# How to Gain Control of Your Time

Channel: Cal Newport
Video: https://www.youtube.com/watch?v=BUjf7Tv8GDE
Duration: 52 min
Language: English
Words: 10519
Transcript page: https://viewrankai.com/tools/youtube-transcript/BUjf7Tv8GDE

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[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

[0:40] push back [music] and say, "We got to get more structured." So, I did. Last week, I sat down and figured out the exact setup for my organizational systems that I'm going to run this fall, including the specific tools I will use and the processes I will use with those tools. And this is what I want to talk to you about today. I'm going to 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 going to leave it there. I'll then step back and talk about a why it's important in general to periodically

[1:12] 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 David Allen making out with a Trello board. It's um it's pretty disturbing. All right, so we got a lot of advice and ideas to cover in this episode. So,

[1:35] let's get right into it. All right, so here's my plan. We're going to proceed in uh three parts. In the first part, I'll go through the details of my system for the fall of 2026. 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

[2:12] 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 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,

[2:45] the technology will make these plans for you. They're happy to hijack your day in a way that's going to allow Mark Zuckerberg to buy the second half of Kawaii. I don't know what what he does out there, but maybe involves David Allen making out with trollboards. I don't know what tech people do. U so I do think it's important to talk about organization, not because [snorts] God, what's this kind of tiresome rhetoric about we're always optimizing ourselves because we're trying to uh we're trying

[3:11] 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 want to talk about my system for the fall of 2026. Now I'm going to proceed by first talking about the material. So that is like the specific tools I'm using and then we're going to 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 sbatical. So I'm running a more lightweight system

[3:43] 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. So 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 sobatical I am storing them all in a computer program called things three. Uh I'll put it up on the screen here for people who are also

[4:15] 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 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 list and then you

[4:49] can also look at on tasks you can look at like hey what's which task are due today or which ones are uh 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 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 not use Trello for my major roles because if I

[5:19] 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 going to use is a time block planner. I have one

[5:35] 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. You haven't seen a time block planner? I'll hold it up here. So you got pages over here for time blocking and then over here for storing task. You have a shutdown 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 task when I'm away from a machine to write them down. Shutdown routine uh justification. There's a

[6:09] 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

[6:44] 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 going to be away or when I'm on calls or whatever, but I don't share the logistics because those

[7:03] 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 going to contain the sort of the core uh ideas for the season ahead of mine. I'll put I made a sample one I'm going to 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

[7:38] 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 what are the big things maybe optional but the big endeavors are going to move me forward to bigger goals or practices I want new practices I want to 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. I think this is

[8:06] 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 going to organize myself this fall. It's an open loop. It's in there. It's floating around. Uh, and you don't want to 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

[8:41] 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 that that 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 want to 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 in your top chore 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

[9:07] 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 this 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 want to do on a regular basis. You got to write down somewhere these are

[9:36] 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 going to be as well as your big vision for that season. That's printed out, put in your sock drawer so you can't avoid it. That's the root for

[9:53] 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 three 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 want to 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

[10:27] 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

[11:00] metrics when I do my shutdown. So I'm putting all of that in next to uh time block plan and my methods, right? Um, for task, the method I'm going to have is 20 minutes a day at least, minimum of 20 minutes a day going through things and trying to make progress on task. 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 rolls and capturing and processing. But for a sobatical, this makes sure I'm not going to forget things that need to be done

[11:31] 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 because 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

[12:02] review my tasks and I review my vision. And 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 going to protect Friday morning and Wednesday afternoon to make progress on like whatever um big initiative I want to make progress on. Right? So weekly plans to get your head on straight for the week. You see what's coming. You remind yourself of your

[12:28] vision. You make sure that your calendar reflects what you want to do. You kind of reset. look through your things list, make sure they're organized, etc. Get kind of reset for the week ahead. All right, so again, this is a very stripped down organizational system because I'm on sobatical, 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. your time block planning, weekly planning, 20 minutes a day in tasks, doing a shutdown routine, keeping

