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we will say no to people even if their
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coding and system design is good this
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guy was a principal engineer at Amazon
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he conducted thousands of interviews
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while he was there and last month I went
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to his Studio to ask him to teach me
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everything he knows about interviewing
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in big Tech he also shared a ton of
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unexpected stories H from his promotion
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to principal engineer at Amazon how many
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people are expected to be cut in Amazon
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typically what I can say
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is the PIP or performance Improvement
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plan and then what about the worst
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manager you had yeah I don't want to
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name names or anything
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but I know that you came from a liberal
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arts background um your major going into
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college was actually English right yeah
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I was creative writing and and English
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literature so can you tell us a little
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bit about you getting into Amazon
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without a CS major yeah I think um just
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getting in as a liberal arts major may
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be a bit disingenuous uh both of my
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parents were electrical engineers and so
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I've always had a computer around the
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house and um you know I used to program
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that computer I still remember my first
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one it was an uh IBM XT
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8088 with uh 640k of ram no hard disk
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two five and two five and a qu uh two 5
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and a qu inch floppy discs so that it's
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a floppy disc that's actually floppy not
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the hard one that you you probably don't
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even remember um and so you know I've
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I've always been been coding and uh
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since a really young age in high school
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I did the computer science uh AP tests
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my sophomore year I did the ab test
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which was in Pascal way back when Pascal
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is a programming language and um my
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junior year uh it was in C++ and I did
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the BC test and so I knew about the
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concepts of you know Big O um algorithms
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and data structures how to write
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programs you know I still remember
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making like a Tetris clone when I was in
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high school so you know the fact that I
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broke in without a computer science
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degree if you just said the part about
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the English degree um like I said it's a
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it's a bit disingenuous and so I I went
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to school I got a liberal arts degree I
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did get a minor um in math and applied
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math and I took some computer science
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courses you know when I when I got out
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of school I
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I was looking for work and it was around
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2005 2006 I still remember this story I
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went and talked to my my writing
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Professor uh in one of my senior year
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seminars at udub and I was like
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Professor bossworth like what type of
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job should I get um I want to be a
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writer and he said he put his hand on my
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shoulder and he was like Steve there's
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no job called writer it's it's like not
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not yet there is a job called waiter and
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so you just have to find a way to sort
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of support
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yourself um while you ply your craft
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right and so just finding some sort of
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way to eek by while you get some
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experience under your belt I wasn't
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really turned on by that and so I
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decided to to revisit the skills that I
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picked up in high school and before that
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I see so I mean to me then it is
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disingenuous to say that as if you came
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from zero skill but your
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resume came from zero is my
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understanding right because if if you
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look if I was a big tech recruiter and I
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was looking through stack of resumΓ©s and
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English major comes
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along you probably would not stand out
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when it comes to you know the the job
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market so what is the thing that you did
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that got you into Amazon it was through
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networking so somebody that I did AP
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Computer Science with work at Amazon he
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went to University of Washington and got
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a proper computer science degree and was
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a software developer at Amazon and so
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they needed some support Engineers uh
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and it was a contract position and so I
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basically was like can you get me an
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interview at the company and I was just
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I was not worried about a coding
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interview because of my prior experience
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but also you know I think with support
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engineers they writing scripts and and
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maintaining systems and so I got through
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on that interview and um you know I was
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a green badge contractor for about nine
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months before I transitioned a fulltime
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what's green badge mean just temp yeah
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it's a temp I see it's an Amazon term
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yeah so the blue badge would be
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full-time and then green badge is a
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contractor yellow is like a vendor or
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got it got it got it like maybe today's
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environment is like a bit more intense
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where people want to get into big TCH
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and you know Amazon's a big name at this
