into many of your suggestions such as reading, having physical activities, mental activities, skill-based activities, things like that. It's been a wonderful reawakening getting back into those principles that made me successful in the first place and trying to make a more balanced and methodical relationship with the tech products that I do use. So this is sort of more of a case study than a question, but I'd love to hear it, right? We talk, you know, abstractly about things like the deep life on here, and it's like why? This is why. Because if you do not have an intentional vision for your life, if you don't live on purpose, in the 21st century technology's gonna do the living for you. It's gonna pull the strings. It's just your, your time and attention is so valuable that you will lose the battle of the workplace and personal technologies if you're just wandering through life trying to get random accomplishments and feeling good. You have to live on purpose to flourish in a technological world. And all these ideas about the deep life, et cetera, this is why. I mean, look, I, I, I have this new book coming out in March called The Deep Life. The subtitle is A Structured Approach. Uh, I called it one-off, but people pushed back last time, said, "It's not one-off. It's at the core of what you do." And I think it's right. Even though it's not a book of technology criticism, it's a book about creating the bulwark to technology. When you live on purpose, when you, when you, you have an intentional life that's deep and remarkable, the allure of TikTok, of LinkedIn, of Instagram, of making your workday devolve into constant Slack conversations and Teams meetings so that you seem like you're a team player, all of that begins to diminish because you're like, "No, I'm, I'm intentional and that's not so great. What I'm doing over here is more important." And so the deep life, I... you know, it's... we can't pull apart the flourishing from the under- you know, reacting to the technological world. Like, all this goes together. You have to control your analog life to push back on the digital. All right, we're gonna take another quick break to hear from some of the sponsors that makes this show possible, but stay tuned because at the end of the inbox session, uh, segment, I go on a rant. I can't help myself. You don't wanna miss it. But let's get to these ads real quick. I probably should have started this podcast earlier. I knew it was a good idea, but I was paralyzed by the technical complexities in getting a show like this up and running. Now, I don't want you to fall in the same trap if you're thinking about starting your own business but are worried about the complexity of actually selling things. Here's the secret to eliminating those fears so you can get going right away. Use Shopify. It gives you everything you need to start selling on day one so you can focus on what really matters, which is growth. Now, here's one feature in particular I think is critical. 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Cal Newport 35:04 please." She then links to an article that is titled The Sharp Rise in Incidents of AI Escaping Users' Control, Research Finds. And it was an article about not the... I mean, it mentions the, the hacking attacks from this summer that I've been, I've been talking about in some of the Tech Decoded episodes of this podcast and in my newsletter, calnewport.com. I've been talking about these attacks. Um, but the report is also finding that, um, other smaller instances where individual users running agents are finding, "Oh my God, it deleted my files," or did something else I didn't want the agent to do. So there's, there's a sharp rise, um, of such reports. So I sent Sandra a response. I'm actually gonna read the email I sent back to Sandra giving my opinion to this article, and then I'll elaborate a little bit. But here's what I said to Sandra: In this article, when they say AI, they are actually responding to a very specific type of system in which a computer program executes a long-running loop in which it repeatedly prompts an LLM, asks it what it should do next, and then automatically executes it. Given all of the unreliability, erratic behavior, and unpredictability of LLM output, such a system is 100% guaranteed to eventually end up doing something you didn't expect or like. This is not a problem with AI, but a problem with a specific type of irresponsible system that the LLM companies want to keep convincing us are critical. This is at the core of my critique right now of what's going on. I don't want to get too much into this because I do this more in, like, my, my newsletter and, and, and other types of episodes on this podcast, but just, like, at a really high level, every time there is bad news surrounding the health of the businesses of the major frontier labs, they drop in our lap, like a cat leaving a dead bird on our doorstep, some sort of anxiety-producing, AI safety tinged, you know, um, uh, Eliezer Yudkowsky fever dream style story about AI, then that's what everyone talks about. And I th- this happened this summer. People started pushing hard on the financials of these companies. OpenAI began losing, uh, top employees again and again. They've had several incidents in