Latest / Freedom Flip / How Elon Musk Works - The Book of Elon by Eric Jorgenson

Transcript

How Elon Musk Works - The Book of Elon by Eric Jorgenson · Freedom Flip

• 0:00
  All right, welcome everyone.
• 0:02
  So we have a new format here.
• 0:04
  So here's the deal.
• 0:05
  Peter loves to read books.
• 0:08
  He reads hundreds of books every year.
• 0:10
  He's a nerd.
• 0:11
  I have dyslexia.
• 0:13
  It takes me one hour to read 10 pages.
• 0:15
  So I don't read books, but I consume a lot of content.
• 0:19
  So we said, why don't I get Peter?
• 0:21
  And then he tells me about the books that he's reading.
• 0:24
  And then we can just go over the books.
• 0:25
  So Peter, all yours.
• 0:27
  Let's do it.
• 0:28
  So this is kind of my nonprofit to give back to the world who can't read books.
• 0:33
  So Pablo can't read.
• 0:34
  Let's go.
• 0:35
  This is an ultimate banger to kick it off.
• 0:38
  So this is The Book of Elon.
• 0:40
  The Book of Elon is written by Eric Jordanson.
• 0:42
  I have to open the page.
• 0:44
  That is Eric Jorgensen's signature.
• 0:47
  But then my five-year-old daughter wrote hearts all over his signature.
• 0:52
  That's good.
• 0:54
  This was one of his first hundred copies he sent out to people.
• 0:57
  I got to read it early.
• 0:59
  I've read a bunch of books on Elon.
• 1:00
  Yeah.
• 1:01
  I think they're all pretty bad because they get lost in stuff that doesn't matter.
• 1:07
  What's really fascinating about this book is if you want to know how to implement in your business or in your life, all of this is original content from Elon.
• 1:17
  So basically Eric was brilliant.
• 1:19
  He goes, why would I try and add my narrative and context and thoughts?
• 1:23
  Like, no, this guy is brilliant.
• 1:25
  Let me just go find everything he's put out in the world and slim it down with his own words.
• 1:32
  And this is what's so powerful.
• 1:34
  So these are quotes.
• 1:35
  This is not the guy.
• 1:37
  The entire book is quotes.
• 1:38
  Oh, that's sick.
• 1:39
  So if you literally go through, the entire back part is all the place that he made the quote.
• 1:47
  Okay, so it's all original content.
• 1:49
  So I'm going to start with just some of the dog-eared pages that were kind of the bangers that got me really, really excited or excited enough to dog-ear.
• 1:58
  Okay.
• 1:58
  And I'm just running through.
• 2:00
  So this is really interesting.
• 2:01
  All of his technical managers have hands-on experience.
• 2:06
  And for example, managers and software teams must spend at least 20% of their time coding.
• 2:11
  Does that make sense?
• 2:12
  Yeah, but go deeper.
• 2:14
  You can't – he goes in this deep where he basically – managers should always take care of their team before they can take care of themselves.
• 2:20
  The supervisor is there to serve his team, not the other way around.
• 2:24
  And I love this.
• 2:25
  It's just servant leadership.
• 2:27
  So he then puts numbers to it, and he basically says, you've got to spend 20% of your time as part of the team or serving the team with the work you're doing, of actual technical work.
• 2:38
  So the idea here is that instead of being just a manager that came from Harvard and has no idea about how to do shit, then he wants people that are able to do stuff.
• 2:50
  You can't have a job.
• 2:51
  You can't have that job.
• 2:52
  Right.
• 2:53
  You're right.
• 2:54
  So basically that disqualifies this person because they'd be like, no, no, no.
• 2:58
  20% a day of your week should be just getting down into the problem, doing the work.
• 3:03
  So I love it.
• 3:04
  He has one quote about hiring, which is one of the questions that he asks when hiring.
• 3:10
  Yeah, he goes in and I think, I don't remember exactly where that book is.
• 3:14
  Do you want to hit that now or you want me to try and find that later?
• 3:16
  The hiring piece.
• 3:17
  Okay, we can go later.
• 3:18
  And I think we'll hit it.
• 3:21
  This page has the second piece that I really like.
• 3:24
  So it says, always be smashing your ego.
• 3:28
  internalized responsibility.
• 3:30
  Whether you're a CEO or any other role, do whatever it takes to succeed.
• 3:34
  So he says a major failure mode is high ego to ability ratio.
• 3:40
  So how do you remember this?
• 3:43
  Ego, E, ability, A, and ratio, R, E-A-R.
• 3:48
  So what I think about is ear, E-A-R.
• 3:52
  When you have somebody who has these big ears, right, or maybe small ears, they're never listening to the other person.
• 4:00
  They're not even listening.
• 4:01
  They're just waiting to communicate how smart they are or how big of an ego they have.
• 4:06
  And so ego to ability.
• 4:07
  So Elon, I think, uses numbers for this, but you could say 1 to 10 ego, right?
• 4:12
  If I'm a 10 ego and a 1 ability, right?
• 4:16
  10 divided by one, that's a 10, that's bad.
• 4:20
  Versus if you were a five ego and a five ability, you're a one.
• 4:24
  So you want this low number in the ego to ability ratio.
• 4:29
  I love that.
• 4:30
  In the book he's putting all the quotes, does he say when were these quotes, what's the year?
• 4:35
  Because Elon went through major transformation.
• 4:38
  No.
• 4:39
  So he doesn't do anything like that.
• 4:41
  You can go back and you can source it to see, you know, on your own what time of day it is.
• 4:45
  But no, it's agnostic to time.
• 4:49
  I love that one.
• 4:49
  Ear, what else?
• 4:50
  Yeah, so Ear is interesting.
• 4:51
  He says, in AI terms...
• 4:54
  If you have a high ego to ability ratio, like a 10, what I said, you'll break the reinforcement learning loop, RL loop.
• 5:02
  So reinforcement learning, you want to have a strong RL loop, which means internalizing responsibility and minimizing ego.
• 5:10
  So I look at that as being in touch with truth.
• 5:13
  and trying to collect truth from anyone, right?
• 5:16
  There's famous stories about a lot of CEOs that realize, or dictators that realize none of the information they're getting is accurate, right?
• 5:23
  Because their ego's high, their ability is low, and people are just feeding them whatever they wanna hear versus the opposite, which is like, hey, my ego's low, my ability's really high.
• 5:35
  People are bringing me all the information because of that low.
• 5:38
  And I just think it's powerful as a reminder.
• 5:40
  We have two ears, one mouth.
• 5:42
  That's what he's reminding us.
• 5:44
  I love it.
