Never Feel Burnout Again with Cal Newport (#61)

0:00:00 How do you define productivity?
0:00:01 That’s a tricky one.
0:00:03 Cal Newport is a New York Times best-selling author.
0:00:05 If you interrupt work, it’s going to make you fatigued.
0:00:08 Are there people that are inherently good at multitasking
0:00:12 or is that complete BS?
0:00:13 We fool ourselves.
0:00:14 The human body can’t do that.
0:00:16 But I think the people who think they’re good at it,
0:00:18 they’re just used to doing things basically at a mediocre level.
0:00:21 Remote work.
0:00:22 Remote jobs.
0:00:23 Working from home.
0:00:23 You’re working quote-unquote from home.
0:00:25 I want, if possible, for where you work to not be in your hope.
0:00:28 You’re trying to work in a cognitive environment.
0:00:31 The thing that you need to fix is the laundry basket
0:00:34 that reminds you that you have to be laundry.
0:00:36 It’s a minefield of distraction.
0:00:37 Open AI, your new technology.
0:00:39 Do you think there is a world where AI gets involved
0:00:43 that will unlock something new that we haven’t seen before?
0:00:46 I think the future of AI is…
0:00:48 So I’m absolutely addicted to rocking.
0:00:51 That’s where you put this weighted backpack on.
0:00:53 I’m doing four miles, probably five times a week.
0:00:56 I actually saw a rattlesnake eat a lizard the other day.
0:00:59 No joke.
0:00:59 It was insane.
0:01:00 Anyway, at the end of these workouts, as you can imagine,
0:01:03 I’m just sweating an absolute a ton.
0:01:05 It’s great cardio, but I need to replenish my electrolytes.
0:01:09 But sadly, most of those replacement powders out there,
0:01:11 they’re just packed with sugar that goes straight to your gut.
0:01:14 Spikes are glucose.
0:01:15 There’s nothing good about that.
0:01:17 And that’s the reason why I use elements.
0:01:19 There’s no sugar and it has the science-backed ratio
0:01:22 of 1,000 milligrams of sodium, 200 milligrams of potassium,
0:01:26 and 60 milligrams of magnesium.
0:01:28 Not only no sugar, no coloring, no artificial ingredients,
0:01:31 but there’s no gluten, no fillers, just no BS.
0:01:34 And I got to say, a new product alert.
0:01:36 Element has just released element sparkling.
0:01:40 It’s the same zero sugar electrolyte formulation
0:01:42 that you know and trust,
0:01:43 but now in 16 ounce cans of sparkling water.
0:01:46 And right now, Element is offering a free sample pack
0:01:49 with any drink mix purchase.
0:01:51 That’s eight single serving packets free
0:01:53 with any element drink mix order.
0:01:56 This is a great way to try out all eight different flavors
0:01:58 and see which one you like.
0:01:59 The deal is only available through my link.
0:02:01 You must go to kevinrose.com/LMNT.
0:02:04 And lastly, and this is the best part, it’s totally risk-free.
0:02:06 So if you don’t like it,
0:02:07 you can just share it with a salty friend.
0:02:09 They’ll give you your money back.
0:02:10 No questions asked.
0:02:12 You have nothing to lose.
0:02:13 Huge thanks to Element for sponsoring today’s show.
0:02:15 One of my promises to all of you out there
0:02:19 is that when I take on advertising partners,
0:02:21 I want them to be actual products that I use.
0:02:23 Things that are battle tested.
0:02:24 Things that aren’t just somebody
0:02:26 that’s pitched me something,
0:02:27 but I’ve used them for months or years.
0:02:30 And I can recommend them with complete confidence.
0:02:32 And today’s sponsor, Copilot, is just that.
0:02:36 Copilot is how I track my spending.
0:02:38 It’s how I do my budgeting.
0:02:40 Back in the day, I used to use an app called Mint.
0:02:42 That’s no longer, they shut it down.
0:02:44 By the way, if you’re a Mint user
0:02:46 and you have all your data back there,
0:02:47 Copilot has a really easy way
0:02:49 that you can import all of your old Mint data.
0:02:52 But the reason I like Copilot
0:02:53 is because they use machine learning.
0:02:55 So they categorize things very accurately.
0:02:59 And they have this engine that you can actually train
0:03:03 and automatically apply rules to transactions
0:03:05 as they come in.
0:03:06 So everything just neatly gets categorized.
0:03:08 And you don’t have to spend a ton of time doing that.
0:03:10 But I actually think this might even be cooler.
0:03:13 I really like that they bring in Amazon
0:03:16 and Venmo Transactions.
0:03:17 So you can actually see the items that you’re buying
0:03:19 with inside of Amazon.
0:03:20 Doesn’t just say Amazon.com.
0:03:22 And of course, you can zoom out
0:03:23 to see your entire live view.
0:03:25 You can get two months completely free
0:03:27 with coupon code KevinRose.
0:03:29 So visit KevinRose.com/copilot.
0:03:32 And you’ll see why I’m ranting and raving about this.
0:03:35 It’s a great product.
0:03:36 It’s beautiful.
0:03:36 It’s easy to use.
0:03:37 KevinRose.com/copilot.
0:03:40 Coupon code KevinRose.
0:03:41 Cal, so great to have you on the show.
0:03:44 Well, Kevin, I’ve been looking forward to this.
0:03:46 It’s good to meet you at last.
0:03:48 I’ve read your work extensively.
0:03:49 I think that your mission and what you talk about
0:03:53 and what you preach is so important and so essential.
0:03:57 And I certainly feel it personally.
0:04:00 It resonates with me deeply because I struggle
0:04:02 with a lot of the things that you are talking about
0:04:04 in your new book, Slow Productivity.
0:04:06 I’m glad to have you here so we can go through it.
0:04:09 Yeah, excellent.
0:04:10 Thanks for saying that.
0:04:10 I’m excited to dig in.
0:04:11 Yeah, I’ve been a startup entrepreneur for so long.
0:04:14 And it’s this weird thing where as an entrepreneur,
0:04:17 you never think that you’re doing enough.
0:04:19 And even after I hand the startup off to someone else,
0:04:22 and I try to be quiet, I try to be still for a bit.
0:04:25 And I think that’s why meditation is a big part of my life.
0:04:28 Because if I didn’t have that, how else could I slow down?
0:04:30 And there’s this little background process
0:04:33 that’s in my brain that says, we must do more.
0:04:36 You must do more.
0:04:37 You just have to keep going, keep going.
0:04:39 We have this whole hustle culture that started here a while ago.
0:04:44 And so to see this book come out, this is a true story.
0:04:48 You guys were kind enough to send me a copy of the book.
0:04:50 But I actually put it on Audible and I downloaded it a couple days ago.
0:04:56 And I didn’t stop.
0:04:57 Like I jammed through it because it resonated with me so deeply.
0:05:01 I guess a great place to start rather than turn this into a therapy session
0:05:04 where you just help me with my life problems.
0:05:07 How do you define productivity?
0:05:09 That’s a tricky one.
0:05:10 I think that’s the problem.
0:05:12 In some sense, the problem where we start the issues
0:05:15 that are addressed in the book comes from exactly that question.
0:05:18 How do we define productivity?
0:05:20 This was a silent crisis in the knowledge sector.
0:05:23 So the way I think about it is that when the knowledge sector became
0:05:26 a real actual economic sector with some economic might,
0:05:30 this would have been in the mid-20th centuries more or less,
0:05:33 there was this crisis, which was there was definitions of productivity
0:05:37 that we had since Adam Smith that were very quantitative and really clear.
0:05:42 It was output produced per in unit of input that goes into the system.
0:05:47 And typically there’s a well-defined production system that mediates between those two.
0:05:50 So if you’re a farmer in the 17th century, you’re thinking,
0:05:54 I’m producing this many bushels of wheat per acre of land cultivated.
0:05:59 Here is how I’m cultivating my land.
0:06:01 If I try now the Norfolk four-row system and that number goes up,
0:06:05 this is a better way to do my land.
0:06:07 Industrial manufacturing comes along this fits perfectly.
0:06:09 This many model teas are being produced per paid labor hour, for example.
0:06:15 I changed my production system from the craft system to the continuous motion assembly line.
0:06:20 That number, which by the way, Ford measured, went up by a factor of 10.
0:06:24 Okay, this is a better way to build cars.
0:06:26 The way that Peter Drucker talks about it is basically the wealth on which the entire modern
0:06:30 world was built in the late 19th, early 20th century came out of this thinking.
0:06:35 So there’s like quantitative looking at production processes to figure out what worked better,
0:06:39 created such leaps in production output per input that the surplus wealth is what defined
0:06:45 the modern world, a world where we all have electricity, where there’s cars, two cars per
0:06:49 family, like the wealth of the modern world actually came out of this idea.
0:06:52 It’s a very powerful idea, but it doesn’t work for knowledge work because in knowledge work,
0:06:57 everything’s much more ambiguous.
0:06:59 So I could be individually working on seven or eight different things at the same time.
0:07:04 It’s different than what the person next to me is working on.
0:07:07 Another key factor of knowledge work when it emerges is there’s no well-defined production
0:07:11 processes.
0:07:12 How you organize and manage your own labor is intensely personal in knowledge work.
0:07:16 So we coined this term personal productivity, like how you keep track of stuff, that’s none
0:07:21 of my business.
0:07:22 So there’s no systems to even tweak to see what makes things better.
0:07:26 So what I argue happened is in the absence of these hundreds of years long, incredibly
0:07:31 powerful quantitative definitions of productivity no longer holding, we fell back to a heuristic
0:07:36 that I call pseudo productivity, which said, let’s just use visible activity as a crude
0:07:41 proxy for useful effort.
0:07:43 If I see you doing stuff, like coming in office, let’s work your eight hours a day.
0:07:46 I want to have eyes on you working.
0:07:48 If I see you’re doing stuff, it’s probably useful stuff.
0:07:50 If we need to be more productive, let’s work longer.
0:07:53 And so visible activity as a proxy for useful effort became this implicit metric for productivity
0:07:59 that we just stumbled into because the stuff that worked wasn’t applying anymore.
0:08:05 This kind of went away for a hot minute during COVID.
0:08:08 And then you see companies like Apple coming in and saying, hey, you have to return to the
0:08:14 office now.
0:08:14 Like it’s time to quote unquote, get back to work.
0:08:17 It’s backfiring a little bit.
0:08:19 I don’t even think it went away during COVID.
0:08:21 To me, the key inflection point in this story, I’m a computer scientist.
0:08:25 I’m a technologist.
0:08:26 I’m a part of this thing at Georgetown called the Center for Digital Ethics that my beat
0:08:30 for the New Yorker is really technology and how technology affects us.
0:08:33 I’m always seeing everything through the lens of technology.
0:08:35 To me, the key inflection point of this story was the front office IT revolution.
0:08:40 So we have personal computers that are networked, followed by mobile computing and then ubiquitous
0:08:44 wireless internet.
0:08:46 When this enters into knowledge work, I think this is when pseudo productivity begins to
0:08:51 falter and really begins to spin off the rails because now demonstrations of visible activity
0:08:57 can happen at this incredibly fine granularity because I have email and then I have Slack.
0:09:02 How quick am I answering this?
0:09:03 How many things am I working on?
0:09:05 It’s not just I’m in the office and you can see me.
0:09:08 It’s, okay, I got an answer to this email after two minutes.
0:09:10 This Slack chat, you’re a part of this Slack conversation.
0:09:14 Another sort of hidden thing that happened when personal computers were introduced into
0:09:18 the front office, the amount of possible work you could be doing exploded.
0:09:22 We forget the degree to which in like the 1980s and before, there’s a lot more specialization
0:09:28 in knowledge work.
0:09:29 Type is typed and there was a travel desk at the company that did travel booking and you
0:09:34 probably had an assistant to handle communications and everything was much more specialized.
0:09:39 After the personal computer, we basically fired most support staff and just said,
0:09:43 do all the things yourself.
0:09:44 So we had way more work than ever before and we could show visible activity at a much finer
0:09:50 grain granularity than ever before.
0:09:53 So when the pandemic hits, it almost doesn’t matter that we’re not in the office because
0:09:57 we can visibly demonstrate activity digitally with emails with Slack with jumping on Zoom.
0:10:01 It’s why a lot of people felt that even though they didn’t have to go to the office,
0:10:04 there was no one looking over their shoulder.
0:10:06 In theory, you had this whole dream of the way Tim envisioned remote work in 2007.
0:10:11 I can do whatever during the day.
0:10:13 That dream completely did not come to fruition because every minute of the day,
0:10:17 you were still having to be answering things, jumping on things,
0:10:21 being in calls, being on Zooms, answering Slack meetings.
0:10:24 And so all the promised benefits for remote work in some sense didn’t come true
0:10:28 because of technology plus shooter productivity.
0:10:31 Fill in the gaps here and correct me if I’m wrong, but essentially the networked office,
0:10:35 the networked front office, it really screwed us over because now all of a sudden,
0:10:41 I am old enough now that I remember the days when networking was just coming online.
