Drew Houston - CEO and Founder of Dropbox

WEBVTT
Kind: captions
Language: en

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- So, excited to have
Drew Houston in here,

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very well known figure amongst
kind of our team out here.

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And for those who are maybe
watching this video later,

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founder of Dropbox, how many
how many billions of people

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do have using?

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I know, it's more like
hundreds of millions only.

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- 300 million.
- And only 300 million people

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- using it file sharing what
we'll talk more about that.

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But, the way I view these things,

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it's definitely for our
team to kind of meet

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and talk to really interesting
people in Silicon Valley

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and beyond but also for
kind of just the general

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Khan Academy user base out
there to kind of get exposure

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to really interesting people
in Silicon Valley and beyond.

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And with that lens, I always
think of kind of myself

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when I was 12 or 13 years old

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and when I used to watch
like Johnny Carson,

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and I always used to wonder, like,

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how do you know who are these people?

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How do they do that, like
what about like major in

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in order to become that person.

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And so I kind of want to have
a little bit of that land.

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So I'll start there.

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When you were a kid,

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kind of what did you see
yourself doing or becoming?

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And how did you try to set that up?

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- So my path started
when I was really little.

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So my my parents had PC Junior.

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So my very first computer
when I was really little.

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So first I would just
play computer games on it

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but a couple years later,
when my dad got showed me

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how there's a thing on
the computer called Basic.

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And so I was lucky, they
showed me how to write

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so my first lines of code and
I was like a really little.

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- Like how little?

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- I was five.
- That's good.

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- Yeah my son needs to get in line.

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(laughs)

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- And it turns out,

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when you're little like
that you have a lot of

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free time on your hands.

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And so, I was always like
playing on the computer

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and I really loved playing games.

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And so that was actually why
I want to learn programming

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is to learn how to make
games, how these things worked

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and like I want to insert
of my exploration of

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how the computer worked,
I would figure out like,

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oh, there's like this...

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There's like files

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and like, okay then when I save a game.

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Like I can go into that file

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and like give myself like 32,767 lives,

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it's like, all these
little things like that.

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- And if only I could
access this file from home

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and kindergarten.

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- Moving this floppy drive around, yeah.

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So I thought it was
gonna be computer games.

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That was what I would does
was interested in beginning

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as then as far as a job
I start up babysitting,

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- Really?
- So I was very good at it

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like watching I was like 12 near 11

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and like I would, the parents would leave

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I put the kids to bed.

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And I like as regular watching like HBO

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and like, this is like a requirement.

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I can only like babysit for, like,

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families that had like
good TV and like Pringles

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and things like that.

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- Then if they didn't
do that is a red flag,

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or your focal point was their cable.

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- Exactly.

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And then like, trying to like.

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And then sometimes I'd be
like watching something

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probably, like I shouldn't be watching.

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They'd be like, shooting
or like bad words.

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And I was very good like
listening from when the lock

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went in there the key were in the lock.

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- Oh yes.

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- Anyway, this has nothing to
do with starting a company,

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- Some time it will.

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- But then I got a little
bit of an upgrade on

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the job front, I was beta testing a game.

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And an online game was maybe 14.

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And they were taking
forever to build the game.

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And so I started getting
restless and curious

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and started poking around
under the hood of this game

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and I found all these security holes.

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I found all these vulnerabilities.

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Anyway first you discover these things.

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You're like, oh, my God, oh, my God.

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I started impersonating,
like the developers

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and things like that and sort of making

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like a little bit of
trouble but then I'm like,

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I sent him an email and
like guys you're really

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you should fix this, you should fix this.

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And you shouldn't have done this this way

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you should have done this way.

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And I'm like, really getting into it.

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And they're like, well,
do you want to work here?

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And so I ended up working
remotely as an engineer are like

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they're like, do you
want to fix those bugs?

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And I'm like okay.

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And then this is the first
kind of startup adventure

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first experience of many where my stock up

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since we were worth nothing.

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- Yes this 14 years old.
- That's 14.

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- 14 years old.
- And this is part time remote

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- but it was like a
cool thing to talk about

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and like, biology class.

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Anyway I had to get my dad to sign

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all the employment paperwork
and things like that.

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So, but that was the path of

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this I was literally working on a game.

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But then fortunately there as we learn

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there's a lot of other things in life.

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Beyond like, Unreal Tournament,

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which are really interesting.

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- Beyond what?

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- Unreal Tournament or
Starcraft at apoint.

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- Unreal Tournament yes that's it.

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- That's a little later on, like

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PC era was like more like
the Sierra games like

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- Yes.
- Kiddy Quest

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- for something that, you
guys weren't born yet.

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- For me it was Pong.
- Okay.

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- Yeah, that was I'm a little older.

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- We're losing up.

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(laughs)

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- Yes I'm little bit we
have a little overlap.

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And then you go to MIT

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many of us have been there as well.

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And I watched your commencement speech.

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(audience laughs)

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I watched your commencement
speech, which was great.

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It helped that the guy before
you really set a new low

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in terms of commencement speech quality,

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but your speech was really I thought,

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a really powerful speech.

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And I think it kind of
hit this issue of like

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you didn't plan on being,

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Drew Houston to Dropbox founder,

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but you did think you were
gonna be an entrepreneur.

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I mean, it seems like
while you were in college,

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you were constantly
thinking about starting

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a business of some kind.

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- Yes, and your speech was great, too.

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- I wasn't fishing for that.

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- No no it was.
- It feels good though,

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- I like it.
- You're sort of like,

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- there's no instruction
manual for these things

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I'm like, you start like
googling excessively for

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like every commencement
speech ever given before.

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Anyway, so but no, I did plan to be...

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I always was excited about doing something

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that was my own thing, whether
it's making a computer game.

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And originally, as I
learned more about business

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and starting a company I
was always just turned out

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that I joined startups as an
engineer or like an intern,

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when I was little, and then
just didn't never really left.

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- And you just keep doing
that while you were in college

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I mean, you already had
that kind of experience.

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- Yeah.
- So you're starting stuff.

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Like when your freshman year, summer year,

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were you doing stuff?

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- So the the game company unfortunately

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folded pretty quickly.

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But that then give me that experience

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and let me get a job at a local company.

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There's another startup

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but it was kind of an MIT founders,

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so there's kind of a relation there.

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But yeah, and the summers
I would taking classes

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and then every summer I would go work at

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first couple years of just the company

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that I worked at in high school.

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So they are like maybe, half hour away,

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half hour outside of Boston.

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- Yeah and the one thing
that I think is mysterious

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for everyone and even
sometimes when people ask me

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I don't have a clear answer

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'cause it's still a
little bit mysterious is

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how do you stumble on this thing
that just kind of takes off

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like wildfire that just...

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And you have an interest right man,

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you actually started kind
of a little bit closer

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to kind of what we do here
kind of your first startup

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which I think you
started your junior year?

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- Yeah.

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- Was around SAT it was called accolade.

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- Right?

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So my, you never know where
these things are gonna go.

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'Cause I mean, I think anybody
who grows up programming

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or whether it's programming
or something else,

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like there's always tinkering with things

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it's all just one project after another.

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And for and then the first
one I want to start a company

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I took my junior year off from MIT.

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So I took it took a year leave,

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which ended up being a
really great experience.

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And I promised my parents
I would come back and I did

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but so the SAT at the time was changed,

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there was like all this
change happening right.

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There emerging in the writing section,

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it's going from 1600 to 2400.

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Now, I know there's all kinds
of other stuff happening.

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But this was back in the day where

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to study for the SAT,

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you'd have to show up at
some like horrible classroom

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and like eight in the
morning on a Saturday

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to listen to some like 17 year old

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who didn't want to be there either.

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And all it was just reading out of a book.

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Like this was the state of
the art in like SAT prep

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and we're like guys like the internet.

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It's not like the internet
as been here for like

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a little while, it's like it's
been here for a long time.

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And why are we still, it's
like how my parents studied

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for the SAT.

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And so I teamed up with actually
one of my former teachers

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from high school and we
started building a new kind of

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course an online course for
the what was then the new SAT.

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- And what's your lesson I
mean, what 'cause you too,

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I guess not do that at some point

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but you worked on it for some time.

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You did.

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- It was interesting.

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So I started working on 'cause I'm like,

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here's like an opportunity.

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Here's something that my
Co-founder and I knew really well.

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I mean, I just, I don't know,

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I treated the SAT...

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Like one of the things I
really like to do is like

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reverse engineer, like how
things work, take things apart.

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So whether that's, more
typical stuff like the kind of

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tinkering that kids do, or like

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the finding all the security
problems in that game.

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When I start working on the
SAT like I had to study for it,

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I was like, how does this thing work?

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And so you can as yo know
they're always like little tricks

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and little patterns you
can take advantage of

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and I'm like, okay, the only
the really hard thing about

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the verbal section is the vocab

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'cause like you can, in
general you can teach someone

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how to do a sentence completion
without really teaching him

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it's the words that are hard.

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So, when I was 16, I
wrote all this software

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to do kind of flashcards
and adapt and remember

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which ones I was getting right

00:10:10.100 --> 00:10:11.200
and which ones I was getting wrong

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and things like that, 'cause
I didn't want it was too lazy

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to like cut out all the paper flashcards

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and I'm like this is so stupid.

00:10:18.425 --> 00:10:21.230
And so I had done that code
actually was kind of on

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the shelf for five years.

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And then and then when the SAT changed

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and I had a friend of
mine, who was a teacher

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who had his own SAT course.

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And we had this whole shtick going

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I was at MIT, he had
graduated from Harvard,

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like as a result of all this

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like reverse engineering
SAT and studying a lot for

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I got to 1600.

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So I was like, we had all
like the boxes checked

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for the parents and we're
like, we know how this works.

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So that it was really
just seeing an opportunity

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and being like, you
don't attach too much of

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an outcome around it.
Like I didn't have a goal,

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like I need to make this
much money or whatever,

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it's sort of like another
interesting project.

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And probably the best
part of that was really

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just having an excuse to learn about

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business in like a rigorous way.

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So and what I mean a rigorous
way I mean like I didn't know

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anything about sales
or marketing or finance

00:11:07.360 --> 00:11:09.500
or like any of these subjects

00:11:09.500 --> 00:11:11.840
and they all seem very
like remote and mysterious

00:11:11.840 --> 00:11:15.970
and so to combat this I
would just go on Amazon

00:11:15.970 --> 00:11:18.480
and type in like sales and then like find

00:11:18.480 --> 00:11:21.660
like the top three rated
or most popular sales books

00:11:21.660 --> 00:11:23.470
and just like read them and repeat that.

