Ep. Ep 381: Life Advice from Legendary Writers | Deep Questions with Cal Newport

In a world in which our lives are increasingly distracted and diluted by forces like digital distraction and artificial intelligence, how do we push back?

How do we create meaningful lives focused on things that actually matter to us?

Today, I want to give you some powerful advice for accomplishing exactly this goal.

Advice that comes from a perhaps unexpected source, famous writers.

Now as a professional writer myself.

I love hunting down advice about my craft from authors I really admire.

But something I've come to realize is that some of my biggest ideas about living a deep life can be understood as generalizations of ideas that authors have had about the art of writing.

So here's what I want to do.

I pulled five of my favorite quotes from five well-known authors talking about the craft of writing, offering advice about how to do it better.

And for each of these quotes I'll explain what the author means.

But then I'm going to generalize a bigger idea out of that quote that could apply to your life in general.

And then I'm going to translate that idea into concrete advice about how you can act on it to make your life deeper in a distracted world.

So let's put on our writing nerd hats and go searching for some wise words.

As always, I'm Cal Newport, and this is Deep Questions.

Today's episode, life-changing lessons from legendary writers.

I'm going to start with a quote from the short storyist, novelist, essayist, George Saunders.

This is a quote that came from his book A Swim in the Pond in the Rain, which is actually like a really cool book that comes out of his creative writing pedagogy a longtime creative writing teacher.

And it's a book that has short stories from masters and then his commentary.

So it's a book about the art of writing.

It's a really cool book.

I'm going to pull a quote out here.

For those who are watching, instead of just listening, I'll put this up on the screen as well.

All right, so here's Saunders.

What makes you as a writer is what you do to any old text by way of this iterative method.

This method overturns the tyranny of the first draft.

Who cares if the first draft is good?

It doesn't need to be good.

It just needs to be so you can revise it.

All right, so what's he talking about here?

Well, the idea that he's picking up on is an idea for which we have some neuroscience backing, which is writing something from scratch, that is, filling in the blank page with words, is cognitively demanding in a unique way.

There's a lot of mental horsepower that gets summoned to accomplish this goal.

You have to fire up a lot of your brain just to create the syntactically correct words that you're putting out there.

Like the sentence itself has to make sense.

You're also describing something from scratch.

You have a lot of other horsepower trying to build from scratch in your mind, whether it's an abstract thing or like a vivid sort of realistic scene that you're writing about.

You have to create this thing you're writing about from scratch.

You have to hold it completely in your mind's eye.

Then you have to put in a lot of work to build sentences around it that actually make sense as good English sentences.

That uses a lot of your brain to do that.

Now compare that to editing a sentence you already wrote.

You have a lot more brain resources now to play with what you're doing.

First of all, the words are already there in reasonable English.

You don't have to have so much of your brain fired up just trying to make sure that words are matching properly with grammar and spelling etc.

Those brain resources are filled up.

Also, when you read what you're writing, that's going to recreate in your mind the image to think about.

You're not building an ex nihilo, but it's being captured in those words.

Now you can play with it more freely.

Play with the idea, look at different aspects of it instead of trying to build it and hold it from scratch.

So now you can think much more deeply about the ideas, and you can think much more deeply and carefully about the actual craft of your sentences, which is to say, it is in revising your words that the really good writing begins to emerge.

And that's why Saunders is saying look my iterative method, and if you get into the details of the method, it's about editing passes.

It says just get something down.

It's going to be the worst version of whatever you do, because you don't have enough brain resources to make the first thing good anyways.

You need something down to edit because editing is where the actual interesting writing happens.

That's a great piece of advice for writers.

Now, how do we generalize this to our lives if we're not writers?

Well, in life it can be hard to figure out the right way to do things, pursue goals, to make progress, to express your values or find meaning.

It can be hard to figure that out all in advance, before you get started.

To sit down and say okay, I'm going to come up with a perfect plan of exactly what I should be doing with all my time, for all my weeks, for the next few years.

It's just really hard to do from scratch.

But if you make some preliminary decisions and start actually living, what happens is you begin to get uh, feedback and knowledge.

The thing that you were thinking about is happening and you're experiencing it and now you can play with it.

Well, what's working, what's not, what's the reality of this path?

Once i'm actually on it, i don't have to conjure up and try to imagine the whole thing.

I'm in it right now and i can play with it, and i can see variations that would not have been obvious when i was starting, before i had started, before i knew about these nuances.

I'm learning new information i might not have had before.

I'm not playing with so much abstraction.

I'm actually looking at options that are actually there in front of me.

So your life is improved in the edit, often with much more nuance and impact than when you're trying to plan it in advance, just like it is trying to produce words.

You make the best decision you can, you go for it, you reflect, you edit.

You repeat that process and you get a really good manuscript of your life.

If you try to wait until you have just the perfect story before you get started, you're going to be 34.

You're still in that basement.

You're still playing Call of Duty, just waiting for like the right time to get going.

All right, so let me turn this into some concrete advice.

So what should you do to cultivate a deep life based off of this Saunders advice?

There's two things I want you to think about.

One, I want you to have a lifestyle vision.

And what I mean by that is that you have written down somewhere a description of the ideal lifestyle that you want to move towards.

At least your best understanding of what this ideal lifestyle would be like at the moment.

You can revise this as time goes on.

Be careful not to get captured in the myopia here and just focus on one aspect of your life.

All I'm thinking about is my job.

All I'm thinking about is like some athletic accomplishment I want to do.

Make sure you have it divided up into buckets, like I often talk about, for different areas of your life.

And your vision touches on each of these buckets.

You want to be describing in the first person sort of what this part of your life is like if you're in your ideal life.

So now you have an ideal lifestyle vision to be working towards.

You should check in on this vision weekly.

You should give it a significant update at least once a year.

I suggest doing that around your birthday.

All right.

The second part is how you edit this.

So this is the sentence.

The original sentence is the life you're trying to lead.

Based off this lifestyle vision, you came up with the best you could.

I think this is what I want in my life.

As you go along and live this life, keep a journal, a very specific type of journal.

I'm not talking about the.

Let me talk about my hopes and dreams, or get into my psychopathy and what's going on in my life.

That's all fine.

But the type of journal I'm talking about here is one where you record your What's resonating with you and what's not, both abstractly and concretely.

So if you come across something that maybe you're not doing in your life, but you come across an example of it and you're like whoa, that's really attractive to me.

I don't know why, but something about the way she's living or something that's really – I've seen her in a documentary, this person,

That's really resonating.

Write that down.

You come across something else.

I'm at my friend's house, and man, the way he lives –

It seems really hectic and the house is like huge, but kind of empty and depressing.

And I don't know something about that doesn't resonate.

Write that down.

The same thing with what you're actually doing in your life.

Like, hey, this project I'm working on is really stressing me out.

Or I really liked I did this little volunteer thing.

I really liked having a place to go each week and meeting with people.

So you're keeping track of what resonates and what doesn't resonate, both in terms of outside world stuff you encounter and in your own life.

This then can become the grist to edit that lifestyle vision.

Now, when you do these more serious check-ins on like the annual basis, or maybe twice a year, you can look through those journals and begin adjusting this vision.

You know, that wasn't so important.

This is important.

I was missing this.

I want to put that in there.

That is where you're editing the sentences of your life.

So Sonder's advice is a great way to approach writing well.

All the cool stuff happens in the edit, but it should happen in your life as well.

You need a lifestyle vision to be your current draft of what you're trying to do, and then you need to be taking the notes you need about what resonates and not so that you can keep editing that vision and getting closer to a polished draft.

All right, so that's our first piece of advice.

Let's see here.

Our second.

This comes from a man, Robert Caro, nonfiction writer, most famous for his national book award-winning multi-volume biography of Lyndon Johnson.

You really should read it.

He wrote this thing over so many years, so he's been working over so many years.

Also, The Power Broker, his biography of Robert Moses, is another sort of like classic in the field.

So he's this like a towering figure in research-based historical nonfiction writing and biography.

In 2019, he wrote a book about his process.

It was called Working, and he did a lot of interviews about this book.

So he did a lot of interviews about his life.

I want to put a quote up here on the screen that comes from an interview he did with the AP.

That was talking about something from his memoir, his professional memoir Working.

All right, so here's Robert Caro.

I can't remember how many times, with that Johnson book and that incredible mass of stuff at the Johnson Library, I felt like giving up.

Not giving up the book, just saying, I've done enough.

But then I would hear Alan saying to me, turn every page.

I hear him saying, never assume a damn thing.

I have that in my mind all the time.

Alright, so the Alan that Robert Caro is referring to here is Alan Hathaway, who was his editor at Newsday.

So Caro's sort of first serious journalistic job was at Newsday.

And Alan Hathaway taught him hey, when you're trying to do research on something, don't just do enough research that you have a story that you like.

Turn every page in that archive.

It's when you turn every page, you read everything that's available, that you actually get at the truth of the matter.

And in the end, the truth is going to be much more interesting and much more powerful than just that initial story.

You came across that you like.

This is a classic piece of advice for research-based nonfiction writers.

Now, this generalizes to our lives as well.

One way to think about this is pursuits don't really get interesting, both in terms of their subjective experience and the opportunities they open to you, until you've really followed them through to an impressive level of accomplishment.

It's once you've symbolically turned every page that you really get to something that's special, something that is award caliber.

And I think this applies to your life as well.

Now this requires two things once you get going.

It requires diligence.

You have to stick with something over a long period of time which, in turn, requires you to say no to other things.

I have the ability to stick with whatever this project is that I think is important to my life, whether it's professional or not for a long amount of time.

It also requires deliberateness.

It's not just enough to stick with something year after year after year.

You have to keep thinking what are the activities here that are going to help me make the most progress?

What are the activities that actually matter, right?

So for caro, as a writer, it was turning every page in that archive, whether you wanted to or not.

That's the thing that actually matters, even though it's a huge pain.

The same holds for almost any pursuit that you might go after in your professional or personal life.