0:10:46 And I was very young, but I could walk into an office.
0:10:49 I remember my dad’s office and there’s no email, right?
0:10:52 You would literally walk to someone else’s office and be like, hey, question about that thing.
0:10:56 That was the way that you got stuff done.
0:10:58 And now because of the explosion of productivity tools, a personal anxiety for me is always,
0:11:05 am I on the latest, greatest, best one so I can be the most productive?
0:11:09 That’s anxiety producing because you’re always having to hop tools.
0:11:13 And then also there’s none of this downtime to really think,
0:11:17 especially someone that’s more on the creative side,
0:11:20 which I’ve always been on the product side of things.
0:11:22 I need that downtime to be able to actually just process things,
0:11:27 just let things stew a little bit, let things bake a little bit.
0:11:30 And the number of emails I’ve sent saying, I’m sorry,
0:11:34 it took me 24 hours to get back to you.
0:11:37 It’s just thousands.
0:11:38 That’s really kind of screwed up.
0:11:41 Am I getting this right?
0:11:42 Is that kind of what led to all of this?
0:11:44 It’s a surprise and almost a paradox that the front office IT revolution
0:11:49 did not make us more productive because the back office IT revolution, yes.
0:11:53 Okay, we’re going to use computerized databases.
0:11:56 We can have just-in-time inventory control systems.
0:12:00 I can now electronically connect into the system in which we’re trying to get the logistics right
0:12:05 for shipping things across the country, putting mini computers, micro computers,
0:12:09 and eventually just servers into the back office, especially in the 70s and 80s,
0:12:14 really was a productivity miracle.
0:12:15 We could do a lot more than we couldn’t do before.
0:12:17 So we just assumed we’ll put computers in the front office.
0:12:21 We’re going to get the same benefit and we didn’t.
0:12:23 And people call this within the sort of tech critical economic circle of productivity paradox.
0:12:28 We didn’t see that rise in productivity.
0:12:31 And I think it’s for all of these reasons that you’re talking about.
0:12:34 I think part of the problem is in the back office IT revolution,
0:12:38 this wasn’t a cybernetic setup.
0:12:40 It’s not people working directly with the machines together.
0:12:43 It was much more just a pure digital play.
0:12:46 Our information is in a database now instead of in filing cabinets.
0:12:50 We could network these two systems so we don’t have to mail stuff across the country
0:12:53 or fax stuff across the country.
0:12:55 But in the front office, you have a human brain interacting with these machines.
0:12:59 And I think the productivity software revolution
0:13:01 did not factor in the reality of how human brains actually operate.
0:13:05 I think that revolution was using a computer processor metaphor
0:13:10 when thinking about productivity.
0:13:11 So if you’re designing a computer processor, what are the things that matter?
0:13:15 A, you got to keep the instruction pipeline full, right?
0:13:17 There’s this view in computer processor design.
0:13:20 You do not want idle cycles.
0:13:22 If the processor main circuitry has to sit there while you go and retrieve some data,
0:13:26 that is a disaster.
0:13:27 So you want to fill this pipeline predictively with the stuff you’re going to need.
0:13:31 And then speed matters.
0:13:32 How fast can we do things?
0:13:33 So what do we get in productivity software?
0:13:36 We want to make sure that it’s as quick and low friction as possible
0:13:40 to send stuff to people to get stuff so that you can always have things to work on.
0:13:44 And we want the task to go as quick as possible.
0:13:46 My word processor, I can type faster.
0:13:48 I can auto complete.
0:13:49 I can have software help me speed up.
0:13:52 But what it didn’t take into account, for example,
0:13:54 is that the human brain takes a long time to switch from one thing to another.
0:13:57 It’s not a processor circuitry.
0:14:00 So trying to have a huge pipeline of a bunch of things to jump back and forth between,
0:14:03 the human brain can’t do that.
0:14:05 It gets exhausted.
0:14:06 It crosses the circuits.
0:14:07 We lose our ability to concentrate.
0:14:09 We can’t work on this other thing if these other things are distracting us.
0:14:12 So I think this fundamental mismatch between the wetwear between our ears
0:14:16 and the digital tools that we’re looking at with our eyes,
0:14:19 that fundamental mismatch really created a productivity disaster in the front office.
0:14:23 It makes complete sense to me.
0:14:25 One of the things that you said in the book is you said time and space are needed to craft
0:14:30 important things.
0:14:31 Why is that?
0:14:33 The human brain, it takes a while to focus on something.
0:14:37 And this is because of cognitive processes.
0:14:39 We have to inhibit unrelated semantic neural networks.
0:14:43 We have to excite networks that are relevant.
0:14:45 That’s why it takes 15 or 20 minutes,
0:14:47 even to just feel like you can make progress on something hard.
0:14:50 That first 15 to 20 minutes is I can’t do this.
0:14:53 And then after 15 or 20 minutes, okay, I’m getting into a run.
0:14:56 That’s because the brain takes a while to focus.
0:14:58 So things need time.
0:14:59 Also, quality just requires often that we come back to something again and again.
0:15:04 Let’s try it from this angle.
0:15:05 Let’s spend a whole afternoon working on it.
0:15:07 Craft is relatively slow.
0:15:09 The pace of most modern knowledge work is not.
0:15:12 It’s very fast and staccato.
0:15:14 Yeah, you said focus.
0:15:15 It takes some time to get into it.
0:15:17 I have this feeling that if I’m presented with a window of time,
0:15:21 and I know I have a big task to go after,
0:15:24 I look at my calendar and I’m like, okay, I have 30 minutes.
0:15:26 It’s a big task.
0:15:27 It’s definitely going to take a few hours.
0:15:29 I almost don’t even want to get started.
0:15:31 Because I know there’s that ramp up just to even get in the zone.
0:15:35 Then you get five minutes of actual work done,
0:15:38 and then you’re kind of right back into something else.
0:15:41 And especially given someone like me that has,
0:15:43 my wife will definitely tell you that I have ADHD based on our interactions.
0:15:48 But someone that has that brain, it is especially hard to do that switching.
0:15:52 Are there people that are inherently good at task switching and multitasking?
0:15:57 Or is that just complete BS?
0:15:58 And we fool ourselves into thinking we’re good at it.
0:16:01 We fool ourselves.
0:16:02 It’s like asking are any people good at breathing underwater?
0:16:05 No, the human body can’t do that.
0:16:07 The human brain, we know how long network switching takes.
0:16:11 It can’t do it instantaneously.
0:16:14 So I think the people who think they’re good at it,
0:16:16 often what they’ve done is just made peace with the physiological subjective feeling
0:16:21 of my brain is muddled and exhausted,
0:16:23 and I never actually get in the full cognitive context.
0:16:26 They’re just used to doing things basically at a mediocre level.
0:16:30 But a human brain is a human brain.
0:16:31 You need 10, 15, up to 20 minutes to really lock on to something hard.
0:16:35 So if you’re checking an email inbox or a Slack channel once every four or five minutes,
0:16:39 you are nowhere near your actual full cognitive capacity.
0:16:43 You are handicapping your brain in a severe way.
0:16:46 You don’t even realize that you’re doing it.
0:16:48 Yeah.
0:16:49 All right.
0:16:51 If you watch this show or you’ve seen me on The Random Show with Tim Ferriss,
0:16:55 you know I love to talk about all things finance.
0:16:57 I’m always looking for better ways to be smarter about this.
0:17:00 One crucial thing that I’ve learned along the way
0:17:02 is that you absolutely don’t want anything that chips away at your returns.
0:17:05 Like the percentages that many certified financial planners take when you work with them.
0:17:10 They oftentimes take a percentage of your net worth.
0:17:12 You don’t realize how much this adds up.
0:17:14 Over the years, it could be thousands and thousands of dollars extracted directly from your wallet.
0:17:20 Do not do this.
0:17:20 If you hear nothing else from this, please do not let them take a percentage of your assets.
0:17:25 That’s why I love my sponsor for today’s episode, Facet.
0:17:28 Facet is cool because they don’t charge you a percentage.
0:17:31 They just have this affordable membership fee that gives you access
0:17:34 to a team of certified financial planners.
0:17:37 They also help with retirement planning, tax strategy, estate planning, and more.
0:17:41 Facet is building the future of financial planning,
0:17:43 making professional high quality financial advice accessible to the masses.
0:17:48 Not just the rich.
0:17:49 You don’t need some crazy minimum to work with them.
0:17:51 And here’s the coolest thing.
0:17:52 There are no product sales.
0:17:54 No one’s trying to sell you anything.
0:17:56 Once you’re in the family, there’s no commissions.
0:17:58 There’s no conflicts.
0:18:00 It’s always a CFP professional, always a fiduciary.
0:18:04 And it’s just, again, an affordable membership fee that doesn’t eat away at your gains.
0:18:08 For listeners of this show, Facet is waiving their $250 enrollment fee
0:18:12 for new annual members for a limited time.
0:18:15 You have to head on over to facet.com.
0:18:17 That’s F-A-C-E-T dot com slash Kevin Rose.
0:18:22 Please use that URL.
0:18:23 It really helps out the show.
0:18:25 All right.
0:18:26 Just a quick plug for my newsletter.
0:18:28 I really don’t like email.
0:18:30 And so for me, a newsletter is only once a month.
0:18:33 I cannot send you any more emails than that.
0:18:35 It would drive me crazy if I was on the receiving side of that.
0:18:38 So my once a month newsletter is just packed with high quality information.
0:18:42 This is all the products that I’m checking out.
0:18:45 Other great clips and YouTube videos that I’m finding across the web.
0:18:49 Oftentimes I have friends that are launching new products.
0:18:51 So I’ll have early beta access to those types of things.
0:18:54 Some of the books that I’m reading, some of my favorite podcast clips,
0:18:57 movies, you can sign up for this over at KevinRose.com.
0:19:01 Join 115,000 other readers.
0:19:03 KevinRose.com.
0:19:04 You’ll find the little newsletter link there and sign up today.
0:19:07 I would say one of the things we’ve been pushing to doing a lot over the last,
0:19:10 call it 10, 15 years is this hunt for the ultimate productivity tool.
0:19:16 There’s been this hunt.
0:19:17 Oh, this will be the solution for me.
0:19:19 I saw that you mentioned, was it 43 folders?
0:19:21 Is that right?
0:19:21 I always forget the name of that.
0:19:23 That’s right.
0:19:23 Yeah, yeah, Merlin Man, right?
0:19:24 Yep.
0:19:25 Yeah, so Merlin, he was such a legendary figure back in the day because he was
0:19:30 a very early kind of productivity blogger and had the great system.
0:19:34 It was the GTD, Getting Things Done system.
0:19:36 And I tried it for a hot minute and then I was just like, this is too much.
0:19:41 I fell away.
0:19:42 And since then, I’ve tried like 15 different productivity systems.
0:19:46 And it earned a connective backlink note taking apps.
0:19:49 You know, you name it, but every three to four months,
0:19:52 I’m just like enough.
0:19:54 It’s too much.
0:19:55 It’s too much.
0:19:56 Do you have any sense why that is?
0:19:58 Why these things don’t stick?
0:19:59 Merlin, first of all, he’s an interesting guy.
0:20:02 I profiled him actually for the New Yorker a few years ago.
0:20:05 I wrote this piece called The Rise and Fall of Getting Things Done
0:20:09 because what’s interesting about Merlin’s story,
0:20:11 it’s exactly what you’re talking about.
0:20:13 He gets overwhelmed in work.
0:20:14 This is like early 2000s tech sector,
0:20:17 which again, is exactly when the front office IT revolution began
0:20:20 making knowledge work intolerable, right?
0:20:23 This happens in the early 2000s.
0:20:25 He finds GTD.
0:20:26 He thinks this is going to save him.
0:20:28 He starts this blog 43 folders, which is a GTT reference to the tickler file.
0:20:33 This gets really popular.
0:20:35 Oh, it was massive back then.
0:20:37 Massively popular.
0:20:38 He gets a book deal actually to write about this.
0:20:40 And he gets completely disillusioned because he eventually realizes
0:20:44 that this incredibly complex system is not making his working life easier
0:20:49 and actually is never going to get him where he wants to get,
0:20:52 which is like creating stuff that matters.
0:20:53 And so it’s this big, essentially drama where he has to give back the book advance.
0:20:58 He gives up on writing the book.
0:21:00 He shutters 43 folders.
0:21:02 It is like, I can’t do this anymore.
0:21:03 And he leaves that whole world, which became known as productivity prawn,
0:21:08 Leedspeak, but PR zero in that whole world was called productivity prawn.
0:21:13 And the basic idea there was the right tool,
0:21:16 the complex enough smart enough tool could bring you to a productivity utopia.
0:21:20 But if you just had the right tool to organize all your information and work,
0:21:24 you could get something that was essentially effortless.
0:21:26 Like the tool is like telling you what to do and giving you the right information.
0:21:31 This is the whole dream right now.
0:21:32 I think these Zettelkasten systems are the new hot thing.
0:21:35 And there’s this whole dream of you’re not going to have to think hard.
