Ep. 355: Quit Social Media  ## Metadata - Author: [[Deep Questions with Cal Newport]] - Full Title: Ep. 355: Quit Social Media - Category: #podcasts - URL: https://share.snipd.com/episode/8a8bc90f-3a19-42d1-96ce-3c7669f82d36 ## Document Notes ## Highlights - **Social Media as Ultra-Processed Food** - Social media content is like "ultra-processed food" that is engineered to hijack human desire and is much harder to consume healthily than other media. - Unlike past media panics (comic books, TV), social media's advanced manipulative content could justify quitting it entirely for mental health. Transcript: Cal Newport Today, I want to talk about your phone. Most phone users, especially of a certain age, aren't particularly happy about how much time they are spending on their phone using social apps like TikTok or Instagram. They've heard people like me recommending for years that they should consider quitting those apps. But most people can't quite bring themselves to do it. And the question is why this is. I have an explanation I want to give here, and then I want to deconstruct this explanation and give you a new way of thinking about improving your relationship with your device. All right, so here's what I want to argue is going on. Part of the resistance or reluctance that people have to, let's say, taking popular apps off their phone is that they worry that it is an overreaction, that perhaps they are falling Into a moral panic. Now, I want to play some audio here to better emphasize what I mean. This comes from the spring of 2019. It was from an interview appearance I did on Brian Koppelman's podcast as part of the book tour for my book, Digital Minimalism. So let's hear this tape for a second, Jesse. Because I could have been a car minimalist and I could have said, you know, that there are all these costs of having a car. You're not going to see the scenery. You know, we need nature and we need to see the nature. You're going to – you're risking – you know, you have a slight inattention you could crash yeah um and so to me it is this this argument is also um the cars are taking over there's nothing You can do about it yeah and we better instead learn how to use this stuff the car how to drive well well but so for the all right so what koppelman was arguing there is a a classic moral panic Argument about we hear about uh technology these days which is like look we often get worried about new things but these things are often not so bad and in the end we might as we end up being Okay with them so we might as well just get along with the process of learning how to use them. So he was saying you just as easily he was talking about my book, Digital Minimalism. He said, look, you say you're a digital minimalist. He was saying that clip. You could use that same argument to have been a car minimalist in the early 20th century and be like, I don't want new cars have these problems. We shouldn't have cars, but cars were inevitable. Cars were coming. And they ended up, you know, we need cars. Life would be much harder without them. We wouldn't have the American growth like we had it without them. And so that was like a waste of time. It was alarmist. This is a common pushback that technocritics are familiar with. Now, I think this type of reasoning, this pushback fits particularly well when we talk about the trajectory of mass media that tools like TikTok and Instagram are at the current end Point of. So if we think about mass media in particular, we see some examples of perhaps people being really worked up into a lather when new medias came along and then eventually relaxing about Them. So consider comic books, for example. These once terrified the fedora-wearing, pearl-clutching adults of the era who were convinced that they were corrupting youth. In a 1954 Senate subcommittee meeting, a leading anti-comic book advocate named Frederick Wortham testified as follows, it is my opinion without any reasonable doubt and without Any reservation that comic books are an important contributing factor in many cases of juvenile delinquency. He went on in that same testimony to say Batman is promoting homoeroticism and Wonder Woman is promoting sadomasochism. Jesse, I probably should have read more comic books. Yeah, and what's going on in those things, but man, I missed out. Television engendered similar concerns. Here's a quote from Wendell Berry. He had a famous essay called Family Life, and it was included in his 1981 essay collection, The Gift of the Good Land. And in it, Berry said the following, as soon as we see that the TV court is a vacuum line piping life and meaning out of the household, we can unplug it. All right. We're okay with comic books today. It blew over. We're okay with TVs today. We all still have them. We all still watch Netflix or Macs. We're not nearly as worried as Barry once was. The question is, maybe we can just think about, or why can't we just think about social media as just the next stop on this trajectory? And in the future, when we're all using VR to hang out with alien versions of Mark Zuckerberg, we'll look back at the social media age like that. Come on. That was just technology that came and went and we're okay with it. But is this right? So I want to take a finer look at this argument of moral panic applied specifically to mass media, applied specifically to whether or not social media is just another thing on this trajectory. To help us make sense of this, here's what I'm going to do. I'm going to return to an analogy that I introduced in an essay last spring that I was thinking about recently and realized, wait, this gives us some useful insight into this very specific Question. So the essay I want to draw from here came out last June. I'm putting on the