• 5:44
  Keep going with another banger.
• 5:46
  So this is banger number one.
• 5:49
  So I'm flipping to the dog-eared pages.
• 5:53
  This is a really good one.
• 5:54
  If you punish people too much for failure, then they will respond accordingly and the innovation you get will be incremental.
• 6:02
  Nobody's going to try anything bold for fear of getting fired or punished in some way.
• 6:06
  If you expect innovation, the compensation structure must reflect that.
• 6:10
  the risk reward must favor taking bold moves.
• 6:13
  That's huge.
• 6:14
  And then he says, failure is a side effect of iteration.
• 6:17
  I once told a discouraged engineer, quote, if you can't tell me four ways you fucked up something before you got it right, you weren't the one doing the real work.
• 6:26
  Oh, I love that.
• 6:27
  So I wrote four ways wrong equals one way right.
• 6:32
  And this is a cool crystallization of like, to get something awesome, you had to try five ways.
• 6:39
  That is a great question for hiring.
• 6:41
  Of course, it's going to depend on what are you hiring people for, right?
• 6:44
  But, man, if you're hiring for a high position, there's no way that they didn't make mistakes.
• 6:50
  Spot on.
• 6:51
  And if they didn't make a mistake, that means that they were not doing shit.
• 6:54
  They weren't doing it.
• 6:56
  And he just drills down.
• 6:57
  You ask why 50 times during the interview on one project.
• 7:00
  And you ask what was the greatest project you were involved on.
• 7:04
  And if they really did it, they can know every detail.
• 7:07
  So the follow-up to the four ways wrong, one way is right, and the you want to incentivize bold.
• 7:13
  And I have a great person that works for me.
• 7:16
  And I told her, I was like, your biggest feedback, have I told you this already?
• 7:20
  The biggest feedback for her?
• 7:21
  No.
• 7:22
  You need to make more mistakes.
• 7:24
  If you're not making more mistakes, you're going too slow because you're looking for my approval and you're too scared of making mistakes.
• 7:30
  But your mistake ratio should be higher than what it is.
• 7:35
  So the second page off of this is page 122 and 123.
• 7:39
  It says, you will lose.
• 7:41
  It will hurt the first 50 times.
• 7:44
  When you get used to losing, you will play each game with less emotion.
• 7:48
  I love that.
• 7:49
  And that's so deep that it just, it removes that really hard punch in the face that kind of rocks you.
• 7:58
  This is interesting.
• 7:59
  This is why potentially many very successful entrepreneurs didn't do very well at school.
• 8:04
  I mean, we got the punch in the face.
• 8:07
  from the official authorities early on.
• 8:10
  And then most A-plus students, they never got punched in the face until they went out into the real world.
• 8:17
  And that really hurt.
• 8:18
  And therefore, I don't, I want to stop trying this thing.
• 8:21
  I was facing this with a conversation today with someone where I was offering a different idea and I said to them,
• 8:30
  Like they had an idea, I had a different one, and I could feel their emotion of being wrong, right?
• 8:35
  They were a great student, and they were stressed at the idea of being wrong.
• 8:38
  And Elon's basically saying, if you just get punched in the face 50 times being wrong, number 51 does not matter.
• 8:45
  WD40, it was the 40th formula, right?
• 8:49
  39 failures.
• 8:50
  And I think this is the key to drive that.
• 8:52
  I'm looking at the following pages, wasn't on the banger list, but I really like.
• 8:56
  So at Tesla,
• 8:58
  It says, what are the benefits of simplicity at scale?
• 9:01
  It says, at Tesla, the Model 3 body line in Fremont was only ever meant to make 5,000 cars a week.
• 9:07
  And it's now doing 7,000.
• 9:10
  We achieve that by removing things.
• 9:13
  We have been doing a lot of foolish things.
• 9:14
  We changed some of the designs and made them simpler and easier to build.
• 9:17
  Simplicity comes from hundreds of little changes.
• 9:20
  And he finalized that by saying, I look at every tiny part of each process and ask, quote, is this necessary, a process necessary, end quote.
• 9:30
  Yeah.
• 9:30
  So that's where his famous phrase of the best part is no part.
• 9:34
  No part.
• 9:35
  Or the best process is no process.
• 9:37
  Spot on.
• 9:38
  And I kind of, I called this a flip and I said, you do more by doing less.
• 9:43
  So like they went from 5,000 cars maximum that that building was made for to doing 7,000 by doing less.
• 9:49
  Yeah.
• 9:51
  There is another very cool story where the whole line gets stopped by something and then he goes like, hey, what's the problem?
• 9:58
  Well, we are waiting for approval from this other department.
• 10:01
  It's like, okay, call this person right now.
• 10:03
  Find the person.
• 10:04
  And then basically the other person was also waiting for the other department, which makes no sense.
• 10:09
  It's like, okay, what happens if we remove it?
• 10:11
  Well, we never removed it.
• 10:12
  Well, let's just try it.
• 10:14
  Yep, and he doesn't even work there anymore.
• 10:15
  Nothing happened.
• 10:16
  The next page, and I don't know if it shows up well, but it says your line, the best part is no part, the best process is no process, and it shows you cutting from 10 steps to three to one, and then it has the quote, the best part is no part, the best process is no process.
• 10:32
  And he summarizes.
• 10:33
  Go ahead.
• 10:34
  He also says that if you don't have to add something back, that means that you did not remove enough.
• 10:41
  Correct, and we'll get into that.
• 10:43
  That's his algorithm that's really powerful.
• 10:45
  Here, the second line, it's a lot of minimizing things that can go wrong and maximizing the efficiency of the simple things.
• 10:52
  And this happens so much, right?
• 10:53
  We create trade-offs or nice-to-haves that shouldn't be there.
• 10:57
  And they really complicate everything versus just cutting them out completely.
• 11:02
  So this is, I think, from Steve Jobs.
• 11:05
  I wrote down on page 128 where he says, it's easy to say simplify, but it's very difficult to do it.
• 11:12
  And that comes back to Steve Jobs as well.
• 11:15
  You know, you want fewer things, not more.
• 11:18
  Okay.
• 11:18
  So here's, here's the algorithm.
• 11:19
  So you, you went into this a little bit.
• 11:22
  This is powerful.
• 11:22
  So it says the algorithm I have.
• 11:25
  Share it.
• 11:25
  Peter, I think that a cool thing would be that for people that like to read the book, just share the page that you're reading.
• 11:31
  Okay.
• 11:32
  Great, great point.
• 11:33
  So page 130 has the algorithm.
• 11:36
  And I love this is I've become a broken record on the algorithm, but it's helpful to say it to an annoying degree.
