Cal Newport: How Entrepreneurs Can Cut Distractions to Instantly Boost Productivity | Productivity | E360

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This myth we tell each other that the more things I'm working on, the more productive I am is just absolute nonsense.

Cal Newport is an MIT trained computer science professor at Georgetown University.

He's the best-selling author behind Deep Work, Digital Minimalism, and his latest book, Slow Productivity.

Workflow transparency is critical to making work much more sustainable, much less exhausting, and also I think it helps organizations be more productive.

What's the difference between deep work and shallow work?

Deep work is what brings in the money, but shallow work is necessary to keep the lights on.

It is a substantial, significant, almost astonishing difference to be working on a small number of things at a time makes you so much better at working than trying to juggle multiple things.

To all the folks out there that are growing their career, how can they really say no and do fewer things?

People imagine that they never say no, and that if they look at advice like do fewing things, they're going to, for the first time in their career, start saying no.

What's really happening is so the elephant in the room is AI.

How you see AI shaping the future of work and productivity?

I had some summaries of what's working now, what's coming, what might work, and what's not going to work.

Like, what's working right now is

Yap Gang, what if the secret to getting ahead wasn't doing more, but doing less with deeper focus?

Today's guest has spent his career helping people escape the chaos of constant busyness and tap into something far more powerful: deep focused work.

Cal Newport is an expert on productivity.

He's an MIT-trained computer science professor at Georgetown University, and he writes about the intersections of technology, work, and the quest to find depth in an increasingly distracted world.

He's the best-selling author behind Deep Work, Digital Minimalism, and his latest book, Slow Productivity.

In this episode, Cal explains why deep work is more valuable than ever in the age of constant digital distraction.

We also dive into his philosophy of slow productivity, a powerful framework built on doing fewer things, working at a natural pace, and obsessing over quality.

Yap, fam, this episode is jam-packed with productivity tips.

I can't wait to dive in.

But before we do so, if you're a new listener, make sure you follow and subscribe to this podcast so that you never miss expert insights like this one.

Cal, welcome to Young and Profiting Podcast.

Hey, thanks for having me.

I was looking forward to this one.

Me too.

Cal, I've been a huge fan of your work for a really long time, back when you released Deep Work in 2016.

And now you've got a newly released book called Slow Productivity, which I really, really enjoyed getting to read.

And you've been doing this work for so long.

I remember I was just talking to my business partner last week when I started studying your work.

And I've always heard your name, but I never really knew what you looked like.

Like, I always would read your books and I didn't know what you looked like.

And I thought you were like a 60-year-old man

because I've just heard your name for so long.

And I just thought you were this older, prolific man.

And then I was like, oh my gosh, he's pretty young.

And he's just been doing this for so long.

So talk to me about how you got started in this field of productivity.

What was that initial spark that made you just so curious about how people work and helping people improve their productivity?

Well, I got started young, which is somewhat unusual.

My first book deal I signed in my summer between my junior and senior year of college.

Crazy.

So by the time I got the deep work, that was my fifth book.

Wow.

My story goes back.

I think the right way to understand it is I got started in writing because I had been an entrepreneur as a teenager.

So if we go all the way back, I'm a teenager in the late 90s.

The first dot-com boom is happening.

This was this time where for whatever reason, people felt like young people knew more about technology.

So they were willing to sign contracts with 17 year olds, assuming, hey, the kids should know more than we did.

So I had a technology company when I was a teenager.

I go to college.

I'm used to reading.

business books, advice books, time management books.

I'm used to them because I was reading them as an entrepreneur as a teenager.

I get to college and I say, great, let me go get some books about how to be a better student.

And they were, in my opinion, terrible because I was used to books that were saying, here's your goal.

Let's break it down.

Here's the advice.

Here's how to do it.

And the college books at that time were much more lifestyle-based.

They were trying really hard to be like cool and clever, what have you.

And so I said, hey, what if I wrote a college advice book in the same way you would write a business book?

So no nonsense.

Hey, you want to do well in school?

You're taking a lot of debt.

You're paying a lot of money in tuition.

Here's how to do well.

I talk to good students.

Here's the advice.

And that's how I got started.

So in that very beginning, I was writing books for students, but I had a frame of systems.

How do you, in a context of doing work with your brain, have the right systems to do this well and to do this without burning out?

And so as I got older, that focus switched from the world of students to the world of work.

And then that's when that transition began to happen for me.

And I know that your undergrad was in computers.

So how did computer science help shape the way you actually think about productivity?

Yeah.

And to this day, I'm a full professor of computer science at Georgetown University.

Oh, Awesome.

Yeah.

I got my doctorate in computer science at MIT.

I mean, that really is my other main thrust has always been an academic computer scientist.

I think what really happened because of that is that when I became a professor, there is a shift that begins to happen in my books.

So Deep Work is the first book I published and wrote after becoming a professor.

And the shift you begin to see is that though it's still, these books are still about the depth principle, they're still about focus, they're still about the danger of distraction and the value of concentration, There's a big technological component in them.

So when I'm talking about deep work, that's a productivity topic.

But the antagonist in that book is computers.

Why do we have to worry about focus?

Why are we getting so bad with focus?

If it's so valuable, it's email, it's computers, it's smartphones.

And I wrote a book, Digital Minimalism, that was all about our relationships to our phone.

And then a book called A World Without Email that was trying to understand how work became so fractured with its communication.

And so I think the main thing that computer science changed in my work is that it took my focus on systems and productivity and how do you do things well with your brain that I started as a student.

And it began to also take more seriously the role of technology in creating problems and the way to use technology to try to solve these problems.

And so now there's a much more of a technology backbone techno-criticism that orbits around the work I do.

Awesome.

I can't wait to dig deep into all these different concepts and all of your core work and everything like that.

But before we do that, since you talk so much much about productivity and you just mentioned you're not only an author, you also teach at MIT.

What does a productive day look like for you?

Well, I always say it depends on the time of year.

I'm a big believer in seasonality.

It's a concept I elaborated in my most recent book that different seasons of your year, which doesn't have to map onto actual meteorological seasons, can have different feels.

So like right now I'm in the summer, right?

And I'm a professor in summertime, which means I have a schedule I love, which tends to be if it's a non-podcasting day, I'm going to get up and I'm going to write for maybe three or four hours.

There'll be a bit of a break, then maybe an hour,

hour 30 of admin, and then I'm done.

That's my ideal summer schedule.

I love that schedule.

The other thing I try to do with my summer schedule is no meetings or appointments, nothing that requires me to get on a phone or go into a meeting room or get on a Zoom room on Mondays or Fridays so that all of that gets consolidated into Tuesday, Wednesday, Thursday.

So I can have an intellectual glide into the weekend and glide back out of the weekend on the other side.

And to me, I love that schedule.

But if it's a semester, let's say it's the fall or the spring and I'm teaching two classes, et cetera, and I'm on a book deadline, that's going to be a very different looking schedule.

And there it's going to be a schedule that's queued around when do I have to be on campus?

When am I teaching?

What's the rhythm of my office hours?

And so I really adjust my schedule depending on the time of year.

And I have to say at Yap Media, we use a lot of your principles to actually schedule our work week.

We do a no meeting day.

We actually do it on Wednesdays.

Now you're making me feel like, oh, we shouldn't do that on Wednesdays.

We should do that on either Friday or Monday so that we could have a smoother transition, like you were mentioning.

But we block out time for deep work and we batch our different things that we need to do when it comes to email and shallow work.

So why don't we actually transition so that people understand?

what deep work is.

I was also surprised to find out that you actually coined the term.

Now this is something that everybody says all the time.

I just thought that it kind of like evolved into this term, but you actually coined it.

So talk to us about deep work.

What's the difference between deep work and shallow work?

Right.

This was the title and the core idea of my book, Deep Work from 2016.

The idea was actually, to me, it was obvious, but in retrospect, it was obvious because of very specific things that were true about my life.

But the general idea was not all work is the same.

There's different types of cognitive efforts that you do.

And some of these efforts are what I call deep work.

And these are where you're really focusing.

You're using hard-won skills and you're trying to apply those skills with great concentration.

So it's where you're trying to typically, this is the effort that produces the things that create value.

It's the writing, it's the researching, it's the business strategy, it's the creating the ad copy that's going to make the big difference.

And then there's shallow work, which I just named as an anthony, and that's everything else.

Now, it's not shallow in a pejorative sense like bad work.

It's just work that doesn't require you to be highly focused or to really be applying hard-won skills.

My argument was was both are important.

Deep work ultimately is what brings in the money, but shallow work is necessary to keep the lights on.

So you have to actually do the effort that might require deep work.

We also have to send the invoices and do HR compliance or the company can't run or what have you.

I said both are important, but we've been shifting more and more towards shallow and we've been minimizing the time we spend doing deep work.

My argument was we should be careful about that.

Deep work is what really matters.

when it comes to bringing in money.

So you want to preserve time for deep work.

You want to practice and get better at deep work.

To me, that was really obvious but then you know it turned out on reflection and i wrote a new yorker piece about this last year that a lot of this idea actually came from my doctoral training so you know i'm a theoretical computer scientist i was in the theory group at mit

which is a very mathematical super abstract type place to study and in the theory group at mit

they talked all the time about focus and concentration.

Like, oh, this was this tier one skill.

If you're solving math theorems for a living, the only way you're going to get a job leaving this grad school is by being really, really good at solving math theorems.

You think a lot about distraction and you talk a lot about focus.

We talked about all the time.

This person can really focus.

Look how good this person can lock in.

So I was just used to separating out focus as a tier one, separatable skill.

So it made sense to me to write a book like, oh, yeah, focus is important.

I was taken off guard, taken aback by how much that was actually sort of a new idea for a lot of people because they were in this digital technology world where they had accidentally given up basically any opportunity to apply focus.

And I think when people heard this thesis, it was like a snap: like, oh, you're right.

Shoot.

This is a problem.

We do have to fix it.

Yeah, because everybody was glorifying multitasking and the fact that technology made everything so faster and there was more ways to communicate.

So everything was just so new.

Slack was still so new.

Email wasn't necessarily new, but I feel like people just didn't really grapple how to use the tools effectively yet.

You talk about the deep work hypothesis back then, the fact that doing deep work is going to become a very, very valuable skill.

It's going to become more and more valuable.

Do you feel like that's even more the case now, almost a decade later?