the past few months where they hired a top employee, and they left within a few weeks. The economics aren't making sense, and analysts are starting to push back on this. They're pushing back on the CapEx spend. They're doing the math and realizing, wait a second, for you to get your projections, um, for all of this CapEx spend, for example, on AI data centers to make sense, there have to be trillions of dollars of revenue. And right now, like, we mainly know how to do coding agents, which is, like, a good business, but not a massive business, and it's struggling and also is not-- doesn't really require frontier models, so this is kind of a difficult place for the big companies. And, like, Google Search, where it costs more money to power the search with these LLMs, the search results, than it is money you can actually make selling ads. So there's some financial issues right now. All this is being pointed out. OpenAI delays its IPO because the numbers aren't there. People are jumping ship. And what, what do they say? Do they come out and be like, "Let's explain the fundamentals of our business. Here's what's going on"? No, they say, "Agent civilizations are trying to take over." And boom, that's what everyone's talking about. So they do this, and it's annoying. Um, but here's the point I'm [chuckles] I'm trying to make in this response, is all of the sort of summer's hysteria about AI getting out of control is about a very specific type of AI system that is guaranteed to get out of control. Guaranteed. It's not AI in general. It's not AI in some general sense as it gets more capable is, uh, misaligning with human intentions. It's a specific type of system where you have a, I call it a loop prompt, where, uh, a prompt loop. We just have a, a, a program written by human beings, nothing fancy here, that ask an LLM, "Hey, here's what I'm trying to do. What should I do next?" The LLM says, "Do this." It executes that, then it comes back, updates, says, "Okay, here's what, here's what I want to do. Here's what's happened so far. What should I do next?" And that's it. And maybe it generates other prompt loops to, to take on particular steps to keep the context clean, so it kind of swarms out and then comes back in. But that's what it is. It's just blindly executing what an LLM suggests. Now, this only really works in the world of, of, uh, computer terminals because in computer programming or cybersecurity, the actions can all be text commands you can run on a, a terminal. So it's very easy for an LLM response to say, "Run this command." It could describe it in text or run this script, which it can describe in text, and then the, the, the agent program can just run it directly on the terminal. That's a very specific type of system. It's a really bad idea to run this for, like, any sort of duration because LLM outputs are unpredictable. They're meant to be lexicographically plausible, not to be normative. They, they, so they don't follow human norms. They don't have, uh, consistent or symbolic planning. They don't have value systems. It just sort of spits out, "I think this is a lexicographically plausible thing I just output." This can have very powerful ideas, like this is a really good hack, but it also means they're gonna drift all over the place. They make things up. They fall into narrative tropes. If in your prompts, like you're an AI system and I need to know what to do next, it's gonna likely fall into sci-fi tropes, right? Because we know this from research. So it's just a very dangerous thing to do outside of, like, here's a very narrow problem, and you can run a prompt loop to try to, like, do multiple steps of a solution so you don't have to do it. But in a very, like, um, narrow context, dealing with computer programming terminal-based tools, this could be useful, but you gotta be really careful. And the computer programmers know this. The, the professional computer programmers, um, really are, have been constraining the horizons on which they send these prompt loops out to handle things because they go off and do weird things. And so these incidents of losing control is just people running their own prompt loops using frameworks like OpenClaw, which lets you write your own prompt loops, run them on their own machine, giving them access to stuff on their machine, and because they're just asking an LLM, "What should I do next? What should I do next?" They, they're erratic and unpredictable, and they do erratic and unpredictable things. This is not AI writ large. There is no AI writ large. This is a LLM and a prompt loose comp- company, uh, program that's prompting the LLM and doing what it says, and anyone who's used a chatbot knows there be dragons. If you do that long enough, you're gonna get into a weird place, right? Fool me once, shame on you. Fool me twice, shame on me. So, uh, again, there's distraction going on here. Prompt loops run for a long period of time, like OpenAI did this summer. It's just irresponsible. Of course it's gonna do crazy things, not because Skynet is getting upset, but because you put a weed whacker on a dog. It's an unreliable source of action. Don't blindly execute LLM outputs as actions. Of course bad stuff will happen. All right, we got, uh, our fourth message here.