0:21:38 Your system, you offload all your information into a system and you link it up.
0:21:42 And you’re just going to surface these brilliant ideas like the system’s going to do the work for you.
0:21:46 This has never really worked.
0:21:48 It’s never really worked.
0:21:49 But the reason why this has never worked is it’s just not how production happens of good stuff.
0:21:54 Like ultimately, there is this really hard step of trying to create ex nihilo value where
0:21:59 there was not before, which takes suffering and concentration and complexity and hard work.
0:22:04 And it’s frustrating.
0:22:05 And that’s ultimately what work comes down to and no system can make that easy.
0:22:09 Do you think there is a world where AI gets involved in the next, call it three to five years?
0:22:16 And it’s not about the perfect tool, quote unquote, but it’s more about us just dumping
0:22:21 all available information and asking questions of that data that will unlock
0:22:25 something new that we haven’t seen before?
0:22:29 I think AI could play a big role here.
0:22:31 It’s going to be beyond the peer language model play.
0:22:34 So I think what that vision you’re thinking about, which is really big right now in the sense of
0:22:39 we can have the sort of interrogatory relationship to data fueled by a language model.
0:22:43 We can ask questions about our information and the language model can find structure
0:22:47 and give us answers.
0:22:48 That’ll be a minor part at best, I think, at the potential productivity impact of AI.
0:22:53 For me, I think where AI could have a huge impact on knowledge work is actually being able to
0:22:58 take over these administrative overhead tasks that are currently the sort of
0:23:03 productivity kudzu that’s making it impossible for us to get things done.
0:23:07 The big problem with our current moment, each of these things we’re working on
0:23:10 generates its own administrative overhead, emails, meetings, like the stuff you need to
0:23:15 sort of just keep the project going.
0:23:17 That stuff piles up, that administrative overhead piles up and that’s why our days get
0:23:21 fragmented with emails and meetings and we can’t get to the actual work.
0:23:25 If AI could take over more of that administrative overhead, not make the task faster,
0:23:31 which is the current play.
0:23:32 All right, I have to send this email, but maybe AI will help me write a draft of this email
0:23:37 or help me find the information from my information system I need for this email,
0:23:41 not make it faster.
0:23:42 Because again, it’s the interruptions I care about, not the duration of the tasks,
0:23:46 but actually take over these tasks, actually send and answer the emails for you,
0:23:50 get the information so you don’t need a meeting.
0:23:53 That’s interesting to me, but that’s not going to be a language model by itself.
0:23:56 I think that play is going to be language models plus other types of models.
0:24:00 The tech media right now is a little bit too short-sighted thinking that just
0:24:03 prompt engineering for GPT-4 is the future of how AI is going to be interacting in our life.
0:24:08 The future I’m interested in is going to be multifunctional models.
0:24:12 Then some interesting stuff could happen.
0:24:13 Yeah, that feels right to me because if you’re just increasing output,
0:24:18 you’re just causing more of the same problem.
0:24:20 If you’re just making it more efficient to send emails,
0:24:23 now I’m dumping more emails on other people that might have inferior productivity
0:24:27 tools and aren’t using AI yet, and it’s loading up on their side,
0:24:31 you’re still adding to the issue versus a world where AI discovers that someone is
0:24:36 requesting a meeting two bots negotiate a time, and it’s automatically done,
0:24:41 and you just don’t even have to think about it, right?
0:24:43 Yeah, I had that conversation years ago with the CEO of x.ai,
0:24:47 which was like a very early player in the AI-facilitated meeting scheduling,
0:24:52 and this was before language models got big and kind of ate this world.
0:24:56 They had this product where you could CC an email address,
0:24:59 and it was an AI agent that could help you set up your meetings,
0:25:02 and it was supposed to process to natural language.
0:25:04 I still remember this, the CEO saying, “Oh, that’s not the end game.”
0:25:08 Like the end game is where my AI agent just talks directly to your AI agent
0:25:13 and sets up that meeting without us having to send the email in the first place.
0:25:16 Yeah, I agree with you.
0:25:17 I think that’s where interesting things begin to happen,
0:25:20 but it’s a really hard technical problem.
0:25:22 I’ve been writing about this recently.
0:25:23 It’s not a problem you can solve by making language models larger
0:25:27 or by having more reinforcement-based fine-tuning.
0:25:30 It’s not a problem you can solve by having bigger training data sets for language models.
0:25:34 It requires new models.
0:25:36 I think that’s where the interesting stuff’s going to happen.
0:25:38 Yeah, but there’s also just so much nuance there
0:25:40 that is almost impossible for AI to capture.
0:25:43 For example, before we got started on this call here,
0:25:46 you were having issues with your camera.
0:25:47 That might push off your next meeting by 15 minutes.
0:25:49 How is AI going to be able to know,
0:25:51 “Oh, Kevin’s really tired today because his daughter’s sick at home
0:25:54 and he had to stay up late last night.”
0:25:56 There’s a thousand things that if you had an EA
0:25:59 or someone else that you’re working with to help you book your things,
0:26:00 you have these conversations.
0:26:02 Not to say you couldn’t have that with AI,
0:26:04 but it is a more challenging problem than just two bots hashing out of time.
0:26:09 Oh yeah, here’s the storyline about that that’s interesting to me.
0:26:12 To me, this is the most interesting storyline of the most.
0:26:15 One of the most interesting storylines in AI,
0:26:17 and it’s not being talked about that much,
0:26:19 and this is what Noam Brown has been up to.
0:26:21 So Noam Brown, who was at Meta, got hired away by open AI.
0:26:25 I wrote this big article a couple of months ago for the New Yorker about this,
0:26:28 and I don’t think it’s being talked about enough.
0:26:30 What Noam did, what brought him to fame in the AI world
0:26:35 is that he created the first AI system
0:26:37 that could win against professional poker players
0:26:40 in no limit, Texas hold them.
0:26:42 So he built a system that could do this, Pluribus.
0:26:45 What was important about this system is that poker,
0:26:48 the chips and the cards are part of what matters,
0:26:52 but equally important is what the other people believe,
0:26:55 which is different than chess or go.
0:26:57 Poker is really a game about not what cards do I have,
0:27:00 but what do you believe I have.
0:27:01 That’s what I’m playing, right?
0:27:03 So he began working on it.
0:27:05 The bluffing aspect of it.
0:27:06 The bluffing aspect, and the value aspect even.
0:27:08 So he built this engine that was really simulation based,
0:27:12 but it was simulating potential mental states of the other players.
0:27:16 Okay.
0:27:17 Wow.
0:27:18 So then he goes to meta and they say,
0:27:20 okay, we’re going to take on a harder challenge,
0:27:22 socially speaking, which is the game diplomacy.
0:27:24 And I don’t know if you know diplomacy,
0:27:26 but like the way that game works is it’s like risk,
0:27:29 except the key to diplomacy is at the beginning of every round,
0:27:33 you have private one-on-one conversations
0:27:35 with every other player.
0:27:36 And it’s all about these subtle alliances and betrayals,
0:27:40 and you double cross and double cross,
0:27:42 and you tell the one player,
0:27:44 I’m going to pretend to have an alliance with Kevin.
0:27:46 And that’s going to get his positions out of place
0:27:48 in Scandinavia.
0:27:49 And then the next round, you can come and we’ll really be a team,
0:27:52 and we can take over that territory.
0:27:53 It’s all a game about negotiation between people.
0:27:56 They built a bot Cicero that started beating human players
0:28:00 on a web-based diplomacy server.
0:28:02 That’s so cool.
0:28:03 And here’s how they did it, is they had a language model,
0:28:07 not some super fancy GPT-clawed model.
0:28:10 It was just Bert, one of the off-the-shelf research models
0:28:13 with a couple billion parameters.
0:28:15 They had a language model, and then they had a planning engine
0:28:18 that, based on what he learned from poker,
0:28:22 was simulating the potential mindsets of the other player.
0:28:25 And well, wait a second, what if this person’s lying to me?
0:28:27 Then what would the implication be if I did this?
0:28:30 Would it make sense if they were lying to me?
0:28:31 Would that be good for them?
0:28:32 So they had a simulation engine that could simulate
0:28:35 the minds of the other players and try to figure out,
0:28:37 given the different possibilities, what’s the best play?
0:28:40 And then they had a language model talk to the players.
0:28:42 So the language model could take what the players were saying
0:28:45 and translate it into a sort of XML type format
0:28:48 that the planning model could understand.
0:28:50 The planning model could then tell the language model,
0:28:52 here’s what we need to do.
0:28:53 We need to get an alliance with this person,
0:28:55 put that into diplomacy speak in a way that they’ll agree.
0:28:59 And the language model talked on behalf.
0:29:01 Those two things put together could win at diplomacy.
0:29:04 I think email is like winning at diplomacy.
0:29:06 I have to simulate the other minds of the other people involved
0:29:09 and what do they need here.
0:29:11 And if I’d say this,
0:29:12 how’s that going to mess up the later part of the plan?
0:29:14 And then once you figure out the right thing to do,
0:29:16 then you can have a language model say that nicely
0:29:18 and professionally and in a way that’s not going to annoy people.
0:29:21 That to me is the interesting play.
0:29:22 And I think that’s why it’s so critical
0:29:24 that OpenAI hired Noam Brown away.
0:29:27 He’s probably the head of Q*.
0:29:28 They’re pretty secretive about this,
0:29:30 but Q* is almost certainly OpenAI’s initiative
0:29:33 to introduce more planning into their products.
0:29:36 So this I think is the future of when AI starts to get interesting
0:29:39 in the knowledge workspace.
0:29:41 Yeah, that is absolutely fascinating.
0:29:43 It’s scary on so many levels because five years from now,
0:29:47 not this cycle, but next election cycle in the United States,
0:29:49 you have to imagine that given everything that you just said
0:29:53 about the diplomacy side of things,
0:29:56 there’s going to be some bot that will be able to have conversations
0:29:59 and simulate your responses to certain things
0:30:01 and try and convince you or sway you in certain beliefs.
0:30:05 Yes.
0:30:05 Right.
0:30:06 That’s just insanity and probably be pretty damn good at it too.
0:30:09 Yeah, one of the examples I give is
0:30:12 if you think about HAL 9000 from 2001,
0:30:16 and it won’t open the pod bay doors
0:30:18 because it doesn’t want Dave to deactivate it
0:30:20 because it’s focused on his mission, like classic scary AI.
0:30:23 GPT can never do that because it can’t simulate the future,
0:30:27 but a Cicero could.
0:30:29 Like for HAL 9000 to know not to open the pod bay doors
0:30:32 is because he’s simulating.
0:30:33 Well, what would happen if I open the pod bay doors?
0:30:36 Why might Dave want me to open the pod bay doors?
0:30:38 Oh, he might want to turn me off and he would get access to my chips.
0:30:42 Okay, I don’t want to do that.
0:30:43 It’s the planning stuff.
0:30:44 I think the future of AI is,
0:30:48 first of all, language models are going to severely contract.
0:30:51 I think this notion of let’s try to have
0:30:54 emergent reasoning capabilities as a side effect
0:30:57 of making language models massive
0:30:59 is an incredibly inefficient way of trying to do that.
0:31:02 Let’s let language models do language,
0:31:04 and then you build explicit reasoning models
0:31:07 to do the reasoning you want to do.
0:31:10 No one Brown found this with poker.
0:31:12 They tried to build a huge neural network
0:31:14 to just learn poker and figure out how to play.
0:31:16 It was huge and they needed supercomputers to run it.
0:31:19 And then when they had an explicit planning engine,
0:31:21 they were able to just contract the neural network part
0:31:24 to something that could run on their laptop.
0:31:25 Like it’s an incredibly inefficient to try to implicitly
0:31:29 learn reasoning emergently in a feedforward neural network.
0:31:32 Explicit planning models plus language emergent language
0:31:36 recognition and generation ability.
0:31:37 I think this is what the future is going to look like.
0:31:40 Interesting.
0:31:40 Is that more just siloed models at that point?
0:31:44 Like individual models that are quite good at one thing?
0:31:47 Yes.
0:31:48 We need language models to be good at understanding language,
0:31:50 translating it into a format that other siloed models understand,
0:31:55 and then taking what those other siloed models come up with
0:31:58 and turning it back into whatever appropriate language
0:32:01 we need to talk to people.
0:32:03 I think that’s a much more efficient future.
0:32:05 Yeah.
0:32:06 I also think it’s a better way of dealing with a lot of trust
0:32:09 and AI issues.
0:32:11 Yes.
0:32:11 I’m a big believer.
0:32:12 I call it intentional AI, like little I, capital A,
0:32:15 capital I.
0:32:16 Intentional AI, if you have an explicit reasoning model
0:32:19 to do this and an explicit other model to do this,
0:32:22 there’s no XAI problem.
0:32:24 I program this reasoning model.
0:32:26 I can tell you how it thinks about things
0:32:29 and separating that from the amorphous hard-to-understand logic
0:32:33 of recognizing and generating language,
0:32:35 I think it makes it much easier.