[13:03] track of metrics. That can power a life that's going to 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 on big projects, you're not dropping the ball on small projects, the AC filters are getting changed, and 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 going to take a quick break from our discussion of organizational systems to hear from some of the sponsors that

[13:35] makes this show possible. But stick around because coming up, I'm going to 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 Superhum here. Too much of the talk about AI these days focuses on abstract benchmark scores or attentiongrabbing stunts like winning a a gold medal or a hacking agent gone arai. But 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

[14:12] about Superhuman Go, a chatbased 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 some project you're leading and you realize that you want to 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 your Gmail at all. You can just pop up a Go window, type in, add a quick summary from Jira at the end, and boom,

[14:48] off it goes. Gets the information on 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 Superhum Go, visit superhum.com. That's superhum.com for more information. I also want to talk quickly about our friends at Monarch. Look, some of my proudest moments from earlier in my life was hitting key financial milestones. I

[15:26] 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

[16:01] your own financial adviser 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 atmonarch.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

[16:38] 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

[17:08] almost always friction. These little bits of friction. I have to do a little bit of extra work. I got to 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 a system altogether. So friction kills systems. So to reduce friction as much as possible

[17:41] um you got to 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

[18:00] the fall it might get more complicated. Maybe the winter you pull it back again. But you always want to be adjusting to the reality of each current season. that 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 use it

[18:19] forever and you'll get tired of it. Novelty is great because when you adjust a system for a given season, you get excited at first about oo 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 in creating a new 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 going to suggest the same for you. Fall, spring, summer at a minimum adjust your organizational

[18:52] 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

[19:18] 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 got to custom build a system to what you're facing. I want to give you uh some best practices for how to do this. I have a helpful diagram here I might load up. Beautifully drawn. 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,

[19:51] when, and why. All right. So, what does that mean? Well, the what is I'll put 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

[20:10] your task? How do you review your task? 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 task lists. Um if you're using like David Allen's getting things done, he suggests answering the win question with physical context. So he divides all his tasks in the context and then when you find yourself in a given context, you just look at the list

[20:43] 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 going to get priority systems. ABC rankings for my task. I do all the A task, most of the B

[21:04] task, and only C task if I have time. Right? So, there's different ways to answer this question of when do I do task? How do I decide what I'm doing next? Well, you need an answer for that in any reasonable organizational system. And the Y 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, etc. Right? So these are the base questions that any reasonable organizational system needs to ask is what, when, and why. Okay. Now

[21:35] 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 going to 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. It's a good way of breaking up the way you

[21:54] 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 want to 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 going to be like? And it's not this is not just

[22:23] accomplishments. Here's my goals. 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 and I want to kind of build my life around it. You need some sort of organizing vision that

[22:39] you're trying to actually move towards. Otherwise, you're just going to 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 on. 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

[23:02] deploy around those materials. Everything should be grounded and divisioned. is 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 is going to 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 going to work for you but covers the thing that these

[23:33] systems should cover. I would like to hear what you end up with. If you want to share whatever organizational system you're using this uh this fall, you can send it the podcast to calart.com. How do you answer what when, why, what material in terms of what materials and methods you use? And if you want to share your vision, you can. Um and maybe in a later episode I will share some of

[23:54] these on the air. All right. So, that's enough about what I'm interested in. Now, I want to 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 want to share or feedback on a past episode, send it to podcast at calupport.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, so 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

[24:28] have to bear with me. All right. Message number one. Methods number one comes from Katherine. And Katherine says, "I thought you would find a comment below from Dervlaw McTurnin, an Irish novelist in Australia about her use of AI." Interesting. All right. So, Katherine sent a link to a newsletter from uh Dervlaw McTurnin, an Australian Irish

[24:55] 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 Katherine 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 can 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

[25:25] 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 tempted to spend all of my time working. All right. I think this is a really good point because it actually dubtales with something I've talked about for years here on this podcast that AI is making