• 11:41
  So I literally was just talking about this last meeting I went to because I just keep repeating it.
• 11:46
  And then the guy that works for me on this nonprofit, he points to the wall and he has the algorithm up on the wall and it's all five steps.
• 11:54
  That's right.
• 11:55
  So the algorithm.
• 11:57
  I have everyone at my companies rigorously implement a five-step process for engineering.
• 12:01
  I call it the algorithm.
• 12:03
  I'll list the steps, then explain the order is very important.
• 12:06
  Number one, make your requirements less dumb.
• 12:10
  Number two, try very hard to delete the parter process.
• 12:15
  Number three, simplify or optimize.
• 12:17
  Number four, accelerate.
• 12:19
  Number five, automate.
• 12:21
  Why?
• 12:21
  And the steps are very important.
• 12:24
  So question.
• 12:25
  Question.
• 12:26
  Make your requirements less dumb.
• 12:27
  Do you want me to tell you how I memorize the algorithm?
• 12:30
  Because this might help.
• 12:31
  Before that, I want to understand it.
• 12:33
  So make the requirements less dumb.
• 12:35
  What would be an example?
• 12:37
  I say... By the way, does he put any examples about that?
• 12:40
  That you can remember?
• 12:41
  Yeah.
• 12:42
  Yeah, I mean, he said this right after he goes, I've personally made this mistake of going backwards on all five steps multiple times.
• 12:49
  Many things at Tesla were automated, accelerated, simplified, and then deleted.
• 12:53
  One example was fiberglass mats on top of the battery pack.
• 12:57
  At one point, I was basically living on the battery pack production line because it was choking the entire car's production.
• 13:02
  Yeah.
• 13:02
  The first mistake was trying to fix the automation to make the robot better, to make it move faster on a short path.
• 13:08
  We increased the rate by 20%, then 100%.
• 13:10
  Then we tried to optimize the use of glue and drying speed.
• 13:13
  Automating was a mistake.
• 13:15
  Then accelerating was a mistake.
• 13:17
  Then optimizing was a mistake.
• 13:18
  Finally, I asked the battery safety team, what the hell are these mats for?
• 13:24
  Fire protection?
• 13:24
  They said, no, they're for noise and vibration.
• 13:28
  I said, but you're the battery team.
• 13:32
  So I asked the noise vibration team, analysis team, what's the mat for?
• 13:36
  They said fire safety.
• 13:38
  It was like being a Dilbert cartoon.
• 13:41
  I feel like I'm a Dilbert cartoon quite frequently.
• 13:45
  So we ran a test, a car with and without fiberglass mats and a microphone in both.
• 13:49
  No one could tell the difference.
• 13:50
  So we deleted the part, the mats, which deleted a step that required $2 million of robotics because it was just a big pile of nonsense.
• 13:57
  Okay, by the way, so these two, for me,
• 14:01
  It's extremely helpful because now I can see with a real example, what he means with the step number one.
• 14:07
  So there was, so the bottom line is there was for whatever reason, there was a request that was very dumb, made zero sense and made everything slower, more inefficient, cost more money.
• 14:20
  Yeah.
• 14:20
  So the goal is first to, okay, what, what, what of all the things that we are requesting here makes no sense.
• 14:27
  Let me show you.
• 14:27
  This is why the book's so good.
• 14:29
  So it explained the steps you said.
• 14:31
  I didn't know.
• 14:32
  You asked me a question, so I just started reading.
• 14:34
  The first paragraph after that was that little explanation.
• 14:38
  And then the next question after says, can you walk me through the steps?
• 14:43
  So now he goes through each one, and he says, for example, step one, you know, the first goal is to make the requirements less dumb.
• 14:51
  You have to start there.
• 14:53
  Otherwise, you could get the perfect answer to the wrong question.
• 14:56
  This step makes the question the least possible wrong.
• 14:58
  Your requirements are definitely dumb.
• 15:01
  It does not matter who gave them to you.
• 15:03
  Requirements, this is I underline because it's so right.
• 15:07
  Requirements from smart people are the most dangerous because you're less likely to question them.
• 15:15
  Always question requirements, even if it came from me.
• 15:18
  Everyone is wrong some of the time.
• 15:21
  Boom.
• 15:22
  Yes.
• 15:22
  I love it.
• 15:23
  How good is that?
• 15:24
  And it's so good.
• 15:25
  It says whatever requirements or constraints you do have must come from a person, not a department.
• 15:32
  You can't actually ask a department.
• 15:34
  You have to be able to ask a person.
• 15:36
  And the person putting forth the requirement must take responsibility.
• 15:39
  So I put a reminder of initials.
• 15:41
  Like I've heard him as a string is saying, I want the initials, each part of who came up with it, which I think is kind of cool as an idea as a business, because one, it gives me pride to be like, I'm on the muffler.
• 15:53
  I think we wouldn't have a muffler, an electric car, but whatever muffler equivalent is.
• 15:58
  But then it also, so one, it's a prideful thing.
• 16:01
  But then two, when you're questioning, well, we have an electric car.
• 16:04
  Do we really need a muffler?
• 16:06
  Oh, let's go ask Peter.
• 16:07
  His initials are on it.
• 16:09
  So it's kind of fascinating to tie it back to the individual over the department.
• 16:13
  Any questions on that one?
• 16:15
  No.
• 16:15
  Keep going.
• 16:16
  Okay.
• 16:16
  So that's number one.
• 16:18
  Number two, step two is, so it says if you're not deleting things back 10% of the time, you're not deleting enough.
• 16:26
  If you're not adding back.
• 16:28
  Yes.
• 16:30
  If you're not adding deleted things back 10% of the time, you're not deleting enough.
• 16:36
  So that's a pretty powerful quote.
• 16:38
  Somewhat illogically, people often feel they've succeeded if they are not forced to put anything back in.
• 16:44
  So that's a flip, right?
• 16:45
  I mean, and I didn't even mark down the flip.
• 16:48
  He's flipping it.
• 16:49
  You only succeed if you're forced to add things back.
• 16:53
  Because then you know you've gone enough on the deleting.
• 16:55
  Which most people would take it as a failure.
• 16:57
  Completely.
• 16:58
  And that's why they want to play it safe.
• 17:00
  And this is why...
• 17:03
  gas powered cars look like they look like, which is a clusterfuck inside.
• 17:07
  It's unbelievable.
• 17:08
  And then you go inside of a Tesla and it's beautiful.
• 17:11
  It's a spectacular machine.
• 17:13
  And so here's another example is at SpaceX, I would tell the team we are on a deletion rampage.
• 17:18
  Nothing is sacred.
