Deep Questions with Cal Newport - Ep. Ep 381: Life Advice from Legendary Writers
Episode Date: December 1, 2025In today’s episode, Cal reviews some of his favorite advice from legendary writers (plus a bonus piece of advice from his own craft). Within each suggestion, he finds a general idea that can apply t...o anyone looking to build a deep life in an increasingly distracted world. He then answers listener questions and responds to comments about last week’s episode.Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here’s the link: bit.ly/3U3sTvoVideo from today’s episode: youtube.com/calnewportmediaDeep Dive: Life Advice from Legendary Writers [0:02]How do you balance managing your energy vs. time? [45:29]How can I recharge without feeling antsy as a working mom? [48:39]Should I eliminate Reddit to gain a more intentional mind? [50:56]What’s the difference for reading based on the Lincoln protocol and for sheer joy? [54:53]Does active podcast listening qualify as a learning endeavor? [57:01]CASE STUDY: A project manager reorganizes his life [1:02:19]CALL: Developing a 5-year plan for work [1:06:54]CAL READS THE COMMENTS: Can LLMs be Conscious? [1:09:51]Links:Buy Cal’s latest book, “Slow Productivity” at calnewport.com/slowGet a signed copy of Cal’s “Slow Productivity” at peoplesbooktakoma.com/event/cal-newport/Cal’s monthly book directory: bramses.notion.site/059db2641def4a88988b4d2cee4657ba?youtube.com/watch?v=CQHK_AlJTQcThanks to our Sponsors: calderalab.com/deepauraframes.com (Use code “DEEPQUESTIONS”)shopify.com/deepvanta.com/deepquestionsThanks to Jesse Miller for production, Jay Kerstens for the intro music, and Mark Miles for mastering. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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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, focus 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-storiest 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 comments.
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.
It's 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, and then you have to put in a lot of work to build sentences around it that actually
makes 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, et cetera. 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 it ex-Nilo, 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 careful.
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
or 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 meeting.
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 as you begin to get 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 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 now 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 in the buckets.
often talk about for different areas of your life and your 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 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 like 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 not 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.
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 Sonders 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 sort of your current draft of what you're trying to do. And then you need to be taking the notes you need about what resonates is 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 my man, Robert Caro, nonfiction writer, most famous for his
National Book Award winning multi-volume biography of Lyndon Johnson.
He really should read it.
He wrote this thing over so many years, so it's been working over so many years.
Also, the power broker, his, 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.
At 2019, he wrote a book about his process.
It was called Working and he did a lot of interviews about this book.
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.
All right.
So the Allen that Robert Caro is referring to here is Alan Hathaway, who was.
his editor at Newsday.
So Kara'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 thing, 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.
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 to 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, you know,
your equivalent of winning the National Book Award is going to require that you turn every page.
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 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 is 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 is 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. You just 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 planner. You say, you know, 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 caro terms,
pursue the story you want to be true. You got 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.
We're rock and rolling here
Jesse. Here's
our next one. Let's see here.
David Grant,
a colleague at the New Yorker.
You might know him for
his book, Killers of the Flower Moon, which has made into a movie
with Martin Scorsese
directed that with Leonardo DiCaprio.
Interestingly, they had optioned
two projects to consider for their next movie,
back then. They were like, okay, we're either going to make this three-hour epic, Martin Scorsese,
DeCaprio vehicle. Either we're going to option and use David Grant's Killer of the Flowers Moon,
which was about these high-profile murders at this Indian reservation to get at oil money and the birth of the FBI.
Like, okay, either we are going to do that or we've also optioned the time block planner.
And so they had these two different movies ideas they were going to be in the time block planner.
It would be really a handheld camera following Leonardo as he's like,
come up. I've fallen off of my block plan.
I went too long.
You got to fix it.
You got to fix the block plan in the column over.
I'm running out of columns. This is my last chance.
I've got to run out of columns.
The meeting went too long.
So they were 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 in the series of hyperfell burst.
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 says great writer,
he's great New Yorker pieces,
he's great books.
His books are super deeply research.
I actually thought about using David Grant.
He's another great example of what we just talked about,
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,
the Neiman 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.
Right, 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's Corsese movie.
Like having the difference and 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 concepts.
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 that nobody left any records behind.
The third level of interrogation is, does this story have another dimension, richer themes or trap doors that lead you places?
It should tell us something larger about the human condition, the mystery of existence, systems of intelligence, systems of engineering.
justice or power, the nature of truth.
That's actually a 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 the terms.
You can write a good story.
Like for his most recent book, The Wager, which is about a shipwreck, I don't
if it was 18th century, where there's two sets of survivors who's finally
survived and had two completely different stories.
There was a ton of, because they had the,
the survivors' 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 Admiral Lee Court.