screen here for people who are watching instead of just listening. I wrote an essay June 19th, 2024 that was called On Ultra Processed Content. And what I did in this essay is I drew a connection between the nutritional notion of ultra processed food and social media content, which I was going to call ultra-processed content. I want to read you a few pieces from this because I think it's going to really help us figure out what's actually going on here with this type of information. All right, so for my essay, I said, ultra-processed foods at their most damaging extreme are made by breaking down core stock ingredients such as corn or soy into their basic organic Building blocks, then recombining these elements into hyper palatable combinations, rich in salt, sugar, and fat soaked with unpronounceable chemical emulsifiers and preservatives. The problem with ultra processed foods is that they are engineered to hijack our desire mechanisms, making them literally irresistible. The result is that we consume way more calories than we need in arguably the least healthy form possible. That's ultra-processed food. Let's connect that to digital information. Reading from the article again here. Something similar happens with social media content. Whereas the stock ingredients for ultra-processed food are found in vast fields of cheap corn and soy, social media content draws on vast databases of user-generated information Post reactions videos quips and memes recommendation algorithms then sift through this monumental collection of proto content to find new hard to resist combinations that will Appeal to users a feedback loop soon develops in which the producers of the stock content adapts to what seems to better please the platform simplifying and purifying their outputs To more efficiently feed the algorithm's global goal of hijacking the human desire mechanisms. In this way, the users of social media platforms simulate something like the food scientist's ability to break down corn and reconstitute it ([Time 0:06:19](https://share.snipd.com/snip/51e2f40a-ac74-464f-9b92-439d4c68a622)) - **Boost Analytical Thinking** - Avoid context switching when learning hard material for an immediate thinking boost. - Train your brain with daily reading (start with 20 pages) and 10 minutes of reflective solitude to improve deep analytical thinking. Transcript: Jesse Miller First question is from Alan. I'm in a new role that demands deeper theoretical understanding. How can I improve my ability to process and critically engage with technical literature so I can become a better, more analytical thinker? Cal Newport I've been thinking a lot recently about thinking. And so this is a timely question, probably because I'm on a chapter of my new book, The Deep Life, that's titled Reclaiming Your Mind or Reclaim Your Brain. So I've been thinking about this stuff a lot. All right. There's an immediate solution and a longer term solution. And I want you to think about both. The immediate solution involves what you do right now when you're in a session where you're trying to learn something hard or you've learned something hard and you want to apply it in A complicated way. Don't context shift. This right away is like taking a reduced dose of the limitless pill from that Bradley Cooper movie. Is that Bradley Cooper? Limitless? Let's just assume it is. I'm going to assume it is because he's a Georgetown grad, so I like to say that. When you're not context switching, you feel much smarter. You're context switching, meaning that you're trying to mainly focus on this one thing, but you're like quick checking your inbox and quick checking your phone. And well, maybe I need to make the same game parlay for the upcoming, you know, Giants Nationals game or whatever it is you're doing. It reduces your IQ points non-trivially. So if you actually, when you do something that requires hard thinking, lock in without context shifting at all, you are going to feel much smarter. So that's an immediate win. Do that right away. Longer-term solution is to get yourself better at doing analytical thinking. A few things here matter. One, you need more comfort with boredom. There's not a lot of novel stimuli when you're sitting down and trying to work within your mind's eye just a single problem. That's boring in the technical sense of lacking novel stimuli. Get used to that. Do at least a few things every day without a distraction, without a phone in your hand or an earbud in your ear, just to get used to being alone with your own thoughts in the world around You. You will acclimatize to it. If you acclimatize to it in these low stakes situation, when you get to the higher-stakes situation of this thing is really hard, your mind isn't going to rebel about we're bored. It's used to that. It knows it's not really a threat. You can also train your brain to better process and make sense of information. To do so, start with what I call the 20-10 rule. 20 pages of reading a day, 10 minutes of being alone with your own thoughts a day, every day. Reading is fantastic for deepening analytical circuits. It's something I'm really looking into now for the book I'm writing. But to give you the super short version of it, reading is unique. It's different than speech. It's different than vision because it's something for which humans do not come pre-equipped with a neural circuit for. We have to train ourselves from scratch how to read. We basically hijack other circuits that are in our brain for other utilities that existed deep into our evolutionary past. We hijack those and we rewire them to do this really novel thing where we have to build these reading circuits. And when we build these new circuits, they make us better able to process information. The