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point but
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also your resume although it was not CS
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the thing that got you in was that you
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knew someone and they gave you like a a
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referral and that made a big difference
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that at least got you the the interview
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and then you had the skills cuz you were
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you had been doing CS for a while yeah I
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think the way to think about it if you
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know when I when I guide people trying
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to get a job it takes two things it
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takes you know some amount of
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opportunity and it takes some amount of
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and so you don't know when the
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opportunity is going to pop up you don't
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know if your Uncle Daniel from
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church you know will talk to somebody
[05:39] (339.76s)
that knows about a job opening you don't
[05:41] (341.40s)
know when that's going to land it's very
[05:42] (342.88s)
unevenly distributed where these
[05:44] (344.80s)
opportunities come from but I think over
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time they will come and and rear their
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their heads or make themselves available
[05:52] (352.12s)
I think the other side of it is the
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preparedness right so upleveling
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yourself gaining knowledge gaining
[05:58] (358.12s)
skills that needs to to occur you can't
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just have the opportunity and then not
[06:02] (362.44s)
have the skills right and so those two
[06:04] (364.08s)
need things need to marry and so you
[06:07] (367.08s)
know I think back then it was much more
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difficult to gain the knowledge that was
[06:11] (371.00s)
necessary to to get into big Tech today
[06:14] (374.68s)
you know you see all of these cottage
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industries around interview prep getting
[06:18] (378.24s)
ready for the coding interview none of
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that stuff existed when I was trying to
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get in and so I think it would actually
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be harder um back then to get your foot
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into the door in Tech from a
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non-traditional background than it is
[06:30] (390.44s)
today now I won't say that it's
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necessarily easy today but at least in
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my mind I think it was more difficult
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for me yeah I remember when we worked on
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that post together you said there wasn't
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even the idea of like uh lists of leak
[06:43] (403.96s)
code questions and things and you were
[06:46] (406.04s)
just collecting interview questions to
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prepare yeah so when I was uh a support
[06:50] (410.72s)
engineer and I um you know they made me
[06:52] (412.88s)
blue badge so full-time employee but I
[06:55] (415.68s)
just I wanted to be an SD so bad and so
[06:58] (418.64s)
all I did for the audience's software
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development engineer yeah and so I
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wanted to be a software developer so bad
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I just cornered everybody I just became
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a collector of questions I was like what
[07:09] (429.96s)
do you ask during interviews and I was
[07:12] (432.40s)
like don't tell me the answer I'm going
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to go and figure it out and so you know
[07:16] (436.32s)
just did it the oldfashioned way um just
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firing up an IDE and you know you don't
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have all these battery of test cases
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they get run like you know with Le code
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and stuff now and so you know generating
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your own test case you know that's
[07:30] (450.56s)
that's a way to sort of uplevel yourself
[07:32] (452.12s)
so I feel like I did it in a just in a
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time where you know we weren't so
[07:38] (458.24s)
resourcer so I imagine that probably
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lowered the average performance of a of
[07:44] (464.32s)
interviewee uh and maybe because you had
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extraordinary uh process of like
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collecting questions that you might have
[07:52] (472.96s)
been like you know very outstanding when
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it comes to everyone because ultimately
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interview prep is a little bit
[07:59] (479.48s)
competitive you need to be better than
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the other people to to get in yes and no
[08:05] (485.00s)
I I think of the distribution of demand
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for software developers is skewed I just
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especially today I don't think there's a
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ton of demand for junior folks I think
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there's a extraordinary amount of demand
[08:20] (500.80s)
for senior and above the reality is that
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seniors come from mid-level and juniors
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and so I think the pipeline is a bit
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busted right now I don't necessarily
[08:29] (509.56s)
think of a ton of competition at the
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upper end um I do think that there is a
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lot at the lower end um but the
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competition doesn't exist at the
[08:40] (520.96s)
interview stage I think the competition
[08:43] (523.28s)
exists at the pre-qualification and
[08:45] (525.08s)
selection phase and so if you're able to
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catch the attention of a recruiter say
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you know somebody that works at the
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company or you're able to go really deep
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in a particular area and and stand out
[08:58] (538.48s)
maybe you built an app
[09:00] (540.20s)
has some amount of customers that's
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where the competition is like you need
[09:03] (543.68s)
to stand out on the selection side by
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the time you get to the interview it
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like it's just a matter of clearing the
[09:09] (549.60s)
bar there and so you're the the
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dimension of competition is not at the
[09:15] (555.56s)
coding level I don't think why do you
[09:17] (557.48s)
think that most interview prep advice is
[09:22] (562.92s)
garbage I think that most interview prep
[09:27] (567.72s)
non-optimal and so
[09:30] (570.80s)
you know there's a there's a hyperfocus
[09:32] (572.56s)
on the coding
[09:34] (574.00s)
interview there's a hyperfocus now on
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design but I think really
[09:40] (580.36s)
people forget they so they they turn it
[09:44] (584.12s)
test and in some sense it is if you
[09:47] (587.72s)
can't code then they they don't want you
[09:50] (590.48s)
um if you can't design a system and
[09:51] (591.92s)
you're a senior like you know it's not
[09:54] (594.36s)
going to work out like if we put you in
[09:56] (596.96s)
a in a role it's it's just you're going
[09:59] (599.56s)
to be that 5% that leave right we don't
[10:01] (601.64s)
want to do that and
[10:03] (603.88s)
so the the big overarching framework is
[10:08] (608.40s)
the people on the other side of the
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table are trying to figure out whether
[10:11] (611.00s)
they want to work with you whether
[10:12] (612.96s)
you're going to be a good fit for the
[10:14] (614.84s)
culture but people think about it in
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terms of a test and
[10:19] (619.32s)
so it's much more like a date than it is
[10:23] (623.20s)
like at the
[10:24] (624.96s)
sat right and but the but the the prep
[10:29] (629.72s)
industry the interview prep
[10:31] (631.96s)
industry it's much easier to think about
[10:34] (634.32s)
it and present it as a
[10:35] (635.96s)
test right and so I wish people would
[10:38] (638.80s)
just embed this uh you know some things
[10:41] (641.76s)
like hey behavioral interviews have an
[10:44] (644.20s)
outsized impact on whether they're going
[10:47] (647.28s)
to hire you and what level you're going
[10:49] (649.04s)