Cal Newport 41:55 It came in anonymously, and it said, "I thought you might find this Reddit post interesting." And it pointed to a Reddit post whose title was "The hype is waning even for large corporations." Now, let me read you the key paragraph of this Reddit post. "I have two colleagues from university who work for two major financial firms. Over the past month, they have been talking about how many problems LLMs are causing behind the scenes and that the cost is coming due for the upper levels. They are moving away from all enterprise AI tools from OpenAI and Claude. It's over, and this starts the slide." Interesting. There's a lot of replies to this. I want to read two replies from farther down in the Reddit thread. Here's one that caught my attention. "I work at a large non-bank financial services firm, so lots of data, lots of spreadsheets and accounting, lots of legal docs, lots of personal data. We can't structurally use LLMs because it would upload all the highly confidential client and, uh, KYC data. So if we use it, it's to double-check some procedural legal requirements via prompt, like Google search. More often than not, it's wrong because it doesn't use the right sources or even reads them correctly. Law firms rarely give clarity for free on their website newsletter, but the LLM will state anything as certainty even when there is none or it has no answer for the prompt. In other words, we have no existing use cases." Here's another reply I want to read. "I'm hearing lots of stories about engineers browsing on their phones while letting Claude do a bunch of work, walking the dog, playing games, all on company time. That doesn't lead to better outcomes for the company, just an engineer burning a bunch of tokens in a way that lets them slack off. Just to be clear, that's not universal. I also know engineers who remain focused, but it's a temptation a lot have given into, and it actually did- doesn't benefit their employer. If top-of-line productivity isn't changing, the token budget is going to get cut." All right. So why am I giving those, uh, particular sort of negative accounts of LLM-based tools out there in the wild? My intention is not to argue that LLMs don't work or there's not use cases for them, but to argue that it's a normal technology. It has these impressive things it can do, like when we're chatting with it, right? But it's hard, and I'm saying this from the perspective of someone who has written many books about the intersection of technology and business. It is hard, often, to integrate new technologies into the professional environment. Work is complicated. Work is ambiguous, especially in the modern knowledge work era. We have many different roles and objectives and ongoing projects all mixed together in ways that are subtle and nuanced and kind of difficult to pull apart. It's hard to come into there, um, and integrate new tools into that environment. Either it's a simple tool that creates massive unintended consequences, like email, which is a very simple tool and was supposed to replace voicemail and fax machines, and it completely changed our collaboration style. So either it's something like that, or it's a tool that's meant to, you know, replace major parts of work, and it takes 10 years instead of one. Personal computer usage was way slower the way that integrated into the office than someone like Steve Jobs in 1979 would have guessed. All right, so I, I use these examples just to emphasize this is going to be the case with, uh, AI as well. It's complicated. AI coding is, like, miraculous that it can produce this code, but it's difficult to figure out what's the best way to actually integrate AI into the computer programming workflow. And when you talk to engineers who are not also AI booster types, they're like, "Yeah, I don't know. I'm using this as better, but this is worse, and I don't think we have this quite figured out yet." When you talk about AI in, like, law firms or other places, there's use cases, but also, like, often they don't work, and it's complicated. They're not miracle tools. And this is why I, I want to move away from this frame of thinking about AI, uh, as, like, an abstraction. Like, we have a brain. That's the way a lot of people think about it, and it was a small brain, and the brain is getting larger. So whenever we hear about advances in this conception, we imagine the brain in general is getting smarter and it can do more and more, and all these jobs are disappearing and whole swaths of work are automating. Read the Bill Gates letter. He just confidently is like, "Well, we know, like, all these jobs are gonna go away." They're not. How do we know that? What tool is gonna make that go away? LLM tools haven't done that. The MIT report from last year studied a bunch of companies. 95% of their generative AI pilots failed. They weren't effective. It's complicated. It's not a silver bullet. So we have to stop thinking about AI as this abstract force. We like to... Here's what I think is going on. People want to have comments. People want to give commentary. The technology is complicated. They don't want to give commentary on how the technology works. That's complicated. And so they say, "Let's deal instead with, uh, the thought experiments, the abstract thought experiments. It's getting more powerful. Whole industries will be automated. Now I can give my, my feedback on what we should do about that." You avoid having to deal with the technical details, but often those abstracts and thought experiments and those assumptions about what the AI is gonna do is not right. And I get it. It is hard to get into the technical weeds. Like, I wrote last week an article where I was trying to explain some of