So like all of the testimony and depositions after they got back.
And then there's endless information about the just the maritime trade and these ships and
who these people were.
And so he had a huge,
he knew for that book like,
oh,
it can 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,
storage, it should be, you find information, but for it to really, you know, get the, the Martin Scrazzasi
film option, it has to have that deeper layer. You're like, oh, there's a, 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 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, we were ached out.
So 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 of 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 excitementless role.
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 the 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 Grant trying to do research on this idea.
I want to talk to everyone involved, read everything I can, find people who did this,
many people who tried this and failed at it.
Like what is really going on here?
And if after all of that, you're even more excited, like, well, 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've just saved yourself from an obstacle.
You saved yourself from waste of 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.
can, 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, makes more work,
and more things than we think aren't exactly what we hope they would be.
There go, David Grant.
He has a cool story about giant squid hunting.
I read that.
Yeah, right?
Not cool.
New Yorker.
Yeah, where he like goes out.
They don't end up catching a squid in the end.
But like, it's just hanging out with this guy who's hunting the giant squid.
That's like quintessential.
They look for the babies and stuff.
Yeah.
Cool article.
I wrote an article about email recently, though.
So 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.
We kind of got into, like, the technology of querian language models.
So like, here's the thing.
Granny and I call him Granny.
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.
He'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 Tufts.
Oh, yeah?
Yeah.
I will say he probably didn't play lacrosse for tuffs.
It doesn't look like an athlete.
He's got a brain.
Yeah.
All right.
Good for him.
Smart guy.
Smart of the mean.
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 is from a 2014 interview for Rolling Stone.
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 a reporter shows up.
And 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 Bing or 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 where 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 want to do a movie about it.
I'm like, Leo, man.
Chill.
Yeah, okay.
I got to do a podcast about
fixed schedule of productivity
I 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 being 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 taxi way 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 to 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 don't want 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 life, like 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 was another delusion of worlds because the photo for this New York Times magazine was David Marquesi's talk column.
I've told you about it, but you had to go to New York.
They had a fashion photographer who did the photos.
And he was so disappointed with me to have a writer coming.
in. I'm like a gargoyle who
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,
ugh.
Ugh.
He'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 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 think you can 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.
So like having a conversation with someone on the phone, watching something meaningful, or you're like doing something professional.
I'm coming up with a business strategy.
I'm writing like a really important memo.
You have to remember that the absolute poison that you need to avoid is contact shifts.
This is what we get wrong about productivity in the digital age.
It's what we get wrong about efficiency of 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 T's, 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, is then 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 stream 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.
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.
It has a timer on it.
And the way you're going to run this process is that if you contact 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 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 contact 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 contact 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 to go to go to the
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 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 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 are watching
the Claire Dane show,
The Beast Within Me or something like that,
about an author and et cetera, et cetera.
I feel like they're doing a lot of that in that show.
You're 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.
All right.
Those are, those are my five ideas.
I think, Jesse, it's time for some takeaway music.
All right.
So when it comes to shape any 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 writers.
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 in the action in your own life.
Let's review these.
Jesse, can you bring this up on the screen here?
I have them here.
So 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.
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 and professional, you need to not be trying to shift your context between
different things.
Do those five things.
five ideas that come out of the world or 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.
It may just 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 like in athletics, there is a lot of reasons.
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 like,
epic biographies he would have said during every page?
Yeah.
Yeah.
Because 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.
I know.
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.
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 arc, you can see in the distance, Robert Carrow just opening up the boxes and we'll
I'm turning every page.
Hey, there's an arc here.
What's in there?
Face melt.
That'd be a twist.
The arc ends up killing and melting the face of rubber care.
That would be a deep.
You know, that's a matte painting, that scene?
So they, it's a warehouse, just like a sound stage.
That's how they did all the effects back then in the 70s and 80s.
They painted that warehouse.
You painted on a piece of glass.
And then you leave like a little bit like unpainted at the bottom.
And you put that later.
So you have a new 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 etc like living in deeper life etc and then
We have a call.
We got a case study.
If I 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 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 going to like make that people think that's true that me and David Grant are just like really tight.
Granny's going to stop by.
We're going to talk to some Tufts lacrosse, you know, research.
Talk about researching and Tufts lacrosse.
It's going to be a good time.
All right.
Enough of that nonsense.
Let's get into some questions.
All right.
First questions from front of the show, David Duane.
I'm currently reading Jim Lerer and Tony Swartz'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 powerful 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 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 writing.
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,
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, 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 Lur 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 like the power pole engagement
I met Tony Schwartz actually
Back in
I god it would have been like 2015
I did an event at Lincoln Center
99 U conference
And I was speaking at one of the stages
At Lincoln Center about
So Good They came out
can't ignore you. And I remember it because, like, I was backstage was me and Bray
Brown.