Yeah, the problems that motivated deep work have only gotten worse.

The deep work hypothesis says mainly because of technological trends, deep work is becoming increasingly rare.

It's just harder.

As we went from email to Slack and from Slack to mobile computing, and we added in the ability to do work virtually and at all places, our schedule gets increasingly fragmented.

So, deep work is becoming increasingly rare.

It's also becoming more valuable.

Back then, I argued it's because, look, it's a competitive economy.

So, the stuff that matters is not the basic stuff that anyone can do.

It's the hard thinking.

It's the stuff that's applying hard won skill in a way that most people can't replicate.

That's only become even more true.

Now, throw AI into that picture as well, which can like really automate the stuff you're doing when you're just throwing Slack and email back and forth.

It's never been more true that the stuff that's going to keep you in the game and matter is the real hard concentration.

And yet the stuff keeping us away from that, the distraction, has only gotten way worse.

Social media, for example, when I wrote deep work,

people were using a lot of social media, but we were only about four years into the period of ubiquitous smartphone use.

A lot of people were still accessing this on browsers.

We didn't have things like TikTok or the sort of hyper-palatable, algorithmically driven social media yet.

Today, that's way more time-consuming and attractive than it was back then.

And there's a hundred other examples like that where attention is more fragment than it was.

So the deep work hypothesis, it is way more true than it was before.

The only good news is that the idea of deep work, at least, is more well known now than it would have been back then.

And I know one of the core principles of your deep work book is that you need to embrace boredom.

And nowadays, to your point, It's so easy to just get hooked on your phone.

We've got these interest-based algorithms that are just feeding us whatever we're interested in.

It's so hard to not be bored because there's so many things to do, especially when your phone is just a world of knowledge and information.

So talk to us about the importance of being bored and how that can support our productivity.

It's all a training exercise because what is the cognitive state if you're sitting down to work on something important that's going to require you to focus?

I got to sit here for an hour and try to crack this hard problem or write this hard chapter.

From a purely physiological point of view, that is a boring experience because you don't have novel stimuli.

You're focusing on one thing and it's hard.

If your brain is not used to boredom, it's going to rebel in that circumstance.

If outside of work, at every slightest hint of boredom, you pull out a phone and you feed yourself algorithmically optimized, tailored entertainment that presses all the right cognitive buttons, you go to the carnival of excitement every time you get the slightest bit antsy, what's going to happen then when you're at work and you say, hey, time to spend three hours with Microsoft Word?

Your brain's going, no, no, it's carnival time.

This is untenable.

Of course, we're not going to do it.

It's just like if you have a toddler, and every time your toddler is like, I want, I want, you give it to them.

When you get to the supermarket, they're going to have that fit when they want the candy at the checkout line and they're not going to stop because they've been taught if they get upset, they get what they want.

Well, anyways, that's what happens to our brain.

The solution to that, it's not that you have to be bored all the time, nor is it that boredom itself should be glorified necessarily, that being bored itself is a very productive state.

I think that's overblown.

The reason why you inject a steady exposure to boredom throughout your day is so that when it comes time to do something boring but important, like deep work, your brain knows what's going on.

I've been there before.

I know what this is like.

It's okay.

We'll be okay.

We go for walks without our phone on a semi-regular basis.

I run an errand at least once a week without my phone.

I know what this is.

It's not so scary.

So it's a conditioning to boredom as a acceptable

psychological state.

That's what you need if you're going to succeed with deep work.

And our phone actually makes it much harder than people realize.

Yeah, we've got to train ourselves not to be so attached to our phones.

So somebody who I've interviewed on the podcast quite a few times is Stephen Kotler, right?

So he's the godfather of the flow concept, which I think goes really hand in hand with deep focus.

How do you think about neuroscience and biology when it comes to deep work?

There's a couple of different things going on.

with deep work.

Like what makes focusing without distraction such a powerful state to be in?

A couple of things I point out.

One is the harm you're avoiding.

If you're not doing deep work, but you're working on something hard, what you're doing instead probably is a lot of quick checks of like an inbox or Slack or looking at your phone and back to your work, right?

This is the normal way people approach any effort because they're just used to all these different diversions.

From a neuroscience perspective, what we know is when you do these quick checks, I'm mainly single tasking on this one hard thing, but I'm just glancing at my inbox, glancing at Slack.

That actually triggers in your brain this sort of cascading cognitive networking switch where it says, oh, here is another target for our attention.

And it's really salient.

If I'm looking at an email inbox, I'm seeing messages from people I trust and care about and my boss and clients and colleagues, and they're urgent.

And your brain says, this is important.

Okay, all hands on deck.

We have to switch our target of attention from this project to the inbox.

And that is an expensive, messy operation that can take 10, 15, up to 20 minutes to actually fully complete.

That's why when you sit down to write, for example, you can't do anything for 15 minutes.

It's because it takes a while for your brain to actually fully switch its focus to a new target.

So when you glance at an inbox, you initiate one of these really messy transitions of cognitive focus, but then before it can complete, you rinse your attention back to the original thing.

So now you have a sort of aborted context switch and you try to switch back again to what you were working on.

But before your mind can completely get back to that context, you check something else.

And now you initiate another context shift.

So we know from a neuroscience perspective that a lot of people in knowledge work spend most of their day in this state of fractured cognitive attention where their mind is switched between multiple targets and is not focused on anyone in general.

And this is an exhausting, anxiety-producing, low-productive state, but it's what most people just associate with work.

So from a neuroscience perspective, that's going on.

On the other hand, we know that when you are focusing on something really intensely, This is actually the best state with which to pick up new skills.

Because the way that we actually increase our ability on something, whether it's cognitive or physical, is that we have to deliberately push our ability past where we're comfortable.

And then that stretches our ability and we get better.

The only way to do that with something cognitive is it needs your full attention so that you're really straining from a neurological perspective to try to isolate the relevant neural circuits.

And in that isolation, the connection strengthen and now it becomes easier and you become better at it.

You can't get better at things without giving them intense concentration.

So the brain science tells us when we're not focusing without distraction, really bad stuff happens.

And when we are, really good stuff happens.

Something that I've been personally embracing because I feel like I get easily distracted is monotasking, the concept of just to your point, doing one task, don't multitask, monotask.

And I've gamified things for me.

So I always think about, can I do this in either 25 minutes or 45 minutes?

I do like the Pomodero technique and I set a timer on my clock and I'm like, okay, set a timer 25 minutes if it's a shorter thing, a longer thing, 45 minutes, or I'll do two 45 minute blocks or three even if it's a bigger project.

And I add something new to it where I give myself a reward at the end of it.

Like I'm not allowed to eat a snack or get up to pee or take a walk or do anything during those 25 or 45 minutes.

But then as soon as the clock is done, then I can go get a snack or get a lemonade or whatever I want.

That's my reward.

I found that this has helped me immensely as somebody who's easily distracted.

Do you have any other tips or what do you feel about that kind of a gamification system to help you get into deep work?

What I think works about what you're talking about is there's two things going on.

One, having specificity for your duration matters.

Oh, I'm doing this for 45 minutes and then I'm done.

That helps your brain a lot because focusing cognitive focus on an abstract thing, like an idea, it's really hard.

Our brain's like, what are we doing here?

Why are we burning energy on this?

And if you don't have specific boundaries of here's how long I'm going to do it, here's the conversation your brain will have.

Well, this is hard.

We can't do this forever.

We're going to have to take a break at some point.

Why not take the break right now?

And you're like, no, no, no, no, not yet.

And then it's like, well, what about right now?

What about right now?

What about right now?

And then soon that's all you're thinking about.

And then you have to take the break.

But if you say, no, I'm doing it for 25 minutes, where that's when we're taking the break.

That gives clarity to your brain.

The other advantage of what you're doing is that when you're on that focus time horizon, I'm doing doing this just for 45 minutes you don't do the quick checks like oh i'll look at my email and my phone after and we underestimate the damage of those quick checks the way i would generalize this advice if you want to build to the next level of it would be doing something like time blocking so like why not make your whole day have a similar type of mentality where you say here's my workday schedule i'm just going to give every hour a job, every 30 minutes a job.

I'm going to make a plan for my time.

All right.

For the first half hour, I'm doing email.

Then for this 90 minutes, I'm working on this deep work type thing.

And then I have a meeting for one hour and then a 30-minute period where I'm going to clean up notes from that meeting and check back in an email.

Then I have an hour.

I'm just working deeply on this.

You might as well block all of the hours of your working day.

And now the commitment your mind learns is I follow my block schedule.

When am I going to check my email?

When I get to the email block, right now I'm in this block.

And this is what I'm going to do is do that block.

And then when I get to the next block, I'll do what I'm supposed to do in that block.

People who time block plan tend to have, and this is anecdotal, but it bears out over a lot of examples.

They feel like their amount of things accomplished goes up by about a factor of two.

That's the advantage that you get from actually monotasking your entire day with intention, as opposed to just saying, what's next?

And then doing that activity with lots of little quick checks and diversions along the way.

So we time block at my company, the entire company.

And we actually have an activity on Fridays called Friday hour 40, which is the last hour on Friday, where we all sit there and we literally time block our calendars for the next week, including anything personal we need to do, lunch, exercise, work, all the projects.

And then your manager actually reviews it and make sure that you're time blocking the right type of stuff and that you're not overworking and stuff like that.

So we call that Friday hour 40 at our company.

I love that idea.

And it underscores what most companies don't do, which they should, which is there's no transparency in a lot of knowledge work about things like workload and schedule.

I don't need to know how many things you're working on.

Is it a reasonable load or an an unreasonable load?

I'm just going to throw things at you when I have things for you to do.

And I just assume you're going to get everything done.

And when you have some transparency of like, no, this is how much time I have.

And is this schedule reasonable or not?

It makes such a difference.

We're really weird in this sector about how we deal with brain work.

And a lot of places, it's just, hey, let's all just rock and roll.

Like, we'll be on email and pass tasks back and forth to each other and kind of hope it all works out.

I'm a huge advocate.

My new book, Slow Productivity, really gets into this.

Workload transparency, I think, is critical to making work much more sustainable, much less exhausting.

And also, I think it helps organizations be more productive.

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Another core principle you talk about is work rituals.

What is some like common work rituals or ones that you recommend so that people understand this concept as well?

It's hard to go into a state of deep work because it expends a lot of energy and it's unnatural.