0:32:36 So it’s no longer this guessing game of, I don’t know,
0:32:38 we fine-tuned a trillion-parameter language model
0:32:41 and I don’t know what’s going to happen.
0:32:43 They don’t have this problem with Cicero.
0:32:46 They hand-coded the engine that makes decisions.
0:32:48 Like they taught it, for example, we’re not going to lie.
0:32:51 So when Cicero plays diplomacy, it plays a clean version
0:32:54 where it doesn’t do deception.
0:32:56 It understands the other players might be able to do it.
0:32:58 It doesn’t do deception.
0:32:59 They could just make that choice
0:33:00 because they had an explicit engine
0:33:03 for actually doing the simulation of game strategy.
0:33:06 So I don’t think that all of AI needs to be as black box
0:33:10 or obfuscated as it is in language models.
0:33:12 And as we separate out different reasoning
0:33:14 in the different models,
0:33:15 we can actually be accountable for what we’re programming.
0:33:18 And I think that’s going to be maybe the future.
0:33:20 IAI might be the way forward to more trust in AI.
0:33:23 That feels right to me because at that point,
0:33:26 I think of it as almost like a choose your own adventure.
0:33:28 I’m already seeing this, like with ChatGPT,
0:33:30 I can go and enable very specific models
0:33:33 that are just for medical research.
0:33:35 There’s one consensus that’s quite good.
0:33:37 It cross all the papers.
0:33:38 It has a better understanding than ChatGPT.
0:33:40 And when I enable that, GPT hands that off to that model.
0:33:44 And I get back better results that has a deeper corpus
0:33:48 of peer-reviewed documents that I can look through.
0:33:50 It’s almost like the app structure
0:33:52 in that you have like on iPhone,
0:33:53 where you have all these different siloed experts
0:33:56 and you pull them together and you can say,
0:33:58 “Hey, if I got a comment about,
0:34:00 I call it the bad Thanksgiving conversations,
0:34:02 which are politics and religion,
0:34:04 if I get something bad back from my AI,
0:34:06 it’s because I enabled a certain module
0:34:08 to give me that information back.”
0:34:10 There’s certain things that I think that we just need to say,
0:34:12 it’s always going to have some bias if you go broad.
0:34:15 And so let’s go niche.
0:34:17 And if you want to be able to pick
0:34:19 and choose your political adventure
0:34:21 and have that incorporated in your AI,
0:34:23 so be it, but it’s on your own watch,
0:34:25 not the fact that we try to solve all of world’s problems
0:34:29 with one generalized intelligence, if that makes sense.
0:34:32 I think that completely makes sense.
0:34:33 I think what we’re seeing in the research community
0:34:36 is the number of parameters you need to understand English grammar,
0:34:40 to understand what people are saying,
0:34:42 and to generate reasonable text back.
0:34:44 It’s tens of billions at most.
0:34:47 Tens of billions of parameters,
0:34:48 plus the specialty, whatever it is,
0:34:51 niche information, medical information,
0:34:53 whatever that you want a niche model to learn,
0:34:55 is very effective.
0:34:56 So I can now, if I have enough data about the niche topic,
0:35:00 the 20 billion of parameters dedicated to language
0:35:02 means I can answer questions about it or talk about it.
0:35:06 But I think there’s a bigger issue here as well.
0:35:08 I had this discussion,
0:35:09 I think it was with Scott Galloway on his podcast,
0:35:12 where I think we’re a little bit too fixated right now
0:35:15 on the current interface we have
0:35:17 with something like ChatGPT or Claude,
0:35:19 this idea that we send prompts through a text interface
0:35:22 and sort of stuff comes back.
0:35:24 To me, that’s very preliminary.
0:35:27 All of the concern we have right now about,
0:35:29 is the text coming back when I have chats
0:35:32 with a language bot politically appropriate?
0:35:35 I think that’s gonna look like in two years,
0:35:37 what a weird diversion.
0:35:39 Our concern was that this digital chat partner
0:35:43 is inappropriate.
0:35:45 Like, who cares in some sense?
0:35:47 It’s not like these chats have some sort of decision function,
0:35:50 that these chats we’re having through these text interfaces
0:35:53 are the basis on which loans are being distributed or whatever.
0:35:57 Let me forget, ChatGPT was a demo.
0:35:59 It was invented as a demo to show the possibilities
0:36:02 for the underlying language model.
0:36:04 This idea of these chat interfaces,
0:36:05 that’s not the future of these models.
0:36:07 These models are gonna be much more integrated
0:36:09 into other types of systems.
0:36:11 They’re gonna be much more specialized.
0:36:13 Their use will be much more specialized.
0:36:15 I told Scott, for example,
0:36:16 I don’t think it matters that you learned
0:36:18 how to do prompt engineering.
0:36:19 Doing prompt engineering today is like
0:36:21 in the early days of Apple too,
0:36:22 where they’re like, you have to learn basic,
0:36:24 or you’re never gonna get any functionality out of your computer.
0:36:26 It’s like, no, the computer evolved,
0:36:28 or you didn’t have to write your own programs anymore.
0:36:30 I think we haven’t seen yet the forms
0:36:32 in which this type of AI, generative AI, is gonna be used.
0:36:35 But it’s not gonna be, almost certainly not gonna be just us,
0:36:38 just talking through a chat interface.
0:36:40 It’s gonna be integrated into systems.
0:36:43 Something else will be prompting it on your behalf.
0:36:45 And I think where it’s a little narrow right now,
0:36:47 that the fact that a company like Google,
0:36:50 their stock price can take a huge hit
0:36:52 because of the complexities of trying to make sure
0:36:54 that this chat demo is the things it says is appropriate.
0:36:58 Conversations over Instant Messenger with robots
0:37:02 is not the end game here.
0:37:03 It’s this intelligence being integrated
0:37:05 into other things we’re already doing.
0:37:06 Yeah, I think it’s because people just want to believe
0:37:10 it’s becoming sentient and they want to know
0:37:12 which way it’s politically leaning
0:37:13 and all of this other stuff.
0:37:14 It is a huge distraction.
0:37:16 And I agree with you on the prompt engineering side.
0:37:19 I was having a conversation with a buddy of mine
0:37:20 that is creating a startup about helping people
0:37:23 create better graphics and abstracting away
0:37:26 the difficult prompting of creating
0:37:28 high quality graphics outputs with AI.
0:37:31 And one of the things that you have to look at
0:37:34 is when you’re doing prompt engineering now,
0:37:35 it’s a series of keywords that you have to learn the code.
0:37:38 Like you said, it’s like learning a programming language.
0:37:41 And the future, and it has to be less than five years out,
0:37:45 it’s gonna be looking at an image and saying,
0:37:46 I like what you did there,
0:37:48 but that arm looks a little bit weird.
0:37:50 Can you twist it a tiny bit?
0:37:51 Call it like 10 to 15 degrees and give me a new output.
0:37:54 That will be what you say to it.
0:37:56 Not like arm, 1960s, all the things that you do
0:38:00 that are so weird and just keywordy,
0:38:03 it’s gonna be a lot more natural language,
0:38:04 I think, in the future.
0:38:05 And a dialogue back and forth versus structured text
0:38:09 that you have to learn.
0:38:10 But anyway, I want to get back to the book.
0:38:11 This is fun going down the A.I. route.
0:38:13 I could do this for another few hours,
0:38:15 but just getting back to the theme of productivity
0:38:17 a little bit, you talk about three things.
0:38:19 And I might not get these exactly right
0:38:20 ’cause these are off the top of my head,
0:38:22 but it’s three things that you’re talking about
0:38:24 and promoting in this book, or do fewer things,
0:38:27 work at a natural pace, and then obsess over quality.
0:38:31 And I’d love for you to just touch on those three things.
0:38:34 And then also, that feels very old school Japanese to me.
0:38:39 It seems like we’re going back to a time of slowness,
0:38:43 which I love, and like quality over quantity.
0:38:46 And that’s really fascinating.
0:38:48 How did you come up with those three main points for the book?
0:38:51 What I did is I went back and I looked for figures to study
0:38:56 who were knowledge workers in the technical sense
0:38:58 that they used their brain to add value to information.
0:39:00 But I looked for people from times past or from professions
0:39:03 that were very distant from office jobs in the 21st century.
0:39:07 ‘Cause I didn’t want to get stuck in the uncanny valley of,
0:39:10 well, this job is almost like mine,
0:39:12 but it differs in this way, so this doesn’t apply.
0:39:14 Then I tried to isolate principles
0:39:16 from these traditional knowledge workers
0:39:18 and then adapt them to the office jobs in 21st century.
0:39:20 So I was studying the whole scope,
0:39:22 sort of the whole sweep of the human adventure
0:39:25 of creating things with their brains.
0:39:26 Those three principles came up.
0:39:29 All three of those principles are pretty adaptable
0:39:32 to 21st century office work.
0:39:34 So do fewer things.
0:39:35 Like how does that adapt to 21st century office work?
0:39:38 It comes back to this administrative overhead problem
0:39:40 I was talking about.
0:39:42 We say yes to too many things in modern work.
0:39:44 So the administrative overhead aggregates
0:39:46 past a threshold in which we really can’t get anything good done.
0:39:49 It’s exhausting, it’s deranging,
0:39:51 all days in Zoom, nothing gets done.
0:39:53 The clear solution there is don’t work on so many things
0:39:56 at the same time.
0:39:58 Because you’re trying to minimize the administrative overhead
0:40:01 you’re dealing with at once.
0:40:03 So if you work at less things at once,
0:40:04 the overall rate at which things are finishing
0:40:07 actually goes up.
0:40:08 And did you say like one big thing per day?
0:40:10 Is that kind of accurate about what you recommend
0:40:12 or how do you think about what to work on every day?
0:40:15 I worry more in this part as well
0:40:17 about how many things you’re just actively working on.
0:40:19 Whether or not you want to work on it in a given day or not,
0:40:22 the things you’re actively work on generate overhead.
0:40:25 If I have agreed to work on 10 projects
0:40:27 and I’m actively working on 10 projects,
0:40:30 whether I want to or not, each day those 10 projects
0:40:33 are generating emails that need answers.
0:40:35 Those 10 projects have stakeholders that are saying,
0:40:36 hey, when can we jump on a call or get on a Zoom
0:40:39 like to see how things are going.
0:40:40 10 projects worth of that overhead hijacks your day.
0:40:44 I can’t get anything else done except talk about these projects.
0:40:47 If you instead just work on two of those projects at a time,
0:40:50 if you only have two projects worth of emails,
0:40:52 two projects worth of meetings,
0:40:53 you can really get through these projects.
0:40:56 I can actually put a lot of time into these things
0:40:58 and do them well.
0:40:58 And then I take two more and then I take two more,
0:41:00 you’ll get through those 10 in a shorter total amount of time.
0:41:04 So doing fewer things is really about concurrency.
0:41:08 Then there’s two really tricky things here
0:41:12 that I wanted to touch on
0:41:14 that I think you were so brilliant to call out.
0:41:16 And I think they were very important to share
0:41:18 with the listeners here.
0:41:20 So when you talk about concurrency
0:41:21 and you talk about how many things that you take on
0:41:24 in a given period of time,
0:41:25 we do say yes to a lot of things.
0:41:27 And you talk about this idea that you want to have,
0:41:32 and I’m paraphrasing here,
0:41:33 but transparency around your workload.
0:41:35 So if you are seen as someone
0:41:38 that actually manages their time well,
0:41:40 then people will actually respect your time more.
0:41:44 And that actually means you can take on less.
0:41:47 Am I getting that right?
0:41:48 Or can you explain it the way you wrote it in the book?
0:41:50 No, you’re basically right there.
0:41:52 Because if you deconstruct,
0:41:55 what people are worried about
0:41:56 is that their boss wants them to do things right away.
0:41:58 And that’s their concern.
0:42:00 So I’ll never get away with doing fewer things.
0:42:02 Or the way I talk about in the book
0:42:03 is you don’t even have to say no more often,
0:42:06 but just differentiate between
0:42:08 these are what I’m actively working on,
0:42:10 and these are things I’ve agreed to,
0:42:11 but I’m waiting to work on.
0:42:13 So I don’t do emails or meetings about the stuff
0:42:15 I’m waiting to work on,
0:42:16 but I’ll let you know when I’m actively working about it.
0:42:18 People worry, like, no, no,
0:42:19 my boss just wants me to do things right away
0:42:21 whenever they have an idea.
0:42:22 But if you deconstruct that,
0:42:23 what’s really going on here
0:42:26 is that the problem you’re solving for your boss
0:42:28 is you’re trying to minimize their stress.
0:42:30 So something comes into their world that needs to get done.
0:42:32 It’s an open loop.
0:42:33 It’s a source of stress in their life
0:42:35 until that gets taken care of.
0:42:37 If they don’t know how you work,
0:42:38 you’re just like this black box
0:42:40 that they email and you do things
0:42:41 and sometimes you forget things.
0:42:43 Just telling you to do this thing
0:42:44 doesn’t relieve their stress.