to come in at so instead of say spending
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80% of your time on
[10:55] (655.72s)
coding or maybe let's say 60% on coding
[10:59] (659.32s)
and then 35% on system design and like
[11:02] (662.88s)
the 5% is like the donate to charity pie
[11:06] (666.68s)
slice like maybe it's much more like 40%
[11:11] (671.64s)
40% 20% right because that behavioral
[11:14] (674.84s)
side I think is really where the match
[11:16] (676.84s)
is made where and where behavioral is
[11:19] (679.84s)
20% I was a bar Razer trainer and I
[11:23] (683.36s)
trained thousands of people at Amazon on
[11:26] (686.04s)
how to conduct interviews assess talent
[11:28] (688.12s)
and then level people before the
[11:30] (690.24s)
training was you know now it's a set of
[11:32] (692.44s)
videos but it used to be live training
[11:33] (693.96s)
so I've trained many people on this and
[11:36] (696.28s)
what I used to say and I'll say it right
[11:38] (698.92s)
now is the coding so the functional
[11:41] (701.84s)
parts of the interview the coding
[11:43] (703.52s)
interview the system design interview
[11:46] (706.72s)
those things are the anti right so
[11:49] (709.68s)
they're the small blind and big blind so
[11:51] (711.44s)
I use a poker analogy they're the small
[11:53] (713.28s)
blind and big blind of of getting into a
[11:57] (717.48s)
company and
[12:00] (720.12s)
the the behavioral part of the
[12:02] (722.96s)
interview that's the poker part of Poker
[12:07] (727.12s)
right that's like do you have a good
[12:08] (728.32s)
hand you know trying to beat the other
[12:10] (730.20s)
hand of the other person and
[12:13] (733.60s)
so if you thought about the coding part
[12:16] (736.16s)
and the system design part as necessary
[12:19] (739.36s)
but not
[12:20] (740.80s)
sufficient like that's the that's the
[12:22] (742.92s)
thing that I wish people
[12:24] (744.36s)
understood right we will say no to
[12:27] (747.16s)
people that have poor behavioral
[12:31] (751.76s)
answers poor not in the sense that they
[12:34] (754.12s)
don't have the experience it needs it's
[12:35] (755.68s)
just we can recognize from far away that
[12:37] (757.56s)
it's not going to be a good fit for the
[12:38] (758.84s)
company we'll say no to those people
[12:41] (761.20s)
even if their coding and system design
[12:43] (763.08s)
is good you're saying at Amazon it's
[12:45] (765.60s)
like the functional part it's like
[12:46] (766.96s)
coding system that's like pass no pass
[12:49] (769.52s)
yes but once you pass it your leveling
[12:52] (772.68s)
and the I guess the color behind how how
[12:55] (775.52s)
good you are is the behavioral yes I see
[12:58] (778.96s)
okay okay so then what what should
[13:02] (782.56s)
people do to kind of um you prevent from
[13:05] (785.52s)
being down leveled because their
[13:07] (787.36s)
behavioral is bad I think
[13:10] (790.76s)
that they should spend some time on what
[13:15] (795.68s)
packaging so if you can package your
[13:18] (798.36s)
experience and sort of communicate that
[13:20] (800.96s)
packaging to your
[13:23] (803.16s)
interviewer I think that's just optimal
[13:25] (805.76s)
for both sides right so you are
[13:29] (809.20s)
packaging your experience you're you're
[13:30] (810.68s)
communicating to them what you're all
[13:32] (812.48s)
about how you operate what things you've
[13:34] (814.72s)
done in the
[13:35] (815.84s)
past and you can make that a good story
[13:38] (818.80s)
you can not it doesn't have to be
[13:40] (820.24s)
entertaining but it can be efficient and
[13:42] (822.44s)
you can you know if if you are able to
[13:45] (825.20s)
effectively articulate yourself and
[13:46] (826.88s)
communicate it to your
[13:48] (828.60s)
interviewer I think now we're talking
[13:50] (830.68s)
about empathy now we're talking about
[13:53] (833.20s)
things like this is the fundamental
[13:55] (835.68s)
question for interviews is like do I
[13:57] (837.88s)
want to work with this person
[13:59] (839.68s)
that's the question that this whole song
[14:02] (842.84s)
and dance for the for the interview
[14:04] (844.76s)
process is trying to figure out do I
[14:06] (846.36s)
want to work with this person or
[14:08] (848.24s)
not and and I think spending some time
[14:11] (851.88s)
on the behavioral side is about trying
[14:15] (855.88s)
to help the interviewer answer that
[14:18] (858.24s)
question so you are just you're really
[14:20] (860.52s)
trying to act like yourself and and not
[14:24] (864.00s)
you know it's not NE you want to put
[14:25] (865.68s)
your best foot
[14:26] (866.92s)
forward you don't want to lie obviously
[14:30] (870.32s)
you want to misrepresent yourself but I
[14:33] (873.44s)
I really think that um you know just
[14:36] (876.32s)
being able to talk about who you are
[14:38] (878.12s)
what you're about and your experience
[14:39] (879.76s)
like that's the important part that's
[14:41] (881.08s)
the missing part from all of this
[14:43] (883.16s)
Cottage like interview prep that's going
[14:46] (886.28s)
on on the internet that's the big thing
[14:48] (888.28s)
that's missing could you give me an
[14:49] (889.76s)
example of packaging like what maybe you
[14:52] (892.04s)
could package your as if you were going
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to sell yourself back and go back to
[14:58] (898.24s)
Tech yeah you know so um just even
[15:01] (901.60s)
something like tell me about yourself
[15:04] (904.60s)
right um I think people people kind of
[15:07] (907.68s)
gloss over that and they kind of run on
[15:09] (909.80s)
sentence their way through it and you
[15:12] (912.52s)
know I think if I were to answer a
[15:15] (915.20s)
question like that it would just be like
[15:16] (916.76s)
hey you know my name is Steve fnn I have
[15:20] (920.28s)
you know I have a a passion for backend
[15:23] (923.00s)
distributed
[15:24] (924.32s)
systems um I really love to work on um
[15:29] (929.44s)
you know customer facing products I'm a
[15:31] (931.92s)
sports fan you know I used to work at
[15:33] (933.48s)
Amazon tickets and and Prime video
[15:36] (936.36s)
sports and um you know I I really love
[15:40] (940.44s)
like building teams and and really you
[15:43] (943.56s)
know taking an organization's
[15:44] (944.96s)
engineering culture and upleveling it at
[15:47] (947.48s)
that level like those are those are some
[15:49] (949.52s)
of my passions right I didn't prep for
[15:51] (951.52s)
that that was kind of a interview off
[15:53] (953.28s)
the cuff but you know hopefully you got
[15:56] (956.36s)
a sense of you know who I am and what
[15:58] (958.48s)
I'm about
[15:59] (959.52s)
and the level that I operate one thing
[16:01] (961.88s)
that I like to say is that the stories
[16:04] (964.36s)
you tell they they sort of betray your
[16:06] (966.60s)
level the way that you you you
[16:08] (968.64s)
communicate with people they betray your
[16:10] (970.56s)
level right and so if you have
[16:13] (973.36s)
stories that are sd1 stories right entry
[16:16] (976.88s)
level stories but you're trying to get a
[16:19] (979.80s)
role that that in congruity is the thing
[16:23] (983.88s)
that's going to lead to the down
[16:25] (985.24s)
leveling yeah that makes sense and like
[16:26] (986.80s)
the last thing that you said there was
[16:28] (988.92s)
upleveling teams you're almost speaking
[16:31] (991.56s)
to like a like a staff or higher rubric
[16:34] (994.44s)
where you know it's not like you said oh
[16:36] (996.80s)
I like to clean up the code or yeah I
[16:40] (1000.72s)
love refactoring code it's like I do
[16:43] (1003.52s)
yeah but that's not that's not how I'm
[16:45] (1005.48s)
going to describe myself yeah right and
[16:47] (1007.96s)
so I um trying to turn this into a video
[16:51] (1011.48s)
of some sort but I just I want to do a
[16:53] (1013.76s)
thing where I just talk with somebody
[16:55] (1015.36s)
for five minutes and I try to figure out
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whether they're senior or mid or staff
[16:59] (1019.96s)
or whatever they are oh that'd be
[17:01] (1021.28s)
interesting like a blind yeah yeah like
[17:04] (1024.00s)
you don't know and you just yeah and
[17:07] (1027.04s)
maybe I'm you know maybe I'm
[17:10] (1030.44s)
overconfident but I just I feel like if
[17:12] (1032.68s)
I talk to a junior entry-level person I
[17:14] (1034.92s)
would know that they're a junior entry
[17:16] (1036.20s)
level person they just they just just
[17:17] (1037.80s)
the way that they carry themselves the
[17:19] (1039.72s)
the things that they talk about you know
[17:22] (1042.32s)
um now maybe on the you know if they're
[17:24] (1044.80s)
a strong senior
[17:26] (1046.88s)
engineer you know are they going to be
[17:28] (1048.68s)
able the pass as a principal yeah
[17:30] (1050.08s)
there's some there's some places where I
[17:32] (1052.92s)
um you know I might struggle but I I
[17:35] (1055.24s)
think I'm really calibrated in terms of
[17:37] (1057.24s)
level so that's for the interview stage
[17:39] (1059.16s)
what about before you get the interview
[17:41] (1061.48s)
right now it's a really competitive job
[17:43] (1063.40s)
market do you have any advice for people
[17:45] (1065.48s)
to stand out you have to be an outlier
[17:48] (1068.36s)
in some regard and so being an outlier
[17:51] (1071.96s)
May mean oh I have a contact that can
[17:54] (1074.48s)
give me a referral to a big tech company
[17:57] (1077.48s)
I think that if you just if you C DMD
[18:03] (1083.88s)
some folks on a team that had an opening
[18:07] (1087.40s)
and it was you know you didn't like spam
[18:09] (1089.40s)
them it didn't look like a like a like
[18:11] (1091.96s)
an auto DM sort of thing or a script you
[18:15] (1095.60s)
didn't sound like Ai and you were just
[18:17] (1097.44s)
like hey my name's Ryan um I noticed you
[18:21] (1101.72s)
work on this team and you have some
[18:23] (1103.40s)
openings like can you tell me what it's
[18:25] (1105.12s)
like on your team like what are the sort
[18:27] (1107.76s)
of things that you do on a day to-day
[18:29] (1109.20s)
basis and then also you know I'm a I'm a
[18:33] (1113.40s)
university student I'm about to graduate
[18:35] (1115.56s)
in 3 months like how can I position
[18:38] (1118.60s)
myself optimally in order to get this
[18:41] (1121.40s)
job I I ran a poll on my
[18:43] (1123.56s)
Discord and 90% of people said that if
[18:47] (1127.68s)