best thinkers are great readers. Reading is as close as we have to cognitive calisthenics. So start reading 20 pages a day. At first, what matters is that you're doing it. So I don't care what it is. Make it something that you're most likely to come back to. So the most fun, possible, interesting, easy, possible thing you can. And then have 10 minutes of being alone with your own thoughts. This gets you not just used to boredom, but it gets you used to grabbing a current out of the turbulent streams within your mind, sticking with it, and trying to actually follow it to its Source. That is something you have to practice as well. When you're reading, you're kind of like actively focused on what's happening here and processing it. But when it comes time to do analytical thinking, you have to put those circuits to work on original information. So you have to be comfortable applying those circuits and being within your own thoughts and working, filtering noise, focusing on what matters. So 20 pages, 10 minutes of time alone with your own thoughts, preferably walking. There's a reason why Aristotle called his philosophical school the peripatetic school. They moved. It helps you think. All right. Once you're comfortable with that, add 10 more pages and five more minutes. Now it becomes a 30-15 rule. I'm reading 30 pages a day, 15 minutes a day of walking and just thinking and trying to hold and make sense of thoughts. Get comfortable with that. Another 10 pages, another five minutes. If you can get to something like 50 or so pages a day, 50 to 60 pages a day, and 20 to 30 minutes of reflective thinking, you're walking and thinking and holding your mind's eye. Now it's like you're doing CrossFit. This is CrossFit for your mind. You're going to be in better shape than most people. Jesse, I'm looking at you because I know you do CrossFit. Jesse explains his CrossFit workouts to me. And here's like my simulation of Jesse explaining his CrossFit workout. He's like, well, they came in and they said, okay, what we're going to do today is 97 sets, 97 sets of clean and jerks followed by 4,000 meters on the rower. And then we're going to do 19,000 box jumps. Is that about right? Yeah, more or less. That's about right. Yeah. So what can I say? This is CrossFit for your brain. If you can get to roughly that, like 60 pages a day, 20 to 30 minutes reflection on most days, now you're ready to do some damage with your brain. ([Time 0:23:04](https://share.snipd.com/snip/83ade9e1-3f60-442e-95f0-cff7249731d8)) - **Remote Internship Time Blocking** - Use time blocking to impose structure and maintain motivation during remote solo work. - Keep work hours focused and tight, then shut down to maintain balance and avoid work creeping into personal time. Transcript: Cal Newport Arjun, you have to time block plan. You have to. If there's no actual physical separation between your work and no work, if there's no actual in-person visible supervision that's going to play against more classic motivational Circuits of the bosses here, I want to do my work. I want to show them what I'm doing. It is up to you to add structure and you have to have structure. Time block plan. When am I starting work? What blocks am I doing work? When is my breaks? When am I doing email? When am I finishing work? Shutdown routine. Then I move on to the rest of the day. Do not allow your time outside of work to blend together with your work and just say like, look, I'll get stuff done at some point today. Time block plan. I would suggest actually trying to keep those actual working hours tight and super intense. And then when you're done, be done. But you got to structure when your remote work structure, your time is more important than ever. ([Time 0:29:08](https://share.snipd.com/snip/84d11851-3a05-4c06-9acc-a61a6043579b)) - **Prioritize Main Skills Over Secondary** - Focus first on producing unambiguous value in your main skill before investing time in secondary skills. - Use secondary skills to support main priorities, but avoid them becoming distractions or pseudo productivity. Transcript: Jesse Miller Next up is Daniel. I'm curious about your thoughts on how much time to spend developing secondary skills like improving typing speed or customizing tools that support our main priorities but can easily Become distracting pseudo productivity and how to set boundaries so that these activities don't take over real skill development i mean i would downplay those secondary skills like Cal Newport When you learn them you learn them because it's clear if i got better at this it's going to help exactly that but really make your main focus in a demonstrable way unambiguously demonstrable Way, doing things that are rare and valuable. You got to get wired for that. Because what a lot of people do with the secondary skill pursuit is they're trying to actually avoid being evaluated. They want to avoid having to at some point just actually put everything on the line and say, here's my thing. How good is it? And they give you your ranking. And if you're like, no, I have a plan. I'm working on this skill. I built a custom productivity tool over here. I'm going to try to learn how to do this like secondary thing. It allows you to seem very like busy and innovative. It allows you to keep the hope of doing well in the future while avoiding the stress of actually just putting out there and seeing how you do. So I want you to get obsessed first about, I'm competing to do good stuff. How am I doing? How much money am I getting from clients? Am I getting the promotion? How many dollars am I bringing into the company? If you have a good laser-like focus on producing unambiguous value, not being afraid of falling short and celebrating when you actually get ahead