• 17:19
  We will delete any remotely questionable tubes, sensors, manifolds, et cetera, tonight.
• 17:24
  Please go ultra hardcore on deletion and simplification.
• 17:28
  Yeah.
• 17:28
  we put immense effort into reducing mass.
• 17:31
  So when I hear that, all I think of is the engines, where they went from the first rocket engine, which was like a cluster of wires and tubes, and then you have the one, two, and three, and the third one's like barely.
• 17:42
  That's incredible.
• 17:43
  Yeah, a picture of something like that.
• 17:45
  So he underlined this.
• 17:46
  I underlined this one.
• 17:47
  The most common mistake for smart engineers is to optimize a thing that should not exist.
• 17:54
  That's a banger.
• 17:55
  Okay.
• 17:56
  And I think that also here is maybe what I would say is I don't have an engineering background nor an engineering company.
• 18:04
  And I think that it's for anybody else that is listening to this.
• 18:08
  This still applies to us.
• 18:09
  Yes.
• 18:10
  We are still making requirements that are dumb, so we need to find what those are.
• 18:15
  We are still overcomplicating things.
• 18:18
  Totally.
• 18:19
  Most of the time, when there is a problem, the default is to create something new.
• 18:25
  So we end up...
• 18:27
  We will never end up having zero problems.
• 18:30
  We always keep going to have, that means that we are growing.
• 18:34
  So then if you are adding something, by the way, is that a must to add that thing?
• 18:40
  Or maybe we need to change something that we are doing, or maybe we need to delete something that we are already doing.
• 18:44
  And when you look at the greats, the Dysons, the Elons, the Steve Jobs, a lot of these people, they were all masters of deleting, not adding.
• 18:53
  And I think that the miscalculation we make is to think we can have everything versus the reality is the solution is it's a tradeoff, right?
• 19:05
  You don't have a solution.
• 19:07
  You have tradeoffs.
• 19:08
  And to think of the solution as just trade-offs solves all your problems, right?
• 19:12
  By elevating one, I'm hurting the other one.
• 19:15
  So he said that this is really deep combined with this algorithm.
• 19:20
  He said, everyone was trained in high school and college to answer the question in front of them.
• 19:26
  It's covert logic.
• 19:27
  You can't tell the professor, professor, your question is dumb.
• 19:31
  You have to answer the question.
• 19:33
  Without knowing it, almost everyone has this mental stray jacket on.
• 19:37
  They'll work on optimizing a thing that should simply not exist.
• 19:41
  And above that, I wrote, it's a flip and it's a question the question.
• 19:46
  And this is what I started noticing.
• 19:47
  You get these really brilliant guys question whether or not the questioner has the right question.
• 19:54
  They hit it on the head.
• 19:55
  They're like, I think what you're trying to ask is X.
• 19:59
  not why.
• 20:00
  And the question will be like, yeah, yeah, actually that is what I'm curious about.
• 20:04
  But we were never trained that in our education and in modern day education.
• 20:08
  So this is a muscle that we don't have a bicep and we're trying to do bicep curls.
• 20:13
  So we have to build this muscle.
• 20:15
  And I think it feels rude when I think about my own, like it's challenging to do because you feel like you're rude, but once you start doing it, you realize it's a goldmine.
• 20:24
  Okay, can I tell you how I remember the algorithm?
• 20:27
  You ready for a bing or a way to remember?
• 20:28
  Okay.
• 20:29
  So we hit hard on school and, you know, blah, blah, blah, and, you know, how this kind of ties to people that are maybe good at school or bad at school in different ways.
• 20:41
  So I memorized it as two Ds.
• 20:44
  So the D students are the start.
• 20:47
  So, like, let the D students start, which is doubt,
• 20:52
  and then delete.
• 20:54
  And then once you've let the D students do their beautiful artwork, then you can bring in the A students to finish the process.
• 21:03
  So like Pablo and Peter, your D students start with doubting, like, why do I need to do this?
• 21:07
  I don't think we need this part.
• 21:09
  I don't think this should exist.
• 21:11
  I don't even want this business.
• 21:13
  delete or doubt all of it after you've doubted these questions of like, well, we need this.
• 21:19
  I'm a PhD.
• 21:20
  I'm a CPA.
• 21:22
  Just doubt it.
• 21:23
  Then you delete.
• 21:25
  So now it's like, no, trash, trash, trash, trash, trash.
• 21:28
  Okay.
• 21:28
  So you brought in the D students, Peter and Pablo, D and D. Now you open the door for the final three steps, which are A.
• 21:35
  The first one, the third one is add back.
• 21:38
  So you want to add back 10%.
• 21:41
  The fourth one is accelerate.
• 21:44
  And the final one is automate.
• 21:46
  And I'm literally building a software business right now.
• 21:48
  And we had to use this process because we were trying to do 100% automation.
• 21:54
  And we kept hitting our heads against the wall.
• 21:56
  So then we used a low-cost person...
• 21:59
  overseas outside of America to do the one task we couldn't automate.
• 22:03
  And it's working so well.
• 22:05
  So when you say Accelerate as well, Elon, what does he mean with that?
• 22:09
  Do you have an example there?
• 22:11
  Yeah.
• 22:13
  Let me check.
• 22:14
  I don't know if he mentions specifically in the algorithm section on Accelerate.
• 22:18
  Or maybe you can butcher it.
• 22:20
  It's fine.
• 22:20
  I mean, a lot of times, so I'm flipping forward a couple of pages.
• 22:23
  He does say stuff like
• 22:26
  the best offense and defense is speed.
• 22:28
  The SR-71 Blackbird is a military plane with almost no defense except acceleration.
• 22:33
  It was never shot down, not even once.
• 22:35
  Over 3,000 miles, missiles were shot at the SR-71 Blackbird and none hit it.
• 22:40
  All it did was go faster.
• 22:42
  The power of speed is underappreciated as a competitive factor.
• 22:45
  And he calls this the rate of innovation, which I consider ROI.
• 22:50
  I think all of that is really what he's driving is
• 22:53
  Accelerating is you want to bring in machinery.
• 22:56
  So, for example, in a recent interview, he said, you can't use 3D printers to do rocket parts because it's not fast enough at scale.
• 23:03
  So, you know, accelerating is the step before you do a full automation.
• 23:10
  And so it just means cycle time, speed, how quickly you can pump out this piece.
• 23:15
  And software, which I'm not familiar with, you just think about it doesn't mean it's – if it's 95% automated or accelerated, awesome.
• 23:24
  That's the goal.
• 23:26
  Okay, cool.
• 23:27
  Okay, so next question to question, we went optimize the thing that should not exist.