somebody did that and they were genuine
[18:49] (1129.32s)
about it that they would interact with
[18:51] (1131.64s)
him and that they would actually extend
[18:53] (1133.56s)
a referral if they asked right and so
[18:56] (1136.92s)
that's a that's an easy way to be an
[18:58] (1138.80s)
outlier in networking you know I I think
[19:02] (1142.32s)
about a lot you know there's this
[19:04] (1144.40s)
networking stuff where it's just like
[19:06] (1146.20s)
hey you know strengthen your your
[19:07] (1147.96s)
networking go up and talk to people
[19:09] (1149.96s)
there's this and it's American style too
[19:11] (1151.92s)
so it's like everybody thinks it's fake
[19:14] (1154.32s)
and surface level but that's not what
[19:16] (1156.24s)
I'm talking about right like you should
[19:17] (1157.84s)
do those things but like really like
[19:20] (1160.32s)
networking is about making some sort of
[19:22] (1162.44s)
connection right and so if you're able
[19:25] (1165.56s)
to connect with people they're in a spot
[19:27] (1167.76s)
to help you if you can provide value to
[19:30] (1170.16s)
them right I think that's the that's one
[19:32] (1172.76s)
way to be an outlier I think um if
[19:38] (1178.28s)
you're if you're new and you're you're
[19:40] (1180.84s)
willing to pick up skills hey what's the
[19:43] (1183.00s)
skill that I should pick up so that I'm
[19:45] (1185.00s)
much more attractive to to uh big Tech
[19:48] (1188.72s)
or to to getting a job I think that most
[19:52] (1192.48s)
people should go deep instead of going
[19:56] (1196.04s)
broad you know they'll be like Oh I'm
[19:58] (1198.40s)
going to
[19:59] (1199.36s)
you know I'm doing a react tutorial and
[20:01] (1201.48s)
I'm going to learn rusts and then
[20:03] (1203.72s)
there's a machine learning python thing
[20:05] (1205.88s)
with you know py toch and they go breath
[20:11] (1211.12s)
and there's no cohesion there it's like
[20:12] (1212.92s)
you know mobile app development and
[20:14] (1214.72s)
machine learning yeah you can make them
[20:16] (1216.96s)
sort of you know connect to each other
[20:19] (1219.48s)
but at some sense it's contrived and
[20:21] (1221.52s)
there's just so much to learn and so I I
[20:24] (1224.60s)
give the general guidance it's just like
[20:26] (1226.40s)
okay well what's the thing that
[20:27] (1227.36s)
interests you in a frame work or a
[20:29] (1229.64s)
language that you are you like you
[20:32] (1232.04s)
already know like how deep can you go in
[20:35] (1235.60s)
a particular you know in a thing that
[20:38] (1238.36s)
you already have some familiarity with
[20:40] (1240.36s)
2025 is there a top programming language
[20:43] (1243.68s)
that you'd recommend for someone to go
[20:45] (1245.48s)
deep in the cheeky answer is English is
[20:49] (1249.28s)
the top programming language in
[20:51] (1251.48s)
2025 um what what do you mean by that
[20:54] (1254.64s)
you know we had talked about it a little
[20:55] (1255.92s)
bit before but the ability to
[20:57] (1257.12s)
communicate yourself the ability to
[20:58] (1258.76s)
package your experience and tell a good
[21:01] (1261.00s)
story I think that's the thing that's
[21:03] (1263.12s)
going that's the high leverage activity
[21:05] (1265.76s)
um in terms of languages you know dude
[21:07] (1267.72s)
I've been I've been programming you know
[21:10] (1270.16s)
I I've done assembly in basic and Pascal
[21:13] (1273.12s)
and c and C+ like I learned c c in 1990
[21:17] (1277.32s)
right like languages
[21:20] (1280.48s)
are they come and they go like I I'm I
[21:23] (1283.68s)
consider myself a pearl expert like that
[21:26] (1286.80s)
that's no longer useful right and so
[21:30] (1290.72s)
like the language itself I think in a
[21:32] (1292.76s)
sense is immaterial I think this is
[21:34] (1294.76s)
where I think you know your your
[21:36] (1296.40s)
personal curiosity like it's totally
[21:38] (1298.56s)
fine to pick up something that um you
[21:42] (1302.00s)
know you have an affinity towards I
[21:43] (1303.84s)
think it's also totally fine to be like
[21:45] (1305.80s)
hey look at all of these jobs in Java I
[21:49] (1309.12s)
don't think Java is going away or at
[21:50] (1310.52s)
least jvm based languages and so I think
[21:53] (1313.08s)
it's totally okay to be like well I'm
[21:54] (1314.44s)
going to become an expert in Java that's
[21:56] (1316.92s)
not very sexy right now but that's a
[21:58] (1318.80s)
totally fine reason so however you get
[22:00] (1320.88s)
there my advice is just just go deep
[22:05] (1325.64s)
right people will be like okay cool well
[22:07] (1327.92s)
I'm going to do a Java tutorial and then
[22:12] (1332.04s)
I think an example of going deep is just
[22:13] (1333.80s)
being like Oh what's going on in this
[22:16] (1336.60s)
virtual machine what are virtual
[22:19] (1339.40s)
machines right um what does it what does
[22:23] (1343.64s)
it mean to tune a garbage collector and
[22:25] (1345.80s)
we can get into a debate about whether
[22:27] (1347.96s)
you're going to shoot yourself in the
[22:29] (1349.36s)
foot with you know trying to tweak your
[22:31] (1351.36s)
jav a garbage collection but if you are
[22:34] (1354.24s)
willing to pop the hood on that and then
[22:37] (1357.64s)
sort of like take a look at what's going
[22:39] (1359.48s)
on in there that's a sort of thing that
[22:41] (1361.80s)
nobody can stop you right like you can
[22:44] (1364.12s)
just you can just try to go deep Steve
[22:46] (1366.04s)
said to go deep so I'm going as deep as
[22:47] (1367.96s)
I can till you get to the ones and the
[22:49] (1369.48s)
zeros that are flowing through on that
[22:51] (1371.68s)
bus right like that is the thing that is
[22:55] (1375.52s)
rare last thing on this topic of um you
[22:58] (1378.64s)
know breaking in recently Zuck he had
[23:02] (1382.40s)
this uh quote he said on an interview
[23:06] (1386.00s)
that you know the capabilities of AI in
[23:09] (1389.28s)
this year will be able to produce
[23:12] (1392.16s)
mid-level engineer code um already do
[23:16] (1396.44s)
you think that Junior Engineers are are
[23:19] (1399.64s)
screwed then because of that I think
[23:22] (1402.52s)
it's super interesting maybe you should
[23:23] (1403.76s)
tell me you're the one that works at
[23:25] (1405.28s)
meta right but I'll I'll say this Folks
[23:28] (1408.20s)
at the CEO
[23:30] (1410.28s)
level you know they can they're very
[23:32] (1412.44s)
high performing their job is to look
[23:34] (1414.64s)
into the future but they tend to make
[23:37] (1417.64s)
predictions that
[23:39] (1419.76s)
are they're not exaggerated but they
[23:42] (1422.32s)
tend to they tend to make things like
[23:44] (1424.48s)
the timeline for which things happen
[23:46] (1426.64s)
they tend to undershoot that and then um
[23:49] (1429.96s)
they tend to overshoot in ability but
[23:51] (1431.72s)
the idea is that the vision exists and
[23:53] (1433.60s)
you work towards it the fact that he
[23:55] (1435.64s)
says he equivocates or at least he's
[23:58] (1438.00s)
hedging he he's saying mid-level
[23:59] (1439.44s)
Engineers later this year if that was
[24:02] (1442.36s)
actually already there he would have
[24:03] (1443.84s)
said senior staff level Engineers or 10x
[24:07] (1447.56s)
Engineers by tomorrow right the fact
[24:10] (1450.56s)
that he's pushing that out makes me
[24:12] (1452.32s)
think that the actual Implement like the
[24:15] (1455.04s)
rollout of a mid-level AI bot within
[24:18] (1458.84s)
meta is a little it's a little further
[24:21] (1461.68s)
away because his job is to move the
[24:23] (1463.12s)
goalposts just a little further than
[24:25] (1465.04s)
where we're at and so I so I have a
[24:28] (1468.52s)
little bit of Doubt there now if you
[24:30] (1470.40s)
want to talk about you know AI taking
[24:33] (1473.40s)
over some tasks yes absolutely they
[24:35] (1475.44s)
should you know I think when I was
[24:37] (1477.52s)
coming up as a mid and Senior oh code
[24:40] (1480.64s)
generation look at these annotations we
[24:42] (1482.80s)
can put lombok in our code you don't
[24:44] (1484.60s)
have to write Getters and Setters um
[24:47] (1487.92s)
there were there was you know I have a
[24:50] (1490.44s)
lot of familiarity with Java Java is a
[24:52] (1492.44s)
very verbose language Oh look The IDE
[24:55] (1495.36s)
can help me refactor some code the IDE
[24:57] (1497.72s)
can write some boiler plate for me yes
[25:00] (1500.28s)
absolutely we should be leveraging tools
[25:02] (1502.76s)
to make us more efficient but at this
[25:05] (1505.48s)
point I think of uh AI help as an
[25:08] (1508.88s)
amplifier if you just go through the
[25:10] (1510.60s)
different levels if you're a non- coder
[25:12] (1512.84s)
I think that you can go from zero to one
[25:14] (1514.52s)
very easily right so we're getting to
[25:17] (1517.20s)
the point with products like repet where
[25:28] (1528.28s)
Soup To Nuts from beginning to end um
[25:31] (1531.72s)
but I have my doubts that if the app
[25:33] (1533.92s)
doesn't work uh exactly the way that
[25:36] (1536.00s)
it's intended um or they're like hey
[25:38] (1538.72s)
scale this thing to meta scale like I I
[25:41] (1541.76s)
don't think an AI is going to be able to
[25:43] (1543.40s)
do that so I think very comfortably
[25:45] (1545.12s)
we'll be able to go from zero to one but
[25:47] (1547.84s)
I don't think that it will go from like
[25:50] (1550.84s)
one to many I think a 1x
[25:53] (1553.32s)
engineer is going to definitely turn
[25:55] (1555.64s)
into a 10x engineer today with the help
[25:57] (1557.92s)
of a I but do I see a zero to 10x
[26:01] (1561.92s)
engineer jump like later this year I I
[26:05] (1565.32s)
don't see it okay so then I guess moving
[26:08] (1568.20s)
into you being at Amazon you went you
[26:12] (1572.72s)
went into Amazon you converted to an SD
[26:15] (1575.48s)
and then you climbed all the way to
[26:17] (1577.72s)
principal uh at Amazon which I know that
[26:20] (1580.64s)
last jump is also very notoriously
[26:22] (1582.84s)
difficult so you went from sd1 to sd2
[26:26] (1586.16s)
sd3 and then principal
[26:28] (1588.96s)
um could you walk me through the the
[26:32] (1592.12s)
high level maybe just tell me you know
[26:34] (1594.80s)
what was the main thing that made the
[26:36] (1596.08s)
difference at each level and you know
[26:38] (1598.40s)
just like a very concise uh high level
[26:41] (1601.56s)
yeah yeah I was able to get you know to