[25:45] 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 going to 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

[26:31] 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 can just execute those and you will have success. And this is really appealing because executing the items and checklist productivity is not competitive. It doesn't typically require deep work. It's more mechanical

[26:53] 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 a 4-hour work week had a real checklist productivity

[27:23] vibe. Here's the secret information. Do these things each of which is like completely accomplishable and predictable. Do these things and success it'll add up to success. Um I'm not a big believer in checklist productivity because it doesn't work for hard things. It's the hard things that matter. It's the creation of the art. It's a 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 one. That's almost always what's what matters. There's no magical list of to-dos that you can execute that's going

[27:59] to get you the same level of success of just doing the hard work of becoming too good to be ignored at something that val 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 Derva is 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

[28:34] technical things. you're like, "Wow, um, I've optimized my setup on Instagram. I have tags now for incoming subscribers and 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

[28:50] 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 use an agent will even do some of this for you. It's addicting, but it's not going to make you a successful novelist and it's not going

[29:24] to make uh it's not going to give you a promotion at work. It's not going to make you, you know, your newsletter 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

[29:42] constrain checklist productivity time. It's not that those activities aren't useful, but they're not the solution. And so, you want to 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's 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

[30:09] reader. 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 uh falling into a pretty bad social media addiction. With all the professional networking opportunities, I found it overwhelming to say the least. Having 247 access to a variety of different professionals I could reach out to, reading up-to-date articles and a

[30:32] 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 that 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

[31:04] 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 is going to do the living for you. It's going to pull the

[31:23] strings. It's just 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 etc. 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 oneoff but people pushed back last time said it's not oneoff. Is that the core of what you do? I think that's right. Even though

[31:56] it's not a book of technology criticism, it's a book about creating the bullwark to technology when you live on purpose. When you when you you have an intentional life that's deep and remarkable. The allure of Tik Tok, 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 to flourishing from the under, you know, reacting to the technological

[32:36] world. Like all this goes together. You have to control your analog life to push back on the digital. We're going to 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 want to 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

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[34:02] free trial at shopify.com/deep. That's shopify.comdeep. Hey, are you looking to get in better shape but are struggling to follow through? Here's the solution. Mybody tutor tu an online coaching program that actually delivers results. Now, how does it work? When you sign up, you're assigned a coach and they help you devise nutrition and exercise plan custom fit to your specific goals and circumstances. And then, and this is the key part, you quickly check in each day on the My Body Tutor app to let your coach know how things went. It's this accountability that really gets you to follow through. It also puts an advocate in your corner who can help you adjust

[34:42] your plan to whatever life throws your ways or notice where you're struggling and offer help. you want to get healthier, go to mybodytutor.com today. And if you do, mention I sent you and they will give you $50 off your first month. That's mybodytutor.com. All right, let's get back to the show. Our third message comes from Sandra, who

[35:02] simply writes, "Opinion, please." She then links to an article that is titled a 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 calort.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

[35:43] there's a sharp rise um of such reports. So I sent Sandra a response. I'm actually going to 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 longunning loop in which it repeatedly prompts an LLM, ask it what it should do next, and then automatically executes it. Given all of the unreliability, erratic behavior, and unpredictability of LLM outputs, such a system is 100% guaranteed to eventually end up doing

[36:21] 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 get too much into this because I do this more in like my my newsletter 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

[36:54] our doorstep. some sort of anxiety producing AI safety tinged, you know, um Eleazar Yukowski feverdream style story about AI and then that's what everyone talks about and I this happened this summer. People started pushing hard on the financials of these companies. Open AAI 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

[37:37] 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 it 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

[38:03] money you can actually make selling ads. So there's some financial issues right now. All this is being pointed out. Open AAI delays it 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 ancient 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 trying to make in this response is all of the sort of Summers hysteria about AI getting out of control is about a very