of where you think, then yeah, throw In secondary skills as you need, and they're not going to be a diversion. They're going to be very utilitarian. Like, man, I'm really doing well here. Ah, if I could type faster, I guess that would really help this. Now I have a reason to learn it. So I just, what I really want you to do here is not allow the secondary skills to become a diversion from actually just becoming so good you can't be ignored. So make that your obsession first. Skills should remain second. ([Time 0:30:11](https://share.snipd.com/snip/8463a52b-5427-4a9b-ba12-6bb1a0724aad)) - **How TikTok Algorithm Works** - TikTok's algorithm works as a simple, repeated weighted random sampler using video watch time data, not complex human-curated rules. - This simple approach quickly tunes content to user interests but limits user control over the algorithm's addictive nature. Transcript: Jesse Miller Right. Next up is from Brian. How does TikTok seem to know so much about me and tailor's contacts so accurately to my interest in behavior? Cal Newport That's a good question because I think it connects to our deep dive where we talked about content like TikTok being ultra processed that unlike other types of content like television Streaming or games on your phone, it has a way of being hyper palatable and it has a way of pushing your buttons in ways that's really psychologically unhealthy. So I think it's worth looking into because I actually think I know something about this. I mean, I did some research on this back when there was an internal document that got leaked and this was sort of making its rounds and I read a bunch of accounts of this document. I have like a generic sense of the techniques used by a tech talk algorithm. It's probably worth briefly going over because I think people have this wrong. Wrong, it changes the way you think about this world and what to do about the harms of this world. I looked up a quote here. I think this sort of establishes the way that we kind of get this wrong. So here's a quote about TikTok that comes from the founder of an organization called Algo Transparency, which I think kind of gives the wrong idea. But let me read this, then I'll give you the right idea. So this quote says, each video a kid watches, TikTok gains a piece of information on him. In a few hours, the algorithm can detect his musical taste, his physical attraction, if he's depressed, if he might be into drugs, and many other sensitive information. There's a high risk that some of this information will be used against him. It could potentially be used to micro-target him or make him more addicted to the platform. Technically, all of that is true, but I think the way that we talk about algorithms here gives us an incomplete understanding of how these things actually work. I think when we see those type of description of algorithms, what we really imagine is sort of like someone making a list of descriptive information about a user. Oh, we've learned that, we learned that, he's into this, not into that. We imagine an algorithm sort of like looking at these semantically rich descriptions of things you're into or not into and deciding according to some sort of complicated rules that Someone programmed in. All right, well, why don't we then take this and mix it with that? And we have some good stuff of that over here. And we're trying to emphasize this type of content. Oh, and I've analyzed, I think this type of content is, it feels like people like it. And so it's like a network scheduler. Let's show him more of that. Like, so I think that that image of an algorithm, it's like a network scheduler looking at a board full of pieces of information on index cards and making a decision like, well, what are We going to schedule next? I think this is really going to catch his attention. We have that idea, which is sort of personified. We imagine like there's a human involved. And it gives us the sense that we can turn these various knobs and say things like, hey, adjust your algorithm to not recommend stuff that is going to be so addictive. Or adjust your algorithm to like turn down the outrage meter from like a 10 to a 9. When we think about the algorithm as like a person with all this information making scheduling decisions, we think we have all this control over it. That's not really how this works. I'm going to try here to draw a picture for those who are watching instead of just listening, and God help us all for me doing this. But I want to give you a better sense of how the general class of algorithms that we think powers TikTok actually works. So you can imagine what we do is that every time you watch a video, there's a piece of information that's gathered, but what's gathered is a description of the video. This description though is going to be a bunch of numbers. So there's going to be, you could think of it like a lot of different categories you could use to apply to a video. You know, cats could be a category. If that's a lot of cats, that number is high or low or something like this, right? And so you have different numbers in each of these categories, sort of gives you a list of numbers that describes the video. So if we had, for example, just two numbers, we could imagine having a flat surface, like a two-dimensional plane, where you could put each spot in here, like if we put a spot right here, Is associated with two numbers, like with that number and with that number, right? Video, we can put a little dot on here that represents its description. And we can make that dot bigger or smaller depending, and this seems to be what's most crucial for TikTok, how long you watch it. Like what percentage of the video you actually watched. So like maybe you watched a video over here