[26:44] (1604.12s)
from support engineer sd1 2 and three
[26:46] (1606.80s)
around three three and a half years
[26:48] (1608.44s)
something like that you know at sd1 I
[26:51] (1611.04s)
think it's the real focus is on some
[26:54] (1614.12s)
amount of Independence so just
[26:56] (1616.76s)
understanding where you fit fit inside
[26:58] (1618.76s)
of the software development life cycle
[27:00] (1620.88s)
getting to the point where you can take
[27:02] (1622.72s)
tasks and see them all the way through
[27:05] (1625.56s)
so you've gained a little bit of trust
[27:07] (1627.12s)
there and you don't have to be
[27:09] (1629.76s)
handheld um I think that's the critical
[27:12] (1632.08s)
piece for um for junior level or
[27:15] (1635.40s)
sd1 um I think I just want to add a
[27:18] (1638.40s)
caveat there which is that doesn't mean
[27:20] (1640.76s)
you know everything and that doesn't
[27:22] (1642.56s)
mean that you don't ask questions it's
[27:25] (1645.32s)
just that you're much more comfortable
[27:28] (1648.24s)
asking a question if you're stuck you're
[27:30] (1650.00s)
much more comfortable surfacing an issue
[27:32] (1652.68s)
there's some folks that have this idea
[27:34] (1654.56s)
that at sd1 or or at any level that you
[27:38] (1658.16s)
are completely self-contained so
[27:39] (1659.72s)
self-contained is not the same thing as
[27:42] (1662.00s)
uh being independent well one of the
[27:43] (1663.76s)
common words that he for that first
[27:45] (1665.76s)
promo is like doing things independently
[27:48] (1668.56s)
without guidance some people interpret
[27:51] (1671.04s)
that as I'm not going to ask for help
[27:53] (1673.28s)
and I got to do it all myself which is
[27:54] (1674.92s)
obviously not right but you need to know
[27:57] (1677.36s)
how to unblock yourself so makes sense
[28:00] (1680.32s)
and it's also Insidious in the sense
[28:02] (1682.20s)
that it's it's not just not right so
[28:04] (1684.44s)
that it will hold you back for longer
[28:06] (1686.72s)
but it actually turns into a performance
[28:08] (1688.52s)
issue if you're hiding the fact that
[28:11] (1691.40s)
you're you know not able to perform or
[28:13] (1693.64s)
you don't know anything if you're hiding
[28:15] (1695.60s)
progress because you're unsure about
[28:18] (1698.28s)
yourself and you sort of beat yourself
[28:20] (1700.20s)
up that you should know this thing and
[28:23] (1703.68s)
you know suppose you have a task and it
[28:25] (1705.16s)
should take two weeks and then you're
[28:27] (1707.48s)
like hey everything everything's on
[28:28] (1708.48s)
track everything's on track and then the
[28:29] (1709.96s)
Thursday before you're like I've been
[28:32] (1712.48s)
blocked this whole time that's a
[28:34] (1714.72s)
performance issue right and so um you
[28:38] (1718.92s)
know there's a there's a difference
[28:40] (1720.04s)
between oh it's just going to take you
[28:41] (1721.28s)
longer to get there to something that's
[28:43] (1723.52s)
actually detrial to get to the next
[28:45] (1725.72s)
level um I think for
[28:48] (1728.68s)
sd2 the the word that pops into my head
[28:51] (1731.44s)
the most is ownership and so you know
[28:55] (1735.20s)
you are an active participant in s
[28:58] (1738.28s)
development life cycle you're much more
[29:00] (1740.04s)
of a steward of say your team's
[29:03] (1743.28s)
codebase and I I just sort of think
[29:06] (1746.52s)
about it like you know hey you're
[29:08] (1748.84s)
littering don't Litter here like and
[29:11] (1751.24s)
then maybe picking up some of the trash
[29:14] (1754.08s)
um that trash being Tech Deb not actual
[29:17] (1757.48s)
trash in the code you know being able to
[29:20] (1760.20s)
get you know you're now you're able to
[29:21] (1761.88s)
leverage this Independence and to start
[29:25] (1765.24s)
to make a contribution to the team's
[29:27] (1767.08s)
code base that's a little bit larger
[29:31] (1771.20s)
right so basically every step up with
[29:34] (1774.08s)
sde is kind of an argument that you
[29:37] (1777.28s)
deserve more scope and so the the scope
[29:40] (1780.56s)
of an sd2 or mid-level engineer
[29:44] (1784.60s)
is you know at the team level right you
[29:48] (1788.64s)
understand your team's code base you
[29:50] (1790.52s)
know you understand its weaknesses its
[29:52] (1792.96s)
strengths you can start to you know make
[29:55] (1795.76s)
suggestions about where it's going to be
[29:58] (1798.04s)
at Amazon we have an operational culture
[30:00] (1800.88s)
and so you know you you're on call you
[30:03] (1803.76s)
know how things break you might have
[30:06] (1806.00s)
some ideas about how to fix some of
[30:08] (1808.08s)
these things and so I you know it's it's
[30:10] (1810.16s)
a very you know meat and potato sort of
[30:12] (1812.84s)
role and you know this this is what you
[30:15] (1815.56s)
need to go from two to three yeah I'm
[30:18] (1818.32s)
just talking about two oh this is table
[30:20] (1820.60s)
Stakes for yeah I think it's
[30:22] (1822.16s)
expectations for at least this is my
[30:23] (1823.92s)
conception of it right M and there's an
[30:26] (1826.76s)
eternal debate at Amazon about whether
[30:29] (1829.40s)
the sd2 or mid-level role is a terminal
[30:33] (1833.12s)
position or not can you retire as an sd2
[30:37] (1837.08s)
the level granularity at Amazon is such
[30:39] (1839.52s)
that I think S2 is a very wide band so I
[30:43] (1843.00s)
think at the upper levels of S2 a lot of
[30:45] (1845.64s)
those folks are senior engineers at
[30:47] (1847.12s)
other companies um even within big Tech
[30:49] (1849.84s)
not just you know oh they a senior
[30:51] (1851.80s)
engineer um at a a smaller company or a
[30:54] (1854.76s)
startup I think they're you're you're
[30:56] (1856.64s)
pretty strong um as an sd2 at Amazon
[30:59] (1859.60s)
just because the granularity for levels
[31:01] (1861.84s)
at Amazon is so
[31:04] (1864.08s)
terrible and um so I I tend to to bias
[31:07] (1867.92s)
towards like yeah actually at
[31:09] (1869.88s)
sd2 you're uh that could be a terminal
[31:13] (1873.12s)
level right now I don't advise that
[31:16] (1876.92s)
people think of it as a terminal level
[31:19] (1879.32s)
but it's just a reflection of you know
[31:21] (1881.52s)
how much scope I think an sd2 at Amazon
[31:24] (1884.04s)
can can actually deliver against so
[31:26] (1886.72s)
there isn't an up and out policy like if
[31:29] (1889.04s)
you were a manager at Amazon and you had
[31:32] (1892.08s)
someone that says Hey I want to just
[31:33] (1893.92s)
stay at at you know
[31:36] (1896.32s)
sd2 um is that okay or would they get
[31:39] (1899.92s)
fired in Amazon's culture eventually so
[31:43] (1903.20s)
and it might have changed you know it's
[31:44] (1904.48s)
been it's been close to a year since
[31:45] (1905.84s)
I've been gone so I say we a lot as
[31:48] (1908.32s)
though I still work there I'm still
[31:49] (1909.76s)
trying to train myself I don't work at
[31:51] (1911.88s)
Amazon yeah um so uh it's definitely up
[31:56] (1916.80s)
and out at sd1 yeah and so if you've
[32:00] (1920.68s)
been at sd1 for more than 2 years you
[32:03] (1923.44s)
know it's it's kind of like H this is is
[32:05] (1925.88s)
there formal formal like you know 24
[32:09] (1929.00s)
months and then they start managing out
[32:11] (1931.16s)
or it's a feel thing I believe it's a
[32:14] (1934.92s)
it's a strong it's a progressively
[32:17] (1937.08s)
stronger Guidance the longer that you've
[32:18] (1938.84s)
been there but it's not a 20 36 months
[32:21] (1941.68s)
and then you're out sort of thing yeah
[32:23] (1943.52s)
yeah um I think for sd2 it's a much more
[32:26] (1946.12s)
interesting conversation I think that
[32:28] (1948.08s)
will depend on
[32:29] (1949.52s)
the where the upper management you know
[32:32] (1952.84s)
for that particular individual where
[32:34] (1954.68s)
they land on whether S2 is a terminal
[32:36] (1956.88s)
level or not MH um and so if you happen
[32:40] (1960.80s)
to get a manager that's basically like
[32:43] (1963.84s)
no you've been there for 10 years you
[32:46] (1966.92s)
should be a three um if you happen to to
[32:50] (1970.84s)
get that person um then I I think it
[32:53] (1973.24s)
might be might be bad news for you and
[32:55] (1975.40s)
you know with the recent news about meta
[32:57] (1977.40s)
a lot of people are likening or they're
[33:00] (1980.68s)
worried that meta would turn into Amazon
[33:03] (1983.08s)
because Amazon's famous for a culture of
[33:06] (1986.88s)
intense performance and cutting people
[33:09] (1989.40s)
who aren't making it um from yeah from
[33:12] (1992.80s)
your time at Amazon I'm kind of curious
[33:14] (1994.56s)
maybe you can give us the the the juicy
[33:16] (1996.92s)
details like how many people are
[33:19] (1999.40s)
expected to be cut in Amazon typically
[33:22] (2002.24s)
like cuz you were there for so many
[33:23] (2003.72s)
years is it you know some percentage per
[33:26] (2006.52s)
year or is it a to the manager's
[33:28] (2008.52s)
discretion how does that work what I can
[33:30] (2010.88s)
say so I won't give an exact number uh
[33:33] (2013.32s)
what I can say is that guidance you know
[33:37] (2017.00s)
suppose it was five or 6% you know for
[33:40] (2020.28s)
an organization that number used to be a
[33:43] (2023.88s)
recommendation it would it would be kind
[33:45] (2025.80s)
of a soft one hey we need to manage out
[33:47] (2027.80s)
x% of folks over the course of a year um
[33:51] (2031.96s)
I think in the past couple of years that
[33:53] (2033.64s)
has turned into a much
[33:55] (2035.68s)
more um it's turned from guidance to
[33:59] (2039.88s)
much more of a mandate I think coupled
[34:02] (2042.00s)
with the fact that up until recently
[34:04] (2044.20s)
they weren't doing backfills for folks
[34:07] (2047.08s)
there was this sort of like hey keep on
[34:08] (2048.92s)
running cuz this thing's chasing you
[34:11] (2051.20s)
right from the back yeah I don't think
[34:13] (2053.16s)
that was necessarily healthy yeah and
[34:15] (2055.92s)
you know if I were to be quite honest I
[34:18] (2058.20s)
I consider myself a high performer and
[34:20] (2060.28s)
so if you're a high performer you don't
[34:22] (2062.92s)
have to think about that stuff and you
[34:25] (2065.48s)
know as much as I'd like to be
[34:26] (2066.72s)
empathetic about about it and you know
[34:28] (2068.72s)
I've been around some of these decisions