[38:38] 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 I call it a loop prompt where a prompt loop. We just have a a program written by human beings. Nothing fancy here that asks an

[39:03] LLM, hey, here's what I'm trying to do. What should I do next? LM 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

[39:20] 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 cyber security, 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 can 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

[39:49] of duration because LLM outputs are unpredictable. They're meant to be lextoraphically plausible, not to be normative. They 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 lexographically plausible thing. I just output. This can have very powerful ideas like this is a really good hack, but it also means they're going to 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 going to likely fall into sci-fi tropes,

[40:22] 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. in a very like um narrow context dealing with computer programming terminal based tools. This can be useful, but you got to be really careful. And the computer programmers know this. The the professional computer programmers um really uh 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

[40:53] 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're erratic and unpredictable. And they do erratic

[41:08] and unpredictable things. This is not AI writ large. There is no AI writ large. This is a LLM and a prompt loose company uh program that's prompting the LLM and doing what it says. And anyone has used a chatbot knows there be dragons. If you do that long enough, you're going to 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

[41:33] of time like OpenAI did this summer. It's just irresponsible. Of course, it's going to 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

[41:53] here. 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

[42:25] 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 is to doublech checkck some procedural legal requirements via prompt like Google search. More often than not, it's wrong because it doesn't use the right

[42:57] 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

[43:22] 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, this not universal. I also know engineers who remain focused, but it's a temptation a lot have given into, and it actually doesn't benefit their employer. If topofline productivity isn't changing,

[43:38] the token budget is going to get cut. All right. So, why am I giving those particular sort of negative accounts of LLM based tools out there in the wild? My intention is not to argue that LLM 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

[44:00] like when we're chatting with it, right? But it's hard. And I'm saying this from the perspective of someone who's written many books about the intersection of technology and business. It [snorts] is hard often to integrate new technologies into the professional environment. Work is complicated. Work is ambiguous. Especially in the modern knowledge work era where you have many different roles and objectives and ongoing projects all mixed together in ways that are subtle and nuanced, 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

[44:38] simple tool and it 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

[45:14] 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 is 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

[45:31] complicated. They're not miracle tools. And this is why 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 swaps of work are

[45:53] automating. Read the Bill Gates letter. He just confidently is like, "Well, we know like all these jobs are going to go away." They're not. How do we know that? What tool is going to make that go away? LM tools haven't done that. The MIT report from last year studied a bunch of companies. 95% of their generative AI

[46:07] 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.

[46:24] 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 going to do is not right. And I get it. It is

[46:46] 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- aent 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 was 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

[47:20] secondary prompt loops. It was actually a huge number of prompt loops generating almost no secondary prop loops, 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 kelport.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

[47:47] technologies are incredibly cool and incredibly normal. And all this is going to 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 our stock market be hijacked. And the the massive amounts of unnecessary global anxiety that's being caused right now out of these more rationalist AI safety narratives could

[48:08] be turned 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 less wrong when they were younger and love the narrative of super intelligence and their neo and the matrix because now they can wear that weird like neopre 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, h and the more we can stop letting

[48:40] 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 about what I am up to. Um, again, Jesse is not here today. She has 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 want to 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 Begar B I G- A R. Uh this should not be

[49:12] confused with Jame 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. 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

[49:31] 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 postcolonial studies had emerged as one of the massive ideological uh forces in woke one and they do not take kindly to any push back against the way they think about colonialism. So it caused a lot of problems. So now he wrote this sort of clinical book about uh woke one was it's ruining the universities we

[50:07] 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 and 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 arudite and the underlying logic it's you know um it's like Wikinstein in action. This 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 oneup in

[50:46] 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 Oxford style. So I I did enjoy the book though you know like everyone acknowledges now woke one when you have AOC saying like oh yeah we got kind of crazy then you're sort of 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 in blue sky right now um trying to figure out

[51:16] 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 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 calupport.com to get these

[51:47] dispatches right into your inbox. Until next time, as always, stay deep.

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