• 23:31
  And then automate.
• 23:32
  Yeah.
• 23:33
  So D, D, A, A.
• 23:35
  D, D, A, A, A. Oh, three A's.
• 23:38
  Three A's.
• 23:39
  So you have add, accelerate, automate.
• 23:41
  Oh, you're right.
• 23:42
  Yes.
• 23:43
  And it's an easy way to remember it because think about it.
• 23:44
  The A students will jump in to just let's automate the whole thing.
• 23:49
  It's the D students that are like a little bit lazy.
• 23:52
  They're like, I think you're full of it.
• 23:54
  Like, I don't think you're right.
• 23:55
  I don't really want to do this, which is me.
• 23:58
  Like, that's how I would approach it.
• 24:01
  And not to say I'm Elon, but it's like Elon summarized a process that I think a lot of successful people do.
• 24:07
  He's obviously the greatest.
• 24:08
  Love it.
• 24:09
  Okay, what else?
• 24:11
  Other banger.
• 24:12
  Yeah, let's go other bangers, then we'll come back to the individual ones.
• 24:16
  So on page 190, he says, people often believe things inversely proportional to the evidence.
• 24:22
  It's so strange.
• 24:24
  Given a set of explanations, why pick the extremely unlikely one?
• 24:28
  So I thought that was interesting.
• 24:31
  For me, I think that hits deep in a book I was reading today where we really should believe in the bizarre, but we're actually, you know, stuck and we're stuck with the familiar.
• 24:45
  So, like, it doesn't matter how much new information.
• 24:47
  So, like, right now, you and I have been in full self-driving.
• 24:51
  But people don't care how many times they hear like, the car saves you nine times less likely to die.
• 24:57
  They're stuck with their own belief based on, well, I've always driven a car, so I'm always gonna drive a car, right?
• 25:02
  And this is gonna age well.
• 25:04
  But right now, I took two people after dinner last night in my full self-driving vehicle, and they were like, no, no, no, I'm just gonna drive my truck.
• 25:11
  I got my F-150 Ford truck.
• 25:13
  And I was like, yeah, no, you should do full self-driving.
• 25:16
  And it's wild to see how much we hang on to our belief, even though evidence, knowledge, all these things start pointing a different way.
• 25:26
  So he said, an example of this, we create as much fresh water.
• 25:30
  We could create as much fresh water as we want.
• 25:32
  Earth is mostly water.
• 25:34
  We should call Earth water.
• 25:36
  It's 70% water by surface area.
• 25:39
  Like, I think that's just a fascinating flip to realize, like, that's what we are as a planet.
• 25:43
  And also as a body, I think we're like 70% water.
• 25:46
  Yeah.
• 25:46
  Okay.
• 25:47
  Okay.
• 25:48
  Next.
• 25:48
  Let's see what other bangers we got.
• 25:51
  Well, let me ask you a question.
• 25:52
  Maybe, maybe you remember this.
• 25:54
  If you have to think of like, okay, what are the top five things from this book?
• 25:59
  And by the way, you, you may already have mentioned a couple of them.
• 26:03
  Yeah, I think let me, I don't have, I don't have five off the top.
• 26:06
  And that's, that's the reason I like summarizing or going back through.
• 26:09
  Like I reread my favorite books a lot because I can't remember it like that.
• 26:14
  The algorithm is number one by far and away.
• 26:17
  If there's only one thing you can take away, take the algorithm because it applies to everything in your life, especially now that bots are real and AI and we're start automating a lot of, we could automate things in our life is crazy.
• 26:30
  But I got one more page of that banger that I see.
• 26:33
  So this hits so deep.
• 26:35
  Start before the world is ready.
• 26:37
  We say things we believe in, even when sometimes those things we believe are delusional.
• 26:42
  So when building a radically new product, people don't know that they want it yet because it's not in their scope.
• 26:48
  Around 1946 to 1948, when they first started making TVs, they did a famous nationwide survey.
• 26:56
  Will you ever buy a TV?
• 26:58
  Right.
• 26:58
  So TVs are brand new.
• 26:59
  Guess what percentage of people said, no, they will not own a TV?
• 27:04
  90.
• 27:04
  96%.
• 27:07
  Yeah.
• 27:08
  And I think that's so powerful to realize.
• 27:12
  And he said, in the beginning of Tesla, no one told us they want an electric car.
• 27:16
  I heard that zero times.
• 27:19
  If you need encouragement, don't start a company.
• 27:21
  Okay, that's a great one.
• 27:23
  If you need encouragement, don't start a company.
• 27:26
  That is an incredible one.
• 27:28
  Yeah.
• 27:29
  Yeah, I think it is deep.
• 27:30
  Especially because nowadays we are living in a world where tons of people can be solopreneurs.
• 27:36
  But to me, there is a big difference between being a solopreneur and starting a company.
• 27:41
  Yeah, solopreneur is just you have a job, you're self-employed with a job.
• 27:47
  Exactly.
• 27:49
  In almost all cases, it's just a job where you are the boss, which arguably is more stressful in certain scenarios, right?
• 27:55
  Because you're dealing with everything and you don't have a team.
• 27:58
  Yeah, you might be able to manage your own time.
• 28:00
  You might be able to decide, I'm not going to work today or Wednesday, or I'm going to stop working at 1 p.m., which you most likely won't be able to do that if you work in an office.
• 28:09
  Yeah.
• 28:10
  But as you are saying, it comes with a lot of
• 28:14
  potential downsides, which is, well, you need to take care of a lot of admin and a lot of things.
• 28:19
  And also your salary is not guaranteed because you need to be chasing for the salary.
• 28:24
  So I think that it's a very, and the reason why I'm saying this is because I see a lot, especially with the boom of YouTube and all these influencers that make it sound so easy and so cool to have a business.
• 28:38
  I think that it's very important to really pause for a second and to recognize, even if you have a business and you're making $3,000 a month or $5,000 a month as a solopreneur or $10,000 a month, is that what you really want?
• 28:52
  Is that...
• 28:54
  Because it gets hard.
• 28:56
  Do you want to scale it?
• 28:57
  Do you want to hire people?
• 28:59
  Do you want to now become a real company?
• 29:01
  Do you really need encouragement?
• 29:03
  Yeah, it's interesting.
• 29:04
  I don't know that I have as strong of thoughts in terms of – I do think you've got to be incredibly self-motivated to not be distracted in today's world and to focus on it.
• 29:14
  It leads into the cool page.
• 29:15
  The next one after the car, 96% of people said they'll never own a TV.
• 29:20
  You will never buy a TV.
• 29:23
  The next page says create more than you consume.