It's not something that our Paleolithic forefathers spent a lot of time actually doing.

If you can have a ritual that you consistently tie to the beginning of a deep work session, it helps you glide path into that cognitive state.

A common one is if you can have a physical ritual, like I'm going to get up and I'm going to walk around the block and begin doing that network switch and thinking about what I'm going to do my deep work on and clear my head.

And then when I sit back down, then I start going.

That is much easier than being in your email inbox and just being like, all right, go.

and trying to switch immediately over to doing focus.

Changing your physical space matters.

A lot of people will do something like, I'm going to clean my entire desk off and maybe even change the lighting.

People maybe will turn off overhead lighting and go to just a task light on their desk with a clear desk.

Now that's signaling to their brain, it's time to do deep work.

The most effective methods really have to do with having dual work locations, right?

This is where I do email.

This is where I work on administrative stuff.

And I have another place I go.

just for fully focused work and it's cognitively completely separated.

At my house, for example, we have a home office upstairs and the the printer is there and the filing cabinets are there and got a big monitor there and we can work on admin and household stuff.

Then downstairs, there's a library and there's no permanent computer in there, no permanent electronics or technology in there.

I have a library desk that was made by a company in Maine that specializes in making desks for college libraries.

I'm surrounded by books and I go down there to read and write or do things that are deep.

And I go upstairs.

to work on my taxes.

I keep a clear separation.

If you can do that, that makes a huge difference.

I love to sit outside when I want to do something really deep, but that's not always helpful because if it's raining or something or too hot, then it prevents me from doing the work that I want to do.

But that's a really good idea.

I feel like I've never really implemented that.

So let's move on to slow productivity.

And I want to understand where does deep work fit into all of this?

Was deep work sort of like a seed that grew into slow productivity or is deep work part of the slow productivity framework?

Deep work was diagnosing a specific problem, which was in knowledge work, individuals are undervaluing focus.

Focus produces all the value, so you should practice focus and protect it in your schedule.

Then I had a book a little later, it was called The World Without Email.

It was trying to understand some of the reasons why focus is so hard.

And in particular, it's like, why are we so distracted with email?

Why are we checking inboxes all the time?

And it talked about this is really damaging, this context switching stuff we talked about.

And it tried to imagine how you could rethink communication.

Slow productivity, which you can think was like the third book in this trilogy, was looking at our definition of productivity itself.

So deep work is, here's a thing that you should do that will make you better.

A world without email was, here's a particular thing distracting us, we should be better about.

And slow productivity is like, well, what is our definition of productivity and knowledge work?

And the core insight that kicks off that book is we don't have a very good one.

Part of the reason why we're so exhausted is because we don't have a good measure of this is what we're trying to do.

And because of that, we're running in circles for doing a lot of unnecessary work, what I call pseudo-productivity in the book.

So it really is a much broader look at what do we think productivity means in knowledge work?

Why is that broken?

And what should it be instead?

So let's go deeper on this pseudo productivity.

Why do we have this definition of productivity backwards?

And what is triggering this pseudo-productivity in general?

So basically the story here is you have knowledge work, working in offices, working with your brain.

This becomes a major part of the economy roughly in the mid-20th century.

So it's relatively new.

When it emerged as a major part of the economy, it was a problem for the managerial class because they didn't know how do we manage this type of work.

And this seems like an obvious question, but it was a really complicated question back then because up until that point, management had been invented for factories.

for industrial manufacturing.

And that had a very clear vision of managing, which said a small number of people will figure out the best way to do something they'll break it down into steps and then they'll tell you the worker what steps to do and then they will watch you to make sure you do that step so it's very centralized and very controlled knowledge work comes along and the early advocates of it like peter drucker who coined the term knowledge work in the early 1950s he said look this is very different it's high skilled and creative and autonomous in fact the people doing knowledge work if you're an engineer in like an r d lab or something know more about what they're doing than their managers.

You can't break down knowledge work into an assembly line.

You You can't say, here's the 10 steps, and you're doing step seven.

And he really preached, you got to give a lot of autonomy to the knowledge worker.

They're just going to have to figure out on their own how they do their work.

Well, this was a problem for the managers because they say, well, what do we manage?

If it's not, hey, how many widgets did you produce on this stage of the assembly line?

How do we manage them?

The solution they came up with was pseudo-productivity, which said we will just use visible activity as a proxy for useful effort.

In other words, the busier you seem, the more valuable we'll assume you are.

And that became the standard by which we began to manage knowledge work.

It's like, look, if we need to be more productive, come early, stay late.

It was just trying to roughly translate me seeing you do something is how I'm going to assume that you're creating value.

That was pseudo-productivity.

And it emerged in like the 1950s and 60s as a band-aid to the problem of we don't really know what to measure or how to manage people who are working with their brains.

And I feel like we all know somebody at work that just seems so busy, but never seems to actually get anything done, right?

And if you're a manager and you're not on the ground, that person can get away with seeming like they're highly productive or, you know, a key asset to the team when people who work with them know really that they're not just getting anything done.

They just seem busy.

Can you talk to us about how COVID shed some more light on this even?

If we look at this whole trajectory of why are things worse?

What happened with pseudo-productivity?

The way I argue is that in like the 60s and 70s, 80s, like when this idea became big and office work got big, it was not a great definition of productivity, but it was okay because we could fake it pretty easily.

Yes, we would have to gather in the office and we're like, okay, we know you're here and you're doing stuff, but you just had to basically be careful of like, oh, the boss is walking by.

Change your conversation at the water cooler.

from football to client meetings or make sure you put the magazine down before the boss walks by and we all fall mad men right We're like, yeah, we're all here and we're working and you're having three martinis at lunch or whatever.

You could fake it.

And so it wasn't too exhausting.

Technology, front office technology, beginning with the computer revolution, began to get rid of our ability to fake it.

So I think first what happens is we get personal computers on everyone's desk in knowledge work.

This greatly increased the number of things that people could be doing.

Because it made a lot of tasks, especially more on the administrative or logistical end, like typing or booking travel or submitting reports or crunching the numbers.

It made a bunch of these things just easy enough with software that an individual could do it and you didn't need specialist people to do different things.

So the number of tasks increased, right?

So now we can begin to lay more and more work on people's plates in the idea that if you have more to do than you have time to do, then you'll never have downtime and that'll be more productive.

Then we had the digital communication revolution.

So we got things like email.

Now the granularity at which we could be demonstrating that we were doing effort got really small.

Now, it's not just when my boss walks by twice a day, I should put the magazine down.

It was every time an email comes in is another test of my pseudo-productivity.

I better answer that really quick.

Then we got the mobile computing revolution, laptops and smartphones.

Well, you know, I could be showing effort even outside of work.

And so, I don't know.

I don't think I should sit on this.

I should answer this email on Sunday.

I should bring the phone to my kids' games.

And so, pseudo-productivity, which we could get away with, became increasingly harder and harder to tolerate.

And then the pandemic pushed it over the edge because two things happened.

One, everyone's workload and knowledge work jumped up by 20 or 30%

basically overnight because shifting remote created a lot of logistical administrative hurdles.

So we were right at the edge of we'd filled our plates with so much stuff and it was just too much when we got that extra work all at once.

And then two, because we switched over to virtual meetings, the problem was the smallest granularity at which you could easily create a Zoom meeting was 30 minutes because you're trying to drag it on a calendar.

And a lot of informal back and forth conversations got a full 30 to 60 minute footprint on people's schedules.

And soon people looked up and said, hey, my entire day is in meetings.

And in the 20 minutes I have free outside of that, I have a thousand emails.

I haven't done anything that resembles actual value production cognitive work since 2019.

I think it made it hard for people to ignore.

What are we doing here?

We do not know what productivity means.

So that got worse and worse and worse and worse.

And by the pandemic, people were saying, we have no idea what we're doing.

If we had a reasonable notion of productivity, there's no way that I would be in eight hour Zoom meetings and then answering emails till like midnight.

The lunatics are running the asylum.

We don't know what we're doing here.

And that became impossible to avoid in the pandemic.

My listeners were pounding on my door, proverbially speaking, like this is broken.

And that's when I got the idea, we need to write a book about this.

So there's three principles in your book.

Do fewer things, work at a natural pace, and obsess over quality.

Can you break down those three at a high level?

Yeah.

And this is, by the way, these form together into slow productivity, which is my alternative to pseudo-productivity.

Right.

So this is what works better.

What should our definition be and how should we achieve that?

So slow productivity says let's care about what you produce and how good it is and not how much effort you're showing.

So those three principles support that notion of productivity.

Do fewer things at a high level is arguing, do fewer things at the same time.

If you do fewer things at the same time, so the number of things I'm actively working on, if I reduce that, not only will my work become more sustainable, but the number of things I finish on a quarter or year is going to go up.

The second principle, work at a natural pace, has two ideas to it.

But at its core is saying, one, this idea that we can be working with full focus all out, all day, all week, all month, all year is super ahistorical and super non-natural and it burns people out.

We need way more variation on different time scales of hard and easy, hard periods, recovery periods, hard seasons, easier periods.

That's more what we're wired for.

The second piece of that is also we're delusional about how long we think things should take.

We're like, yeah, I'll get that done in a week where we really should be giving it three weeks.

Like we need to chill out and be way more generous to ourselves and realistic about how long things take and just slow down.

Let good results aggregate over time and just take the frenzy out of it.

And then the final piece says none of that works unless you really, really care about producing really good stuff.

If you care about how good your stuff is, you are going to increasingly find pseudo-productivity to be intolerable because it gets in the way of producing good work.

And if you get better at things, you'll gain more freedom and flexibility to get rid of pseudo-productivity.

The better you get, the more say you get in what your work actually looks like.

So that's the engine that drives the whole thing.

So let's start off with doing fewer things.

I think a lot of people have trouble saying no, especially if you're in your early or mid-career, mid-career, you want to show that you're going to roll up your sleeves, you're going to do what your boss says.

So to all the folks out there that are growing their career, how can they really say no and do fewer things?

Well, first of all, people say no all the time.

It's a common issue.

People imagine that they never say no.

And that if they look at advice like do reviewing things, they're going to, for the first time in their career, start saying no.

But this, I think, is, of course, nonsense because look at most people's schedules.

What are most people's schedules like?

Like they're doing 20% too much.

So it exactly fills their work week with a little bit of work that they need to do outside of their work week.