You might want to just tell yourself a story like oh, i'm just going to do a little bit of work and it'll be fine, but the things that matter are the things that matter.

If you want to become, you know, better at a sport, there's a types of practicing you have to do to get better.

If you want to get better at an instrument, it's the hard stuff, not just jamming on the songs you know.

It's trying to push yourself on the songs that are a little bit too hard that make you better.

So you've got to be deliberate.

What really matters for the thing I'm doing?

So I can't just stick with it.

I have to be doing the right things.

I think this is a great piece of life advice.

The things that are going to define your life, the stuff that's going to be your equivalent of winning the National Book Award, is going to require that you turn every page and you stick with it for a long amount of time and you do the work that actually matters.

Now, I can translate this into some practical advice.

So if you want to practice these type of efforts and I think it's worth practicing before you're setting off on like a 10-year journey

If you want to practice these type of efforts...

A good way to do that is with what I call a seasonal project.

You come up with one project per season.

I'm talking about the seasons, the weather seasons of the year.

If it goes well, it can span multiple seasons.

You set aside regular time each week to work on that project.

And you have a training plan that's actually written down that says here's what I'm going to do on this project this week.

And here's why I think this is the right thing to do.

Like I talked to this person.

This is what they said actually made a difference.

Or here's my experience trying this, you know, over the last few weeks.

So you have to justify your actions.

So what you get here is practice sticking with something over a longer amount of time, so at least a season putting regular time on it, because you're going to put aside regular time for your single seasonal project.

Regular time is on your calendar.

These days, these times, that's just how I do it.

I go to work late on Thursdays and Saturday morning, whatever it is.

And you're deliberate, because you have to have a training plan where you say no, this is what I did this week on this project and why I did these particular things.

You can't just do what feels good or you can't just, in Karo terms, Pursue the story you want to be true.

You got to actually find the story that actually is happening.

Do this for a little while, a year, maybe two.

You will begin to understand what it feels like to be both diligent and deliberate in the rewards that returns.

You'll realize what it feels like to actually be doing the right thing time over time and not just doing something that's fun in the moment.

How to stick with something past moments of enthusiasm and have a deeper, longer-term motivation.

Now you're ready to get involved in whether it's in your personal, professional life those bigger projects that's going to make a difference.

So if you turn every page on something, that's eventually where the deep story actually emerges.

So good advice there both for your writing and your life.

All right, we're rock and rolling here, Jesse.

All right, here's our next one.

Let's see here.

David Grand, a colleague at The New Yorker.

You might know him for his book Killers of the Flower Moon, which has been into a movie with Martin Scorsese directed that with Leonardo DiCaprio.

Interestingly, they had they had optioned two projects to consider for their next movie back then.

They were like OK, we're either going to make this three hour epic Martin Scorsese, DiCaprio vehicle.

Either we're going to option and use David Grant's killer of the flowers moon, which was about this, these uh high profile murders and at this indian reservation to get oil money and the birth of the fbi like okay, either we are going to do that or we've also optioned uh, the time block planner.

And so they had these two different like movies ideas.

They were going to be uh, in the time block planner.

It'd be really a handheld camera, following leonardo as he's like i'm up, i've fallen off of my block plan and i i went too long.

They're like you got to fix it.

You got to fix the block plan and the column over.

I'm running out of columns.

This is my last chance.

I got to run out of columns.

The meeting went too long.

So they're going to do that with like a really great tracking shot, as he's like with his time block planner, or the story of the birth of the FBI and the series of hyperfobbers.

They went with David Graham for that one.

But I think he has us in mind.

Maybe for the next one.

All right, so David Grant's this great writer.

He writes these great New Yorker pieces.

He writes these great books.

His books are super deeply researched.

I actually thought about using David Grant.

He's another great example of what we just talked about with Robert Caro.

He also has the habit of keep reading, keep reading, keep reading.

Learn more than you think you have to.

Spend years in the archives because then it shows in the story.

But that's not the advice I want to highlight here.

Let me read a quote here.

I'll put it on the screen.

This is from an interview with the Nieman storyboard.

Coming up with the right idea is the hardest part.

I spend a preliminary period ruthlessly interrogating ideas as I come across them, even though it's time consuming and a bit frustrating.

I don't want to wake up two years into a book project saying this isn't going anywhere.

So I like this idea.

He's saying spend longer thinking about what you're going to write your book about, like find the perfect idea, because you're going to be working on this for so many years.

And if the idea is not quite right, You're not going to end up with a Leonardo DiCaprio starring Martin Scorsese movie.

Like having the difference in impact between a great idea and a good one is exponential.

It's worth taking the time to find the right idea.

I didn't put this on the screen, but he actually.

I thought it was interesting because I have the notes here.

He went on in that interview to talk about the three things he looks for.

When David Grant is evaluating an idea as a potential long-form article or book concept.

So I want to go through these briefly.

All right.

So he says the first thing he looks for you try to find a story that grips you and has subjects that are fascinating.

Then you ask, are there underlying materials to tell that story?

Once in a while I come across a rich story, but the records are classified or nobody's alive and nobody left any records behind.

The third level of interrogation is does this story have another dimension, richer themes or trapdoors that lead you places?

It should tell us something larger about the human condition, the mystery of existence, systems of injustice or power, the nature of truth.

That's actually pretty cool.

I mean, just we're going to geek out on writing stuff here.

That's a pretty cool checklist for evaluating an idea.

Like the idea grips you.

You're like, oh, my God, this is fascinating.

But don't stop there.

There's actual resources to pull from. pages to turn so you can write a good story.

Like for his most recent book, The Wager, which is about a shipwreck I don't know if it was 18th century where there's two sets of survivors who finally survived and had two completely different stories.

There was a ton of, because they had the survivor's tales.

There was like a ton of records on what had happened, two different accounts of what had happened.

Then they had all of the testimony from the Admiralty Court.

So like all of the testimony and depositions after they got back.

And then there's endless information about just the maritime trade and these ships and who these people were.

And so he knew for that book like oh, it's going to take me a few years, but I can learn about all of this.

There's like a lot to pull from.

And then his third idea was, yes, it should be a fascinating story.

You should find information.

But for it to really get the Martin Scorsese film option, it has to have that deeper layer.

You're like oh, there's a deeper layer here about – the wager, I think, was about the construction of truth and story and narrative.

And then there was the – obviously, the Flower Moon was about structures of power and injustice and justice and those notions of that and what that meant in our country.

And that's what brings it to the next level.

It's hard to find an idea that has all three.

Probably the Time Block Planner movie fell down on that third piece.

There wasn't – it was probably missing like the deeper observations about structures of power.

That's why we were ached out.

Seriously, I thought that was really cool just to geek out.

It's really hard to find an idea that satisfies all three of those things, but that's what David's looking for.

If it takes some years, it takes some years.

All right.

Let us now generalize this.

In your own life, use what I'm going to call evidence-based planning.

I'm kind of combining the generalization advice here, but let me tell you what I mean.

We often jump at an idea for something to do, a project to pursue, a job, to switch to, a move to make.

We jump at these ideas because there's on the surface like that's exciting.

And I like that feeling of excitement.

Let's roll.

But it might not be to use Grant's terminology an idea that can sustain multiple years of working on that project.

But you really want to run an idea through the ringer.

Before you actually use it as the foundation of making major changes in your life.

And that's where this thing I call evidence-based planning comes in.

This is a concept that comes out of lifestyle-centric planning.

Evidence-based planning.

So this is kind of my concrete advice here.

But evidence-based planning is where you get to the bottom about how whatever world or decision you want to make, how it actually works.

You talk to people, you read things.

Why do some people succeed with this or some people fail?

What's the reality of this place I want to move to?

What's the reality of this job?

What would the economics be of this?

What type of people are they hiring for this?

If I move there, how much do the houses actually cost?

What are the schools like?

Does this job, is it likely to have like a remote element?

Is it nice to work remotely?

Can I talk to someone who's in that situation?

You gather evidence about the thing that you're thinking about doing.

Because if you don't, You might just be stuck on a story that caught your attention today, but two years from now, you're going to say, I can't believe I'm still writing this book.

I'm stuck on it.

So evidence-based planning makes a big deal.

So how do we make that concrete?

Treat your major life decisions like you're a journalist.

You're David Grand trying to do research on this idea.

I want to talk to everyone involved.

Read everything.

I can find people who did this, maybe people who tried this and failed at it.

What is really going on here?

And if, after all of that, you're even more excited like wow, this is even better than I thought, but now I know exactly how to navigate and what to expect and I'm excited about it, then you're going to be much more likely to stick with that decision and get good rewards.

And if you have to throw out the idea, that's okay.

You just saved yourself a problem.

That's not a bad thing.

You just saved yourself from something, an obstacle.

You saved yourself from wasted time.

And it can be frustrating, because evidence-based planning might lead you to throw out a bunch of things that are exciting in the moment.

You might feel like, man, I'm such a killjoy.

I'm always sort of like, is that really going to work?

What about this?

What about that?

I should take more risks.

But it gets you to those, eventually to the ideas that become the blockbuster.

And it's the blockbusters in your life that really in the end make the difference.

So I'm a big fan of deploying something like you got to deploy something like evidence-based planning.

It's easy to find a story that's kind of gripping.

But to get to the bottom of it, to find a story that really works, takes more work And more things than we think aren't exactly what we hoped they would be.

Here we go.

David Grant.

He has a cool story about a giant squid hunting.

One of his favorites.

I read that.

Yeah.

Right.

That cool.

Yeah.

Where he like, goes out and they don't end up catching a squid in the end, but like it's just hanging out with this guy who's hunting a giant squid.

That's like quintessential.

They look for the babies and stuff.

Yeah.

Cool article.

Um, I wrote an article about email recently though.

So I comparable.

He spent two years like hanging out with people hunting giant squids and like on this like high tense adventure.

Like, is he going to catch him or is he not?

But in my most recent New Yorker article and I don't want to brag I let an AI agents filter my inbox and you didn't know like maybe it was going to miss messages.