[34:32] (2072.08s)
and meetings and stuff like that um if
[34:35] (2075.32s)
you're down it's I it's hard for me to
[34:37] (2077.84s)
to speak about what it's actually like
[34:40] (2080.20s)
to to to feel like your job may be at
[34:42] (2082.56s)
stake right and so you know I I think a
[34:46] (2086.24s)
lot of what I would tell you is is just
[34:48] (2088.40s)
kind of cold and numbers based there are
[34:52] (2092.08s)
real people here right if you you know
[34:54] (2094.92s)
getting fired from a job is
[34:57] (2097.76s)
you know that's a that's a very that's a
[34:59] (2099.96s)
highly emotional psychological thing
[35:02] (2102.20s)
right so I just want to make sure that I
[35:04] (2104.48s)
I I bring that up maybe I'll say this
[35:07] (2107.32s)
and this is this is sort of how I I
[35:09] (2109.32s)
guided other folks and other managers
[35:11] (2111.12s)
when they're asking me hey how do I how
[35:12] (2112.84s)
do I think about this the way to think
[35:14] (2114.84s)
about it
[35:16] (2116.32s)
is 5% suppose that was the number right
[35:20] (2120.48s)
so that's one in 20
[35:23] (2123.04s)
people right and so just just take a
[35:26] (2126.12s)
population of 20 people
[35:28] (2128.60s)
and I think there's a distribution there
[35:31] (2131.84s)
and the people on the left hand side of
[35:35] (2135.00s)
distribution in regular years where
[35:37] (2137.28s)
there are backfills I think
[35:40] (2140.36s)
that I think that they're not they're
[35:42] (2142.88s)
not having a good time with Amazon's
[35:44] (2144.88s)
culture right they're not thriving
[35:46] (2146.56s)
almost by definition right we're just
[35:48] (2148.48s)
going to say hey everything on the
[35:49] (2149.72s)
left-and side is um people aren't aren't
[35:52] (2152.32s)
having a great time and so I think it's
[35:54] (2154.84s)
almost a relief that there's a way to
[35:56] (2156.72s)
sort of like leave a situation like that
[35:58] (2158.56s)
what's what's the
[36:00] (2160.80s)
alternative they
[36:02] (2162.64s)
stay and somebody that's not having a
[36:05] (2165.44s)
great time in Amazon's culture which you
[36:08] (2168.56s)
know it's it's it doesn't have a great
[36:11] (2171.48s)
reputation part of me is like oh that's
[36:13] (2173.68s)
kind of nice that you know um it's kind
[36:16] (2176.44s)
of a blessing in
[36:17] (2177.76s)
disguise right that we would move them
[36:19] (2179.76s)
out now without backfills that's where I
[36:23] (2183.24s)
start to get a little
[36:25] (2185.24s)
uncomfortable because in BAS basically
[36:27] (2187.92s)
any other year that they would be at
[36:30] (2190.24s)
Amazon they would be totally fine and I
[36:33] (2193.20s)
think even people you know that are sort
[36:35] (2195.72s)
of left shifted but in that main part of
[36:37] (2197.64s)
the distribution I think they're great
[36:40] (2200.80s)
um so that's where I start to go like
[36:42] (2202.92s)
this is not this is not something that
[36:45] (2205.80s)
um I really agree with you're saying
[36:47] (2207.88s)
because it starts to cannibalize people
[36:49] (2209.88s)
who are they're doing good but now we're
[36:53] (2213.96s)
forced to yeah stack ring people that
[36:57] (2217.28s)
were good so suppose you had a 6% amount
[37:02] (2222.44s)
of folks that were let go and that was a
[37:04] (2224.88s)
hard thing and so you did all of the
[37:07] (2227.32s)
very tough work to identify those folks
[37:11] (2231.64s)
and have them move out and now you need
[37:13] (2233.80s)
to do 6% of those folks that remain and
[37:18] (2238.48s)
then you need to do 6% of those folks
[37:21] (2241.08s)
that remain and so I it's not 18% you
[37:24] (2244.32s)
know I don't I can't do that math but
[37:26] (2246.60s)
now we're starting to talk talk about
[37:27] (2247.96s)
people that are very close to the mid
[37:31] (2251.72s)
point they're operating at a high level
[37:33] (2253.88s)
and in any other year they'd be totally
[37:36] (2256.28s)
fine um but now they're not and so you
[37:39] (2259.92s)
know I I I have colleagues that were let
[37:42] (2262.40s)
go recently and he just kind of blows my
[37:45] (2265.00s)
mind that they would be they would be
[37:47] (2267.40s)
let go and so I think the most amount of
[37:50] (2270.20s)
impact will come from folks that um say
[37:54] (2274.20s)
middle
[37:55] (2275.08s)
management where okay okay well there's
[37:57] (2277.96s)
four middle managers within the subor
[37:59] (2279.96s)
right here the bottom 6% like 6% doesn't
[38:03] (2283.24s)
even make sense when you're talking
[38:04] (2284.24s)
about four people or eight people right
[38:07] (2287.60s)
and so I I was very surprised by some of
[38:09] (2289.68s)
the people that were let go recently so
[38:11] (2291.84s)
you said when in the past I guess as a
[38:14] (2294.80s)
principal engineer once you get higher
[38:16] (2296.36s)
up you were privy to some of the
[38:19] (2299.52s)
conversations where people are being
[38:21] (2301.56s)
discussed if they're getting managed out
[38:23] (2303.76s)
what what happens in those conversations
[38:25] (2305.56s)
how does a high level IC like you
[38:28] (2308.08s)
participate yeah you start getting
[38:29] (2309.76s)
pulled in when you're a senior engineer
[38:31] (2311.64s)
and you definitely get pulled in when
[38:33] (2313.56s)
you're L7 or above those meetings are
[38:36] (2316.32s)
terrible right um they're like three
[38:39] (2319.88s)
days long and you're locked up in a room
[38:43] (2323.44s)
and you're just sitting there talking
[38:44] (2324.80s)
about people and people you start to
[38:46] (2326.24s)
lose the humanity you just start to
[38:47] (2327.84s)
think of them in terms of you know the
[38:50] (2330.92s)
measurables right and and the feedback
[38:53] (2333.04s)
from other folks um I won't go into the
[38:56] (2336.60s)
specific process
[38:58] (2338.56s)
um but what I will say
[39:01] (2341.44s)
is it's not a linear
[39:04] (2344.72s)
algorithm um I think in a in a perfect
[39:07] (2347.48s)
world you would just go through
[39:08] (2348.52s)
everybody in the org and then you would
[39:11] (2351.12s)
you would have equal amount of time to
[39:13] (2353.16s)
talk about them and their strengths and
[39:15] (2355.96s)
weaknesses typically you just talk about
[39:18] (2358.08s)
the edges um and that's not a reflection
[39:21] (2361.12s)
of you know the people that are making
[39:22] (2362.96s)
the decisions and whether that's poor or
[39:24] (2364.72s)
not it's just it's the math there are
[39:26] (2366.60s)
just too many people
[39:28] (2368.16s)
and so the the conversation tends to go
[39:30] (2370.16s)
to either side and
[39:34] (2374.08s)
um yeah it's it's just it's not my
[39:37] (2377.20s)
favorite time of year yeah no definitely
[39:39] (2379.20s)
it sounds intense especially if they cut
[39:41] (2381.48s)
out some low performers and then the
[39:43] (2383.88s)
next iteration is like people where you
[39:46] (2386.24s)
objectively look at them go oh they're
[39:48] (2388.20s)
yeah they're solid but you need to Fork
[39:50] (2390.96s)
over some more people now if you want to
[39:52] (2392.32s)
talk about meta I think meta is on a
[39:54] (2394.48s)
hiring spree if I'm if I'm not mistaken
[39:57] (2397.56s)
think you know if uh if your fearless
[40:00] (2400.40s)
leader is saying Hey low performers are
[40:02] (2402.40s)
leaving and it's say at a 5% number I
[40:05] (2405.16s)
think that's the number that's been
[40:06] (2406.20s)
floated around
[40:08] (2408.52s)
um I I just have a sense that those
[40:11] (2411.32s)
folks are probably not having a good
[40:14] (2414.04s)
time at meta right
[40:15] (2415.48s)
now right um do that everybody no but I
[40:19] (2419.04s)
would say the the vast majority of folks
[40:20] (2420.92s)
there um if you're talking about one in
[40:23] (2423.00s)
20 people 20 random people at meta there
[40:25] (2425.48s)
there's probably somebody that's
[40:26] (2426.40s)
struggling especially when you start
[40:27] (2427.80s)
multiplying that out across a large
[40:29] (2429.80s)
population so because the inflow is much
[40:32] (2432.84s)
larger than the outflow I wouldn't be
[40:34] (2434.80s)
too worried sounds like across big Tech
[40:38] (2438.40s)
there's this increased intensity and uh
[40:42] (2442.72s)
historically Amazon has been the one
[40:45] (2445.68s)
that's always had this level of
[40:47] (2447.88s)
increased intensity or at least this
[40:49] (2449.68s)
this process of like let's manage out
[40:51] (2451.88s)
the low performers quickly and let's
[40:53] (2453.76s)
let's just factor that into our
[40:55] (2455.20s)
processes given that you've been in a
[40:57] (2457.36s)
lot of those performance conversations
[40:59] (2459.40s)
do you have any advice for the people
[41:02] (2462.64s)
who are on the border where you know if
[41:05] (2465.08s)
this is a how we're going to be
[41:06] (2466.76s)
operating in the future people who are
[41:09] (2469.40s)
kind of just meeting expectations what
[41:11] (2471.88s)
is the things that protects you uh in
[41:15] (2475.68s)
conversations um that they could do for
[41:18] (2478.28s)
this coming year to to be safe I think
[41:22] (2482.04s)
it's just that if you meet expectations
[41:25] (2485.16s)
if you solidly meet expectations if
[41:27] (2487.68s)
everybody across the organization met
[41:30] (2490.48s)
expectations I don't think you have a 5%
[41:33] (2493.28s)
stack ranking like removing folks from
[41:37] (2497.12s)
system right and so you know I I don't
[41:40] (2500.76s)
think that people that are and I bristle
[41:44] (2504.16s)
a bit at the low performer
[41:46] (2506.72s)
label I just I just again I think of it
[41:49] (2509.68s)
as like the culture is not working out
[41:52] (2512.16s)
there is a mismatch between me and the
[41:55] (2515.32s)
ambient environment at any particular
[41:57] (2517.44s)
company I don't think it's a low perform
[42:00] (2520.00s)
you know how hard it is to get a an
[42:01] (2521.92s)
offer at
[42:03] (2523.08s)
meta like you are not a um low performer
[42:07] (2527.68s)
yeah right you you have to be driven
[42:09] (2529.80s)
there is a song and dance that you need
[42:11] (2531.68s)
to that you need to perform under
[42:14] (2534.68s)
pressure in front of somebody like you
[42:17] (2537.08s)
go and take a Le code hard and you have
[42:19] (2539.48s)
to go look at some you know you have to
[42:21] (2541.32s)
coat it in front of some SD that's like