It would be an incredible coincidence if the exact amount of work that was pushed at you exactly fill your work week plus a little bit more.

It's as if everyone who's sending work to you, they're all sitting around studying your schedule and trying to figure out how much work.

No, what's really happening is you are saying no, you might not say it so explicitly, but your implicit rule for doing so is stress.

That's what most people actually do.

They wait until they're so overloaded that their stress gives them psychological cover to start pushing back.

Like, well, I feel bad about not taking on this project, but I'm so stressed about how much I have to do, I'm willing to make that trade-off.

So what most people end up then is just in a schedule that's regulated to be just a little bit too much and everyone's in a constant state of stress.

What I'm really advocating is you go from doing 20% too much to 20% below your capacity.

To the outside world, the difference between those two is negligible.

They don't know, are you at 120% or 80%?

I don't know.

That difference, how do I know?

I'm not tracking your workload.

You're saying yes to a lot of stuff.

You're saying no to some stuff.

But for you as an individual, that could be a completely different experience.

So I start by saying that you are saying no.

So you might as well just tweak that threshold at which you begin to think, okay, I need to start pushing back.

You're already doing it.

You need to start doing it a little bit earlier.

In the book, you list some activities that you can do to help yourself organize your to-do lists and your priorities.

And you talk about the push and pull system.

Can you talk to us about the difference between the two and how we can incorporate more of a push system?

Well, it's one of the ways that we get overloaded is that we have an implicit push metaphor for work assignment.

So the push metaphor is when someone needs you to do something, they push it onto your plate.

They send you an email.

Hey, can you do this?

Here you go.

The problem with the push approach to workload is that there's no control over how much stuff is on your plate because I don't know what you're doing when I'm pushing something towards you.

I just want to get this off my plate and you seem like the right person to do it.

It leads to overload, it leads to people having to wait until, like we just talked about, they're so stressed about their workload that they finally feel covered to push back.

The pull methodology is very different, and this comes out of industrial manufacturing.

The pull methodology says the stuff that needs to be done is over here, it's not on my plate, it's over here.

We don't want to forget it, but I'm not working on it yet.

When I'm done with whatever I'm working on, I will go pull something else in from that list.

So, in this way, I'm only ever working on a small number of things at a time, right?

Because Because I don't pull something in until I'm done.

The huge insight from industrial manufacturing processes is actually this pull methodology produces more stuff than the push.

Because what happens is I'm working at exactly the right capacity for me, and I'm avoiding all of the overhead.

When you have conflicting overhead, it slows you down.

So in knowledge work in particular, what happens with if you're not doing a pull methodology, it's not like I'm a computer processor that can just switch cleanly between the different tasks on my plate and then they all will get done at some sort of proportional speed.

Everything you tell me to do that I've agreed to do brings with it administrative overhead, like emails I have to answer and meetings I have to attend.

And that's fixed.

Once I'm working on something, that's a fixed cost I have to pay.

So if you give me 10 different things I have to work on at the same time, I have 10 times that amount of emails and meetings, but my workday is fixed.

So what happens is eventually is that most of my time is spent just dealing with that administrative overhead, which means I'm exhausted.

I'm switching my context back and forth, and very little time is left to actually do the work.

So the rate at which anything gets finished is very, very slow.

By contrast, if I'm just pulling one thing in at a time to work on, most of my day would be working on that.

The administrative overhead of just one thing takes up a little bit of time and I'm going to finish that thing fast.

And then I can pull the next thing and then finish that thing fast.

So a pull methodology for workload management actually finishes a lot more work than a push methodology, but it's a little bit more complicated.

Push is easy.

I just email something when I think about it and then it's off my plate, but it really creates, I think, a productivity disaster.

Yeah, it's more reactive, right?

You're just reacting, reacting.

You're not considering what's actually the most important thing to do.

It's just the most recent thing that came on your plate and you're going to do it.

And that could actually hurt you in the future because you're not getting the things done that are actually the most urgent and the most important.

So we want to do the pull system.

So anytime somebody gives us an assignment, put it on the push list, pull that when you're actually ready to work on it, prioritize it, pull that.

Is that right?

Yeah.

And so if you can do this at the team level, it's fantastic.

So at the team level, you should have a centralized place where the things the team needs to do is stored.

And it's not on an individual's plate.

It's in the centralized list and it could be like a Trello board or a shared document, like the technology doesn't matter.

And then you have these synchronizing meetings.

They can be every day.

They can be every other day where you say, okay, who's working on what?

Who's done?

Great.

What do you want to pull next from our centralized list of things to do?

And what do you need from the rest of us to get this done?

Great, go do it.

That is a fantastic setup.

Now, you can do this as an individual as well.

You have to simulate it though.

So if you're an individual and people are pushing work at you, you can put this work on a queue.

It could be in a Google Doc or something.

Make it public to anyone in your organization.

And then only mark the last three things on this queue as things that you're actively working on.

And so if someone's like, hey, what's going on with this thing?

I haven't heard from you.

Can we have a meeting about it?

You can just point them to that queue.

Be like, yeah, it's in position seven.

And once it makes it into these top three spots, it's going to get my full attention.

And I'm going to call you, and we're going to set up a meeting, and this thing's going to get done, but I only work on three things at a time.

And you're happy to track it.

Oh, and if you're my boss, you're happy to tell me to make swaps.

Sure.

If this is more important, tell me what to swap it within the list, whatever you want to do.

But this is what I'm working on.

These are the only things I'm actively working on.

And I'll pull something new to the active status once I finish one of them.

So you can even simulate push-pull as an individual.

I detail that whole system in the book.

It seems like, oh, what a pain, right?

Isn't it just easier just to email people or whatever?

But it is a substantial, significant, almost astonishing difference to be working on a small number of things at a time makes you so much better at working than trying to juggle multiple things.

This myth we tell each other that the more things I'm working on, the more productive I am is just absolute nonsense.

If there's a number above your head, that says, what's the rate at which you're finishing things?

That's the key productivity metric, right?

What's the rate at which you're finishing things things that matter?

You can imagine that number gets higher as you take on a few things.

And then as you continue to take on things, that number begins to go down and you're trying to optimize that number.

So this is, it's so critical when you're trying to sell this to other people in your organization.

This is not just about making my life easier.

This is about making me more valuable for this organization.

I will produce more stuff.

if I can pull when I'm ready and not just let anyone push when they're ready.

Yeah, because you need time to focus on the deep work projects that need a lot of focus.

And it's also going to help company culture.

I mean, I've been running a company now for over five years.

And I think the biggest complaint that I ever get from employees is if they have complaints is, I don't know what my priorities are.

I feel overloaded.

That's always the same complaints from employees.

And it's just because they need a way to have their priorities being established for them and not feeling like they have to work at everything at the same time, right?

That's everybody's problem.

They feel like they need to work on all these projects at the same time, but really they just need to work on them one by one.

And you also say one big project a day, right?

So to an entrepreneur, I'm like, I don't know if I could only work on one big thing a day, but talk to us about why you believe just one big project a day.

Otherwise, you're going to muddle up your cognitive context.

So if you have three big projects you're working on and you're trying to switch between those three in the same day, it's too much switching.

Your brain can really get into the one and think about it and make progress.

But if you try to switch it to a bunch of different projects you never really settle into any i learned this as a grad student my doctoral advisor said the right way to write papers the way she wrote papers is work on one academic paper and make it great and then when you're done move on to the next i was impatient right because i'm a doctoral student i'm like look i got to publish to get hired as a professor i'm going to work on three or four papers at the same time because i'm going to get more done.

Well, it turned out she was right.

In the end, the number of papers you publish per year, whatever metric you want to use, it doesn't go up when you work on three or four at the same time because you're switching back and forth so much, it's hard to make progress on any of them.

And her method, which seems slow in the short term, like, no, I'm just sticking with this paper, produces better papers.

And then you finish each one faster and you get more done.

So yeah, it feels really slow in the context of a day.

Like there's only one major project I want to touch on.

But if you zoom out to a context of a quarter, you're going to say, oh, I got more major projects done by being more sequential.

And let's be honest with ourselves, when our to-do list is so long, we get overwhelmed.

We end up doing the easy stuff and we actually don't accomplish a big project in the day.

And then it just goes on to the next day, to the next day, to the next day.

So I feel like if we can hold ourselves accountable to just doing one really important hard thing every day, we actually, to your point, we'll get more done.

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So let's talk about natural pacing.

We talked about seasonality.

We talked about time batching and things like that.

What are the other ways that we can ensure that we have a natural pace in the way that we produce our work?

Another thing to keep in mind is your initial estimates of how long something's going to is probably off by a factor of two.

I think it's probably a brain wiring reason.

There are certain things our brains as a species are wired to be really good at predicting.

Like there's certain physical things I can predict really well trajectories and like this rock is going to roll down this hill and I'm walking this way.

It's going to hit me.

Like we're really good at that.

We're very bad at predicting the time required to do abstract cognitive work because it's just not something that was, there's not a relevant skill.

Like being good at predicting how long it's going to take you to empty an email inbox did not help Paleolithic hunter-gatherer survive.

So we're really not good at it.

So what we do when we try to think through a schedule, our default tendency is fairy tale thinking.

We write a fairy tale about what if I could get this done this fast?

And then we get really excited about that possibility.

Wow, that would be great.

If I finished this book chapter by the end of this week, like I'd really be on schedule.

Well, I really want that to be true now because it makes me really happy just thinking about it.

Great.

I think this is going to take me a a week.

So we write these like best case scenario fairy tales that make us happy, but are completely unrealistic.

And then we, of course, don't hit them and we fall into chaos.

So I advise slow down.

Hey, I think I could get this done in a week.

Great.

Let me give myself two and a half to do it.

Just naturally give yourself way more breathing room.

And a lot of that part of the book.

is me telling stories of famous personalities from traditional knowledge workers, scientists, poets, writers, people who use their brain for a living back historically, who we think of today as super productive because they did all this great work.

It's like very impressive.

And a lot of it is going back and looking at their diaries and their day-to-day schedules and saying, look how slow they went by our standards.

They were happy.

They're like, I'm going to work on this over the next few years.

I talk about like Mary Curie, who's honing in on isolating radium, for which she would win her first of two different Nobel prizes.

And summertime comes along.

And she's like, yeah, we're going to go to the French countryside for two months and we need a family vacation.

This is a good thing to do.