• 29:25
  And it's kind of getting to somewhat of a similar area where it's growing the pie, right?
• 29:32
  People, and he says this great quote, I put a lot of stock in having a grow the pie mindset, not a zero sum mindset.
• 29:40
  When I see people, even smart people with bad attitude or doing things that seem morally questionable, it's often because they have a zero sum mindset.
• 29:49
  Those who believe the pie is fixed believe the only way more pie, to have more pie, is to take someone else's pie.
• 29:55
  This is obviously false.
• 29:58
  And I think when he said this in a deep way, he tied this to politicians, right?
• 30:03
  So a lot of politicians, they've never built a business.
• 30:06
  They've never created more than they consume.
• 30:09
  So really, they're just trying to take from others, right?
• 30:11
  And that's regardless of your political leanings, right?
• 30:13
  Left, center, I don't care.
• 30:16
  It's the government's role is to take from those that are creating, right?
• 30:20
  And then they reallocate it.
• 30:21
  And hopefully they reallocate it not to their friends, but in a good way and blah, blah, blah.
• 30:26
  But that becomes a complicated piece.
• 30:29
  So I thought that was a pretty big banger of this create more than you consume.
• 30:32
  And he has a cool chart on page 43 of showing that.
• 30:36
  I do like work like hell because I am wired for war.
• 30:41
  So they said, why don't the world have more Elon Musk?
• 30:45
  And he goes, if you think you want to be me or do things I've done, I would say you're probably mistaken.
• 30:50
  Long periods of my life have been painful and difficult.
• 30:52
  I'm not sure people would want to go through that.
• 30:55
  The amount I torture myself is next level.
• 30:58
  You need to have some kind of rage demon in your skull that drives you.
• 31:03
  It's also very cool to see in the history of Elon that as soon as things start kind of like working out and things start...
• 31:12
  going great, he just creates the next, what we would call hell.
• 31:19
  He creates some hell for himself, but man, he just keeps breaking to new levels and new levels and new levels.
• 31:27
  It's extraordinary to see.
• 31:29
  Now, I want to come back for one second about create more than you consume.
• 31:33
  I think that that applies to everyone, 100% of people.
• 31:35
  Yeah.
• 31:37
  And I think that this is it's really a big problem in nowadays in society where there's no I don't really understand how so many people in the U.S. have no savings.
• 31:48
  And it's just constant consumption, consumption, consumption.
• 31:52
  And I think that this is something that is very, very important for people to to really wrap their heads around and to understand that they're not going to end up in a good way if they consume more than they create.
• 32:03
  Yeah, I think the deeper way I would look at that is what Elon is saying here is he has all the money in the world.
• 32:10
  Spending that money isn't creating more happiness, peace, excitement for him.
• 32:16
  It's actually creating more than he could consume in terms of products, wealth, whatever.
• 32:23
  And it's kind of like it sounds like bullshit because for some reason our brains are convincing ourselves if we spend more money to solve our problems, we'll be happier or peaceful.
• 32:31
  That's not true.
• 32:32
  It's actually by solving the problems, by creating solutions to problems for ourselves and others that that creates the peacefulness and happiness is what I'm reading him as stating, which is a flip.
• 32:44
  He said on the work, you must be extremely tenacious, work like hell.
• 32:48
  You have to put in 80 to 100-hour weeks every week.
• 32:51
  This will improve your odds of success.
• 32:53
  Do the simple math.
• 32:54
  Somebody else is working 50 hours a week and you're working 100.
• 32:57
  You'll get twice as much done in a year.
• 32:59
  If other people are putting in 40-hour work weeks and you're putting in 100, what takes them a year you will achieve in four months.
• 33:06
  Yeah.
• 33:07
  Nobody ever changed the world on 40 hours a week.
• 33:11
  Boom.
• 33:12
  Truth.
• 33:13
  Now, that doesn't mean that you cannot have a quote unquote balanced life, be able to chill.
• 33:19
  But if you are wired for war and if you want to do something massive, you have to be insane like Elon.
• 33:27
  You have to be able to work all the time.
• 33:29
  And yeah, I don't really think that, let's just forget about Elon for one second, but Mark Zuckerberg or Jeff Bezos or Michael Dell or the Microsoft guys or the Google boys.
• 33:42
  These guys were working all the time.
• 33:44
  Now you may see them in their private island, but they were working all the fucking time.
• 33:49
  Yeah, it's deep.
• 33:50
  I'm flipping forward to kind of his next section, which is Seek the Nature of the Universe.
• 33:56
  Yeah.
• 33:57
  So he says, this is the foundation of my philosophy.
• 34:00
  I am curious about the nature of the universe.
• 34:04
  So if we date civilization from the first written language, it was only about 5,000 years ago.
• 34:08
  This is practically no time at all.
• 34:10
  Future humans will think of us as ancient ancients like cavemen.
• 34:15
  So deep.
• 34:16
  And then I highlighted two other paragraphs in this section where he says,
• 34:22
  Basically, mostly hydrogen, though, that over a long period of time, 13.8 billion years, that hydrogen became sentient.
• 34:29
  So basically, the evolution of humans.
• 34:31
  And he says, what I think Douglas Adams was saying in his book, The Hitchhiker's Guide to Galaxy, on page 51, is, quote, the universe is the answer.
• 34:41
  We need to figure out what questions to ask about what to – we need to figure out what questions to ask about –
• 34:50
  the answer that is the universe.
• 34:52
  The question is the hard part.
• 34:54
  And if we can properly frame the question, then the answer, relatively speaking, is easy.
• 34:59
  And it ties back, actually, to we are taught to just answer whatever question is given to us rather than thinking about the questions.
• 35:07
  And I think that's really, that's a powerful shift in terms of, you know, how we think.
• 35:13
  His next section, Think Like a Physicist, you know, he pushes this whole...
• 35:18
  You know, physics is law, everything else is opinions, which is a cool... Oh, I love this.
• 35:24
  Let's go deep in this one.
• 35:25
  Yeah.
• 35:27
  If the reasoning fits and if you're not violating the laws of physics, that's the things you should try and do.
• 35:33
  These things just don't seem that crazy to me.
• 35:36
  So a lot of people say, Elon, you're crazy, or Peter, probably you're crazy with a new idea.
• 35:42
  But that's because they're constrained by just looking at how we currently operate and they're comparing themselves to the herd or the current way.
• 35:49
  What Elon's saying is only use physics as your constraints of variables.
• 35:54
  And everything is just a lack of creativity or it just hasn't been solved yet, right?
• 35:58
  And if it's a problem you want to solve, like he said, then go do it.