0:42:46 Until you finish this,
0:42:48 I have to keep track of this.
0:42:49 And so they’d rather you just do it as soon as possible
0:42:51 because the problem you’re solving
0:42:53 is getting rid of this stress.
0:42:54 If they see instead,
0:42:56 sure, here is my publicly available work queue.
0:42:59 And it’s clearly divided.
0:43:00 These are the things I’m actively working on.
0:43:02 Here’s the sorted list of things I’m waiting to work on.
0:43:05 Every time I finish something I’m actually worked on,
0:43:07 I take the next thing off of the list
0:43:09 and I move it in here.
0:43:10 You can see exactly where your project is in the list.
0:43:12 I will tell you as soon as it crosses over,
0:43:15 the being active, I’ll be like,
0:43:16 “Hey, I’m working on this now.
0:43:17 Call me or email me anytime about this.
0:43:19 I’ll keep you updated.”
0:43:20 You’ve solved their problem a different way.
0:43:23 Great. Cal is going to take care of this.
0:43:24 I don’t have to stress about it.
0:43:26 I have a hundred other things I care about.
0:43:28 In both cases, you’re solving their problem.
0:43:31 Only in one case, you actually have to do the work right away.
0:43:33 And I love that because what you’re doing
0:43:36 from the manager’s point of view,
0:43:37 how the manager is feeling when you say this,
0:43:39 is that they feel like you have your shit together.
0:43:42 They’re like, “Okay, this person is going to track it
0:43:44 and that ball is not going to get dropped.
0:43:46 Yes, it may be two weeks out,
0:43:47 but at least I know they’re tracking it
0:43:50 and they’re going to give me an update
0:43:51 when it crosses into that active list.”
0:43:53 And one of the things that you said in the book
0:43:55 that I thought was brilliant that I’m going to use
0:43:58 is you said, “Okay, you can say to someone that emails you
0:44:02 and says, ‘Hey, I need this done, blah, blah, blah.'”
0:44:03 And it may be another colleague or something.
0:44:05 You can say, “Hey, I have this queue.
0:44:07 I am not yet working on what you just mentioned,
0:44:11 but here are the things that I need from you.
0:44:14 So when the time comes for me to start work on this,
0:44:16 it can be as efficiently done as possible.”
0:44:18 And so you’re actually putting it back on them,
0:44:21 getting all of that payload that you need
0:44:24 to actually be as efficient as possible
0:44:25 when the task does enter your active queue.
0:44:28 And letting them know that, “I take my time seriously.
0:44:30 I manage my time.”
0:44:31 And then everyone is like, “Oh, okay.
0:44:34 This isn’t someone that’s just slacking off.
0:44:37 They have a system.
0:44:38 And if they have a system,
0:44:39 I can trust them to produce high quality work.”
0:44:41 That’s brilliant.
0:44:43 And here’s an even advanced twist on that.
0:44:46 There’s a social dynamic here.
0:44:47 It says, “With a colleague, this will be easier than a boss.”
0:44:50 When they say, “Hey, can you do this for me?”
0:44:51 You have your queue.
0:44:52 You don’t put in the queue.
0:44:53 You say, “Great, I’ve created a document for this project.
0:44:57 I don’t want to rush you.
0:44:58 Whenever you get a chance,
0:44:59 give me the information I need in there.
0:45:00 Once I have all the information I need,
0:45:03 I’ll move this into my queue.”
0:45:04 So it’s not even in your queue.
0:45:07 Because a lot of times what’s happening
0:45:09 is people are playing obligation hot potato.
0:45:11 This thing is on their plate.
0:45:12 It’s a source of stress.
0:45:13 They’re not very organized.
0:45:15 By being like, “Hey, can you do this send?”
0:45:17 They get a temporary relief.
0:45:18 It’s not on their plate anymore.
0:45:19 So this is asymmetry.
0:45:20 It’s very easy to just bounce it over to you
0:45:22 because I’m just trying to reduce my stress in the moment.
0:45:25 But when they say, “Oh, I actually am going to have
0:45:27 to still keep track of this,”
0:45:28 it’s on me to go gather the information
0:45:31 and bring it over there
0:45:31 before I can get this hot potato onto the other plate.
0:45:34 Five times out of 10, they’re just going to let it drop.
0:45:36 They’re like, “I don’t know.
0:45:37 I have too many other things going on.
0:45:39 Maybe it’s not so important.”
0:45:40 And it never gets on your queue in the first place.
0:45:42 So that little twist reduces the incoming by 50%.
0:45:45 That’s amazing.
0:45:47 It’s so funny how when we go on vacation
0:45:50 and we come back and you look at your inbox
0:45:52 and you realize that something’s been sitting there
0:45:54 for a couple of weeks,
0:45:55 how much of it just doesn’t even matter anymore?
0:45:57 You know what I mean?
0:45:58 Like it just somehow gets magically done
0:46:00 or it just didn’t even need to be done.
0:46:02 I do this thing called email bankruptcy every so often
0:46:04 where there’s just so much in my inbox
0:46:06 where I’m like, “I haven’t checked it
0:46:07 and those are three months old.
0:46:09 I’m just going to assume if it’s important again,
0:46:10 they’ll email me.”
0:46:11 Nine times out of 10,
0:46:12 I just never received an email back about it again.
0:46:15 But I like this idea of rather pushing back
0:46:17 and saying I need more information
0:46:18 before it even gets onto my queue, which is huge.
0:46:21 One question, how do we figure out what we can commit to
0:46:27 and if there’s actually enough time
0:46:29 to take on something new?
0:46:30 Something that helps you get a better sense of this
0:46:33 is at least for a while,
0:46:35 trying to advance schedule the time
0:46:37 to work on things you agree to.
0:46:39 Okay, let me just think about this project.
0:46:41 How much time is it going to take?
0:46:42 Let me go find that time on my calendar and protect it.
0:46:46 All right, here’s four hours here.
0:46:47 Here’s two hours here.
0:46:48 I have to find the time for the things I’m going to work on.
0:46:50 You don’t really have to do this perpetually,
0:46:53 but if you do this for a little while,
0:46:55 it really does strengthen
0:46:56 your pattern recognition capabilities
0:46:59 of what is my schedule really like?
0:47:00 How much time is this really going to take?
0:47:03 Do I have that time?
0:47:04 Where is it going to fit in?
0:47:05 So it’s like training.
0:47:06 I want to wait train my pattern recognition
0:47:09 for calendar availability.
0:47:11 So if you try that for six months,
0:47:13 I’m going to put stuff on the calendar
0:47:14 and then I’ll tell the person,
0:47:16 “Yeah, great, I’ll do this for you.
0:47:17 I’ve scheduled it already.
0:47:18 Here’s what I’m working on.
0:47:19 This is the next time I could find the time.”
0:47:21 You tell them exactly when those days are.
0:47:23 When most people try this,
0:47:24 they discover that they’re like three X more optimistic
0:47:26 about their available time than reality.
0:47:28 And things like, “Oh, I could easily fit this in,”
0:47:31 turns out three or four weeks later than I thought
0:47:34 is the next time I have time.
0:47:36 That the workload that I was leaning towards
0:47:38 is reasonable, is probably three times more projects
0:47:40 than I really have room for.
0:47:41 So I think even that exercise is a great bit of training.
0:47:44 Yeah, that’s great.
0:47:46 Can you talk to me about autopilot
0:47:48 and how rituals and location can help us out?
0:47:52 Yeah, autopilot is, work is regular.
0:47:54 I know that we have to file these reports every month
0:47:58 or that the clients need an update
0:48:00 on what happened each week.
0:48:01 If the work is regular, figure out when and where
0:48:04 you’re going to do that work every week.
0:48:05 Take that decision out of your daily scheduling.
0:48:08 It’s just on your calendar.
0:48:09 It’s recurring.
0:48:10 It’s chosen for a really good time
0:48:12 where it’s not in the way like,
0:48:14 “Oh, I always have this hour
0:48:15 between these two standing meetings.
0:48:17 That’s when I’m always going to do this paperwork
0:48:19 and I do it in the conference room
0:48:21 because it’s empty until the next meeting comes.”
0:48:23 So for regularly occurring work,
0:48:25 knowing when and where you do that work
0:48:29 really simplifies things.
0:48:30 And then the other piece here
0:48:31 is like your environment does matter
0:48:33 if you’re doing cognitive work.
0:48:35 If you study professional writers,
0:48:37 this is like a hobby of mine,
0:48:39 where professional writers work,
0:48:41 they almost always, for example,
0:48:42 have a difference between where they do their business
0:48:44 and where they write.
0:48:46 They’ll have really nice home offices
0:48:48 where they send stuff to their agents
0:48:50 and they have to like email with publicity tours
0:48:52 and all the stuff going on,
0:48:53 all the business of being an author.
0:48:55 And then they’ll have a garden shed
0:48:57 where they go to do the actual, right?
0:48:59 Because environment matters.
0:49:00 The cognitive cues, environmental cues matter.
0:49:03 So caring about I do certain types of work
0:49:06 in certain types of places
0:49:07 is just a smart practice
0:49:09 if the work you do involves your brain
0:49:10 because the brain does respond to that.
0:49:13 Yeah, I never thought about using location.
0:49:16 If I’m not a writer,
0:49:18 how might I else apply location
0:49:21 to the things that I do?
0:49:22 What are some other examples of people
0:49:24 using location as part of their workflow?
0:49:26 I think there’s two things
0:49:27 that come up a lot in knowledge work.
0:49:29 One is if you’re working quote unquote from home,
0:49:32 I don’t like that phrase for reasons you’ll see,
0:49:34 but working remotely,
0:49:35 you want if possible for where you work
0:49:37 to not be in your home.
0:49:38 So I don’t like the phrase work from home.
0:49:40 So if it’s just great,
0:49:42 I can now just work at my kitchen table.
0:49:44 You’re trying to work in a cognitive environment
0:49:47 that has all of these salient cues
0:49:49 that have nothing to do with your work.
0:49:50 It’s the thing that you need to fix.
0:49:53 It’s the laundry basket
0:49:54 that reminds you that you have to do laundry.
0:49:56 It’s a minefield of distractions.
0:49:58 I’m a big proponent of what I call work from near home.
0:50:01 It’s the right way to do remote work,
0:50:03 which is it is worth.
0:50:04 It should be subsidized by offices,
0:50:06 but like whatever you can do
0:50:07 to have a space to work that’s not your home
0:50:10 is going to make a really big difference.
0:50:12 And then the other big idea
0:50:13 I’ve really been pushing for
0:50:14 is that in professional workspaces,
0:50:16 there should be two separate places
0:50:18 where deep work is done
0:50:19 and administrative overhead is handled.
0:50:22 It should be physically separate places
0:50:24 if at all possible.
0:50:25 There’s a place where you concentrate and work.
0:50:28 There’s a place where you do emails
0:50:29 and attend meetings.
0:50:31 I think especially in a future
0:50:32 where we have all this commercial real estate
0:50:34 and we don’t need to have permanent offices for everyone,
0:50:36 this is a way to reconfigure it.
0:50:38 Here’s the places you go.
0:50:39 We have a bunch of these computer terminals
0:50:40 you can log into and do email or this or that.
0:50:42 And then here’s the quiet places you go to do deep work.
0:50:44 Separate those two things.
0:50:45 Yeah, I love that.
0:50:47 Do you find that there’s a benefit to walking
0:50:52 and deep work or on the contemplation side?
0:50:54 Where is that best done?
0:50:56 Walking seems to be useful,
0:50:59 especially for ideation or generating a new insight.
0:51:03 We don’t really know exactly why this is,
0:51:05 but there’s speculations
0:51:06 that it has something to do neurologically
0:51:08 with the walking actually quiet certain circuits.
0:51:11 Like so certain circuits get caught up
0:51:14 in the routine rhythmic motion
0:51:15 of what’s happening with the walking,
0:51:17 which actually makes it easier.
0:51:18 The focus with the frontal cortex
0:51:21 on something you’re thinking about.
0:51:22 So like when you’re walking,
0:51:24 it’s easier to manipulate things abstractly in your mind
0:51:26 than if you’re just sitting still and trying to do it.
0:51:29 That’s why we see this, of course,
0:51:31 famous thinkers and philosophers throughout history
0:51:33 have these massive walking habits.
0:51:35 Like that’s where they got their thinking done.
0:51:38 It’s mostly movie based,
0:51:38 but you see like people pacing too.
0:51:40 Just kind of getting around,
0:51:41 hand on the chin, walking around, thinking, pondering.
0:51:45 There’s something about that movement.
0:51:47 I’ve experienced this a few times myself
0:51:49 when these insights,
0:51:51 it doesn’t come from when you’re forced to do something.
0:51:53 It’s like, go be creative.
0:51:55 It’s like telling a comedian,
0:51:56 hey, tell me a funny joke.
0:51:57 It’s no, I can’t do that on command.
0:51:59 I need some space here
0:52:01 to almost let it percolate in the subconscious
0:52:04 before it makes itself known.