00:11:23.470 --> 00:11:24.460
- And you find that valuable?

00:11:24.460 --> 00:11:26.300
- Like reading.
- And it's super useful.

00:11:26.300 --> 00:11:27.850
- Okay, reading is like
one of the probably

00:11:27.850 --> 00:11:30.390
the most important, reading
my business is probably

00:11:30.390 --> 00:11:31.680
the most important thing

00:11:32.840 --> 00:11:35.590
that's prepared me for running Dropbox.

00:11:35.590 --> 00:11:37.390
- And then what was it and
you talk a little bit about

00:11:37.390 --> 00:11:38.710
it in your commencement speech

00:11:38.710 --> 00:11:40.660
but I find this transition is kind of

00:11:40.660 --> 00:11:42.091
the most interesting one is

00:11:42.091 --> 00:11:44.870
you were working on this
for two years I think

00:11:44.870 --> 00:11:46.590
in through graduation.

00:11:46.590 --> 00:11:50.080
What kind of you know, as hard
as you're told to persevere

00:11:50.080 --> 00:11:51.560
and keep working on
something don't give up

00:11:51.560 --> 00:11:53.670
but at some point, maybe you are kind of

00:11:53.670 --> 00:11:54.655
putting good time after bad.

00:11:54.655 --> 00:11:55.488
- Yeah.

00:11:58.240 --> 00:12:01.150
It was super interesting at
the beginning 'cause like

00:12:01.150 --> 00:12:03.083
and when you first get to work,

00:12:05.190 --> 00:12:07.620
you get down to such an
important orders of business of

00:12:07.620 --> 00:12:08.823
like, all right.

00:12:10.950 --> 00:12:13.550
I got to Photoshop a logo
and print out business cards

00:12:13.550 --> 00:12:15.630
as a founder on them
and other very important

00:12:15.630 --> 00:12:16.920
and then hand them out to people

00:12:16.920 --> 00:12:20.120
so that they know that I'm a founder now,

00:12:20.120 --> 00:12:21.197
it's like this is like the stuff you.

00:12:21.197 --> 00:12:22.459
- And I still do that.

00:12:22.459 --> 00:12:24.542
(laughs)

00:12:26.260 --> 00:12:28.744
- But then, what you realize
is after that kind of

00:12:28.744 --> 00:12:31.160
after you're like Incorporated
and you get your like

00:12:31.160 --> 00:12:33.690
facts back from the
Delaware Secretary of State,

00:12:33.690 --> 00:12:36.713
and these things all seem
very official and important.

00:12:36.713 --> 00:12:40.930
After you're like, day number 74 of like

00:12:40.930 --> 00:12:42.700
I gotta take out the trash.

00:12:42.700 --> 00:12:44.950
Like we got to erase the whiteboard

00:12:44.950 --> 00:12:46.410
and like all this.

00:12:46.410 --> 00:12:48.740
You're like actually,
this is a lot of work.

00:12:48.740 --> 00:12:51.320
And which it was good, but...

00:12:52.600 --> 00:12:54.250
So I think with my first company,

00:12:55.870 --> 00:12:58.420
neither of us knew what
we were doing at all

00:12:58.420 --> 00:12:59.770
and so we're bootstrapping it.

00:12:59.770 --> 00:13:02.960
And there's just a lot of kind
of manual labor around like

00:13:02.960 --> 00:13:07.637
we were too cheap to get like employees.

00:13:07.637 --> 00:13:08.470
(laughs)

00:13:08.470 --> 00:13:10.280
And we didn't have any money.

00:13:10.280 --> 00:13:13.857
So, who's gonna write the
math questions is like me

00:13:13.857 --> 00:13:16.750
and I just still remember
having to like force myself

00:13:16.750 --> 00:13:18.570
to like write these math questions

00:13:18.570 --> 00:13:21.210
and draw these diagrams
and be like, all right,

00:13:21.210 --> 00:13:23.200
so where did the train
leave from last time?

00:13:23.200 --> 00:13:26.680
Okay, this train leaves, Sacramento

00:13:27.690 --> 00:13:30.100
and so I'm like, God,
at some point honestly,

00:13:30.100 --> 00:13:31.766
I can't do this.
- We have people who do that.

00:13:31.766 --> 00:13:33.427
So it's actually quite fun to do that.

00:13:33.427 --> 00:13:34.260
- Yeah.

00:13:34.260 --> 00:13:35.407
(audience laughs)

00:13:35.407 --> 00:13:37.163
- Seriously I find that I do.

00:13:39.060 --> 00:13:40.253
- And so but today.

00:13:44.089 --> 00:13:46.100
(audience laughs).

00:13:46.100 --> 00:13:47.377
I feel your pain.

00:13:47.377 --> 00:13:49.585
(laughs)

00:13:49.585 --> 00:13:50.840
No, no,

00:13:50.840 --> 00:13:53.550
but the problem wasn't really the work

00:13:53.550 --> 00:13:57.260
it was just more like we're
putting a lot of effort into it

00:13:57.260 --> 00:13:59.410
and not seeing a lot of return.

00:13:59.410 --> 00:14:02.000
So it was for me, it wasn't

00:14:03.638 --> 00:14:06.513
it's kind of lost some of
the variety of the work.

00:14:08.288 --> 00:14:11.920
And so I just got kind of...

00:14:11.920 --> 00:14:13.140
It just became harder and harder.

00:14:13.140 --> 00:14:15.390
I felt like I had to push myself

00:14:15.390 --> 00:14:17.010
like so much like it.

00:14:17.010 --> 00:14:21.240
And, it just became something I dreaded,

00:14:21.240 --> 00:14:23.380
it became something where
I'd have to trick myself into

00:14:23.380 --> 00:14:24.660
like making progress.

00:14:24.660 --> 00:14:26.800
And I'm like, and then I start,

00:14:26.800 --> 00:14:29.670
it's this like negative spiral, right?

00:14:29.670 --> 00:14:32.363
'Cause you're like, you
start resenting the work,

00:14:32.363 --> 00:14:33.950
you start getting mad at yourself

00:14:33.950 --> 00:14:35.760
'cause you're like why am
I not more disciplined?

00:14:35.760 --> 00:14:38.020
Your like, why is like
why and it's just like,

00:14:38.020 --> 00:14:39.600
then which makes you present it even more

00:14:39.600 --> 00:14:40.640
and thinks there's something
wrong with yourself

00:14:40.640 --> 00:14:43.360
like all this like stuff in your head.

00:14:43.360 --> 00:14:47.220
And then what happened was,
I had a friend of mine,

00:14:47.220 --> 00:14:49.230
who started a company and did things

00:14:49.230 --> 00:14:51.350
a little bit more properly,
like he had a Co-founder

00:14:51.350 --> 00:14:54.030
who he's like, really good friends with.

00:14:54.030 --> 00:14:56.500
They raise money, they could
just set up the company

00:14:56.500 --> 00:14:58.230
like a good normal company

00:14:58.230 --> 00:14:59.840
and then they were just having a blast.

00:14:59.840 --> 00:15:02.770
They were Working every waking hour

00:15:02.770 --> 00:15:05.090
but like there was having
fun like every minute

00:15:05.090 --> 00:15:06.800
this is what it looked like and felt like.

00:15:06.800 --> 00:15:09.510
And so I was like, at
first I'm like oh man

00:15:09.510 --> 00:15:10.700
maybe I'm really defective.

00:15:10.700 --> 00:15:12.710
Like look, these guys are
having no problem with this.

00:15:12.710 --> 00:15:14.515
But then what happened
was I actually started

00:15:14.515 --> 00:15:16.500
I would find these little side projects

00:15:16.500 --> 00:15:18.250
and I start working on a poker bot.

00:15:19.130 --> 00:15:20.290
Again, reverse engineering

00:15:20.290 --> 00:15:22.140
like people said this is impossible

00:15:22.140 --> 00:15:23.300
I'm like it as possible.

00:15:23.300 --> 00:15:24.800
And so I was really good at the security

00:15:24.800 --> 00:15:26.810
and kind of reverse engineering part of it

00:15:26.810 --> 00:15:30.500
and could do enough of the
AI but it was like this,

00:15:30.500 --> 00:15:32.200
I was just possessed.

00:15:32.200 --> 00:15:34.320
Like, I would be like
dragging my computers

00:15:34.320 --> 00:15:36.006
around everywhere.

00:15:36.006 --> 00:15:39.210
Like my parents would ask had
me come up to New Hampshire

00:15:39.210 --> 00:15:40.110
'cause we like a little place

00:15:40.110 --> 00:15:42.910
like this place on a lake
where you're like, supposed

00:15:42.910 --> 00:15:45.150
to get away from technology the next thing

00:15:45.150 --> 00:15:47.010
I'm like putting like
three monitors on like

00:15:47.010 --> 00:15:48.950
the kitchen stove 'cause
there's not enough room

00:15:48.950 --> 00:15:50.730
and like working on this thing.

00:15:50.730 --> 00:15:53.130
And so but it turned out
I mean, you never know

00:15:53.130 --> 00:15:55.110
how these things are
gonna sort of all line up.

00:15:55.110 --> 00:15:58.030
But then when I was working
on I was still working on

00:15:58.030 --> 00:16:00.730
the SAT prep company and my friend Adam

00:16:00.730 --> 00:16:02.150
who I mentioned moved
out to San Francisco.

00:16:02.150 --> 00:16:03.940
And next thing I know he's
two years younger than me

00:16:03.940 --> 00:16:06.100
but the next phone call I get from him,

00:16:06.100 --> 00:16:08.340
he's like, hey, I've raised
five million dollars.

00:16:08.340 --> 00:16:11.960
And like, I was like
that's a lot of money.

00:16:11.960 --> 00:16:13.470
Like that number has
like two commas in it,

00:16:13.470 --> 00:16:14.596
like what the hell.

00:16:14.596 --> 00:16:15.773
And this is like,

00:16:17.070 --> 00:16:19.770
my little brother in our
fraternity I'm like, oh, my God.

00:16:19.770 --> 00:16:24.410
And so, but it just
turned out that in part

00:16:24.410 --> 00:16:27.030
it was sort of the setup was there, like

00:16:27.030 --> 00:16:29.590
I really loved algorithms
and distributed systems

00:16:29.590 --> 00:16:30.884
and I studied computer science

00:16:30.884 --> 00:16:32.970
and like, these are my favorite things.

00:16:32.970 --> 00:16:34.870
And so it sort of sort of fertile ground.

00:16:34.870 --> 00:16:36.950
And then, one time I lost,

00:16:36.950 --> 00:16:38.050
I left my thumb drive at home

00:16:38.050 --> 00:16:41.433
and so I couldn't get any
work done for my company.