And then she came back and let's work on this some more.

We don't know that now, looking back through hindsight, we're like, wow, she got two Nobel Prizes.

She did lots of great work.

She took her time.

Galileo took his time.

Newton took his whole life before he finally pulled together all of his ideas into Prosimpia Mathematica.

This is a big thing: we need to let ourselves off the hook of these ideas of these fairy tales about, in theory, in a perfect world, if there was no distractions and everything happened just right.

In theory, I could get these things done this fast.

Why are we trying to accomplish like hit these almost impossible marks when it doesn't really make a difference difference long term?

What matters long term is steady progress on things that matter.

So I think people should take more time doing things and be okay with it.

I get all these conflicting advices on the podcast.

I just interviewed Benjamin Hardy, whom I'm sure you know about.

And he was talking about this concept of setting impossible goals and moving up your deadlines to always be tighter so that you can think of new pathways of thinking, more creative thinking.

And that sometimes, especially when it comes to really big goals, if you set a shorter deadline, it will force you to think more creatively to get the actual goal rather than thinking more incrementally where you're solving all these different steps that might take 10 years.

What about if you did it in three years?

How can you go straight to your goal instead of solving all these incremental steps that actually don't directly impact your goal?

What are your thoughts about that?

And then the other devil's advocate thing I'll say is with AI, now we're all pressed to do more and do more faster because we all have an assistant, essentially, and a second brain almost.

So how do we grapple with those things?

I'll put AI aside for now because I sort of have my own take on it because I think there's a lot of vibe forecasting and hype.

And I think he's hitting on a really good point here.

There's different ways to act on this point.

So he is getting at the point of we have to worry about analysis paralysis.

We have to worry about perfectionism and procrastination.

These are all issues that come in when you begin to slow down.

They're also issues that come in when you begin to obsess over quality.

Both of these can cause these roadblocks.

So if you're like, look, I'm going to chill out and take my time.

You have the roadblock of I might just make that time be forever.

I've been working on my novel for the last 30 years.

I'm never going to finish it.

I would set a two and a half week deadline and then do it in the last two days, you know?

So you got to keep yourself accountable.

Yeah.

So there's that issue.

And then if you start caring too much about quality, there's the issue of I am working on it every day, but I never think it's good enough.

But putting the perfectionism aside, if we look at the procrastination issue, I think of this more as a time management issue and I think of it it more as a psychology management issue.

So A, a time management issue is, do you have a proper, what I call multi-scale plan where you're connecting your quarterly and annual goals with your plan for the week and your plan with the week for the plan for the day.

And if you have a good system going like that, then you should basically have a plan in advance about here's when I'm working on this.

And when you get there, you do the work on it.

So I think a good multi-scale time management.

gets rid of the scenarios you're talking about where it's like, I don't know, I'm just giving myself a deadline.

I don't know how long it's going to take or when I'm going to work on it.

Then Then of course you're going to wait till you're close to a deadline and then just do what it takes.

But multi-scale time management, I think, can take some of that pressure off of what you're doing.

The psychology aspect of this is the more you understand what it is you're doing, how people succeed in this thing, and the more your brain trusts that your plan is probably going to lead to the goal that you really want.

the more realistic your plans come and the less problems you have with procrastination.

So that's the other thing I push.

I run into a lot of aspiring writers, for example, who seem to be very purposefully not trying to learn about how the world of writing works.

They don't want to find some reality that they don't want to hear.

They've written a story for themselves about this is how I should become a writer.

Here is how I want it to work.

And often it's completely at odds with reality.

And they'll sort of write for a while and drift off.

Whereas if you know, oh, I know exactly how the publishing industry works.

I've talked to people.

I know what the next step would be.

I know.

how good would I have to be to get past this step and what type of effort will get me there and how do I measure it?

When it's that clear, it's much more easy to take regular effort on something because your brain trusts what we're going to do matters.

So I tend to emphasize less having bigger goals than I do having more realistic understanding of your goals and control over your time.

I think that's what allows you to more consistently make practical progress on things that could be pretty cool in the long term.

But if we're, let's say, doubling our timelines of when we're doing something, do you feel like that would make us lazy in terms of trying to figure out how to solve these problems better and faster moving forward.

If I gave myself the amount of time, I wouldn't have to think about how I use AI or how I use different tools or if there's a better way to do what I'm doing because I've given myself so much time.

I think that's a time management problem.

So there's the problem of how do I work on a regular basis on a project?

And there's the problem of how do I figure out how much time I'll need once I'm working on a regular basis on a project.

And I think there are two different problems.

So if you're not working on something at all until like maybe you get near a deadline, then there's one of two things going on.

Either you don't really want to do that project or your brain doesn't trust that you know how to do that project.

You came up with some big goal, but your brain's like, you don't know how to make progress on that.

And I'm not just going to sit here and let you just like do stuff.

I know we're just doing make work.

So let's just not do anything.

Or it's a time management problem where your days are reactive and chaotic.

And so something that's non-urgent but important is not going to enter your screen until like you get to some sort of deadline.

Like, oh, now I'm going to stop everything else and do this just long enough before I have to come back and catch up on everything else.

And to me, that's a time time management problem that you don't want to have too many things you're working on.

And the things you have to work on, you should be working regularly.

And then where my advice comes in is if you have that control over your time to work regularly on things, instead of trying to be like, let's do four hours a day every day and try to get this done in a month, be like, actually, let's do three days a week.

We'll have a good three-hour period.

And if this takes two months, that's going to be a more sustainable pace.

So it's a really good question because I think these are two different points.

How do I work regularly on things that matter?

And then how do I set the pace on work once I can trust myself to actually do it?

And that's where I think we need to slow down a little bit.

How can we get actually better at understanding how much time a specific task will actually take?

Multi-scale planning.

With multi-scale planning, the three scales I use typically is a quarterly or seasonal plan, like this is what I want to do this summer, this fall.

A weekly plan, like here's what's going on this week.

Let me look at the week ahead.

And a daily plan or I'm time blocking, like what do I want to do with my time?

At each of those scales, you only look at the previous scale.

So when I'm building my weekly plan, that's when I look at my quarterly plan, not every day.

And when I'm building my daily plan, I'll just look at my weekly plan.

So that's multi-scale planning.

It gives you a lot of feedback at different scales.

So at the scale of quarters, when you come to your next quarter, you look back at the things you planned for the last one, like, man, I only got one of these three things done.

I'm learning.

This is too ambitious.

I can't write the book and overhaul the company's marketing portal and redo our social strategy.

That was way too much.

I actually don't have enough time to do all three of those things.

So now I'm learning from that feedback of what actually happened at the last unit of the scale.

I should really just choose one of these things per quarter.

When you're on the weekly scale, now you're getting more feedback, like how much work on these sort of big initiatives can I really fit into a typical week?

Because when you build your weekly plan, part of what you do is make sure that you put aside a protected time for your big quarterly plans in your week so that you don't have to just in the moment be like, hey, I want to to work on this big plan.

And this makes you confront realistically how much time you actually have on your schedule to work on these sort of non-urgent, important things.

It's where most people, the epiphany they have in their weekly plan is I have too many meetings and appointments.

Because when they're trying to say, when am I going to make progress on my big initiatives for the quarter?

My God, every day is fractured.

I have no time to do this, right?

So you get this reality check on.

what do my weeks look like?

And then when you're working on a daily time block plan, you get really clear feedback on how long specific tasks take.

So it's where you learn, oh, this idea that I can just check my inbox for 30 minutes at noon and be done is nonsense.

It takes me two hours.

Okay, day after day, I watch myself blow past this time block.

I know how long that takes, or I give myself this two hours to write, but you know what?

I'm learning.

I blow past it because it takes me a half hour just to get warmed up.

And now I'm learning how long, how much time I need each day.

So multi-scale planning gives you feedback on multiple time scales and it makes you a world expert on you and how long your work takes and what your schedule is really like.

I feel like a great way to round out this concept of working more naturally towards your natural rhythm is you've got this phrase, work poetically.

Can you talk to us about how we can work more poetically?

It's an idea that helps your work be less industrialized and grim.

It says care about things like your location, care about things like ritual, find a way to find in certain types of your work, like a real meaning to it.

I mean, if there's a lot of administrative emailing going back and forth and it's kind of grim, maybe what we want to do is, no, we can have a staff meeting and we do it and there's donuts from this place we love and someone else is always in charge of the coffee and it takes an hour and it's fun and it's social.

And we sit there, we put stuff up and we figure out all the things there.

And it saves us all this just grimly emailing on like whatever.

Or like my wife tonight's going to a planning meeting with a woman's group she's in.

And they're like, you know what?

We're going to do it over drinks.

That's like kind of nice.

It's like, yeah, it's, it's planning, but it's going to be fun and kind of so like that can matter.

We talked about having a different location for different types of work.

I think that's nice.

Like, look, I'm going to go, I have a gazebo.

Like, I'm going to go out there.

And I bring when I work on my marketing strategy stuff, I'm going to just go out there and be outside and hear nature.

And if it's raining, I'm sort of drying there.

And it's going to be like more poetic.

I'm going to go on a long walk.

I do a lot of thinking on foot, for example.

That's very poetic.

I like to take a notebook with me, a field note notebook in my pocket and walk on nature trails and work out whatever it is I'm working on.

So finding more ways to add the poetic into your daily work makes it less of this sort of fluorescent lit, grim industrial grind and it makes it more sustainable.

I love that.

And then I love actionable advice on this podcast.

So what is one experiment that somebody could do right now to kind of simplify all the obligations that they have to do?

Do a weekly survey and plan.

Friday into work or Monday beginning to work is the right time to do this.

Look at your week ahead, look at your calendar and get a sense of, okay, how much free time do I have?

And when is this free time, first of all?

So you're going to get a real reality check of, man, these days are really crowded or fragmented or whatever.

Then look at this and be like, what are the minimum changes I can make to some of these appointments or standing things that would make the biggest difference?

And almost always you're going to realize, you know what, there's some small changes here that could really make a difference.

Like this crosstown meeting that's on like Tuesday and Thursday mornings is destroying those mornings.

If I could find a way not to do that or to make it virtual at the end of the day, I have two three-hour blocks that have just freed up and then I can claim those back for deep work.

Or I have seven standing meetings.

Well, wait a second.

These standing meetings are just standing in for people actually having reasonable productivity systems.