Right.

I don't know.

I don't know what's going to happen.

Uh, we kind of got into like the technology of querying language models.

So, like here's the thing, granny and i call him granny.

Uh, granny and i are like and i think i've established this basically the same person in terms of like talent and the importance of our results.

I mean, we kind of do the same sort of things and, you know, some cards fall his way instead of mine, but me and granny like really it's like get me granny's not available, get me noops, like it just goes back and forth.

We're basically the same person.

I know he doesn't listen this podcast.

I think he went the toughs.

Oh yeah, Yeah.

I will say he probably didn't play lacrosse for Tufts.

Doesn't look like an athlete.

He's got a brain.

Yeah.

Good for him.

Smart guy.

Smarter than me.

Cool guy.

All right.

Let's keep rolling.

What do we got here?

All right.

My fourth piece of advice comes from the master, Stephen King.

I'll put this quote up on the screen here for people who are watching this, from a 2014 interview with.

Here's what King says.

I wake up.

I eat breakfast.

I walk about three and a half miles.

I come back.

I go out to my little office where I've got a manuscript and the last page that I was happy with is on top.

I read that, and it's like getting on a taxiway.

I don't spend the day writing.

I'll maybe write fresh copy for two hours and then I'll go back and revise some of it and print what I like and then turn it off.

It's a cool article, Jesse, because... it gets into his HQ because the reporter shows up.

And like the cool thing about it is King has like security concerns and he's just so famous and whatever.

Like he has to not have an easily identifiable place he lives or works.

So it's a really nondescript office building.

He like owns an office building, a nondescript office building in like a nondescript part of Bangor, Maine.

But you go into this building which they say looks like Dunder Mifflin.

And it's like all this King memorabilia and things from his movies and his Gothic Victoria.

Like he's like there's really cool space for him and his staff are, but he couldn't put it in a cool place because otherwise people just start showing up.

That's why.

That's why we're above a restaurant, because otherwise people knew where we were.

Jesse, the problem that me and granny both have people are always trying to chase us down.

Leo is always like, I want to know about your latest book.

Maybe we'll do a movie about it.

I'm like, Leo, man, chill.

Chill, okay?

You got to do a podcast about fixed schedule productivity.

You don't have time to talk about your movie ideas.

But I thought that was cool, so I liked that piece.

All right, so what was King talking about here?

The question that he was answering is like, what's your schedule as a writer?

Writing is hard.

Waiting for the muse...

Or be like, hey, I'm going to get some writing at some point today when I feel up for it.

Like that's amateur hour.

The writers who write a lot like King, and King, he writes a lot.

He's definitely a high volume writer.

They do the same thing every day.

Some days are better than others, but that's what adds up over a lifetime to a lot of books.

Have your schedule.

Put aside the time for things to matter.

Do that time.

Have a ritual around it.

You can have a taxiway as he talks about it for your mind to get into the mode and then do the work.

Well, you can imagine this is something I'm happy to generalize.

Make regular time for the things that matter most in your life, whatever your equivalent is of working on book manuscripts.

Don't wait for having a lot of free time or feeling inspired for it.

Put it on your calendar.

Have a ritual surrounding it and just do it on a regular basis, even if inconvenient, even if it doesn't always go well and even if sometimes nothing of interest is produced.

That is how you make progress on hard things that require a lot of time.

If we're going to make this concrete.

The particular tactic I want to talk about is autopilot scheduling.

This is where you actually have the same time, same place, same day for certain activities and they're on your calendar in repeat for weeks weeks, weeks into the future.

So that time is protected.

Nothing gets scheduled there.

If you went into the day and say I really want to prioritize my big project, that day might already be fractured too much for you to make progress.

But if 10 to 12 for the next six months on Tuesday is put aside for like I –

Work from home and then I go to this library and that's where I work on whatever the thing is, the new skill you're learning, or whatever.

It doesn't get taken up because you've protected that when you're making meetings or appointments.

That time hasn't been available and you have a routine.

You do it week after week.

You don't have to think about it.

You don't have to burn mental energy or convince yourself.

That actually gets done.

You've got to autopilot to schedule the stuff that you know you have to do or the stuff you know you really want to do on a regular basis.

That is the absolute best way to make progress on it.

So you follow something like Stephen King's lead.

All right, we got one more idea here.

For the fifth idea, I'm kind of pulling a fast one, so I apologize.

I am going to turn away from the pantheon of quote-unquote legendary writers, and our final idea is interesting, but it's going to come from an idea who is much less impressive than the other four, and I'm talking about myself.

So I actually have a quote From an interview I did a couple years ago, from which I will draw my final suggestion.

I couldn't help myself.

I don't know.

I've done a lot of interviews.

So I put one of mine in there as well.

Before we get to that final piece of advice that comes from yours truly however, we have to take a real quick break to hear from the sponsors that make this show possible.

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All right, Jesse, let's get back to our deep dive.

We're on to our final piece of writer advice that we're going to apply to our lives.

This one comes, God help us, from me.

I'm going to kind of cheat here Jesse, because I also directly give advice about your life more generally than just writing.

I'm going to give a quote here.

This comes from an interview I did for the New York Times Magazine back in 2023.

Speaking of photos, by the way, there's another collision of worlds, because the photo for this New York Times Magazine was David Marchese's talk column.

I've told you about it, but you had to go to New York.

They had a fashion photographer do the photos.

And he was so disappointed with me. to have a writer come in.

I like, I'm like a gargoyle who, you know, can't control his face.

And he had just done a photo shoot with Iggy pop who had like come in shirtless.

It was just like fascinating to look like.

And I'm like, it's like, look less terrifying lights, bad anyways.

So this is a quote that is both about like writers, but also about everyone's life outside of writing.

So, um, I'm jumping straight to the life advice with the double acting piece.

I'm kind of cheating here, Jesse, but it's my own quote, so I didn't get away with it.

All right, let me load this up here.

Here's what I said.

The critical mindset shift is understanding that even minor context shifts are productivity poison.

When you looked at an email inbox for 15 seconds, you initiated a cascade of cognitive changes.

So if you have to work on something that's cognitively demanding, the rules has to be zero context shifts during that period.

Treat it like a dentist appointment.

You can't check your email when you're having a cavity filled.

You have to see it that way.

All right, so that's kind of about writing.

It's kind of about life outside of writing all at the same time.

But here's the generalized point I'm making.

When doing something important to you, professional or personal, it's like having a conversation with someone on the phone, watching something meaningful.

Or you're doing something professional.

I'm coming up with a business strategy.

I'm writing a really important memo.

You have to remember that the absolute poison that you need to avoid is context shifts.

This is what we get wrong about productivity in the digital age.

It's what we get wrong about efficiency in the digital age.

We're used to productivity being about producing things faster.

What's going to make me move faster?

Because when I was building Model Ts, the way I got the productivity ratio cars produced per input put in, the way I increased that ratio was moving faster.

I had a faster, more efficient way of putting things together.

So we think that's what productivity means.

But in the digital age, that is not our problem.

Our problem is not that we move too slow and that we need to find ways to move faster.

The problem is that in the digital age, the things we're creating, we're creating with our brain.

And our brain is a really fickle thing to work with.

If you change the context even briefly, you show it a brief distraction.

You look at an email inbox for 15 seconds to check for a message.

You just go to see what's going on on social media real quick.

The brain goes haywire.

It initiates a context shift.

This is an expensive cognitive operation.

And before this shift is complete, you try to come back to the thing you're doing.

So it tries to abort that shift.

But before you can fully lock into what you're doing, you check something else.

It's a cognitive disaster.

Your cognitive capacity is reduced.

You're exhausted.

The stuff you produce isn't – you actually end up producing is not very good.

It would be like if in a factory we discovered like the way the human body worked was like let's say you're like moving a wrench.

Like, let's say, the way our human body happened to work is that if you turned your head too far, your arm strength disappeared for 10 minutes.

Like you have a hard time holding a wrench.

Let's just say that was true.

We would keep that in mind when designing factories.

Like, okay, let's be careful.

Let's not build our factory in such a way that the workers keep having to turn their head because they're going to lose their arm strength and they're going to have to wait for a while until they can really speed up again and get the steering wheels back on.

Well, this is what's happening, cognitively speaking, in knowledge work in a digital age.

Context shifting takes all the proverbial arm strength out.

Our ability to concentrate really dies down.

But instead of protecting ourselves from this, We make it even worse.

We've added even faster, more ready forms of context shifting and distraction.

So that's what productivity is in the digital age.

Avoiding context shifts, not trying to go faster.

Avoiding context shifts.

In fact, I've talked about this in multiple books of mine.

I will take on significantly more cumbersome processes slower, more structured processes that are a pain in the moment.

I'll take on a huge amount of hardship if it saves me from context shifts.

Those that's the productivity poison.

So that's the advice I want to give here at a high level is you need to think about context shifting as the thing you want to avoid to be productive, not getting faster.

Now, if we want to get more concrete, you know, read deep work, read a world without email, read slow productivity.

These books of mine get into it, but I'll give you two.

I will give you two concrete ideas you can do just to sort of get more used to thinking about that in the world of work.

If you're working on something deeply, you should have a set rule for what happens in deep work blocks.

How long do I want to go?

And my rule is no context shifting.

Start a timer.

Put the timer on your phone.

Let me tell you why.

Because now your phone is, yeah, it's in front of you, but it's full screen timer.

That's the purpose is it has a timer on it.

And the way you're going to, The way you're going to run this process, is that if you context shift, that means looking at anything.

That's not the work you're doing.

So email, Slack, your text message on your phone, social media, YouTube.

You have to start and restart that.

Stop the timer.

Okay, here's how far I got.

And then you have to restart it again.

I only got seven minutes.

I only got 15 minutes.

So now your phone, which will be one of the biggest sources of context shifting, is pre-mocking you.

You see that number on your, that's what's on your phone is seven minutes.

Like the timer's going.

And so to look at something else on your phone, you have to swipe that time to the side.