0:52:05 This is how I write, for example.
0:52:07 The generation of the ideas,
0:52:09 the structure in which I’m going to present the ideas,
0:52:12 how the pieces fit together,
0:52:13 that’s all on foot.
0:52:13 And then I come in and I sit the focus on my screen
0:52:17 for a separate activity,
0:52:18 which is the craft of writing.
0:52:19 And then that you have to sit for,
0:52:21 because actually to put the final words on paper,
0:52:25 you really need all hands on deck cognitively speaking,
0:52:27 because that’s a very skilled, difficult,
0:52:30 focused task of sentence creation.
0:52:32 You have to spend 20 minutes
0:52:33 to get into that state of focus,
0:52:35 but I can’t come up with ideas that way.
0:52:37 I’m known in my town
0:52:38 as sort of the weird writer, professor guy who,
0:52:40 I just walk and walk like all day long,
0:52:43 because that’s my job in some senses.
0:52:44 I have to come up with the ideas.
0:52:45 That’s the best way to do it.
0:52:47 And it’s also just insanely healthy for you.
0:52:49 Talk about like your mental health
0:52:51 and fitness and everything else.
0:52:52 You should throw on a ruck pack with that
0:52:54 and you’d be good to go.
0:52:55 Get 25 pounds on your back while you’re doing it.
0:52:57 You’re not the first person to tell me that.
0:52:59 I think, yeah, several people,
0:53:01 and they’re all in the West Coast.
0:53:02 I think this is a Silicon Valley thing.
0:53:04 Told me, ruck it.
0:53:06 Have you ever listened to Dr. Peter Tito’s podcast?
0:53:08 He talks about rucking a ton,
0:53:10 and he’s been my physician for a decade.
0:53:13 There’s something really powerful
0:53:14 about getting your heart rate up into that zone two area.
0:53:17 If you can just put on an extra 25 or 35 pounds,
0:53:20 you can get close to that.
0:53:21 It’s actually helped me a ton.
0:53:22 Just like slim my waist up a little bit
0:53:24 and just feel better generally.
0:53:26 And I’m assuming walking with a ruck pack
0:53:28 is different than like running.
0:53:29 Like when you’re running, eventually,
0:53:31 you’re exhausted, you’re short on breath,
0:53:33 and that’s like all your brain goes to that.
0:53:36 And then it’s hard to do anything else.
0:53:37 Like I can’t think when I row or run,
0:53:39 but I assume walking even with that,
0:53:41 because I can think when I hike uphill,
0:53:43 it’s like walking with extra weight.
0:53:44 You get a better benefit, but you can still–
0:53:46 That’s exactly right.
0:53:48 If I’m on the peloton, cranking out
0:53:50 a high-intensity interval training,
0:53:51 there’s no in hell I’m getting anything done.
0:53:53 I’m like, how do I not die from this?
0:53:55 Awesome. So let’s talk about small tasks.
0:53:59 These are the things that are, for me,
0:54:01 it’s death by a thousand cuts.
0:54:03 It’s all these little tiny micro things.
0:54:04 Oh, there’s a doc you signed for here.
0:54:06 It’s got to be signed today.
0:54:07 You’ve got these incoming emails.
0:54:09 This person has a question about this.
0:54:10 How in the hell do we get into a place
0:54:15 where this is something that doesn’t seem
0:54:17 like this horrible distraction
0:54:20 that just rips apart our day, fragments our brain,
0:54:24 and squashes all productivity?
0:54:26 Yeah, I’m surprised that this is not conversation one, two,
0:54:30 and three when we think about running a productive business.
0:54:33 It’s like everything.
0:54:34 These small, urgent distractions
0:54:37 that make it impossible to think.
0:54:39 I don’t know why we don’t fear these
0:54:41 and talk about these all the time.
0:54:43 To me, it’s like I’m running a car factory
0:54:46 and the electricity keeps going out
0:54:47 and the assembly line keeps stopping
0:54:49 and it’s completely reducing the flow massively
0:54:52 of which cars are being built
0:54:53 and we’re just putting up with it.
0:54:54 Yeah, the electricity system’s bad.
0:54:56 This is, I think, issues one, two, and three.
0:54:58 There’s a couple preparation-based things
0:55:01 that you could do here that stop the task
0:55:03 from showing up in the first place.
0:55:04 I think we should start there.
0:55:05 So working on fewer active things is a key.
0:55:09 I was missing this insight in my earlier work,
0:55:11 but in this book I really got into this insight
0:55:14 is just having fewer things generating overhead
0:55:18 has got to be the first step.
0:55:19 Going from 10 active things to 2, that makes a difference.
0:55:22 All right, being careful in your choice of projects
0:55:25 can make a difference as well.
0:55:26 It’s an idea from the book that some types of projects
0:55:29 are going to generate a huge amount
0:55:31 of unscheduled urgent tasks.
0:55:34 Other projects won’t.
0:55:35 You want to prioritize
0:55:36 about reducing those urgent, unscheduled tasks.
0:55:39 Not how hard is the project going to be?
0:55:40 How difficult am I going to have to think?
0:55:43 Even how long it’s going to take, forget that.
0:55:45 What you should care about is
0:55:46 how many unscheduled urgent tasks
0:55:49 is this going to generate?
0:55:50 If it’s a lot, try to avoid taking on that particular project.
0:55:54 Once you actually have the work in your sort of world
0:55:57 and you have to deal with it,
0:55:59 a big thing to tame
0:56:00 becomes actually how the communication collaboration happens.
0:56:03 So a lot of the sort of urgent things
0:56:07 that are unscheduled
0:56:08 but requires you to deal with
0:56:09 tends to be back and forth communication.
0:56:11 So if you don’t specify,
0:56:13 here’s how we’re going to collaborate
0:56:16 on this task to get it done.
0:56:17 If you don’t specify it,
0:56:18 the default will be what I call the hyperactive hive mind,
0:56:21 which is we’ll rock and roll
0:56:22 and figure things out on the fly with emails and Slack.
0:56:25 Let’s just go.
0:56:25 Hey, what about this?
0:56:26 Did you see this?
0:56:26 What do you think about that?
0:56:27 Just we’ll just figure things out back and forth.
0:56:29 That collaboration style is a disaster
0:56:32 because what happens is
0:56:34 everything I’m working on
0:56:35 now has these ongoing conversations.
0:56:37 I have to tend to them.
0:56:39 I can’t just batch and say
0:56:41 I will get back to my email in four hours
0:56:43 because this conversation
0:56:44 we’re having an email over here
0:56:46 is going to have 10 back and forth messages
0:56:48 and we have to get to a conclusion today.
0:56:50 We’re trying to side on something for tomorrow
0:56:52 and so I need to see your next message
0:56:53 within the next 15 minutes
0:56:55 or we’ll never get through everything
0:56:56 in time to actually reach a conclusion.
0:56:58 So it’s this sort of unstructured collaboration
0:57:01 that drives us to have to check our inbox all the time,
0:57:04 to check Slack all the time.
0:57:05 So you can actually just say
0:57:07 once you’ve reduced the amount of things
0:57:09 you’re working on and have some breathing room,
0:57:11 you can talk to the people you’re working with.
0:57:13 How are we going to collaborate on this?
0:57:15 And you figure it out in advance.
0:57:17 You take a little time in advance.
0:57:19 You work on this.
0:57:20 I’ll work on that.
0:57:21 I’ll put my comments into this shared doc
0:57:23 by the end of day on this day.
0:57:24 You can look at them
0:57:25 and put your revisions by the end of day the next day
0:57:28 and then after this meeting on Thursday,
0:57:30 we’ll huddle up for 10 minutes
0:57:32 and figure out what we want to do next.
0:57:33 You just figure out the plan.
0:57:35 Here is how this work is going to unfold.
0:57:38 So we don’t have to rely
0:57:39 on just unscheduled back and forth messaging.
0:57:41 So you constrain the communication on what remains.
0:57:44 Those three things together
0:57:45 is going to make life so much easier.
0:57:47 There’s a lot of devil in the details there though
0:57:49 because if you imagine a typical chunk of people
0:57:52 that are working on a project
0:57:53 and I’m just thinking software development in my head,
0:57:55 let’s just say we have seven or eight people
0:57:58 working on one launch.
0:58:00 You’re right in that it’s going to be slack in email,
0:58:02 largely slack.
0:58:03 And there’s just a quick back and forth expected.
0:58:06 If you’re the one that’s read slow productivity
0:58:08 and nobody else has on that team
0:58:11 and everybody else is just like used to using slack
0:58:15 as this instant back and forth throughout the day,
0:58:18 what can I do to convince my coworkers
0:58:22 to take a beat and move to something.
0:58:24 I don’t want to be the odd one out here.
0:58:26 You know what I’m saying?
0:58:27 How do you get people on board?
0:58:29 You don’t explicitly try to get them on board.
0:58:32 You just say, here’s what we’re doing.
0:58:34 This is one strategy.
0:58:35 So you don’t give a speech about,
0:58:37 let me talk about attention capital
0:58:39 and context switching costs.
0:58:41 And we need to move away from the hyperactive hive mind.
0:58:43 You’re just like, all right team,
0:58:44 like we got to get this website updated
0:58:47 for the new product launch.
0:58:48 Here’s the things that need to get done.
0:58:50 Here’s how I think we should do it.
0:58:51 I will do this by the end of this day.
0:58:52 You can do this on this day.
0:58:53 We’ll then meet here for our final meeting.
0:58:55 Here are the five times that seem to work for everyone.
0:58:58 Just put in the dock before we get there,
0:58:59 like which of the days you’re going to do.
0:59:00 Okay, let’s go.
0:59:01 I call this process-centric emailing,
0:59:03 but you’re just sort of laying out what you’re going to do
0:59:06 and just telling the other people.
0:59:08 You’re not really explaining the philosophy behind it.
0:59:10 So that’s one way.
0:59:10 There’s a couple other things you can do.
0:59:12 On your own end, something that works really well
0:59:14 for things that aren’t so regular is just have office hours.
0:59:18 This is a big sort of Jason Freed base camp idea.
0:59:21 A set time every day in which I’m always available.
0:59:25 My door’s open.
0:59:26 I have like a team’s meeting open.
0:59:28 My phone’s on or whatever.
0:59:29 You can start deflecting stuff to that.
0:59:31 So all you’re saying to people, if it’s not super urgent,
0:59:34 yeah, we should get into that.
0:59:36 I have office hours every day at this time.
0:59:37 Next time it’s convenient, just hop over.
0:59:39 We’ll figure it out.
0:59:40 So now you’re deferring some things, the office hours.
0:59:42 And then the third way is at the team level
0:59:44 to do talk about this and have better systems.
0:59:47 It’s like software development is interesting
0:59:49 because that’s already been done.
0:59:51 That type of thinking has been done
0:59:52 when it comes to the straight up coding.
0:59:54 This was figured out in the early 2000s.
0:59:56 Actually, if we have some sort of agile methodology
0:59:59 where we keep track of features separately from individuals,
1:00:02 an individual sprint on one feature at a time
1:00:05 and we check in with a daily stand up,
1:00:07 that’s an idea for breaking up a workload and communication
1:00:11 that works much better than,
1:00:13 hey, let’s all just like rock and roll.
1:00:15 Can you do this feature?
1:00:16 What’s going on with that feature?
1:00:17 Computer programmers will figure this out.
1:00:19 They have alternative systems.
1:00:20 Yeah, it’s interesting we never applied that everywhere else
1:00:23 because you’re right.
1:00:24 That agile methodology and these ideas of daily stand ups,
1:00:28 it works and yet we stopped there.
1:00:30 We were never like, hey, we should apply this same thing
1:00:33 to other types of workers in the office.
1:00:36 We should.
1:00:36 To me, the core idea behind any sort of Kanban based system,
1:00:40 the core idea that should be relevant to all knowledge
1:00:42 workers is centralization of workload.
1:00:45 We don’t realize the degree to which in most knowledge work
1:00:47 positions, all the work that needs to be done
1:00:50 is haphazardly distributed among individuals.
1:00:52 Everyone owns it, right?
1:00:53 I own this one, you own that one.
1:00:55 It’s all about who emailed who.
1:00:56 In agile and Kanban type systems,
1:00:59 all the work that needs to be done is not owned by individuals.
1:01:02 It’s on a board over here.
1:01:03 The whole team owns it.
1:01:04 And then individuals work on a small number of things at a time
1:01:07 and then pull in something new when they’re ready.
1:01:10 That one insight can transform any knowledge work group
1:01:14 of when something needs to be done,
1:01:16 I have a place to put it so I don’t have to keep track of it.
1:01:18 But I also don’t have to just obligation hot potato it
1:01:21 onto your plate where now it’s something that’s like
1:01:23 generating stress, administrative overhead.
1:01:25 So even that idea of here’s the things our team needs to do.
1:01:30 Here’s what each person is currently working on
1:01:32 and we can see it.
1:01:33 That idea alone is a massive improvement.
1:01:37 I think it’s because software has a foot in industrial
1:01:39 and a foot in knowledge work.