• 36:03
  He said the next page with page 54 is obsess over the truth.
• 36:07
  Start somewhere, then be prepared to question your assumptions, fix what you did wrong and adapt to reality.
• 36:13
  So he said, I am obsessed with the truth, obsessed.
• 36:16
  If you're going to come up with a good solution, the truth is really, really important.
• 36:21
  So just a question here or a statement, tell me if I'm getting it wrong.
• 36:25
  Most people when it's like, hey, why don't we do reusable rockets?
• 36:29
  Well, because that's just not how it works.
• 36:31
  I mean, this is impossible.
• 36:33
  And then what he says is like, well,
• 36:35
  Tell me what law of physics we are going to be breaking by doing a reusable rocket.
• 36:43
  I said, none of that?
• 36:44
  Oh, then it's possible.
• 36:47
  We can do it.
• 36:48
  We can do it.
• 36:49
  Spot on.
• 36:50
  Another example just came out.
• 36:51
  Bill, old Billy Gates, the founder of Microsoft, was visiting him in Austin with him and his engineers.
• 36:58
  This was like months ago.
• 36:59
  And Bill Gates was like, you can't, electric semi-trucks can't exist.
• 37:05
  And Elon was like, I was so confused because this is a guy who should be an engineering science-based mind.
• 37:10
  And so we were like, what do you mean it can't exist?
• 37:13
  And he's like, they can't exist.
• 37:14
  And he couldn't give us a reason with physics why it couldn't exist.
• 37:17
  And then we pulled out one of our semi trucks that's fully operational.
• 37:21
  And we said, Pepsi is using these two day to deliver drinks.
• 37:25
  So I think that's an example of this.
• 37:27
  You know, he has a cool depiction on page 55.
• 37:30
  Physics is law.
• 37:32
  Everything else is a recommendation.
• 37:34
  So I think this is powerful.
• 37:35
  And I think this is like the cool autistic side of him of like, I don't care that everyone hates me or someone's mad at me.
• 37:41
  Like, I'm a friend of truth.
• 37:44
  As long as I'm on the side of truth, it'll work out in time.
• 37:47
  Even if old Billy Gates says I'm an idiot or wrong, it just doesn't really matter.
• 37:51
  I love that.
• 37:53
  So the next page I really get excited about, page 58, goes into first principles thinking.
• 37:58
  Yeah.
• 37:59
  So I mentioned this a little bit, but he said, the normal way we conduct our lives is reasoning by analogy.
• 38:07
  That means we do something because it's similar to something else or what other people are doing.
• 38:12
  So in my notes, I wrote parents, friends, our tribe.
• 38:15
  And in most of life, we should reason by analogy.
• 38:19
  Otherwise, mentally, you wouldn't be able to get through the day.
• 38:21
  It would be too much thinking.
• 38:24
  So basically, we just...
• 38:26
  We optimize for this similarity or analogy, right?
• 38:29
  So like, that looks like what my dad did.
• 38:32
  So I'm going to do it.
• 38:34
  That looks like how my mom did it.
• 38:37
  And really, it reminds me of the old quote where it says, an old fish swam by two young fish.
• 38:42
  And the old fish said, how's the water, boys?
• 38:44
  And the two young fish said, what's water?
• 38:47
  And it's like, we don't even realize that we are these young fish that live all of our decisions by analogy, rather than by a first principles thinking, which is what Elon's recommending here.
• 38:57
  So first principle thinking is incredible.
• 39:00
  But does he go in depth to explaining how he does it, what it is?
• 39:04
  Dude, this is why this is one of your favorite books.
• 39:06
  So the next page, page 59.
• 39:09
  How have you applied first principles thinking to building companies?
• 39:12
  Here's an example from early in building Tesla.
• 39:15
  People said battery packs were too expensive to make cheap electric cars.
• 39:19
  They assumed they would always be expensive because they had been in the past.
• 39:24
  That's pretty dumb.
• 39:26
  If you applied that reasoning to everything new, then you would never try anything new.
• 39:32
  Okay.
• 39:33
  Nobody wants a car.
• 39:34
  Horses are great.
• 39:36
  We're used to them.
• 39:37
  They can eat grass.
• 39:38
  There's lots of grass all over the place.
• 39:40
  There's no gasoline available.
• 39:42
  So people will never buy gas cars.
• 39:44
  People did say that a lot.
• 39:47
  So I wrote as a line below that paragraph, where is the puck going?
• 39:52
  And I think that's a really deep way to think about not where are we today,
• 39:57
  Not what my dad did 50 years ago, but where is the puck going is the question to really ask yourself as an entrepreneur, as a business owner, or as a professional person.
• 40:07
  So in the first principles thinking, he said...
• 40:12
  First principles thinking built SpaceX.
• 40:14
  Most people think, quote, historically, all rockets have been expensive.
• 40:18
  Therefore, in the future, all rockets will be expensive, end quote.
• 40:21
  But that's not true.
• 40:22
  So that is reasoning or thinking by analogy.
• 40:26
  By analogy.
• 40:27
  And this is page 61.
• 40:29
  So just if you simplify it really basic, and Peter Thiel really likes that.
• 40:33
  It was a Stanford professor of this called mimetic desire, which is like we on a human level want to mimetic mirror those around us.
• 40:42
  So first principles thinking, let's apply it right now.
• 40:44
  Why do Pablo and Peter do first principles?
• 40:47
  Because genetically, we only survived as part of a tribe.
• 40:51
  So our brain told us, don't get kicked out of the tribe or you're toast.
• 40:54
  Right?
• 40:55
  Individuality reduced and communal living is really prioritized, is the goal.
• 41:01
  So you raise that up.
• 41:03
  That's in us.
• 41:04
  And if we don't realize that's part of us, then we're this fish swimming in water that don't know what water is.
• 41:10
  If we recognize that, then we can start building this muscle, which is to say, I want to build by, live by, build by first principles.
• 41:18
  First principles are physical laws that exist in nature, and those are our only constraints.
• 41:23
  Does he go in detail explaining first principles?
• 41:28
  No, he doesn't.
• 41:30
  You know, he does explain, I would encourage people to use mental models, mental tools of physics and apply them broadly in life.
• 41:37
  They are the best tools.
• 41:39
  So he kind of talks about that, and then he explains half a page of physics.
• 41:43
  When you think this way, you only get slight iterations.
• 41:45
  It's easier to reason by analogy rather than from first principles.
• 41:48
  So that's what we do most of the time.
• 41:50
  And most of life, we reason by analogy.
• 41:52
  Otherwise, mentally, you wouldn't be able to get through the day.
• 41:54
  It would be too much thinking.