real briefly, small dot. Over here though, there's a video you watched all the way through. There's like a big dot over there, and maybe there's a medium dot, and you kind of sample some videos over here, right? And over time, we're kind of just giving you videos to watch, and we see how long are you watching each of them. So now we have a bunch of these numbers. We have this plot. Technically, it's going to be a sort of weighted multidimensional scatterplot. And now when we want to show you a new video, we being TikTok, the algorithm is super mathematical. It says, okay, I'm just going to randomly choose a video in the spot of possible videos to show you, but I'm not going to select from every area equally likely. The more sort of green real estate there is in a certain place, like the more I'm going to be pulled in that direction. Like I might select something over here, but I'm way more likely to select something over here because there's so many, not only just so many other dots, but so many big dots. There's a lot of watch time over in this space of the possible videos. And what we're implicitly doing here is kind of creating a region. These are all going to be probably roughly similarly types of videos. Now, again, my algorithm is doing something very simple. It's just randomly choose a thing, but wait your choice. You know, the more stuff there is nearby it, more mass you want to put on it. And there's like a lot of probabilistic ways you could do that. So I'm going to start selecting more videos near stuff you already like, but like occasionally, you know, you roll a dice enough time. Sometimes you're going to roll six, three times in a row. Occasionally I'll pull some stuff over here as well. And maybe what I'll do, and we think that the TikTok algorithm does this on purpose, it will on a semi-regular basis say, forget, uh, forget the weights. And let me just like purely draw randomly just to make sure there's not something we haven't tried yet that you really like and then like maybe over here there is like a whole bunch of cal Network memes and immediately these start getting watched well and now it's like you're getting a lot of cal network memes and then like a lot of the times of the stuff over here and occasionally We'll sample other types of things. That's what's happening underneath the covers. It's not just two numbers though. It'll be like a hundred numbers or a thousand numbers. So this is each of these spots is in a thousand dimensional space. So the math is different, but it's the same idea. What's key about this is the algorithm is stupid. The algorithm, there is no complicated code in there that humans wrote that's like, how do I balance ([Time 0:32:09](https://share.snipd.com/snip/847aa36b-ae48-42c6-b758-8d77417f9637)) - **Maintain Flow With AI Agents** - When using AI agents in coding, avoid context switching during wait times by working on related project tasks. - Keep your workflow within the project's cognitive context to maintain flow and productivity. Transcript: Jesse Miller Gene's next. What are the best strategies for workflow when using AI agents? And we have an article that you can react to and we can show the audience. Oh, okay. You sent an article? Yep. All right. I'll pull this on the screen for those who are watching. All right. Cal Newport The article, waiting for agentsents Shouldn't Kill Your Momentum. This post breaks down why no agents and too many agents both stall progress and shares a sweet spot workflow to keep you locked in flow. All right, so the first heading here says Waiting Kills Flow. Now, looking closer at this animation, I'll make this bigger here for those who are watching. What they are showing here is an AI agent working in what is at the moment the only context that I know of where something like agentic AI code is actually not just useful but being somewhat Largely applied, which is in computer programming. So the AI agent that's being shown on the screen here is an AI agent that is helping you write software. So this is, I think, right now perhaps the only major application of agentic AI that I know of. And again, agentic AI is where you have control software surrounding the use of something like a language model. So it can query the language model for an idea or a plan, and then the control software can look at the answer and then take actions based on the answer. So when it comes to computer programming, here's another example here for those who are watching. When it comes to building like a semi-complicated VibeCode and style computer program, you can have these agentic code like Cursor, Windsurf, or Roo, where what you're doing is it'll Like first have the language model give you like a bunch of steps you need to do to build a software product. And then like, okay, you want us to do step one? You say yes. And it's like, great. And then the software will then query the language model to get the code for step one. And then it'll run it and be like, oh, there's errors. You want us to try to fix it like yeah and you kind of work on step one and the agent sort of makes queries on the language model on your behalf until that step has working code and then it's Like you want to go to step two and you go to step two and it allows you to build more complicated software than if you just ask the language model give me code for this like if you say give Me code it has to be a relatively small thing it solves but if you do this multi-step thing, Agenda AI lets you do more things. So the more complicated projects. So the argument here is that, and I've seen this, I've sat next to people that showed me them using these systems. There's a lot of waiting, right? Because these language models aren't fast to query because, you