the more complicated or sensationalized, uh, details around, like, the Hugging Face attack, and I, I was explaining how multi-agent swarms actually work. These are pretty common and coding harnesses, and it's not some scary new form of intelligence. It's really more about prompt management, keeping the context, uh, smaller to get more out of your inference time. And then I got a lot of feedback just like, "Yes, but actually, like, in this Hugging Face attack, it was slightly different. It wasn't a small number of prompt loops generating many secondary prompt loops. It was actually a huge number of prompt loops generating almost no secondary prompt loop," which is a very unusual setup, but OpenAI was doing something unusual. And so I had to go back and add a, like, update to my, my, my essay about this on calnewport.com. This stuff's complicated. I get it. Like, that's not fun. It's more fun to give me the thought experiment, so I can come in and be so- the, the sober statesman and talk about, like, what we need to do in these hard times. But we have to get into the technological weeds because when we do, we find out these technologies are incredibly cool and incredibly normal, and all this is gonna be way more jagged than people say. And the more we're reality-based, the more we have a say in what we like and don't like, the more we can hold companies to account, the more we can stop, like, having our hi- our, our stock market be hijacked into the massive amounts of unnecessary global anxiety that's being caused right now out of these more rationalist AI safety narratives can be tuned down. How much, like, productivity and human happiness are we losing to unnecessary anxiety because some of the big forces talking about AI spent too much time on LessWrong when they were younger and love the narrative of super intelligence and they're Neo in The Matrix because now they can wear that weird, like, neoprene leather stuff? All right. So anyways, I don't mean to rant, but I thought that was useful AI is an exciting technology, but it's a normal technology, and it's messy, and it's complicated. And the more we recognize this, the more we can chill out, uh, and the more we can stop letting AI companies get away with stuff they shouldn't. All right, let's close the inbox for now. I like to end my episodes on Monday with talking

Cal Newport 48:46 about what I am up to. Um, again, Jesse is not here today. He's dealing with some family health issues. We wish him the best, and I am doing my best not to bring Jesse Skeleton into the studio. And if you don't know what that means, you're welcome. You don't wanna know what that means. That's a whole bunch of nonsense. Um, I finished a book last week. I read The New Dark Age by Nigel, uh, Biggar, B-I-G-G-A-R. Uh, this should not be confused with Jam- James Marriott's upcoming book, The New Dark Ages. The New Dark Age, um, Nigel is an ethicist, I believe, at Oxford, um, sort of a, a, a storied British academic type. Uh, and this book is about academia. It's really like a critique of Woke One, as AOC now calls it, the sort of initial woke period that has sort of died off. Nigel was sort of caught up in this because, uh, he wrote a book and I believe had a big grant that was looking critically at colonialism and saying there's a lot that was bad about colonialism. There's other things that was good. It's complicated. It was called Colonialism: A Moral Reckoning. But post-colonial studies had emerged as one of the massive ideological, uh, forces in Woke One, and they do not take kindly to any pushback against the way they think about colonialism, so it caused a lot of problems. So now he wrote this sort of polemical book about, uh, Woke One was it's ruining the universities. We have to push back. The thing I admire, I always admire when I read English, especially like Oxbridge academics, is man, they have this, this tone when they write that is somehow both conversational, brilliant, and cutting. Americans, we can't do this well. It's like I'm being conversational, and you can almost imagine the British accent, but like the references are so erudite, and the underlying logic, it's, you know, um, it's like a, a, a Wittgenstein in action. The pieces all click together, and it's devastating in the end. So, um, I always like reading English. You know, having an English accent already gives you a one-up in debates, but it's not just the accent. The Oxbridge style I find to be very effective. I- Americans don't, I guess, we would rather just have someone yell or be more passionate and, you know, "Hey, this guy's on my team," or whatever. But I like the Oxbridge style. So I, I did enjoy the book, though, you know, I feel like everyone acknowledges now Woke One w- When you have AOC saying like, "Oh yeah, we got kinda crazy then," you're sorta out of... You're starting running... All the people left who are still endorsing all of the extremes of Woke One, I think they're all on Blue Sky right now, um, trying to figure out who to cannibalize next. All right, but anyways, interesting book. Um, I will leave it there for today. Thank you everyone for listening. You know, again, um, I always have a Monday episode of this show, typically on the human flourishing side of the f- the, of my flourishing and technological world. Um, but I try to put out more episodes when I can, including Tech Decoded episodes where I can look closer at big stories like involving AI. But I have some other episode types that might be coming as well, so, you know, stay tuned to this feed or channel. And of course, you can always subscribe to my newsletter at calnewport.com to get these dispatches right into your inbox. Until next time, as always, stay deep. [outro music]