1:01:41 It’s knowledge work because it’s all done with your brain.
1:01:43 But it’s industrial because you’re producing a product
1:01:45 to specs on a timeline.
1:01:47 So they’re much more willing to do process engineering.
1:01:50 Knowledge work is tainted by this big belief in autonomy.
1:01:54 This idea that it’s up to the individual
1:01:56 to figure out how to do their work.
1:01:57 It’s no one else’s business,
1:01:58 but the individual about how they manage their labor,
1:02:01 how they manage their time,
1:02:03 how they manage their workload.
1:02:04 That’s not our business.
1:02:05 Our business as a manager is to give them objectives.
1:02:08 Here’s your KPIs, hit them.
1:02:10 I don’t want to know how you’re doing it.
1:02:11 So we have this sort of barrier between objectives
1:02:15 and process.
1:02:16 And Peter Drucker, who came up with management by objectives
1:02:20 and coined the term knowledge work.
1:02:21 This was his big thing.
1:02:23 I think we’re now paying a price for going too far with this.
1:02:25 We don’t think in peer knowledge work enough
1:02:27 about how the work actually happens.
1:02:29 One of the points that you mentioned in the book,
1:02:31 the last of the three major points,
1:02:33 is this idea of obsessing over quality.
1:02:36 Why is that so important?
1:02:37 Well, if you want to slow down,
1:02:40 ultimately you have to do this.
1:02:42 The first principles are about
1:02:43 you’re doing less things, you’re removing something,
1:02:45 you’re spending more time,
1:02:46 you’re having more variation intensity,
1:02:48 you’re better matching natural rhythms,
1:02:50 just taking things away.
1:02:51 You have to balance that out
1:02:53 with a commitment to the things you’re doing,
1:02:55 doing them better.
1:02:56 I want to do things really well.
1:02:58 That’s what makes the whole slow productivity mindset
1:03:00 not just be I want to work less,
1:03:03 but actually is a sustainable for both the individual
1:03:06 and their clients and their employer
1:03:08 and the people that they’re servicing.
1:03:11 But the other thing that happens
1:03:12 when you really start to care about craft,
1:03:14 slowness no longer seems artificial or unattainable,
1:03:18 but instead begins to seem necessary.
1:03:20 When I really care about doing something really well,
1:03:23 suit or productivity becomes anathema.
1:03:25 My inbox being so full becomes a crisis.
1:03:28 My workload having 10 or 15 other projects
1:03:31 becomes something that I have to fix.
1:03:32 So that mindset of what matters
1:03:34 is the quality of what I do best.
1:03:37 Make slowness makes the non-business
1:03:40 seem like by far like the self-evident way
1:03:43 that you need to work.
1:03:44 So it’s sort of the engine
1:03:45 that drives the slow productivity mindset.
1:03:47 There must also be a component
1:03:49 that is satisfaction with your output,
1:03:52 just being proud of what you have produced for the world.
1:03:55 When I think about some of the artisan Japanese masters
1:03:58 that I’ve had the pleasure of visiting,
1:04:00 they actually in Japan,
1:04:02 they have this designation for living legends
1:04:04 of these craftspeople that are just like producing
1:04:07 high quality works.
1:04:08 I was in this little tiny town
1:04:09 about two and a half hour train ride outside of Tokyo,
1:04:12 and I met one of the living legends
1:04:14 that was a woodworker,
1:04:15 and he had a space that was three people working in there.
1:04:20 He was in his 80s and his hand carving
1:04:24 like these beautiful wooden bowls and polishing them.
1:04:26 And there was just like this attention to detail
1:04:29 and his satisfaction.
1:04:31 And one bowl would take him like three months to produce
1:04:34 this little tiny bowl.
1:04:35 You can’t help but look at that
1:04:36 and say, gosh, when you obsess over quality,
1:04:39 it becomes your life’s work.
1:04:41 There’s something beautiful
1:04:42 and deeply satisfying about that.
1:04:44 Do you think that’s a very important aspect to this
1:04:47 in finding satisfaction in your work
1:04:48 is the quality component?
1:04:50 Yeah, I mean, this is something that
1:04:52 busyness and pseudo productivity robs us of.
1:04:54 So when work becomes all about activity,
1:04:57 we have to begin prioritizing activity.
1:05:00 I’m moving really quick.
1:05:01 I’m answering things.
1:05:01 We have to stay away from things
1:05:03 that require more long-term focused effort.
1:05:06 We get alienated and I use this phrase.
1:05:08 It’s a German concept that comes out of Marxism,
1:05:11 this alienation from labor.
1:05:13 Actually, this is a relevant way to think about
1:05:15 what’s happening with pseudo productivity
1:05:18 is that we get alienated from our ability
1:05:20 to produce things that matter.
1:05:22 And that really is a state that’s psychologically distressing.
1:05:26 It’s the, this is me.
1:05:28 It’s like the Pale King, David Foster Wallace.
1:05:30 Just I’m sitting here moving things back and forth,
1:05:32 emails back and forth.
1:05:33 I’m going on Zooms, taking notes from the meetings
1:05:37 and sending follow-up.
1:05:38 What am I actually doing here?
1:05:39 That is supremely frustrating.
1:05:41 Humans like to see their intentions
1:05:43 made manifest concretely in the world.
1:05:45 That’s a quote from Matt Crawford.
1:05:47 And shop class is soul craft.
1:05:50 When he talks about the pleasures of manual competency,
1:05:53 we like to see our intentions made manifest
1:05:55 concretely in the world.
1:05:57 We do get great pleasure out of it.
1:05:58 So that’s part of what makes slow productivity
1:06:00 a lot more sustainable.
1:06:01 It’s not just that you’re not overloaded,
1:06:03 but you can actually see what you’re producing
1:06:05 and care about it.
1:06:07 This is the nexus of the argument
1:06:08 that I sometimes fall into with more of the anti-work crowd
1:06:12 who’s responding to a similar issue,
1:06:14 which is this sort of sense of nihilism and exhaustion and work.
1:06:17 But they lay the issues entirely at the feet
1:06:20 of just capitalist structures.
1:06:22 And they don’t like when I emphasize this other part
1:06:24 of like, well, actually there’s parts of work
1:06:26 that are really deeply meaningful to people.
1:06:29 And reclaiming that is not only going to be very sustainable,
1:06:33 but it’s probably something that is way more approachable
1:06:35 than replacing capitalism.
1:06:37 That building work more about craft and less about business
1:06:40 is something that could make us much happier
1:06:43 and it’s much more proximate
1:06:44 than waiting for the eventual collapse of late-stage capitalism
1:06:47 or some revolutionary ideology or utopian vision.
1:06:51 So yeah, you’re 100% right.
1:06:52 Work is more satisfying when we’re producing stuff that’s good
1:06:55 and we’re getting better at doing it
1:06:56 and we’re getting recognition that it’s good.
1:06:58 And people are saying that is a really good bowl.
1:07:00 We’re wired for that.
1:07:02 We eat that up.
1:07:03 Yeah, we eat it up.
1:07:04 I bought one of the bowls.
1:07:05 I definitely was like, this is too good.
1:07:07 And then just owning a piece of that
1:07:09 when you can see the effort that went into it
1:07:12 is just a beautiful thing.
1:07:13 I’d like to end on one question for you personally.
1:07:16 It was someone that’s been so prolific
1:07:18 about writing about deep work and slow productivity.
1:07:21 How do you structure your own day?
1:07:22 Can you walk me through a day in the life of Cal Newport?
1:07:26 What does it look like from rise
1:07:27 to actually calling it a day and going to sleep?
1:07:31 I think you have to start with the question
1:07:32 of how do I structure my year?
1:07:33 Because a big part of what I do is I don’t like business
1:07:37 and I don’t like having a ton of things on my calendar.
1:07:39 I work only in roughly a nine to five schedule.
1:07:41 That’s always been my commitment to myself and my family.
1:07:44 And so you have to look at how I schedule my year
1:07:46 because I sequence.
1:07:47 I work on this during this season,
1:07:50 this other thing during that season.
1:07:51 I never want to be working on too much at the same time.
1:07:54 So you’re like seasonal working.
1:07:56 So you divide up work based on seasons?
1:07:59 Yes.
1:08:00 How do you do that?
1:08:00 It doesn’t even make sense to me.
1:08:02 I don’t know how that works.
1:08:03 Partially I’m a college professor,
1:08:04 so it’s a little bit more natural.
1:08:06 For example, this season,
1:08:07 I’m very much in book publicity mode.
1:08:09 So I’m not trying to write a book
1:08:11 or make a major academic breakthrough.
1:08:14 The summers, I disappear.
1:08:15 I’m a college professor.
1:08:16 I don’t take summer salary from research grants
1:08:18 in the summer.
1:08:19 I pay my own way and disappear.
1:08:20 That’s when I do a lot of deep thinking.
1:08:22 I do a lot of writing.
1:08:24 I work through notions for books.
1:08:26 There’ll be certain semesters where I say,
1:08:27 this is really like an academic semester.
1:08:29 I now stack my classes.
1:08:31 So there’ll be a semester where I’m teaching,
1:08:33 doing all my teaching.
1:08:34 Great.
1:08:34 So I can just be locked in on my students
1:08:36 and what they need in academic life.
1:08:38 And another semester, I might be doing no teaching.
1:08:41 It’s like, great, I’m writing these papers
1:08:42 and that’s what I’m focusing on.
1:08:44 I’ll write a book and then after a book,
1:08:45 I’ll focus for a while on a bunch of academic papers.
1:08:48 Then I’ll focus back on a book.
1:08:49 So I sequence.
1:08:50 But if you zoom out over five years or 10 years,
1:08:53 a lot of things finish in there.
1:08:55 The fundamental attribution error, though,
1:08:57 is not to look at the things
1:08:58 that I did in the last 10 years
1:09:00 and imagine me working on all those things
1:09:02 at the same time during those 10 years.
1:09:05 Because I don’t like busyness.
1:09:06 I don’t like having a lot to do.
1:09:08 I like having a lot of breathing room.
1:09:10 If I don’t get a lot of deep work,
1:09:12 I tend to get pretty upset.
1:09:13 But what that look like differs by the day.
1:09:16 So like in the summer, I take no meetings.
1:09:18 I have nothing on my calendar on Mondays or Fridays.
1:09:20 And the things that are on my calendars
1:09:22 are the afternoons, Tuesday, Wednesday, Thursdays.
1:09:24 The rest of this time is just like focused deep work.
1:09:26 That looks very different in a teaching semester.
1:09:28 Where, OK, I’m not getting long periods of deep work.
1:09:32 But what I’m doing is juggling the plates
1:09:34 to handle my classes and administrative duties really well.
1:09:37 My day depends on the season.
1:09:39 And I change up and down different types of things.
1:09:42 I keep varying that.
1:09:43 I love that.
1:09:44 The summertime, Monday, Friday free, must be so nice
1:09:49 in terms of one, the space to get outside.
1:09:52 Because summers times are typically beautiful
1:09:54 and just having a little bit more flexibility on that
1:09:56 and enjoy the weather for what it is.
1:09:58 And then just having the downtime to get creative
1:10:02 on those days must just be beautiful.
1:10:04 It sounds like a fantastic thing.
1:10:06 I might steal from you and pick up.
1:10:07 One of the things that I had the luxury of working at
1:10:10 the Nevada test site for the Department of Energy
1:10:12 when I was very young.
1:10:13 And we did four day work weeks.
1:10:15 And I loved it.
1:10:17 It was every Friday, Saturday, and Sunday you had off.
1:10:20 I’ve heard that starting to pick up again
1:10:22 and that some companies are starting to dabble with that.
1:10:25 Speaking of taking days off, are you a fan of that?
1:10:27 I’m fine with it.
1:10:30 If you deal with the deeper problems first.
1:10:32 So if you deal with the problem of workloads,
1:10:35 I’m working on too many things concurrently,
1:10:37 the administrative overhead is choking me.
1:10:39 Like you need to solve those problems.
1:10:41 If you solve those problems, then you can actually realize,
1:10:44 hey, four days of work might be enough.
1:10:46 Or we don’t need all five days or we change it seasonally.
1:10:49 We have summer hours.
1:10:50 What I don’t think works is taking a culture
1:10:53 where everyone is overworked because they have too much
1:10:55 on their plate and the administrative overhead
1:10:57 is choking off their time and they’re having to work
1:10:58 in the mornings and late at night.
1:11:00 They go into a culture like that and say,
1:11:01 we’ll solve this by saying don’t work on Friday.
1:11:04 You’re not really solving the problem.
1:11:05 Because all of those things are still on your plate.
1:11:07 All that administrative overhead is still there.
1:11:10 It doesn’t make it worse.
1:11:12 This is another sort of Jason Fried case study.
1:11:14 They experimented with this in the summer.
1:11:16 And they found that actually people adapted to their being
1:11:19 less time and they adapted their workloads.
1:11:21 So I don’t think it’s the worst thing.
1:11:22 But I don’t want it to be seen as the ultimate solution.