know, you might have 500 billion parameters being executed by multiple GPUs. There's queues. It's slow. So all of these animations I showed you, a lot of it is like thinking line by line. You see things happening. So this whole article is like, how do you not get too distracted while you're waiting for your agentic software when you're building software to like finish thinking? And I think they are fans of my work because they talk about if you're jumping over to social media, like your phone, man, you're going to get so context shifted and overloaded that you're Going to, your brain's going to burn out. So then they argue here, like what you should do. And here's their solution is you should have something like an Obsidian-powered to-do list next to your coding so that when this starts thinking, you can go over here and work on something Productive, and then when it's done, go back over here, and then you're never really leaving the context of the project, but you're also not just sitting there bored. So I don't know, there's something I like and something I dislike about this. I like their general application of, hey, be wary of context shifts. We have this idea of deep breaks where like if you want to take a mini break from what you're doing, there's ways to do it so that you don't fry your mental circuit. So working on the to-do list for the larger project keeps you within like the general cognitive context. But the sort of less exciting side of this example is like, this is kind of it for agentic AI right now. So I'm still, we talked about this last week at the end of the show. I talked about this in my recent email newsletter, post AI and work, which you can find at calnewport.com. We're not sure how many applications we're going to have for agentic AI. Open AI says everything's going to be done by agents and we're never going to have to have jobs again. And it's going to somehow generate like $20 billion like next year. But there's a lot of technical obstacles to applying this agentic approach to other types of work that we do. That's not just like building somewhat subtly constructed small size software applications. So there's a bunch of stuff going on here. I think it's an interesting application. So yeah, if you're coding with agentic AI, this is actually like a new problem we haven't had before. What do you do when you're waiting for the, actually we have had this before, it's compile time. I take that back. This is a common problem for computer programmers is computers didn't used to be super powerful. So every time you change your code to rerun it, you had to compile and rebuild the project. And it takes a while to test to see if it works. And so I actually, you know what? I take it back. Programmers have been talking about this forever. What do you do while you're waiting to compile? I think we've had questions like this before on the show. So there's nothing new here, but I think it's a good insight, at least from an AI perspective. ([Time 0:43:46](https://share.snipd.com/snip/2c18993d-1635-40f0-a076-2cbf77f5ac3a)) - **Analog Time Blocking Success** - A maintenance technician maintains sanity by planning his work year hour-by-hour with a simple pen and notepad. - His analog system exemplifies clarity and focus without complicated digital tools, helping manage distractions and overload. Transcript: Cal Newport Not there yet though. All right. It looks like we have a case study this week. It's where people send in their examples of using the type of advice. I talk about this show in their own life. So we can see what it looks like in the real world. If you have a case study to share, send it to Jesse at Cal newport.com all right today's case study comes from adam adam says while walking our manufacturing floor the other day i struck Up a conversation with one of our maintenance technicians i noticed he had a small well-worn notepad he kept referring to out of curiosity i asked him what he was writing down. He flipped through the pages and casually said, I plan out my year hour by hour. I asked what he meant by that, and he showed me how he divided each page into days with lines for each hour of his shift. Each hour had a specific task or category of responsibility tied to it. Things like preventative maintenance, troubleshooting, parts ordering, time for training or documenting issues. He explained that without this system, he'd never be able to keep up with all the side projects he and his managers were working on, on top of his normal day-to tasks. What struck me was his clarity. If I don't write it all out like this, I'll get pulled into too many directions, never get ahead. He said he even has a similar version for his personal life. I told him that what he was doing had a name, time blocking, and that people like you talk about this method in books and podcasts. He proceeded to give me a severe concussion by beating me around the head with a socket wrench. All right, I added that last part. But I was just imagining lecturing a maintenance technician about, excuse me, but there's a podcast in which this technique has been thoroughly discussed. You're going to get a steel-toed work boot to the backside. All right, let me go back to what he actually said. He said he'd never heard the term before. It was just the only thing that kept him sane. This conversation was a grounding reminder for me as someone who's constantly tempted to over optimize their productivity system is refreshing to see someone use a simple analog Approach to say focus and intentional, no apps, no elaborate dashboards, just pen and paper and approach rooted in necessity and clarity. I'll tell you what article this guy probably did not read. Article on how to make progress on your obsidian open source