00:16:41.433 --> 00:16:44.900
And the sort of non PR, like
the director's cut version of

00:16:44.900 --> 00:16:47.203
sort of the Dropbox origin story.

00:16:48.593 --> 00:16:52.110
So as taking a ride on the Chinatown Bus,

00:16:52.110 --> 00:16:54.480
the Fung Wah from from Boston in New York

00:16:54.480 --> 00:16:56.170
and I left my thumb drive behind

00:16:56.170 --> 00:16:57.230
and I'm just like, I hate I'm like

00:16:57.230 --> 00:16:59.370
what do you do in these situations

00:16:59.370 --> 00:17:01.520
that you're like, Oh,
I hate my thumb drive.

00:17:01.520 --> 00:17:02.683
I'm like, I hate myself.

00:17:02.683 --> 00:17:05.090
I'm so like, stupid.

00:17:05.090 --> 00:17:07.230
I'm so disorganized,
like I keep doing this,

00:17:07.230 --> 00:17:10.220
why can't I be better and
just the self flagellation.

00:17:10.220 --> 00:17:11.800
And that's like, there's
nothing else to do

00:17:11.800 --> 00:17:13.410
for like four and a half hours

00:17:13.410 --> 00:17:15.900
but but I had this three gigabyte

00:17:15.900 --> 00:17:17.920
Linux virtual machine image,

00:17:17.920 --> 00:17:19.750
they need to keep in sync
across all these computers.

00:17:19.750 --> 00:17:22.650
'Cause I have worked
on a laptop sometimes,

00:17:22.650 --> 00:17:24.670
sometimes a desktop,
sometimes another computer

00:17:24.670 --> 00:17:28.000
and like nothing, there are
a million things that claim

00:17:28.000 --> 00:17:29.900
to solve this problem and
none of them actually did.

00:17:29.900 --> 00:17:32.590
And so it was really personal frustration

00:17:32.590 --> 00:17:34.030
that led me to open up the editor

00:17:34.030 --> 00:17:35.540
and start writing some code

00:17:35.540 --> 00:17:36.790
that eventually turned into Dropbox.

00:17:36.790 --> 00:17:40.590
Although I had no idea that
would be the case at that time.

00:17:40.590 --> 00:17:42.510
- And I mean, I think this
is an important moment

00:17:42.510 --> 00:17:44.980
because a lot of times
when you read about Dropbox

00:17:44.980 --> 00:17:47.810
you say, oh, yeah, he
had the idea of having

00:17:47.810 --> 00:17:49.910
sharing files across multiple devices

00:17:49.910 --> 00:17:51.484
and all that but whenever
I realized now that

00:17:51.484 --> 00:17:55.290
what's amazing isn't the idea
is that you very old idea,

00:17:55.290 --> 00:17:58.050
in fact, almost anyone
who's worked on data storage

00:17:58.050 --> 00:18:00.050
or anything has for the last 40 years.

00:18:00.050 --> 00:18:01.740
has been trying to do this.

00:18:01.740 --> 00:18:05.970
And so to me the power of
or almost the audacity of

00:18:05.970 --> 00:18:08.070
what is this was like a big problem

00:18:08.070 --> 00:18:11.500
that a lot of really smart
people had kind of tried to do

00:18:11.500 --> 00:18:13.520
as you mentioned maybe
even launch companies on it

00:18:13.520 --> 00:18:15.440
didn't have really complete solutions.

00:18:15.440 --> 00:18:17.460
What was kind of going on in your head

00:18:17.460 --> 00:18:19.373
that convinced you that know, like,

00:18:19.373 --> 00:18:21.300
I think the past that I'm
about to take on this problem

00:18:21.300 --> 00:18:23.400
is going to be the one that works.

00:18:23.400 --> 00:18:25.370
- Well, it was just so clear from trying

00:18:25.370 --> 00:18:27.790
all the other things that like,

00:18:27.790 --> 00:18:30.590
all like 100 things that
claim to solve this on paper

00:18:30.590 --> 00:18:33.090
but in like in practice,
they never really worked.

00:18:34.050 --> 00:18:36.100
And there at school at MIT,

00:18:36.100 --> 00:18:38.790
they have that you sometimes
you like a campus network

00:18:38.790 --> 00:18:42.670
or an sort of hardcore
Unix kind of way of solving

00:18:42.670 --> 00:18:45.110
this problem, but like
for a Windows computer

00:18:45.110 --> 00:18:48.880
or like a MacBook like there's
just you're stuck carrying

00:18:48.880 --> 00:18:51.400
around a thumb drive and
emailing yourself stuff

00:18:51.400 --> 00:18:53.689
and that was your point I was more just

00:18:53.689 --> 00:18:55.390
amplify the frustration.

00:18:55.390 --> 00:18:57.120
I'm like, guys, this is not a new idea.

00:18:57.120 --> 00:18:59.580
We've thought about this is like the 60s

00:18:59.580 --> 00:19:02.630
like why does hell am I
forced to do this like

00:19:02.630 --> 00:19:04.513
really made me upset.

00:19:05.510 --> 00:19:07.540
And then, there's some
conviction of it like,

00:19:07.540 --> 00:19:10.800
look that the problem with
like the online drives

00:19:10.800 --> 00:19:12.660
is like these very
specific technical things

00:19:12.660 --> 00:19:15.383
where it's like it's all a big hack where

00:19:15.383 --> 00:19:18.060
the way the online drive the
AI drives and extra drives

00:19:18.060 --> 00:19:20.390
and for every letter there's been a drive

00:19:21.911 --> 00:19:24.160
for all of them that they all worked on

00:19:24.160 --> 00:19:26.141
the same basic principle
which was like, okay,

00:19:26.141 --> 00:19:29.320
we're gonna trick your applications

00:19:29.320 --> 00:19:32.036
and operating system into
thinking that instead of like,

00:19:32.036 --> 00:19:35.320
when a program write
something to the disk,

00:19:35.320 --> 00:19:38.110
instead of running it to the
disk on the inside the laptop

00:19:38.110 --> 00:19:40.490
it actually intercepts it
sends it over to the internet

00:19:40.490 --> 00:19:42.660
to server somewhere and gets it back.

00:19:42.660 --> 00:19:46.320
So, at first glance like
this is a great idea

00:19:46.320 --> 00:19:49.920
will work with everything
it's not that hard.

00:19:49.920 --> 00:19:52.770
But the problem is, you're
sent like if the server is

00:19:52.770 --> 00:19:54.850
100 milliseconds away,
instead of five milliseconds

00:19:54.850 --> 00:19:56.763
away like your hard drive or less.

00:19:57.970 --> 00:20:00.690
Then you get all these
inexplicable problems

00:20:00.690 --> 00:20:03.530
because like millions of millions
of millions lines of code

00:20:03.530 --> 00:20:05.410
are all written with assumption
that this thing is like

00:20:05.410 --> 00:20:07.033
five, 10 milliseconds away.

00:20:08.440 --> 00:20:10.470
And I'm going into detail on this,

00:20:10.470 --> 00:20:12.440
but it just like this there's like no way

00:20:12.440 --> 00:20:14.230
you can ever make that work.

00:20:14.230 --> 00:20:16.890
Like it's just like laws of physics

00:20:16.890 --> 00:20:18.920
and so you need a completely
different approach.

00:20:18.920 --> 00:20:21.009
And sort of a hybrid where like, okay,

00:20:21.009 --> 00:20:24.980
you have big and cheap
and fast storage locally

00:20:24.980 --> 00:20:27.530
and on a server it's but
it's like two swimming pools

00:20:27.530 --> 00:20:29.920
connected by a straw, right?

00:20:29.920 --> 00:20:33.940
And so first use the straw well,

00:20:33.940 --> 00:20:35.690
and two like make it so that,

00:20:35.690 --> 00:20:38.420
you're not waiting for the swimming pool

00:20:38.420 --> 00:20:39.300
to make it back and forth.

00:20:39.300 --> 00:20:42.140
Like, use it efficiently do
that in the background syncing

00:20:42.140 --> 00:20:42.973
right, so.

00:20:44.470 --> 00:20:47.230
And then it just turned
out no one had gotten

00:20:47.230 --> 00:20:48.120
the technical part, right.

00:20:48.120 --> 00:20:49.700
But then there's also like a user

00:20:49.700 --> 00:20:52.830
there's like a design piece
of like how do you design

00:20:52.830 --> 00:20:54.020
the interface, how do you make this.

00:20:54.020 --> 00:20:56.850
What's a metaphor that
people can understand.

00:20:56.850 --> 00:20:58.950
And then there's like
an academic piece of it

00:20:58.950 --> 00:21:02.600
which like the algorithms
and how do you move the files

00:21:02.600 --> 00:21:04.480
around and things like
that and store them.

00:21:04.480 --> 00:21:05.860
But then there's like
a lot of grungy kind of

00:21:05.860 --> 00:21:07.930
operating systems work.

00:21:07.930 --> 00:21:10.452
Where how do you make it so that you work,

00:21:10.452 --> 00:21:13.280
the fat 32 file system.

00:21:13.280 --> 00:21:16.210
Every other file system
when it stores in the next

00:21:16.210 --> 00:21:17.550
to the name of the file it stores like

00:21:17.550 --> 00:21:19.590
when the file was modified.

00:21:19.590 --> 00:21:22.633
And it's a timestamp and its
resolution of one second.

00:21:24.760 --> 00:21:26.247
There's actually more
detailed now but just listen.

00:21:26.247 --> 00:21:28.120
And then he likes just randomly

00:21:28.120 --> 00:21:30.490
some random operating system
some some random hard drive

00:21:30.490 --> 00:21:31.670
you can have a fat 32,000 that's stores

00:21:31.670 --> 00:21:35.530
that modification time with
a resolution to two seconds.

00:21:35.530 --> 00:21:36.850
And it's like, none of
the other ones do that

00:21:36.850 --> 00:21:37.683
but that one does.

00:21:37.683 --> 00:21:39.490
And suddenly, there's
all this weird complexity

00:21:39.490 --> 00:21:42.720
to the code or like Windows
XP Service Pack three,

00:21:42.720 --> 00:21:45.830
there be bugs were like
the Swedish version of that

00:21:45.830 --> 00:21:48.507
not the Norwegian version, the
Swedish version of this way

00:21:48.507 --> 00:21:50.358
and we're just like
cause Dropbox to crash.

00:21:50.358 --> 00:21:53.890
And so part it says two things.