1:11:26 I think the ultimate things we need to do are internal.
1:11:28 How do we manage our workloads?
1:11:30 How much work should people be working on at once?
1:11:32 How do we communicate about this work?
1:11:34 Do we focus on activity or do we focus on output?
1:11:37 You make those changes.
1:11:38 You get the really big results and then you can mess around
1:11:41 with things like what days you work or should we care?
1:11:44 Or what hybrid schedule or like a lot of that stuff
1:11:46 can’t solve these problems by itself.
1:11:50 But become interesting options once you solve the deeper
1:11:53 original problems.
1:11:54 Yeah, you must be friendly with Jason Fried.
1:11:58 Yeah, we did a book launch event for two books ago.
1:12:00 Yeah, I know Jason.
1:12:01 That’s awesome.
1:12:02 Yeah, Jason is one of my favorite humans in terms of just being
1:12:06 such a creative thinker when it comes to how to run a business
1:12:11 and reimagine almost every aspect of running a business.
1:12:14 I’ve had the chance to brainstorm with them.
1:12:16 We used to be on a board together.
1:12:17 So we would just shoot the shit from time to time.
1:12:20 His mind and where it goes and the things he dreams up for
1:12:23 his employees and the series of experiments.
1:12:26 It’s just so fun to watch.
1:12:27 So fun to watch.
1:12:28 He’s a chill guy.
1:12:29 I think most people in the startup culture I’m assuming
1:12:32 feel like I don’t have time or I can’t risk doing this.
1:12:35 That’s right.
1:12:35 But I’m always surprised.
1:12:36 There’s not more people who have these sort of stable startups
1:12:40 like Basecamp is that aren’t being super experimental
1:12:44 and like swapping best practices and just read their manual,
1:12:48 which is online.
1:12:49 It’s just full of interesting ideas like cycling is another one.
1:12:53 Like we have off cycles and down cycles.
1:12:55 I wish there was 100 startups that were equivalently
1:12:59 aggressive about experimenting because imagine all the
1:13:01 interesting stuff we’d come up with if we had so much sampling
1:13:04 going on out there.
1:13:05 You know what the key was for Jason is that he never took
1:13:07 on venture capital.
1:13:08 He was never beholden to go and have some massive exit.
1:13:13 And so it wasn’t like he was shooting to be a multi-billion
1:13:16 dollar company and he has a massive business.
1:13:17 Basecamp’s a huge tool as is Hay and the other stuff that he
1:13:21 experiments with, but he kept it all private so he could grow
1:13:24 at his own natural organic pace.
1:13:26 He had the luxury of being able to say I don’t have to be
1:13:29 beholden to these other venture capitals.
1:13:30 I can just go and mix things up whenever I want,
1:13:32 which I think is is essential.
1:13:34 Do you agree with this theory that part of what happens is
1:13:37 when you’re a small startup, actually you do need to work
1:13:39 in a sort of hyperactive all hands on deck way because
1:13:42 there’s just too much going on to structure.
1:13:44 And then once you’re used to that, it’s hard to turn off
1:13:46 once you get bigger.
1:13:47 One of my theories like venture capitalists are like,
1:13:49 I want to see the lights on.
1:13:50 But for good reason, because if you’re a four person startup,
1:13:54 you have to just be on Slack all day or in the same room
1:13:56 because there’s a thousand things and it’s all new.
1:13:59 And then my theory is it becomes hard.
1:14:01 You then say this is fundamentally what you need to
1:14:03 succeed in a business, but a business is at a thousand
1:14:06 employees is a completely different beast than four
1:14:09 employees in three weeks in.
1:14:11 There’s different stages of pain.
1:14:13 You can manage the general kind of philosophy and ethos
1:14:16 within your organization up to about 20, 25 people.
1:14:20 And then all of a sudden not everyone can be in the same
1:14:22 meeting.
1:14:23 And then there’s a whole another set of problems of,
1:14:25 oh, I missed that meeting.
1:14:26 Why wasn’t I included or now I’m not on the same page?
1:14:29 And now you’re dealing with just broken lines of communication
1:14:32 that need to be repaired and you have to figure out new
1:14:35 workarounds.
1:14:36 There is some truth to every time you add a new employee,
1:14:39 you’re actually starting over again.
1:14:41 Like you have a brand new startup because it grows the
1:14:44 team and things break in certain ways.
1:14:46 It’s really challenging, but I would say the thing that’s
1:14:50 tough almost more than anything else is when you get to a
1:14:55 size call it 50 or 75 where you realize that that team that
1:15:00 you had when it was 10 people needs a little bit more
1:15:03 structure.
1:15:04 And oftentimes people tend to go too hard in that
1:15:06 direction and you lose the creativity.
1:15:09 And then all of a sudden you’re trying to implement
1:15:11 processes from Google and other big companies and you
1:15:14 become a big company and the innovation suffers because
1:15:17 of it.
1:15:18 Start ups are a pain in the ass.
1:15:20 I’m done building them.
1:15:22 They are so difficult.
1:15:23 There’s nonstop fires, which for me, I feel like I’m
1:15:26 finally starting to realize that let’s just stick to
1:15:28 podcasting and doing investments on the side.
1:15:30 That sounds like a much better.
1:15:31 And hopefully interview people like you and help other
1:15:33 people adopt some of these better practices that are
1:15:35 coming to light.
1:15:37 So, Cal, it was a pleasure having you on.
1:15:38 But before we go, slow productivity.
1:15:40 We covered bits and pieces of it sprinkled throughout
1:15:42 our conversation today.
1:15:44 But for people that, okay, that was a really
1:15:46 interesting conversation.
1:15:47 I want to learn more.
1:15:48 What can people expect to learn in this book?
1:15:50 How would you present it to someone that had never
1:15:53 read anything that you’ve done in the past?
1:15:54 Right.
1:15:55 So in the first part of the book, I make that argument
1:15:57 about how do we get to where we are today with
1:15:59 pseudo productivity and the front office IT revolution
1:16:02 and why that spun off the rails.
1:16:03 The second part, I give those three principles for the
1:16:06 slower, more outcome based philosophy.
1:16:09 I really see two audiences for the book.
1:16:11 They’re both served.
1:16:12 So entrepreneurs or solopreneurs or freelancers who
1:16:16 have a huge amount of autonomy.
1:16:17 You’re going to get pretty radical ideas in here about
1:16:20 how to radically reshape what you do around these
1:16:22 principles.
1:16:23 And then the other audience are people who work for
1:16:25 large companies.
1:16:26 And how can you personally change the way that you
1:16:28 approach your work and manage your workload and
1:16:30 communicate with other people and conceptualize your
1:16:32 career to integrate these ideas?
1:16:35 So really both audiences are served by the book.
1:16:39 But what I hope you come away with is an
1:16:41 understanding of what you think of as productivity
1:16:44 right now really is broken.
1:16:45 And there are alternatives.
1:16:47 They’re not easy, but they’re also not impossible.
1:16:49 There’s some principles that make sense.
1:16:51 And there’s a bunch of tactics in there to give you
1:16:53 ideas about how you put them in the practice.
1:16:55 Yeah, I love this.
1:16:56 This is a true story.
1:16:58 Last night, when I was going through the book and
1:17:00 reading it and finishing up on it, I emailed
1:17:02 my assistant and she’s amazing.
1:17:04 She’s like this ultimate Swiss Army knife.
1:17:06 And we’re always trying to figure out how to be on
1:17:07 the same page about things and how not to overload
1:17:10 calendars and all of that stuff.
1:17:12 I told her, I said, you can expense this.
1:17:14 Please go download this book right away.
1:17:16 We need to start implementing some of the ideas here
1:17:18 because they’re not obvious.
1:17:20 But when you hear them, they feel very obvious.
1:17:22 I wouldn’t have thought of that on my own, but when I
1:17:24 hear it, I’m like, oh my God, this makes a ton of sense.
1:17:26 It’s funny.
1:17:27 Last thing, and I’ll let you go.
1:17:28 I promise I had this idea about a decade ago because
1:17:32 I always have had an issue with email stacking up.
1:17:34 And I wanted to write an email application that, you talk
1:17:38 about this, and we didn’t really cover this much detail
1:17:39 today, but you talked about this idea of push versus
1:17:42 pull strategies, which is quite fascinating.
1:17:44 And one of the things that I wanted to do in an email
1:17:47 client was that when you emailed me, if I had a Q longer
1:17:51 than a certain amount of unread emails, you would get
1:17:54 an auto response back and it would say, hey, just so
1:17:56 you know, Kevin reads about 10 to 15 emails on average.
1:18:00 You are currently number 87 in the queue.
1:18:03 We expect that he will read your email by this time and date.
1:18:06 And if you would like to jump the queue because this is
1:18:08 ultra urgent, click this button.
1:18:10 And so if you click the button, it would then enable
1:18:12 them to jump the queue because they’re saying this is
1:18:14 super important.
1:18:15 Otherwise, then I could just slowly pick away at that
1:18:18 list and not feel uncomfortable about it.
1:18:20 And I never built it, but it was this idea.
1:18:22 And I was reading your book and I was like,
1:18:23 somebody needs to build a suite of slow tools.
1:18:26 Screw the modern productivity stuff.
1:18:28 Let’s build the stuff to slow us down.
1:18:30 Is anybody doing that?
1:18:31 It’s a problem.
1:18:32 I’m thinking about this.
1:18:33 I call this psychologically aware productivity or
1:18:35 neurologically aware productivity.
1:18:37 So productivity that’s not based on speed of doing
1:18:40 things, but on the reality of how the human brain works.
1:18:43 Some of this stuff is creeping in.
1:18:46 There is a menu somewhere, for example, in Microsoft Outlook
1:18:49 where the term deep work for my book, Deep Work from 2016,
1:18:52 does show up.
1:18:52 So these things are out there.
1:18:54 Focus time, deep work time.
1:18:56 This is something that’s coming up in some of these tools.
1:18:59 But I like the way you’re thinking about it.
1:19:01 Let’s just go all out.
1:19:02 Like our goal here is to give people less context switching,
1:19:06 be able to spend more time on things without distraction,
1:19:09 more efficiency in how they consolidate communication.
1:19:13 So it’s not happening spread out throughout the day.
1:19:16 I think it would completely change.
1:19:17 Like another thing your tool could say is you have a
1:19:20 couple options there.
1:19:21 One of the options also being here’s a bunch of quick
1:19:24 10 minute slots that are available later today.
1:19:27 Yes.
1:19:28 That you could just discuss this and figure it out.
1:19:30 That’s my office hours.
1:19:31 That’s it.
1:19:31 Just click on one of these right now.
1:19:33 Okay, that doesn’t work.
1:19:34 Okay, what about it that’s going to take this long
1:19:36 or give these options for when and how can I talk about
1:19:40 these things?
1:19:41 Yeah, I love that idea.
1:19:42 Here, I’ll tell you this.
1:19:43 I have talked to some CEOs from well-known companies in
1:19:46 the space who recognize that there’s so much money on
1:19:48 the table in knowledge work, just in terms of the value
1:19:52 being produced per human brain hired.
1:19:54 There’s so much money on the table because we are
1:19:58 so bad at utilizing human brains because we keep
1:20:00 them context switching and overloaded that there’s a
1:20:04 trillion dollar market cap on the table.
1:20:06 And so they know one of the CEOs said figuring out
1:20:08 how to really work with human brains and have the
1:20:10 tools to do that’s the moonshot of the 21st century.
1:20:12 They know there’s huge opportunity here.
1:20:15 They’re having a hard time getting through the
1:20:16 mindset of what matters is accessibility of
1:20:19 information, speed of execution.
1:20:21 And I do not think just accessibility of
1:20:23 information and speed of execution.
1:20:25 That’s what computer processors need.
1:20:27 Human brains need less information bothering them.
1:20:31 They need less context switching.
1:20:34 They need to be able to focus on one thing at a time.
1:20:37 Yeah, I agree.
1:20:38 There’s a slow suite of tools to be deployed here
1:20:41 that are built on.
1:20:42 We want a human brain to do what human brains do best.
1:20:45 A company that said that is our number one ethos.
1:20:48 Giving human brains the best possible environment
1:20:50 to do human brain stuff.
1:20:51 And I do think it would look very different than
1:20:53 what we’re doing right now.
1:20:55 Yeah, I agree.
1:20:55 Someone needs to build that.
1:20:57 Sadly, I’m out of the game.
1:20:58 Maybe it’s your turn to go jump in.
1:20:59 No, you just taught me how terrible startups are, Kevin.
1:21:02 That’s the problem.
1:21:03 It is horrible.
1:21:03 Just scared everyone off.
1:21:05 Yeah, exactly.
1:21:06 Someone will listen to this and hopefully go build it.
1:21:08 But, Cal, thank you so much, man.
1:21:09 It’s been a pleasure to hang out, to chat about this stuff,
1:21:12 to meet you for the first time even virtually.
1:21:14 And I hope we get a chat again soon.
1:21:16 I enjoyed it. Thanks.