Like, you know exactly, oh my God, I only made it seven minutes.

Like you have to confront what you're doing.

So I think have your phone with a timer, full screen.

That's what you're timing.

And be like, I want to get an hour, I want to do a half hour, whatever it is.

And like, hey, if I context shift, I'm going to restart.

At home, the answer is really simple.

You've got to plug your phone in the kitchen.

Just plug it in the charge.

If you need it, go to the kitchen.

It's not with you while you do other things.

It's not with you while you're watching TV.

It's not with you at the dinner table.

It's not with you when you're reading.

When you're doing other things, you actually have to do those things.

There is no easy distraction to turn towards.

You'll lose a lot of your taste for the context shifting.

This really has to do with your short-term motivation systems, what's happening in your brain.

Don't worry about the neurological details.

Keep your phone plugged in the kitchen when you're at home.

I can tell you what though, it's going to make certain shows more boring, especially if you're watching Netflix.

Netflix does more of this.

Supposedly Netflix is doing more of this engineering shows with a stimuli stacking in mind.

They assume that their viewers are going to be looking at their phones while they watch the show.

So they have to telegraph much more clearly what's happening.

So you can kind of listen out of one ear or be brought back up to speed of what's happening.

My wife and I were watching the uh, the Claire Danes show, The Beast Within Me or something like that about an author and etc etc.

I feel like they're doing a lot of that in that show like, oh my god, you just told me this and that is bad.

For these reasons and I worry because I worry that I'm now responsible for the thing that you did you know like there's a lot of this type of telegraphing because I think they're assuming so you might find Netflix kind of boring actually if you do this, but it's worth doing.

Those are my five ideas.

I think, Jesse, it's time for some takeaway music.

All right.

So, when it comes to shaping a more intentional and meaningful life, there are all sorts of different sources of wisdom.

Today, we looked at one source that's particularly close to my heart, which is We took five pieces of reasonable advice about the craft of writing and we transformed them into five more general ideas about cultivating a deeper life.

This resulted in five concrete suggestions for actually putting these ideas into action in your own life.

Let's review these.

Jesse, can you bring this up on the screen here?

I have them here.

Our five pieces of advice were to have a lifestyle vision and use an insight journal to help edit it.

Practice diligence and deliberateness with seasonal projects.

Make sure that you have a training plan.

Use evidence-based planning when trying to make decisions in your life.

Turn every page.

Actually study the thing closely before you go after it.

Use autopilot scheduling to make sure that you're making progress on a regular basis without having to expend any decision-making energy on the stuff that matters.

And finally, minimize context shifts in almost anything you're doing important in your life, whether it's personal or professional.

You need to not be trying to shift your context between different things.

Do those five things.

Those are five ideas that come out of the world of writing, but it will apply to the life of basically anyone who's listening to this show, and you will find some more depth.

So, whether you're writing a book or authoring a deeper existence, how you approach the task matters, and it was worth taking a moment to learn from those who have spent their time mastering this craft.

All right, there we go, Jesse.

I love the generalization part.

Yeah, I don't know why.

Maybe it's because I know writers, but I feel like writing advice often is pretty generalizable to life.

The other field where this is true is athletics.

Yeah, golf.

Golf, like all lessons come from golf.

But in athletics, there is a lot of reason.

Yeah, in golf and other places, there's often these lessons that carry out to other sorts of things.

Do you think Alan, if he had known Robert Carroll's career directory and writing these epic biographies, he would have said turn every page.

Yeah.

Cause I mean, that was advice when he was writing for a magazine, right?

Yeah, I know.

I think like he created a Frankenstein's monster.

Sounds like, all right, so I'm going to go away for 12 years to the Johnson library.

Just like reading, you know, the menus from the white house chef menu.

Yeah.

I guess you can take these things to an extreme.

I think I would be good at that type of lifestyle.

It's like an Indiana Jones and they go into the basement and there's like never ending.

Yes.

And then in the very back, so here's the thing you don't know about that scene.

In the very back of that giant warehouse where they're taking the Ark.

You can see in the distance Robert Caro just opening up the boxes and looking through.

Oh, and I'm turning every page.

Hey, there's an Ark here.

What's in there?

Face melt.

That'd be a twist.

The Ark ends up killing and melting the face of Robert Caro.

That would be a deep dive.

You know, that's a matte painting, that scene.

So they it's a warehouse, just like a soundstage.

That's how they did all the effects back then um the 70s and 80s.

They painted that warehouse.

You paint it on a piece of glass and then you leave like a little bit like unpainted at the bottom and you you put that uh later.

So you have a, you film just someone pushing that cart on like an empty concrete floor and a soundstage, and then you film it through that matte painting and then that gets on the film.

So now it looks like you're walking into these like this vast, you know background And they're big.

These matte paintings are big, like the size of our wall in here.

Yeah.

Old school special effects are pretty cool.

All right.

Let's see.

What else we got going on?

We got a bunch of questions coming up.

So what's happening in our show?

We got questions from you about these type of issues et cetera, like living a deeper life, et cetera.

And then we have a call.

We got a case study.

And then back by popular demand in the third act, I'm going to react to some more comments.

So kind of get back, get the word of the people and uh respond.

Some i agree with, some i don't, some i think are funny and some they change my mind on.

So we'll get into all of that as well.

My good friend granny might stop by at some point to talk writing.

I'm gonna like make that people think that's true, that me and david grant are just like really tight.

Granny's gonna stop by.

We're gonna talk some tufts lacrosse.

You know research, talk about researching and tufts lacrosse.

It's gonna be a good time.

All right, enough of that nonsense, let's get into some questions, All right.

First question is from a friend of the show, David Duane.

I'm currently reading Jim Lehrer and Tony Schwartz's book The Power of Full Engagement, which encourage you to manage your energy with equal focus as you manage your time.

What are your thoughts on managing energy versus time?

I like that book a lot.

I remember that book from the 90s, The Power of Full Engagement.

And that was the idea.

We talk about time management, but not energy management.

But if you're careful about increasing your energy and then matching your energy to the things you want to produce, you're going to get a lot more out of your business.

So it's a really smart idea.

These are the type of books I came up on in like the 90s, when I was reading all these business books as a teenage entrepreneur.

They really influenced the way I write today.

I think it was probably for the good.

It's a style of book that's not as, maybe it's not as popular as it once was.

It really was big in the 80s or 90s.

Books are just like, hey, here's an idea.

I mean, you see this so much in my writings.

Here is an idea for like, organizing a part of your life or doing this type of work, or organizing your tasks or trying to maximize like, what you get out of your day.

I'm just going to walk through it.

It's like a concrete idea.

We get this wrong and we talk about it.

There's – we have like steps to it and matrices.

It was just like this sort of business pragmatic nonfiction was like a really big thing, because people are like yeah, I want to – it's hard to be in business and I want to know how to do better.

These books are a little bit less common now, but it's definitely – like my writing is basically – a mixture of like Jim Ler and Tony Schwartz style writing with like New Yorker writing.

And I just put those two things together.

So they were both very influential.

So I liked the, the power pole engagement.

I met Tony Schwartz actually back in, uh, I got, it would have been like 2015.

I did an event at Lincoln center, um, 99 new conference.

And I was speaking at one of the stages at Lincoln center about so good.

They can't ignore you.

And I remember it because like I was backstage, uh, was me and Brene Brown.

And so we were like, yeah, that was that event.

Well, it was a cool event.

I might be mixing events up.

I think that was an event.

I met Gretchen Rubin was there and we were hanging out and I met Tony Schwartz there.

Interesting guy.

I think he co-wrote one of like Donald Trump's books, like the art of the deal type books or whatever.

And then he, like during the first Donald Trump election, came out against him and it was like a big controversy at the time or something.

So I don't know.

Tony Schwartz, interesting guy.

I like powerful engagement.

I'm a big believer in energy management.

This is an idea.

Maybe we should do a deep dive on this book at some point.

It's an idea that really should come back.

It's a really smart one.

Low energy, you can't do much work, so it matters.

So do important stuff when you have high energy, less important stuff when you have low energy, but also manage your energy itself with diet and exercise and sleep.

That point that the physical matters for the cognitive.

I think we accept it more now, but we don't do much about it.

And so I think there's a good book.

I recommend it.

It's like, again, it's 90 style business books.

You didn't have to have stories, not like an Adam Grant book where you're going to like let me have stories and ideas, or whatever.

It was just like, here's something else that's important.

We worked with our clients on it.

Here's like the five things we tell them to do.

Like, that's what these books were.

Maybe they're still writing these books.

I don't know.

All right.

Who do we have next?

Next up is Lauren.

I struggle with me time because of my family work and hobbies.

When I sit at home, I feel antsy.

What should I do?

I think it's a bias towards action.

I think it's absolutely fine.

And if anything helps stave off anxiety for a lot of people the sort of sit still like, let me just like have an empty evening, go for a slow walk or take a bath.

Like some people, it makes them really anxious and activity makes them feel better.

And I think there's nothing wrong with that.

And I think this is really a personality type.

I know people that have to constantly be working on projects and other people who really would like to minimize work altogether.

Like they're like, I want to just sit and enjoy the sun in the afternoon and listen to a ball game.

And like, I don't want to do things.

And there's people that are in between.

So there's nothing wrong with the bias towards action.

As long as here's the caveat if all of that action is imposed from outside, it's extrinsic, it's inflexible and it's deadline-driven, then you're going to burn out and be stressed.

That's just the people who have the really hard jobs and have to work 100 hours a week.

They have a lot of action.

They're also burnt out.

What you need if you have an action bias is a lot of action that is autonomous and flexible.

You're choosing to work on it because intrinsically it's interesting to you, but it's also flexible.

If you don't do it today, where you're feeling sick and you're like I'm just going to cut this short.

Nothing happens.

It's just you choosing to work on these projects and you make progress as you can.

And you're not stressed out.

If something you can't make progress on for a while, that works really well for action oriented people intrinsic autonomous, flexible action then fill your time with as much action as you want.