00:21:53.890 --> 00:21:57.500
One is a fundamentally different approach

00:21:57.500 --> 00:21:58.850
from what some of the other guys are doing

00:21:58.850 --> 00:22:01.960
and then two is the a lot
of just like that kind of

00:22:01.960 --> 00:22:03.400
obsession like the same thing,

00:22:03.400 --> 00:22:04.760
the same way I was like obsessed with like

00:22:04.760 --> 00:22:09.620
making a very well crafted
like SAT question about

00:22:09.620 --> 00:22:11.510
quadrilateral and making
the diagram look like

00:22:11.510 --> 00:22:13.740
the actual list is like
that then obsessing

00:22:13.740 --> 00:22:15.950
over making really fast, reliable

00:22:15.950 --> 00:22:19.631
and fixing that obscure
bug with Swedish windows.

00:22:19.631 --> 00:22:21.930
- And when did you realize this,

00:22:21.930 --> 00:22:23.340
you start on this you see a problem,

00:22:23.340 --> 00:22:26.380
you start tackling and it is
an audacious problem to tackle.

00:22:26.380 --> 00:22:28.450
What did you say, this is real this is

00:22:28.450 --> 00:22:29.870
like I have a solution here.

00:22:29.870 --> 00:22:32.680
Like this is already better
than what's out there industry.

00:22:32.680 --> 00:22:34.620
- So first was when I just made something

00:22:34.620 --> 00:22:36.592
that worked for myself.

00:22:36.592 --> 00:22:39.100
And I'm like, I could actually use it

00:22:39.100 --> 00:22:40.350
like I would put save something

00:22:40.350 --> 00:22:41.780
and it would like show
up on my other computer

00:22:41.780 --> 00:22:43.980
and I'd be like, finally.

00:22:43.980 --> 00:22:46.260
And then but it really
started to take shape

00:22:46.260 --> 00:22:49.182
once I made a video a
demo video of Dropbox

00:22:49.182 --> 00:22:50.810
like a three minute little

00:22:50.810 --> 00:22:52.352
it's it's still online somewhere

00:22:52.352 --> 00:22:53.650
or you can find it.

00:22:53.650 --> 00:22:56.790
And I put it on Hacker News.

00:22:56.790 --> 00:22:58.600
There's this new site for startups

00:22:58.600 --> 00:23:01.350
and it just got a ton of it
was like top of Hacker News

00:23:01.350 --> 00:23:02.540
for like two days.

00:23:02.540 --> 00:23:05.383
Like, these are the old days
so it was easier to do that.

00:23:06.410 --> 00:23:08.390
But that gave me like, a ton of...

00:23:08.390 --> 00:23:10.490
I mean, I'd already decided to quit my job

00:23:11.325 --> 00:23:12.158
it's complicated.

00:23:12.158 --> 00:23:15.610
So I just graduated, I
was working as an engineer

00:23:15.610 --> 00:23:18.850
at a startup and I was
moonlighting on my SAT prep thing

00:23:18.850 --> 00:23:19.920
that was the other thing.

00:23:19.920 --> 00:23:22.320
So like you're asking why,

00:23:22.320 --> 00:23:24.730
like why did I kind of get frustrated.

00:23:24.730 --> 00:23:27.750
It's like we my Co-founder
wasn't gonna quit his job

00:23:27.750 --> 00:23:29.060
I wasn't really either.

00:23:29.060 --> 00:23:31.133
The thing was never
really going to succeed

00:23:31.133 --> 00:23:33.300
but also wasn't gonna die.

00:23:33.300 --> 00:23:36.230
So like it just got kind of frustrating

00:23:36.230 --> 00:23:38.740
But anyway, so Dropbox really

00:23:38.740 --> 00:23:42.360
the first real turning point
was when I put the video up

00:23:42.360 --> 00:23:45.764
and then Arash my Co-founder
saw it on Hacker News,

00:23:45.764 --> 00:23:49.700
like a week later, we got
introduced through mutual friend.

00:23:49.700 --> 00:23:52.090
So I got a Co-founder from it, Paul Graham

00:23:53.230 --> 00:23:56.040
Arash my Co-founder and
then our first investor

00:23:56.040 --> 00:23:59.500
Paul Graham saw the video
and emailed me saying

00:24:00.342 --> 00:24:02.980
'cause we just I just
applied solo to Y Combinator

00:24:02.980 --> 00:24:03.813
with the idea.

00:24:05.785 --> 00:24:07.060
- And that's one for this
was your second interaction

00:24:07.060 --> 00:24:08.660
with Paul Graham.

00:24:08.660 --> 00:24:11.260
- I had a complicated series
of interactions before.

00:24:13.114 --> 00:24:15.480
So Y Combinator is kind of
like a planet college, right?

00:24:15.480 --> 00:24:17.970
Lots of people want to
get in not enough spots,

00:24:17.970 --> 00:24:19.440
you have this very competitive dynamic.

00:24:19.440 --> 00:24:22.460
And so actually, the sort
of admission system was

00:24:22.460 --> 00:24:24.370
how I thought about
getting into Y Combinator.

00:24:24.370 --> 00:24:29.370
And so I had actually been
flown out to California

00:24:30.360 --> 00:24:32.210
to hang out with some other
Y Combinator founders.

00:24:32.210 --> 00:24:34.800
And I also want to pitch Paul on Dropbox.

00:24:34.800 --> 00:24:37.010
And so I showed up at Y
Combinator a little early

00:24:37.010 --> 00:24:39.480
before one of the dinners
and walked into his office

00:24:39.480 --> 00:24:42.051
and asked if I could show him Dropbox

00:24:42.051 --> 00:24:44.804
and he was very angry about that,

00:24:44.804 --> 00:24:46.603
visitors are not welcome.

00:24:48.253 --> 00:24:50.300
But the problem with that is like imagine,

00:24:50.300 --> 00:24:51.860
we all remember playing the school.

00:24:51.860 --> 00:24:53.280
Imagine having like five minutes

00:24:53.280 --> 00:24:54.930
with like the dean of admissions

00:24:54.930 --> 00:24:58.120
and the one thing that
they learn is that like,

00:24:58.120 --> 00:24:59.020
you're an asshole.

00:24:59.020 --> 00:24:59.970
(all laughs)

00:24:59.970 --> 00:25:00.803
All right.

00:25:01.710 --> 00:25:02.543
I know I'm so--

00:25:02.543 --> 00:25:05.020
- No that's cool yeah, we keep it real.

00:25:05.020 --> 00:25:07.640
- Sorry to all the 12
year olds watching this

00:25:07.640 --> 00:25:09.093
- don't say that.
- Yes.

00:25:12.861 --> 00:25:14.550
- But that first video was like huge

00:25:14.550 --> 00:25:15.760
in terms of getting started.

00:25:15.760 --> 00:25:17.600
- Yeah and then you get started

00:25:17.600 --> 00:25:21.709
and I mean, and what
year was this was 2007?

00:25:21.709 --> 00:25:23.770
- 2007.
- 2007.

00:25:23.770 --> 00:25:26.310
- And then it's just been kind of...

00:25:26.310 --> 00:25:27.897
I mean, I actually I don't
think I've ever seen it.

00:25:27.897 --> 00:25:31.310
I mean you guys have got to
be one of the fastest growing

00:25:31.310 --> 00:25:34.023
organizations maybe in
the history of the Valley.

00:25:35.520 --> 00:25:37.230
- Also, it's been growing quickly.

00:25:37.230 --> 00:25:39.230
I don't either they're all
like people are setting

00:25:39.230 --> 00:25:40.670
all kinds of records these days

00:25:40.670 --> 00:25:43.090
but but the company in terms of headcount

00:25:43.090 --> 00:25:44.810
has grown really fast.

00:25:44.810 --> 00:25:47.780
And then the user base has
grown from 2009 we're like

00:25:47.780 --> 00:25:49.780
a million users now we're over 300.

00:25:49.780 --> 00:25:52.920
- And I mean, what are your,

00:25:52.920 --> 00:25:55.590
kind of in in hindsight are
now that you can look over

00:25:55.590 --> 00:25:57.750
the last seven years.

00:25:57.750 --> 00:25:59.880
I mean, what it been
and I almost view this

00:25:59.880 --> 00:26:01.050
we were talk a little bit about this one

00:26:01.050 --> 00:26:02.430
before we did this is

00:26:05.100 --> 00:26:06.300
what would you have told yourself

00:26:06.300 --> 00:26:08.050
when you if it was an 80% organization

00:26:08.050 --> 00:26:10.210
or 90% organization that to kind of

00:26:10.210 --> 00:26:12.300
like either ease your
stress or let you know

00:26:12.300 --> 00:26:15.960
that something's coming or
ways to manage it as you grow?

00:26:15.960 --> 00:26:17.420
- Well, I think there's a lot

00:26:17.420 --> 00:26:20.540
and it's hard to kind of
boil it down to, like pithy,

00:26:20.540 --> 00:26:23.970
like phrases of like oh, this
is how you build a company.

00:26:23.970 --> 00:26:26.270
It's like how do you play basketball?

00:26:26.270 --> 00:26:28.250
Like I wanted to take a
while to explain, right?

00:26:28.250 --> 00:26:31.140
So, but I think the...

00:26:31.140 --> 00:26:32.050
I don't really know how to play

00:26:32.050 --> 00:26:34.000
I'm not very good at basketball.

00:26:34.000 --> 00:26:37.175
- I am, but I'm not I'm kidding.

00:26:37.175 --> 00:26:38.008
- Alright.

00:26:38.980 --> 00:26:42.860
So what I would say is,
some of the earliest

00:26:42.860 --> 00:26:45.200
most helpful advice that we got was really

00:26:45.200 --> 00:26:47.140
to focus on the people we
brought into the company

00:26:47.140 --> 00:26:49.153
like make sure everybody's
like really, really talented.

00:26:49.153 --> 00:26:52.250
Like, that's probably the best like hack

00:26:52.250 --> 00:26:53.840
you can do to make everything
else easier, right?

00:26:53.840 --> 00:26:57.600
'Cause, put a good person
between you and all your problems

00:26:57.600 --> 00:26:58.433
right.

00:27:00.233 --> 00:27:03.285
And our angel investors and
some early folks were like,

00:27:03.285 --> 00:27:05.330
there's kept drilling that into our heads

00:27:05.330 --> 00:27:08.453
like make sure the talent bar
is really high be very choosy.

00:27:09.527 --> 00:27:12.780
And I think just sort of an attitude

00:27:12.780 --> 00:27:16.210
of really trying to systematically train

00:27:16.210 --> 00:27:17.970
to like, understand like, okay, well,

00:27:17.970 --> 00:27:20.350
here's what I'm dealing with today

00:27:20.350 --> 00:27:22.290
but I'm gonna talk to people
who are maybe six months ahead,

00:27:22.290 --> 00:27:23.930
a year ahead, five years ahead.