Like it's not my job to help you make progress on projects.

Don't put a repeating meeting on the calendar.

Have a time management system.

If I could get rid of four of these, so you begin to get insights when you look at your calendar at the weekly basis and say, what would make this calendar less stressful?

And it leads to, I call it a meta-productivity tactic because it leads to all sorts of other more concrete changes.

And now you begin protecting the mornings.

You have a rule about like, I don't do meetings on Monday and Friday afternoons.

Like you begin to see.

What are the smallest things that could make the biggest difference?

And so it's like a laboratory for learning how to improve your own schedule.

The calendar is a fantastic feedback tool.

And the weekly scale is a great scale at which to actually analyze this tool.

So your third principle is all about obsessing over quality.

Talk to us more about this principle.

What are some of the things that we can do to ensure that we have super high quality?

What are some of the challenges that people typically face?

So if you're really good at what you do and you care about getting better at what you do, the two things that happen is one, pseudo-productivity and busyness becomes increasingly intolerable.

So you become motivated to act on the two principles we already talked about, doing fewer things and working at a natural pace, because you begin to realize, oh my God, being busy gets in the way of doing this well.

These crazy schedules gets in the way of doing this well.

And I really want to do this well.

So it puts your mind into a slow productivity mindset and makes you feel more comfortable about leaving pseudo productivity because you have something else you're moving towards that you think is going to be even more successful.

And without that, this could be a problem for a lot of people, some of these other ideas, because they think, this is just about making me worse at my job.

I'm really nervous about this.

It's easy to fall into a mindset of, look, I want to do less things and slow down.

And they see it like a labor conflict debate.

Like, look, it's me fighting with management to make my life easier at the expense of making me less valuable to my company.

But you know what?

We have to have this fight.

That's a hard psychological place to be.

But when you begin obsessing over quality, you're like, no, no, I'm leaving pseudo-productivity not just to like make my life better.

This is a different model of being valuable.

I feel more comfortable and confident pushing and pulling differently and having, you know, weekly plans because I'm heading towards this thing.

It's going to be really good for me in my career as well.

The other thing that happens is as you get better at things, because you obsess over quality, you get more leverage.

So now the levers you have the pull, the reduced busyness,

get more numerous.

The better you are, the more you can negotiate, the more leverage and autonomy you have about how your work's going to unfold.

So it's like a self-reinforcing cycle that I think is really important.

So like what people need to do, and it's easier said than done, figure out what is the thing I do or the small number of things I do that is most unambiguously valuable to the market.

How do I do those better?

And that's what really matters.

What can I do that's valuable?

Answering emails by itself is not valuable.

Being busy by itself doesn't actually produce value.

No client actually pays you for how many times you opened an inbox or how frantic you were, your heart rate going up or your indicators of stress going up, heart rate variability jumping off the scale.

That doesn't directly get translated into how much revenue comes into the company.

company what matters is the things i produce that are unambiguously rare and valuable and everyone needs to identify in my current stage of career what are those things and then how do i get better at them that's the mindset of quality obsession one more question about slow productivity and then i want to just get into ai and your thoughts about ai since you mentioned you have a lot of thoughts about it when it comes to all the ways that we communicate right we've got to respond to emails we've got to respond to slack what is your guidance in terms of consolidating that type of stuff or saving time when it comes to having to communicate with your team, which is really important, but can take up your schedule?

My big argument is you have to change the way that you think about collaboration to try to minimize a very specific thing, which is unscheduled messages that require a response.

That is the killer.

Unscheduled messages that require a response is the killer of attention because what happens is, is if we're just working things out with back and forth emails or Slacks, just a bunch of unscheduled messages, we're ping-ponging back and forth to try to figure something out.

That is going to demand that I check my inbox or chat channels constantly.

Because if we're trying to work things out with these unscheduled messages, there might be 10 messages that have to go back and forth for us to reach a decision by the end of the day.

And maybe we need to make this decision by the end of the day.

Well, if we're going to have to get 10 messages back and forth, I better see your next message.

immediately after it gets here.

So we have time for all of these messages to make it back and forth today.

Well, if I have to see your next message immediately, I got to check my inbox all the time so that I'll see it as soon as it arrives.

This is what causes the constant inbox and chat channel checking is that we have these ongoing back and forth interactions that are unfold with these sort of unscheduled messages that require responses.

Once that's the way you collaborate, there is no way to avoid having to check channels all the time and constantly be distracted.

You can't fix that problem by having rules about when you check your email.

You can't fix that problem by having norms in your company about when to expect responses.

If we're going to figure things out with back and forth messages, I have to check my inbox.

So my big argument is you have to find alternative ways to collaborate that isn't based on just sending messages back and forth.

And this is where things like office hours make a big deal.

If you have a question for me that I can't answer with one message, come to my daily office hours.

You can call me.

You can log into a Zoom room that's always open or come to my office.

It's an hour every day at the same time.

Just give me a call.

We'll work it out in real-time conversation right then.

So I think like group docket clearing meetings really matter.

Okay, if there's things our team needs to work on or a group needs to work on, we add them to a shared document.

Every other day, we all get together, we look at this document, we go through the things one by one.

We say, which of these things need to be done, who's doing it, what do you need and who do you need it by?

Okay, everyone, put that down, you know what they need from you, great.

We have just in one hour gotten through things that might have generated 100 back and forth messages, which in turn would have generated over our team of 10, something like 10,000 different inbox checks.

So to me, it's not about...

what you do with the messages that are already in your inbox.

It's about preventing urgent, non-scheduled messages from getting your inbox in the first place.

Alternative collaboration structures and processes is the entire ballgame, I really think, or at least the most important first step if you want to transform your organization away from this constant, conflicted, exhausting, burnout-inducing distraction.

Yeah, I'm like shaking my head vigorously because it's like triggered me because I've got culprits for sure in my organization that always, even though there's other channels, they always just shoot, even though I'm the CEO, they'll like shoot me a message.

And I'm somebody who likes to respond I'm a people pleaser so I'll just respond right away and then before I know it I'm like oh man I'm five minutes late to this meeting or I missed doing what I was supposed to do because I was answering this unscheduled message some of the things that we do that might be helpful for our listeners is that every manager has a review channel in slack and there's a certain template that people have to use so for me whenever I have downtime or I actually schedule it sometimes anything that my team needs me to review is neatly organized in a Slack channel rather than 20 different messages direct direct DMs.

They know the format.

They know that I'm only going to check it when I have time.

And they've got to think it through.

They can't just write me a random message that they haven't thought through.

They need to think, when is it due?

Is it urgent?

Here's the link to whatever you need to review and so on.

So that has worked super well for us.

The other thing I'll just mention is if you have a sales team.

For us, we do this daily meeting called Deal Desk.

And essentially, it's like some meeting that I made up that, again, has like a format of these are the pieces of information we need to know.

And it's a place for me to just review everything from my team in just 30 minutes every single day.

And then I don't talk to them the rest of the day.

It's like, you know, that at this meeting, any sort of blocker that you have, you bring it, you have a format, we go over it.

And then that's it.

If you have another problem, I'm here tomorrow for 30 minutes for you to ask me what to do.

Perfect.

That's exactly what more organizations should do.

Exactly these type of ideas.

Or the thing you do with the Slack channel.

The other way to do it is you have a reverse task list.

Like, hey, here's a shared document.

It's my task list.

You have to put the stuff on it and it has to have all these details.

And when you do that, now you have to confront how many other things are on my plate and you get a realistic sense and removal meetings.

Like, this stuff is fantastic.

It's exactly what more organizations should do.

But the default pressure is towards that's hard, there's rough edges.

And the easiest thing to do is to put everyone on Slack and email and just rock and roll.

That is the default.

I call it the hyperactive hive mind in one of my books.

That is the default mode of collaboration.

And to me, it's the productivity equivalent of going around everyone's desk every hour and being like, hey, take a shot of whiskey.

It has the same impact on people's ability to think clearly and their energy or whatever.

Might be fun in the moment, but long term, it's not going to be good.

Such great advice.

I feel like anybody who runs an organization or even is who's an individual contributor has learned so much in this conversation.

So the elephant in the room is AI.

We all have.

AI at our fingertips now.

I personally use ChatGPT for almost everything that I do.

It's something that I just have open all day.

Every email, every contract, pretty much every single project that I use now, I do it with AI.

Talk to us about how you see AI shaping the future of work and productivity.

It's a topic I've been tracking closely as, especially my journalists who work for the New Yorker.

I'm like their resident computer scientist.

So AI is something I've been tracking carefully of a lot of sources in the industry and academia.

I just finished a large piece actually for my personal site on where is AI in business right now and where is is it going based on everything that I've been following the last year or two.

So, okay, I had some summaries of what's working now, what's coming, what might work and what's not going to work.

What's working right now is thinking of some sort of supercharged search service, right?

And by supercharged, I mean a couple of things.

One, when you need information that exists out there on the web, increasingly people turn to chatbots instead of a tool like Google, because it can not only do searches, but it can do interpretation and format change of the information for you.

So you can say, not only I'm interested in this, it can summarize just what you care about.

You don't have to get that out of a web page.

It can put in the formats that are useful.

So really like a supercharged search, but also internally, right?

So you can give it your own documents, your own emails.

You can say, hey, check through this.

Do you see any problems?

Can you spell check this for me?

Am I getting this terminology right based on like what you've read before?

So like your own information, you can interact with your own information as well as interact with this about information that's out there.

This is a huge business opportunity.

I think it's probably the number one use of these tools in the professional context right now.

I do think this is a big leap forward.

I talked about in the article, even just web search and Google, this is something like a $175 billion a year business.

And so there's a huge amount of money on the table that if chatbots can take and expand that, that is, I think, the clearest route that a company like OpenAI probably has the profitability.

Something that's coming that's not here yet, but I think it's going to be a really big difference maker is also going to be natural language interfacing to existing software.

So, one of the things these language models are good at is not just outputting good stuff, but understanding what you're asking.

That's super valuable.

So, there's a big push right now to have on-device models, some much smaller models that you can just run on your phone or computer.

So, it's much cheaper and much faster, that can act as a natural language interface between you and existing software.

So, now I won't have to master Microsoft Excel.

I can just say, hey, can you go through column B, delete every row where the dollar amount is less than $5?

Then I want you to sort the whole thing on that column and then create a chart where the X axis is the amount and the Y axis is this.