That's not going to stress you out because you don't have deadlines.

You're not falling behind.

You don't have a sense of like being forced to do something you don't want to do.

So I like it.

I wish I, I do have an action bias and, But I don't have an extreme one.

I wish I did.

It does help my anxiety though, when I try to stay busy with intrinsic flexible, autonomous things.

I think it's a pretty good.

I mean, this is sort of Arnold Bennett's How to Live on 24 Hours a Day, where he's like yeah, you should really be filling your time pretty intentionally.

He's like, there's nothing really good... You recharge when you sleep.

Otherwise, you're supposed to be doing things.

And it should be outside of work, things you choose that are meaningful...

Flexible and Autonomous.

That's basically his book.

I think it's a good idea.

All right, who do we got next?

Next up is Frank.

How should someone think about Reddit, which blends meaningful information and attention traps?

Yeah, I think Reddit.

It falls into a category of multiple other online information sources in today's day and age.

Where, on the one hand, it is true that the information source has a lot of good information in it, that there's a lot of people who are contributing information, or if it has really good creative output.

Like Reddit, will be an example of a place where there's a lot of really good information, like people talking about stuff they know about.

And on YouTube is another example.

There's like a lot of really good creative output, right?

There's junk on there, but you can also see really interesting, cool stuff as well.

At the same time, it's also true of these services.

They have attention traps.

They can put you in addictive loops.

They can give you that consistent purity signal, reward signal that overwhelms your short-term motivation system, and now you just turn to it for numbing or distraction.

It's just if I just get lost in Reddit.

There will be debates and arguments and they're suggesting new things to look at.

What about this argument over here?

And you go read that, and next thing you know, you've been on it for hours.

YouTube, of course, is the same way.

You go down those auto-recommendations, and God knows where you show up.

For those type of information sources I always say like you need to use them, like you would use a reference library and not like you would use your television.

So if you use them as I am bored or uncomfortable or feeling strained and looking for numbing or distraction, let me just go and see what I find.

You're exposing yourself to the attention traps.

If instead you say I am looking for this particular thing, let me go see if I can find it, on here you're extracting the valuable information.

So like, oh, I want to know more about, I'll give a concrete example where Reddit was useful to me.

This was back when I was writing my book, World Without Email.

I was looking for a good concrete example about the arrival of email.

What was it like when email arrived at companies in the 80s and 90s?

I mean, I had done a lot of archival research about the business journalism, about email and how it was being written about.

But I was like, what was it like?

And I was just searching around Reddit on Google searches and I found like a great Reddit thread where like an engineer from IBM was like, let me tell you, like someone asked that question.

He's like, let me tell you, I was involved and let me tell you the story.

And then I kind of tracked him down and it was really useful.

That's good Reddit.

Bad Reddit would be if I then was like let me just stick around and now see people just like fighting about you know, email marketing, blame wars and use net and people getting like whatever, like nonsense.

That's like not really relevant to what I was trying to do.

YouTube is the same way.

If you want to look something up, it's like a great resource library.

Also, if there's like a particular show you like to say yeah, I know that show comes out on Mondays and I I'm going to watch the video on YouTube of it.

That's actually, that's fine as well.

You're like look, I'm a big fan of like Mark Rober's science videos, or I'm a maker and I like the Wicked Makers channel, or something like this.

And if they have a new video out, I'll go and set it up and watch it on my TV.

Like that's fine as well.

But if you're just sitting there on your iPad following the recommendation, you're following the recommendations and you end up in some sort of like weird corner where something like completely unusual or weird or mean is happening, that's a bad use.

So that's the way I think about those type of dual use platforms.

For appointment, viewing or looking things up.

They're great for distraction or numbing danger, will Robinson?

So don't use them for your distraction or numbing.

Have higher quality things that you use for distraction or numbing and use those that have the attention traps just for looking things up or appointment viewing.

I talked about that in my book, digital minimalism.

There's a chapter on joining the attention resistance.

So that's one of the strategies of like actively resisting the sort of attention trap economy is having this particular uses for those platforms.

And, in particular, being very careful of about what you allow to be used for distraction and numbing.

All right.

What else do we got here?

Next up is Maya.

Can you explain the difference between the Lincoln Protocol on reading specific books for a purpose and the more expansive view of reading for the sheer joy and mental workout of reading?

Should I shift my own eclectic reading habit towards the Lincoln Protocol or some hybrid of the two?

You should do a hybrid.

These are two related but not completely the same type of purposes.

The Lincoln Protocol is to seek out books that are going to make your life better and that you maybe have to stretch to understand or build up to being able to consume.

And that's like an important way to self-improve, and it also makes your mind very sharp.

Not all your reading should be trying to pour over Euclid like Lincoln did to try to learn geometry.

You should also have reading you do for fun, and you do both.

Like, I just like this.

It's elegiac.

It's fun.

It's an escape, or it's just really interesting.

And also I'm working on something over here that is – it's hard and pointed towards a particular purpose.

Do both those things.

And you know what?

That ratio can change depending on the season of life and your energy.

If it's a busy period, like I'm about to enter Thriller December, you're reading a lot of dumb stuff.

January, some other periods or in the summer sometimes, when I have a lot of energy, I'm maybe reading a lot more Lincoln Protocol-type expansive.

So the ratio can change, but they're two separate – related but separate types of reading –

I think it's important to have both.

The big thing to avoid is having none because then you're letting the devices win.

They are just going to get those tentacles into your brain.

That's not good.

All right, what do we got?

Do you know any of the books that you're going to be reading for 3rd of December?

I'll read the Dan Brown book you got me for sure.

Some folks have been asking.

They want to read along with you.

I don't know yet.

I'm going to read that one.

It's Secret of Secrets.

That's the new one that came out.

Okay, so I'll read that.

I got to see what the new crop of thrillers are that I should know about.

And then I go back and look for classics.

I like first books often.

Oh, here's someone who's been writing for 25 years and I haven't read their first book.

I like first books.

So I haven't got into it yet, but maybe I should try to announce, try to remind me.

I will.

I'll remind you next week.

I'm working on this one or here's an interesting one I'm thinking about.

Yeah.

Thriller December.

All right.

Do we have one more question?

Yep.

Next up is Welby.

Do you think that active podcast listening, done with focus and reflection, can ever rank high in the learning process?

Or is it, more often than not, just another form of distraction disguised as productivity for the knowledge class?

Well, I don't think it's pure distraction.

I don't think it's productivity.

I think it's entertainment.

What I mean by that is it's like any other source of entertainment watching a TV show or listening to a radio show.

It's something that's interesting to you.

And some of the stuff might be kind of dumb and some of it might be kind of smart, but I'm not being productive.

I'm not trying to master.

If I really want to learn a new skill that's important for my job, I should actually learn that skill and get direct to practice and do deliberate practice.

So think of it as entertainment.

But it's a good source of entertainment because you can focus it and target it.

Unlike TV or radio, you can find shows about exactly what you are interested in.

My kids and I were getting excited about going to one of our local theme parks.

Podcasts where all they do is review theme parks.

Oh, there's a great one, Jesse.

I hadn't heard this format before.

And I feel bad because I forgot what it was called.

But it was a travel log format.

So he would go to an amusement park and take audio.

And then he would edit it and narrate it.

And it would be like, you would hear the audio in the background.

It's like, and then I went to like the such and such ride line was not that bad.

I talked to someone in the and then when I clicked in it to the and the turns, let it out.

He's just kind of like narrating.

And then I got this food and it was actually pretty good.

He's narrating his day with audio clips in it.

And it's like super interesting, relaxing aspiration.

Like, man, I just kind of want to be at the park with this guy.

New Yorker does similar stuff with their podcast.

I just listened to that one darkness in the darkness with a.

She did the research of that crime.

Yeah, my wife was talking about this.

Yeah, i like that.

That's a cool.

But so here's what i thought was cool about that format is it's a great format, but in like true crime, you have to do a lot of work because you have to like actually have a crime that you're investigating.

This guy was just like traveling and but it ran into the travel channel like yeah, it's like any show that's popular on travel channel, but like this, on this very particular thing, i happen to care about that moment, and there are shows like that for like anything that you're interested in, And there's probably like good shows on it as well.

So it's like hyper-targeted cable TV.

That's the way I think about podcasts.

And you're like, oh, this is good.

I have a good source of – I'm not watching a lot of TV shows, but I have podcasts.

Like it's a higher quality source of entertainment.

So it's not about productivity.

It's not like mindless distraction either.

So I'm a fan of it.

No attention engineering either.

You got to win fans the old-fashioned way.

Like be interesting.

Be useful.

Be entertaining.

Be somewhere where people want to keep coming back to.

They have to just hear about it and subscribe and choose to stay.

So there you go, Welby.

Listen to more podcasts, especially ours.

All right.

Speaking of podcasts, we got reactions coming up where I'm going to actually read.

God help me read the comments.

And before that, we have a case study and a call as well.

So a lot of good material still to come.

But first, we got to take another quick break to hear from our sponsors.

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All right, Jesse, let's get back to the show.

All right, so we're going to do a case study here.

This is where people send in their descriptions or accounts of using type of advice.

We talk about the show in their own life.

It is also an excuse to play our often requested games.

Case study music.

All right, now we can relax.

Today's case study comes from Owen.

Owen writes the following.

In 2024, I received some hard hitting feedback where I almost lost my job as a project manager.

I could barely focus for 15 minutes at a time and I wasn't making progress on my projects.

I was behind schedule and way over budget.

My problem was that I stayed up late every night scrolling social media.

I came across your YouTube video, how to reinvent your life in four months.

I started with discipline in the fall of 2024.

I prayed, set my bedtime alarm and connected with friends and family every day.

I tracked those core habits.

I wrote up my lifestyle center career plan.

I implemented multi-scale planning.

I started a values document.

These adjustments helped decrease my daily screen time from nine hours to 1.5 hours per day.

This past March, I decided to let these new systems run for a bit.