00:27:23.930 --> 00:27:25.980
And like what are they dealing with?

00:27:25.980 --> 00:27:28.980
I asked as quick as I
was talking to their CEO

00:27:28.980 --> 00:27:30.720
eight thousand person company.

00:27:30.720 --> 00:27:33.030
I'm like, all right, we're
approaching 1000 people

00:27:33.030 --> 00:27:34.300
at Dropbox.

00:27:34.300 --> 00:27:36.770
What am I going to see between 1000, 2001?

00:27:36.770 --> 00:27:37.730
What should I watch out for?

00:27:37.730 --> 00:27:40.230
Like what would you put in place now,

00:27:40.230 --> 00:27:42.170
so that as you've done all these things

00:27:42.170 --> 00:27:43.680
and grown the company.

00:27:43.680 --> 00:27:45.242
What do you wish you could do today?

00:27:45.242 --> 00:27:50.010
So a lot of what I do is
sort of think about that

00:27:50.010 --> 00:27:53.010
and sort of all you have to
be able to see around corners

00:27:53.010 --> 00:27:54.780
and one way to do that is reading.

00:27:54.780 --> 00:27:57.773
One way to do that is having
mentors and getting advice.

00:27:59.570 --> 00:28:01.730
And then the other the thing
that gives you some calm is

00:28:01.730 --> 00:28:06.730
that what you read on TechCrunch
or in the press generally.

00:28:08.690 --> 00:28:10.260
When someone tells a story of a company,

00:28:10.260 --> 00:28:12.090
they're like, oh, yeah
Dropbox it started out

00:28:12.090 --> 00:28:14.510
with not a lot of users then
later they had a lot of users

00:28:14.510 --> 00:28:15.547
and they did great.

00:28:15.547 --> 00:28:18.084
(audience laughs)

00:28:18.084 --> 00:28:20.030
And they just have this sort of this like

00:28:20.030 --> 00:28:22.620
this narrative arc that they just,

00:28:22.620 --> 00:28:24.278
they're like well the real truth is

00:28:24.278 --> 00:28:26.160
this complicated stuff happened?

00:28:26.160 --> 00:28:27.060
And this was actually really hard.

00:28:27.060 --> 00:28:28.280
They're like yeah, no, okay.

00:28:28.280 --> 00:28:31.180
Two kids, two MIT kids in
a dorm room have an idea

00:28:31.180 --> 00:28:32.600
they've been...

00:28:32.600 --> 00:28:35.310
And so, the truth is like
it's actually very complicated

00:28:35.310 --> 00:28:37.610
and hard but that all
kind of gets glossed over

00:28:37.610 --> 00:28:40.462
but when when you read like profiles

00:28:40.462 --> 00:28:42.660
there's a lot of books that
have been written about

00:28:42.660 --> 00:28:45.850
their lately that the
everything store is a book about

00:28:45.850 --> 00:28:47.100
Amazon it's a great book.

00:28:48.070 --> 00:28:50.720
Steve Jobs biography,
Google, Apple, Microsoft,

00:28:50.720 --> 00:28:53.140
Facebook, all these Intel like Oracle.

00:28:53.140 --> 00:28:55.470
Like I've read as much as
many kind of profiles on

00:28:55.470 --> 00:28:57.470
tech companies and other companies

00:28:57.470 --> 00:28:59.940
as I could get my hands on
over these companies have

00:28:59.940 --> 00:29:01.027
last a few decades.

00:29:01.027 --> 00:29:03.710
And what you learn is that

00:29:05.526 --> 00:29:06.790
there's enough that once
you sort of look behind

00:29:06.790 --> 00:29:09.103
the curtain there's nothing
that's that magical.

00:29:11.018 --> 00:29:12.850
And that's important
for people to understand

00:29:12.850 --> 00:29:14.420
because you may think like oh,

00:29:14.420 --> 00:29:16.160
I don't know anything about business.

00:29:16.160 --> 00:29:18.990
So I should just go like not,
I'm never gonna be good at it

00:29:18.990 --> 00:29:20.420
because I've never been good at it.

00:29:20.420 --> 00:29:22.060
And that's just something
as I should go get

00:29:22.060 --> 00:29:26.330
like a business guy or
person like to do that stuff

00:29:26.330 --> 00:29:27.831
'cause I'll never be good at it

00:29:27.831 --> 00:29:29.610
but it's actually something you can learn.

00:29:29.610 --> 00:29:34.020
And so I think that
mindset of like in a week

00:29:34.020 --> 00:29:36.040
you can probably limited
in terms of what you can do

00:29:36.040 --> 00:29:38.210
but like think about playing an instrument

00:29:38.210 --> 00:29:39.700
or becoming a doctor like any these things

00:29:39.700 --> 00:29:42.010
it's like all of us can realize like yeah,

00:29:42.010 --> 00:29:45.040
it's a lot of work but I can
sort of see a path from A to B.

00:29:45.040 --> 00:29:46.830
Turns out like most things
you want to learn have

00:29:46.830 --> 00:29:48.093
that kind of potential,

00:29:49.670 --> 00:29:51.060
whether it's public speaking

00:29:51.060 --> 00:29:54.570
or building a company
or any of those things

00:29:54.570 --> 00:29:59.438
if you have the attitude that like that

00:29:59.438 --> 00:30:00.330
and you give yourself time

00:30:00.330 --> 00:30:01.750
like you can actually pick these things up

00:30:01.750 --> 00:30:02.950
there's nothing that magical about them.

00:30:02.950 --> 00:30:05.100
So and that's one thing
from these profiles.

00:30:05.100 --> 00:30:07.610
And then the other thing 'cause
you see in the early days

00:30:07.610 --> 00:30:09.040
they make all these like really crazy

00:30:09.040 --> 00:30:11.337
stupid mistakes and
like do all these things

00:30:11.337 --> 00:30:12.880
that are like really, really wrong.

00:30:12.880 --> 00:30:15.660
And then that's also
therapeutic is like you realize

00:30:15.660 --> 00:30:17.810
all these companies
were like a total mess.

00:30:19.406 --> 00:30:21.210
And actually, I see Albert in the corner

00:30:21.210 --> 00:30:23.460
Albert is early Dropboxer.

00:30:23.460 --> 00:30:26.000
Albert can tell you how what
a mess really Dropbox was.

00:30:26.000 --> 00:30:27.860
And so what you read about

00:30:27.860 --> 00:30:29.550
is actually not reflective of reality.

00:30:29.550 --> 00:30:31.060
It's a much mess here

00:30:31.060 --> 00:30:34.130
and kind of less glamorous process.

00:30:34.130 --> 00:30:36.630
- Yeah and I'm about to open
it go into some questions

00:30:36.630 --> 00:30:39.370
that from the team but
just my last question is

00:30:39.370 --> 00:30:44.150
where do you see kind of
Dropbox in five, 10, 50 years,

00:30:44.150 --> 00:30:47.723
the end of your life what do
you hope Dropbox has done?

00:30:49.080 --> 00:30:49.974
- 50 years.

00:30:49.974 --> 00:30:51.610
I don't know if anybody's made it's like

00:30:51.610 --> 00:30:53.141
self driving boats yet.

00:30:53.141 --> 00:30:55.060
- That would be an innovation.

00:30:55.060 --> 00:30:58.640
- I mean, you can't
really look that far out,

00:30:58.640 --> 00:31:03.320
but we've realized and
what we we talk a lot about

00:31:03.320 --> 00:31:05.540
is we have this opportunity

00:31:05.540 --> 00:31:07.700
where now we have a lot of resources,

00:31:07.700 --> 00:31:09.510
a lot of really talented people,

00:31:09.510 --> 00:31:11.070
we can solve these really big problems.

00:31:11.070 --> 00:31:16.070
And then what we're really
working on is building this home

00:31:16.240 --> 00:31:18.580
for everybody is most
important stuff, right?

00:31:18.580 --> 00:31:20.660
'Cause you think about
your house 20 years ago

00:31:20.660 --> 00:31:22.420
like you'd walk into your house

00:31:22.420 --> 00:31:24.300
it'd be like, you know mail on the table

00:31:24.300 --> 00:31:25.320
you'd go in your living room,

00:31:25.320 --> 00:31:28.050
all your photos are on your kitchen,

00:31:28.050 --> 00:31:30.210
your photos are on your
refrigerator, right?

00:31:30.210 --> 00:31:32.320
And you go down the hall
and your briefcase has

00:31:32.320 --> 00:31:34.330
like your documents
and like all that stuff

00:31:34.330 --> 00:31:35.581
is now on servers or in your Dropbox.

00:31:35.581 --> 00:31:37.540
And so we need this like new kind of home.

00:31:37.540 --> 00:31:40.390
So we we think all the time about like

00:31:40.390 --> 00:31:43.770
how can we save hundreds of
millions of people from like

00:31:43.770 --> 00:31:44.950
these things are really painful

00:31:44.950 --> 00:31:46.580
and annoying about technology.

00:31:46.580 --> 00:31:48.450
Like all these little paper
cuts like forgetting your thumb

00:31:48.450 --> 00:31:50.490
like the equivalent of like these little

00:31:50.490 --> 00:31:52.490
thumb drive problems are
like everywhere, right?

00:31:52.490 --> 00:31:54.700
And so how do we find the biggest ones

00:31:54.700 --> 00:31:56.537
and solve them at massive scale.

00:31:56.537 --> 00:31:59.521
And so and then,
specifically we started out

00:31:59.521 --> 00:32:01.440
with this app that you
put on your computer

00:32:01.440 --> 00:32:03.660
or your phone that gives you
this like Dropbox folder.

00:32:03.660 --> 00:32:06.000
But really what you want is

00:32:06.000 --> 00:32:07.740
what you're using that folder for is often

00:32:07.740 --> 00:32:09.065
you're putting photos in there.

00:32:09.065 --> 00:32:11.220
You're getting work done,
you're collaborating

00:32:11.220 --> 00:32:12.280
with other people.

00:32:12.280 --> 00:32:15.550
And so we were, we're
starting to dig into some of

00:32:15.550 --> 00:32:16.860
those use cases, a little more things.

00:32:16.860 --> 00:32:19.460
Like we just launched a
photo app called Carousel,

00:32:19.460 --> 00:32:21.960
which is like if the
gallery on your phone had

00:32:21.960 --> 00:32:23.513
like every picture you've ever taken.

00:32:23.513 --> 00:32:26.530
And if you could text
like 100 or 1000 photos

00:32:26.530 --> 00:32:27.885
and videos at a time.