And then you look at it, like, can you make it red though instead of whatever?

It's going to unlock.

It's not sexy from if you're like Sam Altman, but it's incredibly productivity enhancing.

It's going to allow amateur users to get expert utility out of existing software.

So that's coming really soon as well.

And that's going to be a really big bump.

When it it comes to agentic software, so this is like the big push that a lot of the AI companies and particularly Sem Altman and OpenAI are like, look, we're going to be able to automate big portions of your job in the future.

And in fact, this is the argument for like lots of jobs are going to be outsourced.

They're struggling a lot more with that than they want to admit.

They were sort of hoping.

So what was happening was this hope that as they increasingly scaled the size of the parameters and data on which language models were training, they were hoping that this would continue to just increase the general capability of language models.

And then like a GPT-5 or a GPT-6 could be the foundation of like an agent to do almost anything in your job.

The scaling has petered out.

They're not getting the same improvements they got from two to three through and three to four.

They're finding that the scaling laws are starting to falter.

And so now to get extra capability out of language models, they're doing reinforcement training on specific tasks like coding or contrived reasoning or mathematics problems where they have very specific synthetic data sets.

This is a much harder game of whackable.

So So, I think the progress on the ability of models to do stuff that they can't do now, that progress is going to be more piecemeal and slower than people realize because the AI CEOs are basically obfuscating this and making crazy predictions to try to distract investors from this reality.

So, I don't see us about the fall into a future in a year from now where AI has massive new capabilities compared to what it is now.

I think we're actually at a sort of slowing down point.

So, we're not going to automate huge swaths of knowledge work anytime soon.

And then, things like AGI and super intelligence, I think there's a huge amount of hot air there.

And we can get into that separately.

But I do think the super search, that's the battle.

I can search and have AI search and understand external information and process and make sense of my internal information, written information.

This is a massive market and the natural language interfaces.

So I think AI is going to be transformative.

I don't think, though, that this talk we see out of these AI companies about existential threat or even massive economic shakeups that we're not going to know how to recover from.

I think a lot of this is CEOs of these companies that are trying to distract their investors from the fact that we're not making nearly enough profits yet.

Oh my gosh, this is so relieving to hear.

I interview a lot of AI people.

So I just had Nick Bollstrom on, who wrote Super Intelligence.

I had Mustafa Suleiman, who's the CEO of Microsoft AI.

Stephen Wolverine.

I've had every AI person on the show, and it's been really scary.

So talk to us about AGI superintelligence.

Tell us why it's not going to happen because that has become like a huge fear of mine, especially since I always hear the worst of it, I feel like, with all these AI experts that I talk to.

Hopefully, this is comforting, but there's a huge intersection split in the technology world.

And it's really interesting where I call it like the West Coast, East Coast school.

The people in Silicon Valley or adjacent to Silicon Valley, like every name you just mentioned, right?

They are almost off the rails convinced that there's these massive massive changes happening tomorrow.

It's like a religion.

The academic community, the world's experts on AI working on this technology, where all these ideas come from, are incredibly lower blood pressure.

Also, including when I talk off the record with big engineers at some of these companies too, incredibly lower blood pressure.

Like, no, of course, none of that stuff's about to happen.

Like Fei Fei Lee, for example, I feel like was more lax about everything that was happening.

Yeah.

So there's a split between Silicon Valley and non-Silicon Valley academic experts who work on this topic, right?

I honestly think there's going to be a reckoning in a couple of years from now where they're going to look at tech journalism from this period and be like, we're going to teach this in journalism schools of all these tech reporters that just went along with what Dario and Sam and Nick and all this huge hype they were saying, all these journalists that just went along with it.

And the problem is, is a lot of this is what I call vibe forecasting, which is, look, the vibe is this stuff got a lot better over the last few years.

So it makes sense to me that it could get further better in this way.

That story makes sense to me, but it's not technology forecasting.

So what the academic researchers say is, whatever, tell me what is the system that's going to do this thing?

What capabilities do we lack right now that we need for that system to work?

And why do we think those capabilities are going to be solved within this timeline you're talking about?

None of these predictions are doing that.

Here's what's really happening in the industry, right?

Is the scaling laws have faltered, right?

So again, the original idea for AGI was GPT-4, for example, was better on almost everything than GPT-3.

And it got better by just making it bigger and training on more data.

GPT-3 was better on everything as compared to GPT-2.

And the difference was they just made it bigger, they trained it on more data.

So there is this idea that we'll just be able to keep scaling that way.

So no, GPT-4, you can't build AGI on.

And you can't automate most work tasks with it, but maybe GPT-5, yes, or maybe GPT-6.

But the progress faltered after around this GPT-4 time.

That's why there has been no GPT-5 released.

It's why Meta had to announce last month that their BMIT model, which was going to be their equivalent, they said it wasn't better enough compared to the last models, even though it was much bigger and they delayed its release.

It's why the latest Grok was incrementally better than the Grok before, even though they 10x the size of it.

So the scaling laws, they can't get to AGI.

just by making these models bigger.

And where all of the energy is now in the field is tuning existing native base models for specific tasks.

And so you see these big accomplishments, like, look, they're really good at this type of coding or it can do this type of reasoning now.

But what you're not seeing is they're having the cherry-pick now particular capabilities for which you can build these very specific synthetic data sets you need to do that training.

So like programming is something you can fine-tune GPT-4 to do really well at and call it, you know, whatever, because you can have a lot of programming examples and you can check whether or not an answer is right or wrong by actually running it or whatever.

The GPT-O models that are good at reasoning, you can build a lot of these synthetic data sets that are good for this type of step-by-step reasoning.

But now it's a bit of a whack-a-mole for every particular capability you want one of these things to learn.

You actually have to figure out how to train it to do that thing.

And it's really hard.

And most things we fail to do it at.

So it's like creating agents, right?

Is that the concept of creating agents for specific things or no?

Well, so the idea of agents is we can connect software to language models.

So like if we had a really, really smart language model, we could just say like, okay, we want to schedule a meeting.

Give me the 10 steps to do that.

And then the software could take those steps and go execute them and then come back and tell the language model, okay.

So an agent is just control software connected to a language model.

So the language model does all the thinking and the software then goes off and does stuff.

So you can talk to it like a person, basically.

Yeah, but then it has access, like it can read your email and give that to the language model, ask it about it, and then ask it what it should say in return.

And then the software can go back and send the email because the language model can't interface directly with software.

It can just input text and output text.

But the problem is, is they were hoping that these language models would get so advanced, you could just use them to control everything.

And that's just not happening, right?

So now, if you look at how they talk about superintelligence, like look at the AI 2027 report, for example, it's all based on what's the technical story?

Well, how do we get super intelligence?

What does that look like?

They don't know.

What does the architecture of a system like that look like?

We don't know.

What's the specific thing a system like that would need to do that we're getting better at and we should worry about?

They don't know.

The whole story is we think these language models are just going to be good enough at programming next year that they can build a program that's just going to be smarter.

And then it'll recursive self-improvement.

It's a crazy story.

We're tuning these base models on specific programming examples and they get better at doing this type of programming.

But the idea that we can somehow fine-tune a language model so that it can produce a program that requires massive breakthroughs in the very notion of how intelligence works, this is crazy stuff.

We have no idea how to do that.

So most of this is built on this recursive self-improvement idea that's been around since the 60s that like, I don't know, somehow they're good at programming now.

They'll get better at programming.

And that will allow them somehow to build a program that is the biggest AI breakthrough the last 20 years.

Like somehow the language model will figure that out because we've been tuning it on programming examples from like textbooks.

I think it's really become almost like this object of belief out there that disruption, this massive world-changing singularity style disruption is going to happen and we're so excited that it's possible that everything is working backwards for it but the entire academic community is like no there's real disruptions we need to care about this is distraction this idea that we're going to have these like super intelligent machines there is no compelling technical story for it computer scientists want to see what is the architecture that does this what are the capabilities that we don't have that we would need Why do we think we're going to get those capabilities?

And everything, if you talk to any of these people, it's all vibe forecasting.

It's, well, look how far we've come.

We made these other changes that we thought were hard.

None of this is forecasting.

You can't look back and say, we did this that was hard.

Therefore, this other thing without any technical details, I'm going to argue we can do it.

I think there's enough real disruption coming from AI that that's where we need to keep our focus.

It feels like a distraction sometimes how obsessed Silicon Valley has become about these stories.

It really does feel like a religion out there.

So if there's like one message I can tell to your audience is that the academic community, the AI community is not nearly as sold on this religion as almost anyone you'll talk to in Silicon Valley is.

Oh my God, that makes me feel so much better.

I've been feeling really stressed out because some of these people that come on, they say that everything as we know it, basically they're saying that if we do hit super intelligence, that everything will just change very fast.

Yeah, that's all thought experiment.

Nick Bostrom is just doing philosophical thought experiments.

And if you look at, I mean, he's a very smart philosopher, but if you, you know, there's a recent video interview of Nick I was watching, right?

And what they always talk about is his terminology: you know, it's very hypothetical.

We could be a few key unlocks away from that happening.

That word unlock is doing a lot of work.

It's not this is how one of these systems would work.

Here's the roadblock: we don't yet have this capability, but we figure because we're on this trajectory, that's how we'll over.

It's not specific like that at all.

It's all the thought experiment of if a system got smarter than us, it could build a system even smarter than it.

and you would have this takeoff.

It's thought experiments, but there's nothing in the technical, I'll give an article recommendation for everyone who's stressed out.

I think it's a very good article.

Arvind Arijan wrote this from Princeton, a great computer scientist, runs a center there also for ethical public policy.

It's called AI is normal technology.

It's very respected within academic circles.

It roughly matches the consensus of what people who understand this technology thinks.

And it talks about all the ways that AI is going to be a very disruptive force, but it very systematically dismantles these hype cycles.

I mean, I saw someone do this math the other day.

It's like the harder the financial situation gets for open AI, the crazier thing Sam Altman says.

And every time there's some concern or quarterly report that's concerning, you get an even crazier thing.

So there was like a recent report where like, man, they're burning 4 billion, right?

It's like a $6 billion spin rate.

They're only making two.

Like, shoot, we got a big hole.