I really like Cal's advice.

Run the systems for a while, take note, and then start from the beginning again.

So it's November 2025, and it's time for me to start back at discipline.

I read Slow Productivity over the summer, and I started implementing the ideas.

I got pushback on not opening emails immediately.

I got pushback on meeting my team's notifications.

However, all this pushback came from colleagues at the same level.

My bosses and managers didn't notice.

In fact, they just commented on the improvement in my work.

My systems and habits provide rigor and efficient structure to my professional endeavors.

These systems allow me to use my time efficiently and lift the cognitive load.

But most importantly, my systems continue confined work to designated times and locations.

My work shutdown routine ensures that I can confidently put work aside.

I have many pursuits outside of work that energize me on a weekly basis."

Oh, and I love that case study.

It both shows the problem of living a fully distracted life.

It will just keep pulling more and more from you until, like oh, and you're up all night long scrolling social media.

Like you're literally toiling for free in the attention factories of Mark Zuckerberg, right?

So you can buy the other half of Kauai while your main job is suffering.

Like, look, you can barely focus.

So the danger of living with uncontrolled distractions.

There in the story, but also we see Some realities about fixing.

In that video, Reinvent Your Life.

One of the things I talked about was like let's go in order, like discipline and organization.

I had a few things.

I said, start with some simple habits in each.

Just a signal to yourself that you take those seriously and then rotate through and keep working on those parts of your life.

There's sort of a rotation to that.

Well, look at the difference it made in Owen.

Slowly.

If you focus on the right areas, start small but are continuously going through them and improving slowly over time, real change can happen.

The other thing that happened here is he put into place the type of ideas I talked about in slow productivity.

And his boss is like, wow, your work's better.

Because ultimately that's what matters.

The people who are in charge of your job is how good is the work you're doing.

To your colleagues, it might be make my life easier by answering my email.

Make my life easier by being on teams all the time.

But for your bosses, for your customers, for your clients, the value of what you do matters.

And taking your time doing things well, obsessing over quality, spending more time on each thing you do not doing too much things at once those principles of slow productivity it produces better work over time.

It produces more work over time because you have less of the overhead tax eating away at your schedule.

It's a great example of the type of things I talk about, like the digital thing.

The motivation for my work is the digital age is eating us alive and we don't even realize why we weren't ready for it.

But there are ways, if we're systematic and careful, that we can push back against that erosion and still build successful lives that are meaningful and not overwhelmed.

Again I hate to harp on this, but it's why I hate this straw man that any talk about systems and organization or improvement is somehow like hustle culture or productivity culture, or it's coded as like online bros or something like that.

Not about hustling, not about how do i produce more and crush it or whatever.

It's about surviving our current digital moment that's eroding all the things that makes life meaningful and we didn't even realize it's happening until it's too late.

It's about thriving as a human is incredibly humanistic what i talk about in an age that's increasingly anti-human and digital.

So there we go.

Oh, and great case study.

All right, do we have a call this week?

We do.

All right, let's hear this.

I'd like to get your opinion on where somebody like me should be focusing their efforts for the next five years.

And when I say somebody like me, I mean somebody who works in technology, not necessarily cybersecurity.

I'm doing all the stuff I can with optimizing my time and trying to develop a deep life and um, a lot of the things you've covered.

They've been transformational um, but i just thought if anybody knows um, it would be you guys, all right.

So jesse, he's asking about what he should focus on professionally.

Yeah okay, i cut off some of the beginning of it because it's a little long, all right.

So he's saying like look, i don't know what he's doing.

All the the advice I talk about about your life and being intentional, but he's like what should I be focusing on?

Probably he's worried about AI if I had to guess.

Yeah.

This is where going back to the deep dive, evidence-based planning matters.

You want to identify what are the skills that are in the same arena where you play, that are producing value and are useful actually producing value and useful.

Like if you do this thing, customers will pay for it.

If you know how to do this thing, Other companies are going to try to hire you away.

I saw this person get hired away at double the salary because they have those skills.

So things that you have evidence are valuable and are adjacent or in the same arena where you already play.

Always be thinking about that and surveying that and be ready to make moves every like two to seven years.

And that's like deliberate diligence to get there.

Okay, now I need the diligently and deliberately.

So, over time, with focus and deliberately working on things that actually make me better, not the things I want to do move towards those new skills.

You probably should be doing that every two to five years, maybe every two to seven years in most tech industries.

The important thing here is the evidence.

You need evidence that this is producing money.

Otherwise you'll get lost in trends and then you'll end up, you know, writing all of these like pie torch calls to LLMs to build these like simplistic agents that, like everyone and their brother, is building, and they don't really do much.

And there's no actual value proposition there.

And it doesn't help where.

What you really need to be learning was, like you know some sort of new like virtualization technology that is being used on the new class of of of servers that are happening for like hot swap you know whatever web apps like that.

Oh, this is like really a better way of doing things.

And it's highly valued.

And because it's hard, not everyone knows how to do it.

You got to constantly survey that arena.

You don't want to change all the time.

If you're changing every year to something new, you'll never catch up.

But every two to seven years, maybe every two to five, You should be like.

Am I moving diligently and deliberately towards a new skill that's in the same arena that I play, so I'm not learning something completely new and that I have evidence, which is going to be.

People are willing to spend money to hire or pay me.

Clients are people trying to hire me away.

Do I have evidence like this is actually valuable?

All right, good call.

Let's go on to our final part.

Recently we've been having a tradition here of me going back and responding to comments from recent episodes.

We're going to continue doing that today.

We actually have them all on screen today as well if you're watching instead of listening.

Our last episode was about LLMs and whether or not they could be conscious.

I was responding to Brett Weinstein's discussion of AI consciousness on the Joe Rogan podcast and I said look, I think there's something sort of somewhat pre-modern about this.

I think he told a story to explain what he sees and now he's reacting to his own story, not to the reality of how these systems are actually architected.

As with all things AI... this generated some responses.

I don't know if the inboxes were like Jesse, but you know, generated a lot of comments.

And so I figured I'd go through and let's respond to some.

Some are really smart.

Some are smart, but I disagree with some.

I agree with, and some I think are just funny.

All right.

Let me bring the first one up on the screen here from Brandon Harrell, nine, six, two, who says LLMs do have a goal.

Understand the world well enough to predict the next token.

All right.

So that was in response.

I was saying in that last piece that, They're not – LLMs don't have like goals.

They're not trying to – Weinstein said something about.

LLMs are doing experiments to try to understand how different things affect the world and what things affect the world in ways they like versus not.

It's sort of implying that they would have goals towards which they might like manipulate us eventually.

And I say, well, they don't have goals.

It's once trained, they're static.

So what Brandon's talking about is like well, technically you could say they do have a goal, which is to predict the next token.

That's true.

But I don't think I would use the terminology goal.

I would say LLMs are optimized in training such that, once deployed, the tokens they generate tend to minimize loss on the token guessing game.

That's what's really happening during training.

Is we're adjusting weights in a way that reduces our average loss when we give it a bunch of token guessing?

Examples from our testing set

And we, we kept adjusting these weights until we were happy with the average loss.

We were getting the testing set.

To me, that's different than talking about goals.

Those goals to me require some notion of agency, right?

You need like a dynamic system which is evaluating possible actions based on competing priorities and some sort of notion of value judgments.

A static LLM doesn't have that.

It was optimized for, Intel, it did well on a particular game.

And then once you deploy it, it doesn't change again.

So somehow that seems different to me than having a goal.

So it's like saying I guess saying like LLM, their goal is a token predict, is like saying a lawnmower's goal is to cut the grass.

Yes, they optimized in the development and training of the lawnmower to be good at cutting grass.

But then once you deploy the lawnmower, it has no agency, right?

It doesn't evaluate the world and make decisions and pursue and evaluate different options, it just runs.

Nothing about it can ever change.

It just runs the same way every time you turn it on.

And the way it runs tends to be good at cutting grass we'll see with an llm after.

Trained it is static and so once it's deployed in the world it produces tokens.

It does pretty well because we optimize to do well at that, but it's without agency.

I don't like the terminology of goals.

All right, put up another comment here.

Put on the screen.

This one's from leonard.

Uh, you said b, He says hi Cal.

I just recently discovered the show and I'm enjoying it a lot.

I think you are misinterpreting what Weinstein said about doing experiments.

The way I hear it, he's referring to the way the RL post-training works.

Let the LLM generate a bunch of different outputs and reinforce the ones that work.

This is similar to doing experiments and learning from them.

Um, but it only applies during training.

Well, it's a, it's a, it's a good, but nuanced comment.

Leonard.

So I'm glad you brought it up.

Um, I wouldn't bet a lot of money, based off of the discussion that Weinstein had with Rogan, that he's really deep in the weeds on how sort of post-training post-pre-training, RL-based tuning actually functions and the different ways it runs.

I don't know that he was thinking that closely, but it is a good point.

So let me respond to you about this because I think it's worth talking about.

Let me tell you the way I think about reinforcement learning.

That's what he means by RL.

Let me tell you the way I think about reinforcement-based tuning.

And it's a bit of a simplification, but to me it kind of gets at the core of what's going on here.

During pre-training, which is that really long period of time where you use real text and you knock out the words and the model tries to guess the word and then you do gradient descent to adjust its weights that make its output be a little bit closer.

So this is where you keep doing this until the average loss on the token guessing game testing set is practical.

This is where you run this for days and days, and these giant data centers with 50000 or a hundred thousand GPUs.

That's where you're optimizing it to produce guest tokens.

If I give you real text with a word knocked out, you do a pretty good job of guessing what that word is, right?

That's this massive pre-training.

This was, by the way, the thing that was making these, this is my New Yorker piece from August.

The thing that was making language models more capable over the last few years, until more recently, was was they made them larger and they pre-trained them longer.

And so for a while we had this sort of scaling effect that, as you made language models bigger and you trained them longer and on more data, they seem more generally capable on all sorts of different things.

And what that article was about in August is that those scaling benefits actually really started to die off about a year ago.