• 41:56
  What he's saying more in very critical decisions, we need to understand we are automatically always going and thinking by analogy.
• 42:04
  But in very important things, we should use that extra brain with and create this muscle to think in first principles.
• 42:11
  The way that I think about or I implement first principle is I keep asking questions to get to the root, to get to the core and immutable nature of what we are discussing.
• 42:25
  And which point of that is the algorithm?
• 42:27
  That is...
• 42:29
  The first D. That's right.
• 42:31
  First D. You're the first D student.
• 42:33
  I'm the second D student, right?
• 42:34
  Let's go.
• 42:35
  Pablo starts doubting it all.
• 42:38
  And then there's Peter deleting it, just throwing him in the trash, right?
• 42:41
  Like, yep, that's not needed.
• 42:42
  Throw it in the trash.
• 42:43
  And I think that's what's so neat.
• 42:44
  And Elon is so good at cutting through noise to explain what many people think that are successful thinkers.
• 42:53
  But then he summarizes in a way where like, oh, wow.
• 42:55
  Wow.
• 42:56
  He really nailed it on how he said it.
• 42:58
  So first principles, he doesn't go in deep.
• 43:01
  This is page 60 and 61.
• 43:04
  I really like this one.
• 43:06
  So he's talking about how to build SpaceX.
• 43:08
  And he says, this is so good.
• 43:10
  That's going to set the floor of the Casa Rocket.
• 43:12
  I call this the magic wand number.
• 43:14
  So he starts where he basically says,
• 43:17
  Just imagine you're producing at a really high level.
• 43:21
  So I'll read this, the full paragraph.
• 43:23
  The way we applied first principles thinking to rocketry was asking, what are the materials that go into a rocket?
• 43:29
  And this is literally when he sold SpaceX.
• 43:31
  He hopped on a plane and he just opened an Excel sheet and started adding up the different components with the raw cost.
• 43:39
  And he went out to Russia to compare it against the raw class.
• 43:42
  So what are the materials that go into a rocket?
• 43:44
  A rocket is made from aluminum, titanium, copper, and carbon fiber.
• 43:49
  Break it down further and ask how much of each material is used.
• 43:52
  Now, what is the cost of all these raw components?
• 43:55
  If you have them stacked on the floor and could wave a magic wand to create the rocket, what would the cost of the rocket be?
• 44:01
  We imagine the cost of rearranging the atoms was zero.
• 44:05
  That's going to set the floor of the cost of the rocket.
• 44:07
  I call this the, quote, magic wand number, end quote.
• 44:11
  The hypothetical best-case scenario for rockets, that turned out to be a relatively small number, well under what percent would you guess, Pablo?
• 44:18
  I don't know.
• 44:20
  Well under 5% of the current cost, in some cases closer to 1% or 2% of the cost.
• 44:27
  From the magic one number?
• 44:29
  Yes.
• 44:30
  So let me see.
• 44:31
  So he says, okay, what is the cost to produce a rocket?
• 44:35
  He just goes and separates every single component to the price of each of them.
• 44:40
  And it's like, okay, total $10 million to do the rocket.
• 44:43
  Okay.
• 44:44
  And you're saying that the final cost, when they did it, it's around between 1% to 5%.
• 44:51
  So what you just said, let's play that out.
• 44:53
  He adds them up, it's $10 million.
• 44:56
  That's 1%.
• 44:58
  So the cost of the current rockets when he did that calculation was a billion dollars when he did that calculation.
• 45:05
  So?
• 45:06
  So it was a billion dollars to build a rocket.
• 45:08
  The raw materials were only $10 million.
• 45:10
  I see.
• 45:10
  Okay.
• 45:12
  So he looks at that map and he says, he calls this the idiot index?
• 45:17
  The idiot index, yeah.
• 45:18
  So he said… Explain that.
• 45:23
  The first principles thought process was around the rocket became general purpose for all parts.
• 45:28
  I call it the idiot index.
• 45:30
  How much more does a finished product cost than the cost of the materials?
• 45:35
  If a part or product had a high idiot index, we would cut the cost with more efficient manufacturing techniques.
• 45:42
  A component that costs $1,000 when the aluminum it was made from costs only $10 likely has a design that is too complex or an inefficient manufacturing process.
• 45:52
  If the ratio is high, you're an idiot.
• 45:57
  So he wraps it up by saying later on on page 62, what are all other rocket companies doing?
• 46:03
  What do their rockets cost?
• 46:05
  What historically have rockets cost?
• 46:07
  That is reasoning by analogy, but it really doesn't illustrate what the true potential is.
• 46:14
  The first principles approach is a good way to figure out counterintuitive solutions.
• 46:18
  It was a helpful thing to learn.
• 46:21
  I love it.
• 46:24
  Let me hit one more.
• 46:25
  Thinking in limits, it's another good physics tool is thinking about things in the limit.
• 46:31
  Take a particular idea and imagine scaling it to very large or very small numbers.
• 46:36
  How do things change?
• 46:38
  So I think about that, the phrase is,
• 46:41
  Thinking in extremes informs the means.
• 46:43
  The Boring Company is a great example.
• 46:45
  This is why the book is so amazing.
• 46:46
  It gives an example each one.
• 46:47
  A common criticism of the idea of tunnels is the tunnel will get used up and there will be traffic congestion.
• 46:54
  They don't realize there's no real limit to how many levels of tunnels you can have.
• 46:59
  You can go much farther deep underground than you can build up.
• 47:03
  The deepest mines are much deeper than the tallest buildings are.
• 47:06
  If you do just two things, you can get approximately an order of magnitude improvement in tunneling.
• 47:12
  But I think you can go even beyond that.
• 47:14
  So what he's saying is people are stuck thinking that a tunnel is just going to get clogged because they only have one analogy example of being in a tunnel.
• 47:23
  They're not thinking that you could do 50 tunnels on top of each other.
• 47:27
  So you go to the extremes, it breaks your brain, and then it brings you back to the best answer.
• 47:32
  Okay.
• 47:33
  This is what Elon does, right?
• 47:35
  Thinking and limits.
• 47:36
  So he says, no, no, let's go think 10,000.
• 47:40
  Now it forces us, and this is a really good example of, it forces us to throw out, Steve Jobs would always say this too.
• 47:45
  You want to say no to a lot of good ideas.
• 47:47
  Warren Buffett says this, Elon says this.
• 47:49
  You have to say no to a lot of good ideas to make space and room for the one great one.
• 47:54
  Yeah, I love it.
• 47:55
  All right, brother.
• 47:56
  That's a wrap.
• 47:56
  Book of Elon by Eric Jorgensen.