He comes out and gives a talk about AI will be so good, we're going to have to build Dyson spheres around the sun to harness every last like it's crazy sci-fi talk like it gets crazier dario came out and was like you know half of knowledge work is going to be automated next year or within two years there's just no plausible technical story for this yet and the other thing i'll tell people is if these things were true there's like 10 steps in between that would happen first so look for those so if AI got good enough to create a better AI, to have massive breakthroughs in intelligence, well before it got that good, it would get good enough to write supply chain software systems that made walmart twice as profitable like these are much easier problems so look for that first there's a lot more very profitable milestones along the way it's like the academics are fighting back a little bit like wait a second you're getting out ahead of your skis it's become a bit of a religion there's real disruptions coming but this idea that because we made really fast i think people just felt it's exciting and they fell in love with this idea of we made these really really impressive breakthroughs on language modeling so now we'll continue to have really, really impressive breakthroughs.

And then I can just come up with anything I want and vibe forecast it and say, then that's going to happen because look at all these other things that happened or look at these like weird contrived benchmarks we use.

I think there's going to be a reckoning.

There's certainly going to be an investor reckoning because I think there's going to be a lot of profit in this field, but not enough for the money being spent right now.

So there'll be a reckoning among investors.

And I think there's going to be a reckoning among journalists, perhaps, where it's like, why did you report this without ever asking the questions, but what is the the system?

What are the features that system needs that we don't have now?

And why do you think those features?

We're not asking the technical questions.

We're vibe forecasting.

We say, you run the company.

You know what you're talking about.

We've done other really cool stuff recently.

I can believe we could do more cool stuff.

So I'll just take it at your word that work will be automated in two years and we'll have super intelligence in three.

Like we're not actually asking the technical question of like, but how?

And if the answer is, I don't know, the AIs we have today will just program better AIs.

Not only are they not nearly capable of this, we have no reasonable story of how you would train.

How would you tune a language model to produce an artificial intelligence program that's better than any programs we have today?

Where's the synthetic data set we're using to tune it?

It's true.

It's like, let's get real.

I mean, I can't even get AI to write a perfect email for me,

let alone it becoming smarter than, I guess, you know, human or having super intelligence.

There could be, as Bostrom would say, unlocks that happen in the near future.

But assuming these unexpected unlocks don't happen, I think more realistically, what we're going to see is a lot of focus on how to actually productize this technology.

It's a fantastic technology we have right now.

We haven't yet done a lot of product market fit yet, right?

Like we just have a chatbot interface that you can paste stuff into.

I think there's going to be huge, really, really useful breakthroughs that are based around not massive technology breakthroughs, but product market fit.

Like, oh, in my particular type of work, there's a lot of people who are trying to build products that use the power of language models to help my work.

And there's a lot of experimentation going on.

And this company stumbled across something great.

And now that everyone uses this tool now in my field, something like that is going to happen in many, many fields.

And I think this is really important.

I think right now, the power users like yourself are mainly working with web-based interfaces.

I do think in five years, everyone is going to have three or four tools in their life that are powered in the back end by some of these AI.

It's really going to be a really big economic story, just like everyone uses Google, right?

There's a lot of money at stake.

And it's a really big economic story, but this vibe forecasting stuff, I think, is a distraction from like the real economic story.

What we should be caring about is the tools that are coming for our fields that could be really great.

And we're being distracted because of what I think is a lot of hot air about work being automated and AGI and super intelligence.

It's distracting us from the real stuff.

It's almost like nobody's talking about this interim period.

To your point, for entrepreneurs, especially that could have so much opportunity because everybody's making us feel like this is going to skip over really fast.

We don't know what's going to happen in a few years.

And so even for me, I keep thinking, oh, well, what's going to happen with my company?

What's going to happen with my job?

Cause it just seems like everything is about to flip so fast and this interim period is really short.

But you're giving me a lot of confidence that hopefully it's not going to change so quickly and it's just going to be a slow evolution.

And really useful.

Like you could be building right now

bespoke productivity tools.

for your company because you can vibe code these things much quicker.

You don't need dedicated expert teams or programmers.

I'm hearing these stories a lot where people are realizing like, wait, I could actually right now use this tech to build some internal tool that really, really helps exactly what we do.

That's a big opportunity now that I think a lot of people are missing.

If you're a software company, you should be trying to win this product market fit game for small niches.

I think there's a huge amount of economic success that's going to happen there.

Look, they've been saying large portions of the economy are going to be automated for the last two and a half years, right?

This idea that, look, your job's not even going to be here next year.

So why bother?

It's like, don't let that distract you i think we're things are sort of slowing the hype is increasing as the actual just think about the breakthroughs you've heard recently how like esoteric they are how they only are really measurable on benchmarks that you don't know what they are right the breakthroughs you're not seeing are this company doubled their profit This company fired this whole division and it's all done by AI.

It's all, we've increased the reasoning ability that when we measure it on this benchmark we created, it shows like a 50% increase.

It's all pretty esoteric.

We tuned a model to be able to do math, Olympiad, and now I can do it.

Look closely at the breakthroughs recently.

They're not nuts and bolts.

This company now can do this and it's a massive change.

And so I think we're in a period where we're more adapting our capabilities we have now to industry is what's happening.

More so than like there's a shoe that's about to drop.

And until that shoe drops, why bother?

So I think you're absolutely right.

We shouldn't, the interim period is the period.

What are we going to do with GPT-4 and and 03 and how are we going to build tools off of it that helps my business?

That's really the question, not, hey, should we wait till some GPT-5 comes out that's just going to automate half my workforce?

I love that we ended on this note.

I feel like it was really helpful.

I feel like my listeners have been getting a lot of this like hype on the podcast recently.

And I'm sorry if I've scared anybody through the people that I brought on the show, but I feel like, Cal, you really helped us understand what's really going on.

And I'm really happy that we heard your perspective.

So I end my show with two questions that I ask all of my guests.

You can just answer from your heart.

The first one is, what is one actionable thing our young improfiters can do today to become more profitable tomorrow?

This is counterintuitive, but being much more clear about when you shut down your work for the day.

So when you're done having a ritual, get all the open loops out of your mind.

Make sure you're not missing what's my plan for tomorrow.

Did I miss some urgent thing?

Am I okay with my plan?

Did I leave anything open?

No, I'm good.

Great.

Schedule shutdown.

And it feels like, oh, that means doing less work.

But having a clear break between work and non-work allows you the next day to do that work all the more better.

It makes life more interesting, more sustainable.

You get more insight.

So shutting down your work more clearly, I think, increases the quality and therefore the profitability of your work in the long term.

And what would you say your secret to profiting in all areas of life?

For me, it's always the depth principle, right?

I do fewer things.

I try to do them very well and I do it at a sustainable pace.

You said the depth principle?

Yeah, I think of it as as the depth principle like it's a theme that goes through a lot of my writing do fewer things do them well do them at a sustainable pace and trust that over time that's going to add up to really cool things there's a sort of a patience to it that matters like i want to be a writer it might take 10 years before like i really get traction and it might take 20 years and just what it was for me it was 10 years of just slow and steady right not burning myself out but just slow and steady.

Here's a book.

Let me try to do a new one.

Let me try to make each book a little bit better.

It took 10 years of that before I had my first major cardback national release.

And then it was another five years after that, or 10 years after that, where it's really like I'm a very successful writer and the multiple New York Times bestsellers.

10 years just to get reasonable, another 10 years to be successful.

Academia is the same way.

So that's always my idea of do fewer things, do them really well, know why you're doing them, work at a sustainable pace, let the rewards aggregate.

I think it's, that's the way that the really cool stuff comes.

There's only so long you can frenzy.

But if you stay relentlessly focused on something and just keep getting better and better, it doesn't matter if you take breaks or don't work past five, but you keep coming back to it and get better relentlessly.

Over time, really cool stuff happens.

Yeah.

You got to get your reps in.

You got to be an expert on things.

You got to have lots of skills in a similar area.

That's what's going to make you super, super successful.

Cal.

I loved having you on the show.

I'm so happy that I finally had you on Young and Profiting Podcast.

I should have interviewed you like four times already.

I hope that you always come back on next time you have something to promote.

You're always welcome on the show.

No, thanks.

It was my pleasure.

Well guys, that's a wrap on my conversation with Cal Newport.

He really challenged the way we think about productivity and success in our hyper-connected world.

If there's one thing to take away from this, it's that Cal's concept of deep work has completely revolutionized how we should approach our most important tasks.

As he explained, not all work is created equal.

Deep work requires intense focus and concentration to create real value.

In today's tech-saturated world where our attention is constantly pulled in every direction, deep work is becoming increasingly rare, and that makes it more valuable than ever.

Cal recommends scheduling distraction-free time blocks, being specific about what you need to accomplish, and creating work rituals that signal to your brain that it's time to go deep.

Something as simple as changing your physical space can create that crucial separation between shallow and deep work.

But Cal's wisdom doesn't just stop there.

His philosophy of slow productivity completely flips the script on our culture of busyness.

Instead of glorifying busy schedules and long to-do lists, he challenges us to focus on three core principles.

Do fewer things, work at a natural pace, and then obsess over quality.

He called out the trap of pseudo-productivity where we confuse being busy with being effective.

Real productivity isn't about looking active on Slack or jumping between meetings.

It's about being intentional, deliberate, and deeply focusing on work that actually matters.

Cal recommends multi-scale planning, a strategy that aligns your daily actions with your quarterly vision and long-term goals.

It shifts you from reacting to the urgent to intentionally building something sustainable.

Every entrepreneur should recognize that wearing busyness like a badge of honor and juggling endless tasks can actually hold you back.

By focusing on fewer, high-quality projects instead of spreading yourself then across mediocre ones, you start building something meaningful and sustainable.

And lastly, don't be afraid of AI.

We've had all sorts of experts on the show forecasting our future with AI.

And the fact is, we don't know what will happen.

We don't know if super intelligent AGI is going to take over the world or if things will just incrementally change from where they are now.

All you can do is pay attention to what's happening and figure out how to use AI tools available now that will help yourself and your team become more productive or leverage AI to solve problems and innovate within your niche.

Like Cal said, a lot of what we hear is just hype.

So get back to your business, slow it down, and stay focused.

Thanks for listening to this episode of Young and Profiting.

If you listen, learned, and profited from this conversation with the brilliant Cal Newport, then please share it with somebody who needs to slow it down and focus on what truly matters.

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It's Halata Taha.

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Thank you for all that you do.

This is your host, Halataha, aka the podcast princess, signing off.