And now just purely making it bigger and pre-training longer is not making the models better.

There's actually like a big figure from OpenAI's past, Ilya S, because I don't know how to pronounce his last name.

I don't have his last name handy.

He actually came out recently, Jesse, and said, yeah, the age of scaling is over.

He had this kind of nice quote where he's like we had this long period of research and then a five-year period 2020, 2025 which is about scaling.

Now we're back to a period of research because scaling is not giving us any more rewards.

So what did they do?

Once just making the networks bigger and train them longer, didn't make them more capable.

They turned to tuning, which happened after all.

The pre-training is over and, Without getting too much into the details, because there's different ways to do this, the one way to think about the more common types of tuning is that you have prompts and correct answers to that prompt.

Here's a question, and here's a correct answer.

That's very different than how pre-training works, where it's unsupervised.

You're just guessing a missing word and you know what that word is, so I guess that word is the correct answer.

But in tuning you might have a math problem and you might have a detailed proof as the correct answer.

Or you might have a question about building a bomb.

And the correct answer you paired with that is I'm not allowed to talk about that.

And what you do, very roughly speaking, is it's like you load that prompt into the language model and it's activating all of the relevant sort of circuits and attention and pattern recognizers that are sort of parsing and figuring out what is this question and what are the types of things we could say next.

And then you used a correct answer at that point in a reinforcement learning-based algorithm to sort of zap those final logics.

And please don't yell at me, AI people.

This is just simplifying.

But to kind of zap those final logics that help you select among the right words to come next, once you've identified what type of answer that should be given here, to really say let's reinforce the logics that are closer to this particular right answer.

Now, if you do that, it's like so you're not Teaching it how to understand – you're not teaching it in tuning.

You're not making it smarter in some sense, right?

You're not – it's not in this phase.

It's not the type of training where it's like learning whole new concepts or it's learning to recognize things it couldn't recognize before.

What you're doing in tuning is saying like okay, you have all this pre-training that was very expensive to recognize and understand.

You know what you're doing.

You know this is like a joke and that you're at the punchline.

And that the punchline has to refer back to this thing that was a cat.

Like all the pre-training has all these circuits like lined up.

And then if you come back in and you're reinforcement learning with like I don't do cat joke answers, you're then going to have like these final wires at the end of all these layers.

When all these other things are activated, really push it towards whatever token is next and saying like I don't do cat jokes.

And if you do that reinforcement learning on enough examples, you're kind of like brute force training it.

Hey, whenever you find yourself with a cat joke again, just say I don't like cat jokes, right?

So it's like a final layer of tuning.

So you're being more precise about how it should use the smarts that it learned in pre-training.

That's roughly how I think about the different forms of reinforcement learning and the impacts they have.

No, so this is not.

I really don't think about this here as a language model, experimenting to figure out more about the world.

I think about this more like... trainer coming in like in a dog training example and shocking the dog to prevent them from doing certain things or like you better always go and chase after the lure when it's thrown because when you don't like I like I hit you with a training crop it's like more of that type of thing so it's not a language model like it's out there like learning and trying to understand how different things do it is having its behavior curtailed push down particular avenues and shutting off other avenues we don't want you going this way go this type of way This is what a lot of the reasoning reinforcement learning was about.

It was give answers that have lots of steps in it as opposed to just giving an answer.

So it kind of shuts down the circuits.

That one of its opportunities and all the different ways it might answer a question.

There's ways where it might answer briefly with like, yeah, the answer is seven.

Let's turn down the weights on those types of circuits and turn up the weights on the circuits you already had.

Like you're going to show your work,

And so it's all about – aiming the way these things behave towards the end.

And that's really a simplification.

But to me, again, I don't see this as running experiments to learn more about the world.

The learning really happens in pre-training.

The reinforcement learning is more about now constraining and focusing what you want to do with those smarts it already has.

But in all cases, here's the key thing.

Yes, but that's when humans are building this thing.

Once deployed, it's static.

It's a lawnmower.

I don't care how many super advanced laser studies of grass you did, that you could build in these sensors to the lawnmower to change the different modes it goes in.

The lawnmower is always just going to statically do these things every time you run it.

So to me, that's the key.

The key thing is, Weinstein is clearly thinking about this as an active agent that's learning as it learns more.

Who knows what it's going to do?

And it's static once it's trained.

But if we even look at how it's trained and we're careful about that And this is semantic, but I don't see that as a machine running experiments to learn more

There are machines that do that, but language models don't.

That's not what reinforcement learning is.

All right.

I don't know.

That's my technical answer.

All right.

Let's see what we got here next.

GubbyGPunked7028 says, Whereas Brett seems to be discussing qualia the subjective experience of what it is like to exist.

The philosophical consensus regarding whether synthetic structures can possess qualia is currently agnostic.

We simply do not know.

Asserting that AI cannot be conscious, based solely on the difference between biological and artificial information integration, is philosophically premature.

Well, GubbyGPunkT728, that's not what I'm arguing.

I am also agnostic on the idea about whether...

Different non-neuronal substances can have the emergent phenomenon of awareness that we in cognitive science and brain circles they call qualia.

I'm agnostic on that as well.

I don't think it's impossible for, for example, a computing machine, an artificially intelligent machine, to maybe have something like emergent consciousness.

That's not my argument.

It's not about the substance.

And it's not about the underlying operations that happen in the substance.

My argument about consciousness and I think almost any consciousness researcher except for – there are philosophical theories of consciousness.

It's basically like everything has some amount of consciousness and it's all on the spectrum.

It's a little bit more out there.

But the brain researcher side of consciousness thinkers, they would all agree.

Like, look, we don't know exactly all the things you need to get recognizable consciousness.

But we know you're going to need some sort of dynamic collection of ongoing consciousness, ongoing dynamic interconnected processes.

And we don't know exactly what they are, but some sort of world model or updatable state and drives and memory, and you need some sort of sensing and action and be able to react to action and update information.

And all of this has to be pretty deeply interconnected in the right ways.

And if you have the right processes and the right dynamism, then you get somewhere.

You're going to get some sort of emerging consciousness.

My argument about language models is it doesn't have... nearly enough of those things.

I mean, nothing in the language model is dynamic.

It is static.

It is statically deployed.

It's not even deployed on a single machine.

How can you talk about interconnection?

They're too big to fit in the memory model of a particular GPU.

So now you have precast weights for different layers spread out over all sorts of different GPUs which are just running through multiplications for multiple different queries on those layers, for multiple different queries at the same time, and then eventually passing those numbers back around.

They're integrated different.

There is no even...

There is no even like hold.

You can't even point to like.

This is where the computation is happening for this word that was just generated.

But more importantly, it's static.

There's no state that upstates.

There's no world model.

There's no drives.

There's no actuation or reaction.

There's no online learning.

So my argument about LLMs not being conscious is a purely architectural argument that's engaging specifically with the architecture of LLMs, which are static feed forward, unchanging.

You've got to have a lot more things that are dynamic and deeply interconnected before you have a chance of the subjective experience of consciousness arising.

We don't know where that happens, but almost no one would say a static table of numbers that are divided among a couple hundred GPUs are dealing with a lot of things at the same time.

This somehow has any sort of notion of emergent consciousness.

If that does, like everything does.

Every data center does.

Google does.

Every distributed system does.

My phone does.

That's too loose of a definition.

So I have a very particular functionalist, architect-based argument for consciousness here.

I'm not falling into reductionist traps.

All right.

This is fun.

What do we got next?

Mabel4367.

The biggest risk of AI today is people and organizations not understanding the technology and applying it to problems they can't handle in a satisfactory way.

Like profiling people to determine things like credit ratings or profitability of committing a crime.

It's kind of interesting.

So these examples, they might hit like the average listener who's just been watching or listening to a lot of LLM content online.

Super intelligence, all jobs will be automated.

Like what are you talking about?

Credit ratings or profitability of committing a crime or profiling, etc.

Where this comes from.

And it's just an interesting story to know is sort of pre-LLMs.

There was a robust academic AI safety community that was looking at AI.

Now we're talking this is much broader of all these different types of AI systems that have been around for a long time decision systems recognizers, neural network-based recognizers, machine learning-based tools.

A lot of these systems existed.

They weren't particularly sexy, but a lot of them existed.

This is a much a field in which we've been building lots of tools and traditional AI safety was like.

We should be nervous about tools that make decisions using like machine learning or AI, because they're often obfuscated decisions.

And we don't know how they're making the decision.

So how do we know that they aren't encoding things that we would never want like a human to do?

Like how do we know they're not encoding some sort of something that we would think if a human was doing is like clearly discriminatory.

We don't know if we're just.

It's dangerous just to Suck up a bunch of data, build a model that data may be biased and then it builds up a model that's discriminatory.

And now the AI is spitting out loan decisions, and you've just encoded discrimination into AI.

It's a real issue.

It's also a perfect topic if you're a humanist, critical theorist or someone who cares about these issues right.

You're like here's technology going to – you're being too fast and my expertise can help make sure we don't create trouble.

And it was a really good issue, very niche, very academic, whole conferences on it, but not something that had a lot of discussion in the broader population.

And the LLMs came along and it kind of sucked for the AI safety people, because now the discussions were like is this an alien mind that's going to liquefy our children to power its server farm batteries?

It became this outlandish, are all jobs going to disappear within a year?

And now the AI safety researchers are like.

We've been very carefully building these frameworks about how to evaluate data from like a Kantian perspective.

And now you have, you know people going on the dorkish podcast and it's.

I think if we use like wooden tip spears we can get past the terminator.

Robots, human sensors

When the wars begin, when the data center wars begin next year, it's just like this crazy outlandish, you know whatever.

And they kind of got left behind a little bit.

But those issues are still out there.

That community is still out there.

That's what this, this commenter speaking about.

And yeah, those are real issues.

Again, most AI is not language models.

It's not stuff that we think is going to automate our jobs or become alive, but it's integrated into lots of things.

And so those are still interesting questions, but it's a hard time.