[42:23] (2543.08s)
got a bad expression on their face like
[42:24] (2544.68s)
you are more than qualified your
[42:27] (2547.64s)
smart as hell and now you're working at
[42:31] (2551.28s)
a company
[42:32] (2552.76s)
and maybe you thought it was something
[42:35] (2555.92s)
different than what it actually was what
[42:38] (2558.16s)
I would say is I don't think these low
[42:40] (2560.24s)
performers these so-called low
[42:41] (2561.52s)
performers they should try to become
[42:44] (2564.52s)
performers right I
[42:46] (2566.76s)
think by focusing on trying to be a high
[42:49] (2569.32s)
performer or focusing on trying to get
[42:50] (2570.88s)
to the next
[42:52] (2572.12s)
level there's usually a reason why
[42:54] (2574.76s)
you're considered you're labeled that
[42:56] (2576.56s)
way and so try to figure out what is
[42:59] (2579.08s)
that Dimension that you're being judged
[43:01] (2581.24s)
and measured against that's that's
[43:03] (2583.56s)
holding you back from meeting
[43:05] (2585.20s)
expectations so I think you need to
[43:06] (2586.96s)
crawl before you walk before you run
[43:09] (2589.16s)
what is that thing that they're judging
[43:11] (2591.00s)
you on and then I think you should be
[43:12] (2592.88s)
real with your manager and you should
[43:14] (2594.48s)
say hey I just wanted to check in am I
[43:16] (2596.36s)
meeting expectations and if I'm
[43:18] (2598.92s)
not then like let's let's do a
[43:21] (2601.76s)
preemptive plan right so pip stands for
[43:24] (2604.56s)
performance Improvement plan can you do
[43:26] (2606.44s)
a pre tip can you can you proactively
[43:29] (2609.68s)
put together a plan to get you to a spot
[43:33] (2613.64s)
where you're going to be safe that's
[43:35] (2615.44s)
what I would that's what I would
[43:36] (2616.76s)
recommend just be proactive about growth
[43:39] (2619.32s)
to get back to the median asking your
[43:41] (2621.56s)
manager for a proactive pip is I would
[43:44] (2624.08s)
maybe not use those words that's
[43:46] (2626.36s)
hilarious um okay so it sounds like I
[43:49] (2629.84s)
mean obviously meet expectations work
[43:51] (2631.76s)
with your manager well I don't think
[43:53] (2633.20s)
it's obvious I don't I actually if you
[43:56] (2636.24s)
if you took a Sur
[43:58] (2638.08s)
of software developers and you asked
[44:00] (2640.32s)
them have you used these words with your
[44:03] (2643.32s)
manager suppose you're my manager yeah
[44:05] (2645.80s)
hey Ryan um you know I just started here
[44:08] (2648.96s)
at meta um I just wanted to get a sense
[44:11] (2651.60s)
of what my your expectations of me what
[44:14] (2654.80s)
are those right have they have you
[44:16] (2656.60s)
explicitly asked about expectations with
[44:19] (2659.04s)
your manager I think like 25% of of
[44:22] (2662.88s)
people have actually done that I think
[44:24] (2664.96s)
most people are trying to guess
[44:27] (2667.56s)
at what those expectations are and so I
[44:30] (2670.00s)
think that would be my first bit of
[44:31] (2671.96s)
advice is just like straight up ask what
[44:34] (2674.84s)
expectations are and then ask if you're
[44:37] (2677.44s)
meeting them or not right that would go
[44:39] (2679.44s)
so far definitely yeah that makes a lot
[44:42] (2682.52s)
of sense I think most people all right I
[44:45] (2685.32s)
don't know if it's um being shy or or
[44:48] (2688.40s)
what but feel like most ic's don't
[44:50] (2690.84s)
directly talk to their manager and say I
[44:53] (2693.60s)
want this or you know how do I meet
[44:55] (2695.76s)
expectations how do I get promoted
[44:57] (2697.84s)
kind of just do the work and do it well
[45:00] (2700.64s)
and hope that things go go well well
[45:03] (2703.04s)
obviously there's going to be an answer
[45:04] (2704.84s)
yeah and so it's like hey Ryan Ryan
[45:07] (2707.04s)
what's your expectation of me and am I
[45:08] (2708.68s)
meeting it it's like no Steve you are
[45:11] (2711.28s)
not meeting expectations and um it's
[45:14] (2714.28s)
starting to become a problem even that
[45:16] (2716.36s)
is a better situation than not knowing
[45:18] (2718.96s)
oh yeah for sure right and so um there's
[45:21] (2721.76s)
a mutual friend of ours Rahul Pandy from
[45:24] (2724.00s)
Tero yeah yeah I stole this saying from
[45:26] (2726.12s)
him and I don't know if he stole it from
[45:28] (2728.80s)
somebody else that worked at meta but
[45:31] (2731.44s)
it's basically like um bad news that's
[45:35] (2735.48s)
delivered early is just
[45:38] (2738.96s)
news right right bad news that's
[45:42] (2742.04s)
delivered late is terrible news yeah so
[45:45] (2745.20s)
the the you know so if you are asking
[45:47] (2747.40s)
about expectations and it's early in
[45:49] (2749.28s)
your career it's early in cycle you know
[45:52] (2752.00s)
and they're like hey this is a problem
[45:54] (2754.40s)
well now you've surfaced the issue
[45:57] (2757.48s)
and you have a like you have a Fighting
[45:59] (2759.40s)
Chance of actually addressing it if you
[46:03] (2763.20s)
are like hey what's up with my
[46:04] (2764.72s)
expectations oh it's really bad and it's
[46:07] (2767.72s)
December right so the month's preceding
[46:10] (2770.56s)
performance review you're not in a good
[46:12] (2772.56s)
spot yeah right and so I I just
[46:14] (2774.88s)
encourage people to deliver or try to
[46:18] (2778.68s)
find as much bad news as early as
[46:21] (2781.76s)
possible for your principal promo I
[46:24] (2784.88s)
think a lot of it comes down to
[46:27] (2787.60s)
having the opportunity and then
[46:29] (2789.36s)
delivering but I it's it's interesting
[46:31] (2791.56s)
to dig into how you got the opportunity
[46:34] (2794.44s)
to even deliver on principal scope so
[46:37] (2797.92s)
kind of curious can you tell the story
[46:39] (2799.20s)
about how you got that so I was reorg
[46:43] (2803.80s)
back into Prime video and so the
[46:45] (2805.68s)
previous team to that was a team that I
[46:48] (2808.04s)
cared deeply about it was called Amazon
[46:50] (2810.12s)
tickets we sold tickets like Ticket
[46:52] (2812.68s)
Master Built a bunch of really awesome
[46:55] (2815.28s)
Tech um a ton of
[46:58] (2818.20s)
patents um I love music I love going to
[47:00] (2820.80s)
live shows and so I was like oh this is
[47:03] (2823.36s)
great they spun that business down and
[47:06] (2826.76s)
they reorg that whole team into Prime
[47:09] (2829.04s)
videoo and
[47:12] (2832.20s)
um basically the 30 or 40 devs that were
[47:16] (2836.60s)
in that
[47:18] (2838.36s)
organization they kind of just scattered
[47:20] (2840.48s)
into the wind right and um I was I had a
[47:26] (2846.12s)
bad taste in my MTH and so I was and I
[47:28] (2848.68s)
didn't want to talk to any of their team
[47:30] (2850.56s)
so I was basically like okay well what
[47:32] (2852.60s)
do I have here what what they had was a
[47:35] (2855.48s)
a team that was focused on delivering
[47:38] (2858.40s)
live sports on the Prime video
[47:41] (2861.48s)
platform and uh I'm a big sports fan as
[47:44] (2864.96s)
well and so I was like okay well this is
[47:47] (2867.00s)
interesting and then I looked around I
[47:48] (2868.48s)
was like oh there's a bunch of principal
[47:49] (2869.76s)
Engineers here okay so cool I can I can
[47:52] (2872.52s)
learn about what's going on there and um
[47:56] (2876.28s)
there is this really big need that was
[47:58] (2878.64s)
there um just the the catalog work
[48:02] (2882.64s)
and you know I I just made a decision
[48:05] (2885.16s)
about whether I wanted to pick it up or
[48:06] (2886.64s)
not right um and I decided to it was
[48:12] (2892.96s)
just in reality much larger than any
[48:16] (2896.44s)
other project that I had ever done I
[48:18] (2898.60s)
wouldn't say it would it landed on my
[48:19] (2899.92s)
lap I it was a combination of staying
[48:22] (2902.40s)
and then sort of saying okay well if I
[48:23] (2903.84s)
stay I need to do this I see so it's
[48:25] (2905.76s)
some scope that
[48:27] (2907.32s)
principal Engineers were aware of needed
[48:30] (2910.28s)
to be done was particularly difficult it
[48:32] (2912.88s)
was it was just sitting there for
[48:34] (2914.60s)
someone to take it on yeah you took the
[48:37] (2917.60s)
initiative say all right I'm going to
[48:38] (2918.76s)
take it and stay on this team and then
[48:40] (2920.72s)
you delivered on it yeah it's you know
[48:42] (2922.92s)
the way that the principles were
[48:44] (2924.96s)
organized back then it's changed now but
[48:47] (2927.64s)
essentially the principles were assigned
[48:49] (2929.48s)
to different areas say like playback or
[48:51] (2931.96s)
clients or catalog or wherever they were
[48:55] (2935.28s)
and the work that needs to be done
[48:58] (2938.56s)
was in the gaps between those or so it
[49:01] (2941.92s)
had to be an end to-end
[49:03] (2943.32s)
solution and so even though the the the
[49:06] (2946.00s)
thrust the main thrust of the work was
[49:07] (2947.56s)
in these sort of centralized services
[49:11] (2951.20s)
so that's why you know nobody none of
[49:15] (2955.08s)
the other principles had done it because
[49:16] (2956.44s)
they were kind of they were doing all of
[49:18] (2958.76s)
this other stuff that was necessary for
[49:20] (2960.32s)
us to deliver okay so that that makes a
[49:22] (2962.56s)
lot sense too cuz I imagine also if you
[49:25] (2965.20s)
delivered on that so each principal to
[49:27] (2967.68s)
each um I guess Central vertical and
[49:31] (2971.08s)
you're delivering some glue work um if
[49:33] (2973.76s)
you did that job really well not only is
[49:35] (2975.72s)
the scope huge but also these principal
[49:39] (2979.00s)
Engineers are you know they're going to
[49:42] (2982.20s)
have context on your work and speak to
[49:44] (2984.44s)
your packet and be champions for you so
[49:47] (2987.40s)
I'm sure that was helpful too A lot of
[49:49] (2989.04s)
people they say getting to principle
[49:51] (2991.36s)
Amazon is so difficult people don't even
[49:53] (2993.84s)
recommend doing it you know there's all
[49:55] (2995.72s)
this job hop advice
[49:57] (2997.68s)
so what is the thing that usually blocks
[50:00] (3000.52s)
people from going from senior to
[50:02] (3002.48s)
principal at Amazon there's a lot of
[50:04] (3004.28s)
reasons um I
[50:06] (3006.52s)
think just to back up a little bit I am
[50:09] (3009.64s)
of the impression that Amazon just
[50:11] (3011.60s)