And so we were like, yeah, that was that event.
Well, it was a cool event. And 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, like
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.
We have high energy, less important stuff.
We 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 it.
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 lock or take a bath.
Like,
some people that makes them really anxious.
Activity makes them feel better.
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 ballgame 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 an extrinsic, it's inflexible and it's deadlight driven, then you're going to burn down and be stressed.
Like that's just the people, like the people who have like the really hard jobs 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.
Like if you don't do it today or 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,
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.
Or 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, like, 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.
Here 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-dage, where on the one hand, it is.
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's a
maybe has really good creative output.
Like Reddit will be an example of a place.
Like there's a lot of really good information.
Like people talking about stuff they know about.
And on YouTube as other example,
there's like a lot of really good creative, you know, output, right?
There's there's junk on there.
But, you know, 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,
rewards 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'll 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 I'm 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, like, business journalism about email and how it was being written about.
But I was like, what was it like in the companies?
And I was just searching around Reddit on it's just using 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.
It was,
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,
blame wars and us net
and people get,
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, they say, yeah, I know that show comes out on Mondays and 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 you 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
or 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,
Dangerwell 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. 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 about what you allow to be used for distraction and numbing. All right. Do we got,
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
for the sheer joy and mental work out of reading.
Should I shift my own eclectic reading habit towards the link of 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 be 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, you know, 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 this, 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 a, 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 read a lot of dumb stuff.
January, you know, some other periods are.
in the summer sometimes when like 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 laying the devices when.
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 a three or 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 no one that came.
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.
Like I like first books often.
Oh, here's someone's been writing for 25 years and I haven't read the 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 one.
I'm working on this one.
Here's an interesting one I'm thinking about.
Yeah.
Thriller, December.
All right, do we have one more question?
Yep, next up as well be.
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 distractions disguises 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.
I mean by that is it's like any other source of entertainment, watching a TV show, or listen 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 it's not,
I'm not being productive.
I'm not trying to, like, master.
If I really want to, like, 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 an entertainment.
But it's a good source of entertainment
because you can focus it and target it.
Right?
Unlike TV or radio,
you could find shows about exactly what you are interested in.
Like my kids and I were getting excited
about going to one of our local theme parks.
There's, I do what,
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.
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 down.
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 listen to that one,
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's like any show that's popular in a travel channel.
Like, yeah,
it's like any show that's popular in travel channel.
But like 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 a TV.
I'm not watching a lot of TV shows, but I have podcasts.
It's like a higher quality search for 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 more podcasts, especially ours.
All right.
We got, 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 materials 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 the type of advice. We talk about this show
in their own life. It is also an excuse to play
our often requested 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
focused 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 that I tracked those core habits.
I wrote out 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 work, 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
and tell like Owen 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 we 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 is like let's go in order
or like discipline and organization I had a few things I said start with some simple habits
in each just a signal to yourself do 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 it like it slowly if you focus on the right area start small but
are continuously going through them and improving slowly over time real change can happen
The other thing to happen here is you put into place the type of ideas I talked about 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 to 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 what you do matters.
And taking your time, doing things well, obsessing over quality, spending more time in these 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 eaten away at your schedule.
It's a great example of the type of things I talk about.
Like the digital, 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 the 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.
Owen, 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 a lot of the things you've covered.
They've been transformational.
But I just thought if anybody knows, 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 was a little long.
All right.
So he's saying, like, look, I don't know what.
But he's doing all 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 in 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 servers that are happening for like hot swap, you know, whatever, web apps.
Like, 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've 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 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 Harold,
962, 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, 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 is sort of implying that they
would have goals towards which they might
manipulate us eventually. And I say, well, they don't have goals.
It's once trained their static.
What Brandon is 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 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.
Because 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 until it did well on a particular game.
And then once you deployed, 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 could 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 it 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 Yusebi.
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, but it only applies during training.
Well, it's a good but nuanced comment.
Leonard, so I'm glad you brought it up.
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 that you're, so let me respond to you about this because I think it's worth, 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 in these giant data centers with 50,000.
or 100,000 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
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 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 pass, Ilya S, because I don't know how to pronounce it.
I don't have his last name handy.
He actually came out recently, Jesse, and said, yeah, the age of scaling's 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 and 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 training them longer,
didn't make them more capable,
they turned to tuning,
which happened after all the pre-training is over.
Without getting too much in 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.
It's unsupervised.
You're just guessing a missing word.
And you know what that word is.
So I guess that word is to correct answer.
But in tuning, you might have a math problem and you might have like a detailed proof as like 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 loan.