00:32:27.885 --> 00:32:29.963
That's what Carousel lets you do,

00:32:30.910 --> 00:32:33.420
for some reason that had
not really existed or no one

00:32:33.420 --> 00:32:35.990
like everybody has this
problem just no one solved it.

00:32:35.990 --> 00:32:38.430
- Yeah awesome. So I'll go
into some of these questions.

00:32:38.430 --> 00:32:39.887
The first one this is this is from Marcia,

00:32:39.887 --> 00:32:41.220
you can raise your hand
Marcia if you're here.

00:32:41.220 --> 00:32:42.053
Where is Marcia?

00:32:42.053 --> 00:32:43.659
I don't know, where is Marcia?

00:32:43.659 --> 00:32:44.492
- [Woman] She training remotely.

00:32:44.492 --> 00:32:45.380
- Oh, she's remotely.

00:32:45.380 --> 00:32:47.180
So what's your typical workday like?

00:32:48.380 --> 00:32:50.660
- Probably the biggest thing
I spend time on is recruiting.

00:32:50.660 --> 00:32:54.660
And so there's, often there'll
be some kind of fire drill

00:32:54.660 --> 00:32:57.330
at night where it's like,
okay we're acquiring a company

00:32:57.330 --> 00:32:59.310
or there's some candidate
and we're fighting

00:32:59.310 --> 00:33:03.660
with Google or some
startup to try to get them,

00:33:03.660 --> 00:33:04.980
there's a tug of war.

00:33:04.980 --> 00:33:07.990
And like I'm often
finding myself down here

00:33:07.990 --> 00:33:12.610
like gone big game hunting
for people to join Dropbox.

00:33:12.610 --> 00:33:15.470
So I'll be like in the Google campus

00:33:15.470 --> 00:33:17.900
or if you see me in one of this companies

00:33:17.900 --> 00:33:19.227
you know what I'm doing.

00:33:19.227 --> 00:33:20.520
(audience laughs)

00:33:20.520 --> 00:33:22.350
And so recruiting is the biggest thing.

00:33:22.350 --> 00:33:24.980
And then the probably
the next biggest thing

00:33:24.980 --> 00:33:28.210
is just meetings some small numbers

00:33:28.210 --> 00:33:30.510
with people on my team
around certain projects.

00:33:30.510 --> 00:33:33.291
So every six months, we
pick like a dozen things

00:33:33.291 --> 00:33:36.410
that are really important
that we wanna get done

00:33:36.410 --> 00:33:40.350
and then I'll be spending time

00:33:40.350 --> 00:33:42.270
with them like, okay, here's
this, here's a new stuff

00:33:42.270 --> 00:33:43.820
we're gonna do in collaboration

00:33:46.210 --> 00:33:48.100
answering questions like
that, what is Dropbox?

00:33:48.100 --> 00:33:49.410
Like what should it be in five years?

00:33:49.410 --> 00:33:50.767
What will it be in 50 years?

00:33:50.767 --> 00:33:52.917
And what kind of place
do we want to create

00:33:56.198 --> 00:33:59.170
and then there's this
is much longer tail of

00:33:59.170 --> 00:34:00.940
all kinds of other stuff
or there is like partners

00:34:00.940 --> 00:34:05.940
or customers or just other things.

00:34:06.140 --> 00:34:06.973
- Yeah.

00:34:06.973 --> 00:34:08.520
- It's a hard question
to answer succinctly.

00:34:08.520 --> 00:34:10.330
- Yeah, that's pretty good.

00:34:10.330 --> 00:34:11.310
I'm just show up at the--

00:34:11.310 --> 00:34:13.790
- I had I made something that downloads

00:34:13.790 --> 00:34:16.320
my Google Calendar and
I wrote Python script

00:34:16.320 --> 00:34:18.800
that downloads my Google
Calendar into Excel spreadsheet

00:34:18.800 --> 00:34:20.493
and like triage is my time.

00:34:20.493 --> 00:34:21.570
- [Khan] Automatically?

00:34:21.570 --> 00:34:23.696
- Well it's not you have to supervise,

00:34:23.696 --> 00:34:26.590
you have to triage stuff or
you have someone help you

00:34:26.590 --> 00:34:27.423
triage other stuff.

00:34:27.423 --> 00:34:30.510
but then I had these like
rolling charts of like

00:34:30.510 --> 00:34:32.740
how I spent the last week
or the last four weeks

00:34:32.740 --> 00:34:33.790
or the last 12 weeks.

00:34:35.425 --> 00:34:36.550
'Cause a lot of people say--

00:34:36.550 --> 00:34:38.250
- That's a product I'll use that.

00:34:38.250 --> 00:34:39.083
- All right.

00:34:40.300 --> 00:34:42.840
- That's interesting you get
data analytics on your time.

00:34:42.840 --> 00:34:43.673
That's good.

00:34:43.673 --> 00:34:45.850
- It is, it's super important.

00:34:45.850 --> 00:34:47.763
So I did that more.

00:34:48.830 --> 00:34:50.030
Like one of the most
important things you need

00:34:50.030 --> 00:34:52.323
to think about like as your
job gets more complicated

00:34:52.323 --> 00:34:54.940
there's just more stuff
competing for your time.

00:34:54.940 --> 00:34:57.640
It's really important
understand where it goes

00:34:57.640 --> 00:34:59.040
that's a book called

00:34:59.040 --> 00:35:01.280
The Effective Executive by Peter Drucker,

00:35:01.280 --> 00:35:05.130
it's like any book on management
will like focus on that.

00:35:05.130 --> 00:35:08.100
So, but there's another thing
is like no one's created

00:35:08.100 --> 00:35:09.570
a tool where you can see
where your time goes.

00:35:09.570 --> 00:35:12.513
It's like everybody, a lot
of people have that problem.

00:35:16.094 --> 00:35:21.094
So I have been at times very
like rigorous about that.

00:35:21.270 --> 00:35:22.360
- Very cool.

00:35:22.360 --> 00:35:23.790
And so I have a question from Dylan.

00:35:23.790 --> 00:35:25.920
And Dylan is right over there.

00:35:25.920 --> 00:35:27.200
So what are some of the most interesting,

00:35:27.200 --> 00:35:28.920
unexpected, fun, technical challenges

00:35:28.920 --> 00:35:30.680
that you and your team have
faced in the process of

00:35:30.680 --> 00:35:33.453
scaling Dropbox to hundreds
of millions of users?

00:35:35.850 --> 00:35:36.980
- So I think it's just fundamentally

00:35:36.980 --> 00:35:38.490
the challenge of Dropbox itself.

00:35:38.490 --> 00:35:41.760
I mean, we're trying to
build like the file system

00:35:41.760 --> 00:35:42.660
for the internet.

00:35:42.660 --> 00:35:46.944
And so how do you connect
a billion devices, right.

00:35:46.944 --> 00:35:50.340
And so that comes along with all kinds of

00:35:50.340 --> 00:35:53.770
technical challenges where
people are saving a billion files

00:35:53.770 --> 00:35:54.900
every day on Dropbox.

00:35:54.900 --> 00:35:59.160
And so, that's more than
there are Tweets on Twitter.

00:35:59.160 --> 00:36:00.910
And this is not like Little
hundred, 40 characters

00:36:00.910 --> 00:36:02.860
it's like you're like wedding photos.

00:36:02.860 --> 00:36:04.033
- Pictures yeah.

00:36:04.950 --> 00:36:07.700
- You connect nothing, you
can't have a bad day, right?

00:36:09.550 --> 00:36:11.170
So even just the core service

00:36:11.170 --> 00:36:13.740
but then as you branch
out then there's all these

00:36:13.740 --> 00:36:16.550
interesting things with,
how do we make a...

00:36:22.210 --> 00:36:24.880
There's sort of far afield
things like computer version

00:36:24.880 --> 00:36:26.920
like how do we infer photos or something

00:36:26.920 --> 00:36:29.370
you may how do we organize
your photos for you.

00:36:29.370 --> 00:36:30.303
Search.

00:36:31.758 --> 00:36:34.510
Pretty much every kind of
lay like client software,

00:36:34.510 --> 00:36:37.470
we have big data, we have data science,

00:36:37.470 --> 00:36:41.640
we have a bunch of infrastructure stuff.

00:36:41.640 --> 00:36:44.400
Every permutation,
every possible platform.

00:36:44.400 --> 00:36:46.360
If people are like really
into like hardcore algorithms

00:36:46.360 --> 00:36:47.740
we need like that.

00:36:47.740 --> 00:36:49.890
If we have people really deep into systems

00:36:49.890 --> 00:36:52.330
we like unlimited need for
that much storage stuff.

00:36:52.330 --> 00:36:54.534
I mean, it's really all over the map like

00:36:54.534 --> 00:36:58.260
it feels like any permutation
of technical challenge.

00:36:58.260 --> 00:37:00.690
We have it at least in Software.

00:37:00.690 --> 00:37:02.630
- Yeah, absolutely.

00:37:02.630 --> 00:37:05.050
And I think we have time for one more.

00:37:05.050 --> 00:37:06.500
So this from Joel.

00:37:06.500 --> 00:37:07.333
Where is Joel?

00:37:07.333 --> 00:37:08.220
There is Joel right there.

00:37:08.220 --> 00:37:09.630
So he'd like to hear about Hack Week.

00:37:09.630 --> 00:37:11.760
And this is where we've
had a little bit of

00:37:11.760 --> 00:37:13.020
we want to do more of this.

00:37:13.020 --> 00:37:16.040
How did it get started
and has any what new stuff

00:37:16.040 --> 00:37:16.873
has come out of it?

00:37:16.873 --> 00:37:18.140
Has anything actually been privatized?

00:37:18.140 --> 00:37:22.064
- And so Hack Week is basically
something we do every year

00:37:22.064 --> 00:37:24.640
where you guys have probably
heard of a hackathon

00:37:24.640 --> 00:37:27.280
or do like a one day hacking event

00:37:27.280 --> 00:37:29.750
but we're like all right,
let's take this to 11

00:37:29.750 --> 00:37:31.760
we'll do a whole week.

00:37:31.760 --> 00:37:35.170
And because sometimes
Dropbox would have been hard

00:37:35.170 --> 00:37:37.769
to prove that in a day but
actually the first prototype

00:37:37.769 --> 00:37:40.571
had something reasonably
working in a week.

00:37:40.571 --> 00:37:44.273
And so it's something we do, really,

00:37:45.713 --> 00:37:48.750
to sort of get back to the
spirit of like where we started

00:37:48.750 --> 00:37:50.763
where there are no constraints.

00:37:50.763 --> 00:37:52.450
A lot of people were telling us that

00:37:52.450 --> 00:37:53.330
what we were doing was...