It's a hard time to be talking about these pre-LLM systems.

All right, let's see.

Let's do a couple others here.

FelixMD5CY says, if LLMs can be compared to the speech centers of the brain...

Is it possible to design complementary mathematical systems that model other brain regions and integrate them into a unified whole?

Great follow-up question.

What I was saying before.

My architectural argument against LLM consciousness says we know, or at least we suspect, that consciousness, artificial or natural, requires a sufficiently diverse collection of dynamic processes that are deeply interconnected.

So FelixMD5CY is basically asking so what if we just build LLMs or 1s component of our artificial brain and we build these other types of processes digitally and we connect them enough, can we get consciousness?

The answer is maybe yes, but we don't really know how to do this for so many of those components.

It's like not something that we're close to.

Part of the problem here is LLMs, which are focused on language understanding production.

We have a lot of data to train them.

We can use the whole corpus of human written language.

This whole massive corpus of humans recording like thoughts and ideas.

We can train them on that.

And that allowed us to get like something that was really good at that purpose.

The vision is similar.

There are a lot of good data sets where it's basically pictures and descriptions of what that thing is.

They get these off the web because there's often tags that explain what an image is, or they look at text near an image.

So you can train models to like recognize images, what's in an image.

Or if you use these sort of the diffusion models, you can reverse it and have it learn how to go the other way and produce an image from text which is like how these image producing AIs work or how Sora works.

They the way they train those is.

There's a lot of different ways they do it but, like they'll all, still they'll.

One way is you get a picture and you take a bunch of pixels out and they try to fill in the missing pixels.

And then another way is you have them like go from text to like an image.

You compare it to what, like I have a real image of that thing.

There's all sorts of different things you can do.

So we have data for vision.

We have data for language.

But for all these other things, we can't just do unsupervised learning with data.

That's the problem.

How do we build a world model that generalizes how the world functions?

The roboticists are working on this.

The LLM people are like, oh, it's easy.

We'll do it from text.

Nah, it's not working.

We train these models with 100000 GPUs and all the text ever written by humans and they have no real, consistent model of the world.

The roboticists are trying to figure out how to do this from vision data. and experience data.

This is really, really hard.

And I've talked to a bunch of roboticists about it.

It's hard, and they're not close to having this answer.

How do we model things like short-term motivation or drives?

We're not sure.

I don't know.

So yes, I think it is theoretically possible.

In fact, maybe one day we'll do it.

I bet we will.

But most of the other systems maybe are much harder than language models to build.

So it's probably better...

The thing of language models is a great breakthrough on the thing they do really well.

It's like we built an artificial language processing center of our brain.

That could be really useful.

But that language processing center from our brain.

If we destroy the rest of our brain, you ain't conscious.

Things aren't going to go well for you.

You can destroy the language part and probably still have enough things left for an Oliver Sacks case study.

I have a hard time like remembering things i can't read, but i can still have like some subjective experience.

But if you destroy the whole brain but the language processing part, i don't care how developed that thing is, he ain't going to be conscious.

All right, move quicker here.

User gizmo says cal, aren't you stating a version of the chinese room argument?

The counter to that is something like if you look at individual neurons, it's just a cell passing electrical signals, so it can't be conscious.

But of course it is at the macro level.

But i do agree with you nonetheless.

There's some key things missing lms like continuous learning.

I like that you agree.

The first part.

No, this is not like John Searle's Chinese Room, because I'm not making a reductionist argument about the actual underlying substrate as being relevant to consciousness.

Again, I have an architectural argument.

Enough sufficiently dynamic systems doing the right dynamic things, sufficiently interconnected.

LLMs are static and only really do one thing.

Aren't going to satisfy that.

Chinese Room argument is interesting.

It has a lot to say.

It's very relevant in the age of LLMs.

Uh, it's.

It's a thought experiment jesse, where you're basically translating, i guess, from like english to chinese and there's a person inside this room and he has all these like manuals he can look through.

They give him steps and rules that he follows and the other end he has like a well-written, the proper chinese version what, what came in?

But you wouldn't say that anything in that room understands chinese.

That was john searle's argument about like what does it mean to know something?

It's a good argument, but it's not what i'm drawing upon here.

All right,

Gragas1337.

I feel like these comments are getting longer as we move forward.

Eventually, there's going to be like four or five columns and just like continuously scrolling.

People who think about AI are verbose.

My God.

All right.

Gragas1337 says, Cal, you're making the classic reductive argument of LLMs.

It's just a bunch of numbers that go through matrix operations, et cetera.

All right.

I guess I'll stop there because at least that particular question.

I'm not making a reductive argument.

I don't care about the substrate on which LLMs are built.

It has to do with specifically, the process of the implement and whether they're sufficiently diverse, dynamic and connected.

And they're not.

I don't care that they're numbers or ions.

All right.

Spider-Man in London.

He says, He's quoting me.

Language models don't run experiments.

And then he says But ChatGPT Pro literally performs multiple parallel operations, then compares them to pick the most right answer.

That's what distinguishes Pro from the standard model.

All right, let me just stop right there.

What he's talking about.

There is what's known as inference time compute, which is again one of these host of features, along with a lot of reinforcement, learning-based tuning that was introduced after scaling failed in the last year to try to find some way to get some sort of measurable improvement on something out of these models so they could keep trying to keep excitement investment going.

Inference time computing.

So this particular type of inference time computing says the control program that calls to LLM calls to LLM multiple times, gets multiple answers and then decide which one is best.

This is like wildly impractical from like a financial perspective.

Like people don't.

This feature is not widely used because it's it's super increases the cost of inference, since you're doing the inference like four or five times and On certain benchmarks that OpenAI cared about.

Hey, if you have an answer four times and, for example, one of the ways they did this was ask it five times and whatever answer it gets, the majority return that.

Hey, these things hallucinate 20 of the time.

You get a better answer that way, because it's unlikely to hallucinate in the same way three times in a row, or something like that.

On certain benchmarks the performance was better.

If the control program asked the same question three or four times and then returns the most common answer or sends all of those answers to another LLM and says which one of these looks best.

But it's a marginal improvement and it was expensive.

So it's not widely used.

But no, that is not the same as the LLM runs experiments to better understand the world because they're static.

They're static.

Once they're optimized and tuned, they cannot change.

They cannot learn.

They cannot, the LLM does not learn anything.

It doesn't know that you asked it to run four times.

It's just a table of numbers.

You get a bunch of answers and another program chooses one of those.

That's not learning.

There's nothing that's stored.

There's no model of the world that's updated.

So let's roll on here.

Now we get a couple.

I think we're ending with a couple more interesting or funny ones.

No more arguments about reductive models of consciousness.

Jules 5347 says, this all reminds me of the Kostrup quote.

These people are simulating a kidney and expecting that, with sufficiently complex, model P is going to come out of the CPU.

A funny quote we got here.

MarkDev1 brother, if you continue down this path, you'll have to mention on a pod that you would never kill yourself.

It took me a second to understand that.

What he's saying is that computers and or open AI are going to come after me to kill me.

So I better make it really clear if they try to make it look like a suicide situation.

Look to Sam Altman if something suspicious happens to me.

If I die of like severe electrical burns coming out of my computer, go see where Sam Altman was up to.

All right.

Or maybe some of these other commenters baptized imagination says anyone who has to use these things at their job knows they aren't conscious in any way.

Good way to probably in this discussion.

It is true.

Weinstein's fears aside, you actually use these, you realize like there's something weirder going on here than just uh, conscious being.

So there we go, i don't know.

I think these are really smart questions, jesse.

I think, like the comments are really smart, we're getting the deep things.

I don't know if i'm right about all these, but it's a cool back and forth um, and it belies the idea that internet comments, i guess, are always.

You know just, you're a poop clown and then it's a gif of taylor swift.

You know it's smarter than that.

So you know, take it a grain of salt, some of my stuff might be right, so it might.

I love the comments.

I love getting into it.

And I want to emphasize the thing I said in that podcast episode too is I wasn't picking on Brett Weinstein.

He actually was saying things that a lot of people are saying.

He just talks really clearly.

And he was on a big platform.

So this is a great way to summarize a common thought about fears about AI.

So it's not like Weinstein has some particularly pathologically bad thinking.

He just stated really clearly something.

I think a huge percentage of AI users would if you push them like yeah, probably something like that's true.

So, um, there we go.

All right.

That's all the episode we have time we have for today.

I need to write my next episode, which is going to be three hours, on the architecture based model of substrate agnostic consciousness.

I just feel like, I feel like there's not going to be a demand for that.

Maybe I'll get my friend granny to come write it with me.

All right.

That's enough of this nonsense.

See you next week.

Um, I guess it's coming out after Thanksgiving.

So I hope you had a good Thanksgiving.

We'll see you two weeks after Thanksgiving, deep and thriller December.

Until then, as always, stay deep.

Hi, it's Cal here.

One more thing before you go.

If you like the Deep Questions podcast, you will love my email newsletter, which you can sign up for at calnewportcom.

Each week I send out a new essay about the theory or practice of living deeply.

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So if you are serious about resisting the forces of distraction and shallowness that afflict our world, you got to sign up for my newsletter at calnewportcom and get some deep wisdom delivered to your inbox each week.

[Life-Changing Lessons from Legendary Writers]-[Ep. Ep 381: Life Advice from Legendary Writers]

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Life-Changing Lessons from Legendary Writers

1. The Iterative Life: The Power of Revision

2. Diligence and Deliberateness: Turning Every Page

3. Evidence-Based Planning

4. Autopilot Scheduling

5. The Poison of Context Shifting

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[Life-Changing Lessons from Legendary Writers]-[Ep. Ep 381: Life Advice from Legendary Writers]

📋 Summary

Life-Changing Lessons from Legendary Writers

1. The Iterative Life: The Power of Revision

2. Diligence and Deliberateness: Turning Every Page

3. Evidence-Based Planning

4. Autopilot Scheduling

5. The Poison of Context Shifting

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