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 algorithms to sort of zap those final logics. And please don't yell
at me AI people. This is just simplifying. But they kind of zap those final logics that help you
select among the right words to come next. Once you've identified like what type of answer that should be
giving here to really, so 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 that 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 punch line
and that the punch line
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 choke 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 choke 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 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 a 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 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 there.
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 give it an answer.
So it kind of shuts down the circuits that,
one of its opportunities and all the different ways
that might answer a question.
There's ways where it might answer briefly with like,
yeah, the answer is seven.
Like, 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 that, 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, you know, I don't care how many like 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 like the lawnmower is always just going to like 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'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
and there are machines to 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.
Gubbighy Punkt 7028
says, your definition of consciousness
appears strictly functional,
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, G. Punk T728, 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, you know, in cognitive science and brain circles, they call qualia.
I'm agnostic on that as well.
I don't think it's impossible.
Or, for example, a computing machine, an artificially intelligent machine to maybe have something like emerging 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, 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,
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 pre-cast 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's 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
reaction. There's no online learning.
My argument about LLM's
not being conscious is a purely
architectural argument that's engaging
specifically with the architecture of LLMs,
which are static feed forward on changing.
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
or dealing with a lot of things at the same time,
that 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 right
like 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
we got next
mabel 4367
the biggest risk of AI
today is people
and organizations
not understanding the technology
and applying
to problems
they can't handle
in a satisfactory way
like profiling
people who 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,
superintelligence, all jobs are being 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 free LLMs.
There was a robust,
academic AI safety community.
It 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 field in which we've been building lots of tools.
And traditionally, 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.
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 just bias 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
like AI. It's a real issue. It's also like a perfect topic if you're, you know, a humanist,
critical theorist or somebody who cares about these issues, right? You're like, here's technology
going to, you know, you're being too fast and my expertise can help make sure we don't create
trouble. And it was like a really good issue, very niche, very academic whole conferences on it,
but not something to have like a lot of discussion in like 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 at server farm batteries?
Like it became this like outlandish are all jobs going to disappear within a year?
And now like the AHA safety researchers are like we've been very carefully like building these
frameworks about, you know, how to evaluate data from like a Kantian perspective.
And now you have, you know, people going on the Dworkish podcast.
And it's, I think if we use like wooden tip spears, we can get past the termination
robots, human sensors when the wars begin, when the day of the 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 comment are 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 there are still interesting questions, but it's a hard time, you know, it's a hard time
to be talking about these pre-LLLM systems.
All right, let's see. Let's do a couple others here.
Felix MD5CY 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,
like 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 Felix MD5CY is basically asking,
like, so what if we just build, you know, LLMs or one 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.
They have 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.
And 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 AI's work or how SORA works.
The way they train those is there's a lot of different ways they do it.
But 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 like for all these other things like that we can't just do unsupertive.
supervised learning with data. That's the problem. How do we build a world model that like generalizes how like the world functions? Like 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 100,000 GPUs and all the texts 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.
You know, I don't know.
So, yes, I think it is theoretically possible.
In fact, like 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.
I think 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, he 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, you know, it's like 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
as just a cell
passing electrical signal
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 LLM's
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 do 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. It's a thought ofic sermon, 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 that give him steps and rules that he follows.
And the other end, he has like a well written, the proper Chinese version, 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.
Grigas 1-337.
I feel like these comments are being longer
as we're going to be like four or five columns
and just like continuously scrolling.
People who think about AI are verbose.
My God.
All right.
Gragus 1337 says,
Cal,
you're making the classic reductive argument at LLMs.
It's just a bunch of numbers
that go through matrix operations, etc.
All right, I guess I'll stop there because, at least that particular question, I'm not making the reductive argument.
I don't care about the substrate on which LLMs are built.
It has to do with like specifically the process of they 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, language models don't run experiments, but, no, he's quoting me, language models don't run experiments.
And then he says, but chat, GPT 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 like 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 try to keep excitement and 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.
This feature is not widely used
because it's super increases
to cost of inference since you're doing the inference
like four or five times.
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 like 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, right?
And so you can, on certain benchmarks, the performance was better
if you asked the same, the control program asks the same question three or four times
and then return some 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's 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.
The LLM does not learn.
It doesn't know that you ask 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, all right, 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.
Funny quote.
We got here, Mark Dev 1.
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.
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.
a 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 a 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.
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 not be.
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.
It's like this is a great.
And he was on a big platform.
So this is like a great way to get into 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.
But if you push them like, yeah, probably something like that's true.
So 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 there's now 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.
I guess this is coming out after things.
So I hope you had a good Thanksgiving.
We'll see you two weeks after Thanksgiving,
deep and thriller in December.
Until then, as always, stay deep.
Hi, it's Cal here.
One more thing before you go.
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