00:37:53.330 --> 00:37:56.480
A lot of investors told me that Dropbox

00:37:56.480 --> 00:37:58.800
it's a stupid thing to get into have a yet

00:37:58.800 --> 00:38:02.350
another storage company or all
the other ones that failed.

00:38:02.350 --> 00:38:03.690
But like it just doesn't
matter like instead of

00:38:03.690 --> 00:38:06.320
like talking or debating
like actually write code

00:38:06.320 --> 00:38:09.100
and just if you do it
right, like you can change

00:38:09.100 --> 00:38:10.180
how people think.

00:38:10.180 --> 00:38:13.835
And so a ton of things have
made it into the products

00:38:13.835 --> 00:38:16.860
from having to account having a personal

00:38:16.860 --> 00:38:19.200
and business account and
Dropbox that was a huge project

00:38:19.200 --> 00:38:22.176
that started out as a Hack Week project.

00:38:22.176 --> 00:38:26.220
One of my Hack Week projects was the new

00:38:26.220 --> 00:38:28.400
and the way you do notifications
are like those sort of

00:38:28.400 --> 00:38:30.470
the menu bar and Dropbox
is not like the native

00:38:30.470 --> 00:38:32.692
and then you can see like what's changed

00:38:32.692 --> 00:38:35.470
and have a different UI around that.

00:38:35.470 --> 00:38:37.260
Things like a bunch of security stuff.

00:38:37.260 --> 00:38:39.804
So two factor authentication was something

00:38:39.804 --> 00:38:44.280
that started there a lot
of how you can like rewind

00:38:44.280 --> 00:38:46.760
your files or undo things
that was at Hack Week project.

00:38:46.760 --> 00:38:49.540
And then a lot of other stuff
which maybe didn't make it

00:38:49.540 --> 00:38:51.850
one to one later like
make it pound for pound

00:38:51.850 --> 00:38:52.683
into the product.

00:38:52.683 --> 00:38:55.960
But even just like when
we watch people build

00:38:55.960 --> 00:38:58.020
like all these apps on top of Dropbox

00:38:58.020 --> 00:38:59.310
like that informed like someone made

00:38:59.310 --> 00:39:03.110
like a Jukebox kind of music
player as a separate app

00:39:03.110 --> 00:39:05.440
and it just sort of like plants a seed

00:39:05.440 --> 00:39:09.540
that may manifest itself years
later in something like oh,

00:39:09.540 --> 00:39:11.370
well now instead of just
having the Dropbox app,

00:39:11.370 --> 00:39:13.470
you have all family of apps.

00:39:13.470 --> 00:39:15.300
Like Carousel , Mailbox, Dropbox.

00:39:15.300 --> 00:39:18.700
So that it's really just a time for A

00:39:18.700 --> 00:39:20.670
just to work on anything except

00:39:20.670 --> 00:39:22.560
what you're supposed to be working on.

00:39:22.560 --> 00:39:25.261
B like kind of unleash
people and remember kind of

00:39:25.261 --> 00:39:28.230
like lift the constraints of day to day.

00:39:28.230 --> 00:39:31.720
And three it's to change
how people think about

00:39:31.720 --> 00:39:33.730
if you have an idea like prove it

00:39:33.730 --> 00:39:38.190
and you learn as people
have like a lot of really

00:39:38.190 --> 00:39:39.900
this is pretty amazing group of people

00:39:39.900 --> 00:39:40.780
we have in the company.

00:39:40.780 --> 00:39:42.620
Where the interns like take Dropbox

00:39:42.620 --> 00:39:44.420
and put it put it in a weather balloon

00:39:44.420 --> 00:39:47.870
and put an Android phone into space

00:39:47.870 --> 00:39:50.010
where that this phone
will be taking pictures of

00:39:50.010 --> 00:39:51.560
the ride up and down.

00:39:51.560 --> 00:39:52.970
And so they're just crazy.

00:39:52.970 --> 00:39:54.220
It was just have this like pictures,

00:39:54.220 --> 00:39:56.100
uploading the Dropbox of like space.

00:39:56.100 --> 00:39:57.020
- Well, I just want to thank you.

00:39:57.020 --> 00:40:00.320
I think I speak for everyone here

00:40:00.320 --> 00:40:02.620
that it's been a real treat to kind of

00:40:02.620 --> 00:40:04.390
get to know you just now.

00:40:04.390 --> 00:40:05.580
So thank you very much.

00:40:05.580 --> 00:40:06.680
- Okay thanks awesome.

00:40:07.910 --> 00:40:08.743
Thank you.

00:40:08.743 --> 00:40:11.685
(audience clapping)


Monopsony employers and minimum wages

WEBVTT
Kind: captions
Language: en

00:00:00.400 --> 00:00:02.120
- [Instructor] We've already
talked about the notion

00:00:02.120 --> 00:00:06.180
of a monopsony employer in other videos,

00:00:06.180 --> 00:00:07.940
but now we're going to
review it a little bit.

00:00:07.940 --> 00:00:09.250
And we're going to introduce a twist,

00:00:09.250 --> 00:00:10.990
and the twist is what happens

00:00:10.990 --> 00:00:13.530
when they have to deal
with a minimum wage?

00:00:13.530 --> 00:00:16.230
And as we'll see, it's
kind of counterintuitive.

00:00:16.230 --> 00:00:17.640
So first of all, just as a review,

00:00:17.640 --> 00:00:20.770
a monopsony is a situation
where you have one buyer

00:00:20.770 --> 00:00:24.233
and you have many sellers of something.

00:00:25.230 --> 00:00:28.170
And when we're talking
about a monopsony employer,

00:00:28.170 --> 00:00:31.580
the buyer is the buyer of labor.

00:00:31.580 --> 00:00:34.780
We're talking about the buyer
in the labor factor markets,

00:00:34.780 --> 00:00:36.150
and the seller are the workers,

00:00:36.150 --> 00:00:39.830
the people who would sell
their labor for a wage.

00:00:39.830 --> 00:00:42.640
And we have already studied monopsony

00:00:42.640 --> 00:00:46.540
employers situations
before, but I will redo it.

00:00:46.540 --> 00:00:48.560
It never hurts to get the practice.

00:00:48.560 --> 00:00:51.270
In the vertical axis, you have the wage,

00:00:51.270 --> 00:00:54.100
which is really the price of this factor

00:00:54.100 --> 00:00:56.610
of labor that we're studying right now.

00:00:56.610 --> 00:00:58.160
And in the horizontal axis,

00:00:58.160 --> 00:01:00.730
you have the quantity of the
factor that we care about,

00:01:00.730 --> 00:01:03.700
and this is quantity of labor.

00:01:03.700 --> 00:01:07.100
Now, we have seen this
show many times before.

00:01:07.100 --> 00:01:08.790
You're going to have or you typically have

00:01:08.790 --> 00:01:13.170
a downward-sloping marginal
revenue product curve.

00:01:13.170 --> 00:01:15.300
And that describes a situation

00:01:15.300 --> 00:01:18.140
where every incremental
unit of labor you bring on,

00:01:18.140 --> 00:01:20.910
the marginal revenue, the
incremental revenue you get,

00:01:20.910 --> 00:01:22.840
goes lower and lower and lower because of,

00:01:22.840 --> 00:01:25.220
arguably, diminishing returns in some way.

00:01:25.220 --> 00:01:28.870
So this is marginal
revenue product of labor.

00:01:28.870 --> 00:01:31.590
You could also have marginal
revenue product of capital

00:01:31.590 --> 00:01:33.650
or of land, other factors.

00:01:33.650 --> 00:01:36.430
And then we could think
about the supply of labor.

00:01:36.430 --> 00:01:38.180
Or actually, really what
we're trying to get at is

00:01:38.180 --> 00:01:41.110
what is the marginal factor cost curve?

00:01:41.110 --> 00:01:43.180
And if this employer

00:01:43.180 --> 00:01:45.430
were not a monopsony employer,
if they were just operating

00:01:45.430 --> 00:01:47.560
in a perfectly competitive labor market,

00:01:47.560 --> 00:01:49.190
the marginal factor cost curve

00:01:49.190 --> 00:01:50.910
would just be the market wage.

00:01:50.910 --> 00:01:53.090
So it might look something like that.

00:01:53.090 --> 00:01:55.570
But we are dealing with
a monopsony employer,

00:01:55.570 --> 00:01:59.820
and so they don't just take
the market wage, they have,

00:01:59.820 --> 00:02:02.420
you could view it as a
supply curve for labor

00:02:02.420 --> 00:02:03.680
that's specific to them.

00:02:03.680 --> 00:02:06.310
Because remember, they're
the only show in town.

00:02:06.310 --> 00:02:09.180
They are the big employer
maybe in this small town.

00:02:09.180 --> 00:02:11.203
And so you have this supply curve.

00:02:12.380 --> 00:02:13.990
This, this is supply

00:02:15.420 --> 00:02:17.540
of labor.

00:02:17.540 --> 00:02:19.610
But this is not the
marginal factor cost curve,

00:02:19.610 --> 00:02:21.630
and we've explained this before.

00:02:21.630 --> 00:02:23.720
But that's because as you bring on

00:02:23.720 --> 00:02:25.660
higher and higher quantities of labor,

00:02:25.660 --> 00:02:28.560
you need to pay more to
that incremental person.

00:02:28.560 --> 00:02:30.320
But what typically happens
is if you need to pay

00:02:30.320 --> 00:02:33.110
one person more, you need to
pay everyone the same wage.

00:02:33.110 --> 00:02:34.830
So as you bring on that incremental labor,

00:02:34.830 --> 00:02:37.100
not only you have to pay more
for that incremental unit,

00:02:37.100 --> 00:02:38.760
but you have to raise
the wage for everyone.

00:02:38.760 --> 00:02:41.950
So the marginal factor
cost goes up twice as fast

00:02:41.950 --> 00:02:44.160
as the supply of labor curve.

00:02:44.160 --> 00:02:47.453
So the marginal factor
cost curve, it would look,

00:02:49.242 --> 00:02:51.600
might look something like this.

00:02:51.600 --> 00:02:55.150
And then what's rational
is a firm would keep

00:02:55.150 --> 00:02:57.400
bringing on that factors,
in this case, labor.

00:02:57.400 --> 00:02:58.970
It would keep hiring folks

00:02:58.970 --> 00:03:02.360
as long as the incremental
revenue that it gets

00:03:02.360 --> 00:03:05.450
from hiring that next unit is higher

00:03:06.314 --> 00:03:08.410
than the marginal or the incremental cost.