to-do list while waiting for your agentic AI to make its inference times complete. The maintenance technician was probably not reading that article and he's the better for it. I like that example. Look, it's simple. When you're at work, you have a certain amount of time. That's what you have to allocate to doing things. The whole game is allocating that to the right things that solves the dual problem of you making progress on things that are sufficiently valued to keep you with a lot of career capital While also not burning you out or making you upset. That's the whole game. That's it. How you do that, right? It's like whatever works for you. It depends on the job, whatever. But if you're not having some sort of system, this is how I win at that game, you're not winning at it. If you just rock and roll, here's my email, here's my Slack, there's stuff coming in and out. There's all these meeting invites coming at me. I'm trying to optimize my Obsidian setup while I wait for the inference time and my agentic AI, just doing all this stuff, but you don't have a clear answer to the question. How do you choose what to do with the time you have so as to achieve these two goals, capital and sustainability? If you do not have a specific answer to that, you are being pushed around by forces outside of your control. You're operating at a fraction of your capacity. You're probably exhausting your brain. So that's a great example. I love the simplicity of it. In the end, that's what it comes down to. And it doesn't necessarily require all that much technology to actually get it done. ([Time 0:49:30](https://share.snipd.com/snip/7873112e-b9d4-4663-ba0c-e8eafee7cb44)) - **Doctoral Success Through Collaboration** - To succeed in doctoral studies, work closely with your advisor on their best papers. - Contributing to high-quality research teaches you the skills to write your own impactful papers later. Transcript: Cal Newport Let's hear it. Hi, Cal. My name is Emil Foligno and I've been a lecturer within computer science at the Swedish Higher Education Institute for the past 8 plus years. I've used some of your approaches to deep work and time management to become great at teaching. And was promoted to expert lecturer a couple of years ago. I've now invested some of my career capital and will start doctoral studies in general, but with my lecturer's salary. To be able to obsess over quality, I will need to develop a new set of skills related to research. As an experienced researcher, what general and specific skills would you recommend that I hone in on? Right, it's a great question. But first, congratulations. You worked a career capital system well. Now you're going for your doctorate, but at a salary and not at like a research assistant salary or, you know, you've worked it well. You became an expert lecturer. You have a connection to this university. You can do a salaried program. It's probably going to open up slots for you when you're done. So well played the way you've done this so far. All right. When it comes to how to succeed in this doctoral program, you need expert guidance. So you fortunately have this built in, your advisor. Choose an advisor who's doing good work in their field and it's a field that you think is interesting and has value. And then say, I want to learn how to do this. Let it's right off the bat let me write it let me be useful to you what paper are you working on now i want to learn about it and i want to be useful and i want to write papers with you right off The bat to learn how it happens to learn how it happens so this is what i did so a little bit of a brief divergence here. When I first arrived, so I arrived in a theory group, I was working in the theory of distributed systems group, in the theory of computation group at MIT. And technically, I was sort of hired to do systems work for this theory group, but I wanted to learn how to do theory. And I remember the first thing I did when I got there is there was a paper they were working on for a good conference, a conference I ended up down the line, publishing a ton of papers at and Being in the steering committee for. But I said, how can I help on this paper? Here's what I know how to do. I just want to be involved in this paper because I want to learn how people write papers for this good conference. I don't want to write papers for less conferences. I don't want to go on my own and start writing stuff for like secondary conferences and trying to figure this out. I want to publish in the best places. I said, here's what I can do. I'm a kind of a systemsy guy. I can build like simulations and stuff like this. I could add a simulation sort of section here. I'll figure it out. It'd be like a nice, you know, half page to your paper. Like, I find you can do that for us. And now I was in the door and I was involved in this paper and I was there and I saw every draft and I saw how it worked. And when the next paper came up, which was like a follow up, I was like, well, here's a corner of the theory that I think I can do. It's not too hard. And so like I found a way to be useful on the high quality stuff, a small handhold on a big swing project. And I made those handholds bigger and bigger until after a year or so, I was like, now I know what goes into writing these papers and I could really take off. And now I wasn't dependent on waiting for other people to be writing a paper to work on and I could start my own and I published a lot of papers. So work with your advisor on the best possible papers. That is the skill you want to learn. And the only way to learn it is to work on really good papers with people who know how to publish them. ([Time 0:53:18](https://share.snipd.com/snip/2e83851e-aeed-489f-ad5a-50059d120621))