00:03:08.410 --> 00:03:10.050
And so they'll keep bringing people on

00:03:10.050 --> 00:03:13.230
as long as the MRP is higher than the MFC,

00:03:13.230 --> 00:03:16.130
and so we would get to
that point right there.

00:03:16.130 --> 00:03:18.890
And so it'd be rational for this firm

00:03:18.890 --> 00:03:20.980
to hire this quantity of labor.

00:03:20.980 --> 00:03:22.250
Let's call that Q sub one.

00:03:22.250 --> 00:03:24.310
And then what wage are they paying?

00:03:24.310 --> 00:03:25.710
Pause this video, and think about that

00:03:25.710 --> 00:03:28.460
'cause this is always a little bit tricky.

00:03:28.460 --> 00:03:30.560
Well, you might be tempted
to draw a line here.

00:03:30.560 --> 00:03:33.760
But remember, this doesn't
describe the actual wage.

00:03:33.760 --> 00:03:35.420
The wage at that quantity is described

00:03:35.420 --> 00:03:36.990
by the supply of labor.

00:03:36.990 --> 00:03:41.300
So this would be the wage
that the firm would pay.

00:03:41.300 --> 00:03:44.080
So now let's introduce our twist.

00:03:44.080 --> 00:03:46.570
Let's think about what happens

00:03:46.570 --> 00:03:50.610
if a minimum wage is
employed in this region,

00:03:50.610 --> 00:03:52.500
that, for whatever reason,
the city council says,

00:03:52.500 --> 00:03:54.590
hey, that employer needs
to be paying more money.

00:03:54.590 --> 00:03:58.740
And let's say they
institute a minimum wage at,

00:03:58.740 --> 00:04:00.780
I will do this in a bold color.

00:04:00.780 --> 00:04:03.900
Let's say they institute a
minimum wage right over here.

00:04:03.900 --> 00:04:07.920
Let's call this wage sub m.

00:04:07.920 --> 00:04:11.320
Pause the video, and think
about what would then happen.

00:04:11.320 --> 00:04:14.020
What would the marginal
factor cost curve look like?

00:04:14.020 --> 00:04:16.220
And then what would be
the rational quantity

00:04:16.220 --> 00:04:17.663
for the firm to hire?

00:04:18.700 --> 00:04:22.530
All right, so now that
the town has instituted

00:04:22.530 --> 00:04:26.070
a minimum wage and it's
higher than the rational wage

00:04:26.070 --> 00:04:29.900
that the firm would've
otherwise paid for labor,

00:04:29.900 --> 00:04:30.770
what it does is it,

00:04:30.770 --> 00:04:34.600
at least at a certain
range of quantities, it,

00:04:34.600 --> 00:04:36.930
of quantities of labor being employed,

00:04:36.930 --> 00:04:40.190
it essentially makes this
monopsony employer have to think

00:04:40.190 --> 00:04:44.000
a little bit like an employer
in a competitive labor market

00:04:44.000 --> 00:04:45.920
where you just have to accept a wage.

00:04:45.920 --> 00:04:48.710
Now, this wage isn't
being set by some market.

00:04:48.710 --> 00:04:51.200
It's being set by a government.

00:04:51.200 --> 00:04:54.220
So as long as this wage

00:04:54.220 --> 00:04:58.340
is higher than the supply of labor,

00:04:58.340 --> 00:04:59.530
well, then this is going to be,

00:04:59.530 --> 00:05:01.940
or higher than our old supply curve,

00:05:01.940 --> 00:05:04.040
well, this is going to be,
from the firm's point of view,

00:05:04.040 --> 00:05:05.160
the new supply curve.

00:05:05.160 --> 00:05:08.520
So it's going to look something like this.

00:05:08.520 --> 00:05:10.350
But then when the supply curve,

00:05:10.350 --> 00:05:12.740
when the wages that the
supply curve describes

00:05:12.740 --> 00:05:14.130
go higher than that minimum wage,

00:05:14.130 --> 00:05:15.860
well, then it will track that.

00:05:15.860 --> 00:05:19.750
So this is our new supply
curve right over here.

00:05:19.750 --> 00:05:21.510
So new,

00:05:21.510 --> 00:05:25.100
new supply curve, and we're
talking about supply of labor,

00:05:25.100 --> 00:05:27.440
and it's this whole red thing.

00:05:27.440 --> 00:05:31.403
And what would be our new
marginal factor cost curve?

00:05:32.330 --> 00:05:34.250
Well, we said that it has twice the slope,

00:05:34.250 --> 00:05:36.300
but when the slope is just flat here,

00:05:36.300 --> 00:05:37.930
I'm gonna do this in a new color.

00:05:37.930 --> 00:05:40.100
So the marginal factor cost curve,

00:05:40.100 --> 00:05:44.190
it's going to track this
horizontal line right over here.

00:05:44.190 --> 00:05:45.680
And then all of a sudden,

00:05:45.680 --> 00:05:48.720
when the supply curve starts to go up,

00:05:48.720 --> 00:05:50.520
well, then it's going to jump back

00:05:50.520 --> 00:05:52.690
to the old marginal factor cost curve.

00:05:52.690 --> 00:05:54.100
So it's going to look something like this.

00:05:54.100 --> 00:05:58.630
So MFC, I'll call it two, that's in blue.

00:05:58.630 --> 00:06:02.520
So it tracks the supply curve
here when it's horizontal.

00:06:02.520 --> 00:06:04.510
And it is really just analogous

00:06:04.510 --> 00:06:07.800
to when we just have to accept
a wage, and then it jumps.

00:06:07.800 --> 00:06:11.580
We have a bit of a discontinuity,
and then you get up there.

00:06:11.580 --> 00:06:16.540
But what's rational, as always,
is a firm to keep hiring

00:06:16.540 --> 00:06:19.190
as long as the marginal
revenue product is higher

00:06:19.190 --> 00:06:21.060
than the marginal factor cost.

00:06:21.060 --> 00:06:23.110
So it's going to keep hiring.

00:06:23.110 --> 00:06:25.890
As long as this yellow line
is above the blue line,

00:06:25.890 --> 00:06:27.220
it would keep hiring, keep hiring,

00:06:27.220 --> 00:06:30.510
all the way until this
point right over here.

00:06:30.510 --> 00:06:32.650
So notice what just happened.

00:06:32.650 --> 00:06:34.800
It is now rational

00:06:34.800 --> 00:06:38.240
for the firm to hire more people,

00:06:38.240 --> 00:06:39.810
and that is counterintuitive.

00:06:39.810 --> 00:06:40.870
In everyday thought,

00:06:40.870 --> 00:06:42.730
if I thought I was running
some type of a business,

00:06:42.730 --> 00:06:44.000
if I was running a burger joint,

00:06:44.000 --> 00:06:46.740
and all of a sudden if there
was a higher minimum wage,

00:06:46.740 --> 00:06:48.660
then it feels like, hey, I
might not have enough money

00:06:48.660 --> 00:06:51.970
to hire people, I might lower
the number of people I hired.

00:06:51.970 --> 00:06:53.710
But we just showed, at least with some,

00:06:53.710 --> 00:06:57.060
with a very simplified economics
model, that theoretically

00:06:57.060 --> 00:06:59.400
when you're dealing with
a monopsony employer,

00:06:59.400 --> 00:07:03.990
it actually might get
them to hire more people.

00:07:03.990 --> 00:07:05.220
So an interesting question is

00:07:05.220 --> 00:07:08.120
why did this counterintuitive
thing happen?

00:07:08.120 --> 00:07:10.210
And one hand-wavy argument,

00:07:10.210 --> 00:07:12.010
but I encourage you to ponder it,

00:07:12.010 --> 00:07:14.890
is to realize that, in the old world,

00:07:14.890 --> 00:07:17.140
every time they brought
on an incremental person,

00:07:17.140 --> 00:07:19.820
they had to raise the salary of everyone,

00:07:19.820 --> 00:07:21.990
and that's what made
the marginal factor cost

00:07:21.990 --> 00:07:23.470
go up so quickly.

00:07:23.470 --> 00:07:25.570
But now since you have
this whole flat part

00:07:25.570 --> 00:07:26.910
of your supply curve,

00:07:26.910 --> 00:07:30.010
because regardless of
how many people you hire

00:07:30.010 --> 00:07:31.510
in this range right over here,

00:07:31.510 --> 00:07:32.870
you're paying the same amount,

00:07:32.870 --> 00:07:34.330
that incremental person

00:07:34.330 --> 00:07:37.180
does not increase the
wage for everyone else.

00:07:37.180 --> 00:07:39.810
So that is what made it
rational for the firm

00:07:39.810 --> 00:07:41.630
to go and keep hiring.

00:07:41.630 --> 00:07:43.530
Now, the community, the government,

00:07:43.530 --> 00:07:45.150
the city council would
have to be very careful

00:07:45.150 --> 00:07:47.940
about what this minimum wage
is because it's very possible

00:07:47.940 --> 00:07:49.970
that they could overshoot
and actually end up

00:07:49.970 --> 00:07:52.960
in a situation where the firm hires less.

00:07:52.960 --> 00:07:55.720
So, for example, if they
made this the minimum wage

00:07:55.720 --> 00:08:00.020
right over here, let's
call that W two or W three,

00:08:00.020 --> 00:08:01.610
well, now all of a sudden,

00:08:01.610 --> 00:08:04.720
you would have a marginal
factor cost curve

00:08:04.720 --> 00:08:07.600
that is going like this

00:08:07.600 --> 00:08:09.310
for at least a good bit.

00:08:09.310 --> 00:08:10.780
We can think about it a little bit later,

00:08:10.780 --> 00:08:13.380
as what happens is you go
further and further to the right.

00:08:13.380 --> 00:08:14.720
But then it would only be rational

00:08:14.720 --> 00:08:16.570
for the firm to hire that much,

00:08:16.570 --> 00:08:20.660
and so then you would have
a decrease in employment.

00:08:20.660 --> 00:08:22.690
But if we go back to
the original situation,

00:08:22.690 --> 00:08:24.130
another thing that you
might be thinking about,

00:08:24.130 --> 00:08:26.710
hey, this seems too good to be true.

00:08:26.710 --> 00:08:29.780
It's now rational for the
firm to hire more folks,

00:08:29.780 --> 00:08:31.570
and those folks are getting more income.

00:08:31.570 --> 00:08:33.850
Surely someone must be losing.

00:08:33.850 --> 00:08:36.160
And it is the case that the firm

00:08:36.160 --> 00:08:39.330
is now going to lose more of,

00:08:39.330 --> 00:08:41.090
I guess you could say the surplus

00:08:41.090 --> 00:08:43.680
that it was having in the old world,

00:08:43.680 --> 00:08:48.363
and more of that is now
being given to the workers.