skipped a level so they should just
[50:14] (3014.84s)
insert a staff level uh staff
[50:18] (3018.64s)
level they could do that right now
[50:21] (3021.40s)
basically they would say okay well
[50:22] (3022.72s)
everybody that's principal will'll call
[50:24] (3024.00s)
you principls shove staff in there and
[50:27] (3027.08s)
then just say hey for you know for the
[50:29] (3029.64s)
really high performing S3s we're just
[50:32] (3032.24s)
going to move you there preemptively and
[50:35] (3035.68s)
that would be so great but I think the
[50:37] (3037.88s)
big problem is that you're essentially
[50:39] (3039.48s)
jumping two levels uh for that
[50:42] (3042.16s)
particular promotion and
[50:45] (3045.12s)
so the the big thing that's holding them
[50:47] (3047.60s)
back is that you need to jump two levels
[50:49] (3049.88s)
right so there's there's basically
[50:51] (3051.20s)
double the amount of criteria to get to
[50:53] (3053.88s)
that next level and I think it's kind of
[50:57] (3057.52s)
impossible to um exhibit all of the
[51:01] (3061.92s)
moving to criteria for principal in a
[51:04] (3064.20s)
year so if you think you're ready hey
[51:06] (3066.68s)
I'm a senior engineer I've been doing
[51:08] (3068.08s)
really well I'm going to make a big
[51:10] (3070.16s)
push I think it's like it's it's because
[51:13] (3073.96s)
the job is so different because now
[51:15] (3075.80s)
you're influencing multiple
[51:18] (3078.20s)
teams it's very difficult to find the
[51:20] (3080.88s)
opportunity and then also be able to
[51:23] (3083.16s)
perform at a level where people would
[51:25] (3085.96s)
consider you the next level 12 18 months
[51:29] (3089.56s)
and so what ends up happening for you
[51:32] (3092.32s)
know the the failure mode that I see the
[51:34] (3094.08s)
most is they think they're ready they
[51:37] (3097.48s)
will make a push they will get a
[51:41] (3101.32s)
rejection and they will get some amount
[51:44] (3104.96s)
feedback
[51:46] (3106.52s)
and then what they'll do is they'll you
[51:49] (3109.56s)
know they'll just go back to their
[51:51] (3111.52s)
strengths and then they'll continue to
[51:53] (3113.64s)
work on their they might like address
[51:55] (3115.48s)
one or two of these pieces of feedback
[51:58] (3118.28s)
but it just takes so long to um to close
[52:01] (3121.64s)
one of these
[52:02] (3122.60s)
cycles and so a lot of people give up I
[52:06] (3126.16s)
I know so many folks that you know went
[52:08] (3128.56s)
to meta and they're they're thri or they
[52:10] (3130.16s)
went to Google absolutely thriving right
[52:12] (3132.60s)
now senior staff
[52:15] (3135.56s)
E8 you know principal at Google which is
[52:18] (3138.88s)
you know two levels past staff and uh in
[52:21] (3141.60s)
and one level above senior staff they're
[52:23] (3143.60s)
doing awesome they just couldn't make
[52:26] (3146.36s)
that jump right from sd3 to principal
[52:30] (3150.00s)
and so it it turns into this thing where
[52:31] (3151.88s)
I think there's this 2-year sliding
[52:33] (3153.92s)
window of where you kind of have to pack
[52:37] (3157.60s)
in basically a new job you have to
[52:40] (3160.84s)
basically be doing two jobs because
[52:42] (3162.28s)
there's a there's an anti- pattern where
[52:45] (3165.16s)
you just stop doing all the things that
[52:46] (3166.92s)
you need to do for sd3 and you just
[52:49] (3169.64s)
focus on the principal level stuff and
[52:52] (3172.56s)
then performance review time comes
[52:54] (3174.24s)
around and then they're like uh you're
[52:56] (3176.84s)
actually low performance at sd3 even
[52:59] (3179.60s)
though you're a high performer doing
[53:01] (3181.72s)
principal level things H how's that
[53:03] (3183.84s)
possible like what are those two jobs
[53:05] (3185.36s)
and how are they so different well the
[53:06] (3186.96s)
reason it's possible is because um
[53:09] (3189.32s)
performance and promotion are decoupled
[53:11] (3191.64s)
two different processes what's the
[53:13] (3193.92s)
performance process at Amazon
[53:15] (3195.56s)
performance process is you know uh
[53:17] (3197.36s)
yearly and then you know every six
[53:19] (3199.36s)
months there's a smaller version of that
[53:21] (3201.32s)
and then the promotion process is
[53:23] (3203.68s)
depends on the level so it could be
[53:25] (3205.04s)
quarterly or it could be every six
[53:26] (3206.76s)
months so they might line up generally
[53:29] (3209.92s)
but the idea is that there's not a
[53:31] (3211.28s)
dependency on one with the other and so
[53:35] (3215.20s)
if you're trying to make a big push for
[53:36] (3216.88s)
a promotion and you're doing all this
[53:38] (3218.84s)
principal stuff and then you know then
[53:41] (3221.28s)
it's so here's here's a big example
[53:43] (3223.36s)
senior Engineers need to code right
[53:45] (3225.80s)
that's a that's a very important thing
[53:47] (3227.64s)
that they
[53:48] (3228.44s)
do and um principles are also expected
[53:52] (3232.12s)
to code but not as large of a
[53:54] (3234.00s)
contribution generally like Direct
[53:56] (3236.00s)
contribu ution is not rare but it just
[54:00] (3240.04s)
that needs to be balanced with their
[54:01] (3241.72s)
other obligations so they might be a
[54:04] (3244.04s)
sponsor of a project or they might be
[54:06] (3246.00s)
acting as a back stop or they might be
[54:08] (3248.36s)
acting as a catalyst or an evangelist
[54:10] (3250.40s)
for a particular
[54:12] (3252.12s)
initiative and so you know those
[54:16] (3256.64s)
roles they are pan team right so it's
[54:21] (3261.36s)
it's cross functional teams there might
[54:23] (3263.08s)
be product teams there might be five Dev
[54:24] (3264.84s)
teams these Dev teams
[54:26] (3266.96s)
maybe spanning multiple organizations
[54:29] (3269.80s)
you might act like a TPM I was accused
[54:32] (3272.28s)
of that in one of my um promotion
[54:35] (3275.96s)
assessments uh it's kind of hard to
[54:37] (3277.80s)
figure out whether Steve's an SD or a
[54:39] (3279.68s)
TPM kind of took offense to that I'm
[54:43] (3283.32s)
like are are you kidding me dude and and
[54:45] (3285.76s)
you know one of them came back like hey
[54:47] (3287.16s)
you need to code more and I'm like I
[54:49] (3289.36s)
have checked in so many lines of code
[54:53] (3293.32s)
and so okay well I there's some sporadic
[54:56] (3296.08s)
you know six months where I didn't code
[54:57] (3297.76s)
a lot it's like I didn't get any credit
[55:00] (3300.36s)
for time served I see okay so they
[55:02] (3302.60s)
looked at the code delivered in those
[55:05] (3305.00s)
six months when you're going for
[55:06] (3306.68s)
principal they looked at it not a lot of
[55:08] (3308.92s)
code and so they said okay we're
[55:11] (3311.44s)
blocking you because you're not doing
[55:12] (3312.80s)
the senior job yeah but principal was
[55:16] (3316.24s)
good because you were doing all the
[55:17] (3317.88s)
cross functional yeah and so then it got
[55:20] (3320.00s)
kicked so then it's like okay well now
[55:22] (3322.24s)
I'll go code right and they'll be like
[55:24] (3324.32s)
oh it's been you know it's been a long
[55:26] (3326.00s)
time since he's been on call he's not on
[55:28] (3328.12s)
the day-to-day operations for an
[55:29] (3329.64s)
individual team it's like I've been you
[55:32] (3332.08s)
know I I was there for 18 years I have
[55:34] (3334.48s)
been on
[55:35] (3335.80s)
call longer than Pro like time on call
[55:40] (3340.56s)
longer than most people's careers at
[55:42] (3342.32s)
Amazon by far I've probably been on call
[55:45] (3345.52s)
like four years continuously yeah and so
[55:49] (3349.16s)
you get feedback like that and you're
[55:50] (3350.56s)
just like this like I'm battling the
[55:52] (3352.44s)
process now right and so to to be quite
[55:55] (3355.48s)
honest I was promoted in
[55:57] (3357.52s)
2020 um and I thought I was ready at
[56:00] (3360.44s)
2016 so you know I I was promoted to
[56:02] (3362.84s)
senior in 2012 so it took 8 years to get
[56:04] (3364.96s)
there I thought I was there in 2016 and
[56:07] (3367.76s)
four years and you went for promo every
[56:10] (3370.00s)
year and they gave you like this TPM
[56:12] (3372.48s)
feedback or other yeah there was there
[56:15] (3375.20s)
were a number of obstacles but you know
[56:17] (3377.12s)
they changed the process three times
[56:19] (3379.60s)
during that four year span um I I just
[56:22] (3382.88s)
to be honest I probably hadn't generated
[56:26] (3386.56s)
evidence that I was operating at that
[56:28] (3388.68s)
level that's not to say that I didn't
[56:30] (3390.36s)
have the ability but you need to
[56:32] (3392.16s)
generate this tangible evidence that
[56:33] (3393.80s)
goes into your packet so I wasn't quite
[56:36] (3396.04s)
there yet you need the support of your
[56:37] (3397.80s)
manager and so there was a there was a
[56:40] (3400.00s)
number of reasons why I wasn't able to
[56:41] (3401.76s)
get there um but a lot of it was just
[56:44] (3404.84s)
battling the process itself I don't
[56:47] (3407.20s)
think I necessarily up leveled myself I
[56:49] (3409.56s)
think I just became an expert in the
[56:52] (3412.12s)
process of getting promoted and so what
[56:54] (3414.12s)
did you learn from becoming an expert of
[56:57] (3417.16s)
that promo process for senior 2 yeah I
[57:01] (3421.08s)
you know I I think about it and like is
[57:03] (3423.72s)
that a useful skill yeah I think so I
[57:05] (3425.68s)
think it's useful for people that are in
[57:07] (3427.08s)
Amazon I learned a couple of things so
[57:10] (3430.28s)
the big ones are don't wait to start I
[57:13] (3433.64s)
think a lot of people postpone
[57:15] (3435.08s)
themselves and so they're like oh well
[57:17] (3437.44s)
after this big project
[57:19] (3439.36s)
lands that's when I'll get my packet
[57:22] (3442.28s)
together but the project Landing may not
[57:25] (3445.04s)
be the thing that that you would be
[57:27] (3447.28s)
rejected for and so I'm a big proponent
[57:30] (3450.80s)
of being kind of impatient and putting
[57:33] (3453.64s)
your packet in early and then getting
[57:35] (3455.92s)
that actual feedback about where the
[57:37] (3457.88s)
gaps are so that's one failure pattern I
[57:40] (3460.88s)
think the other is you
[57:43] (3463.08s)
know you do get some amount of credit
[57:45] (3465.84s)
for strengths in your promo packet and
[57:48] (3468.72s)
so suppose your strengths are you know
[57:50] (3470.52s)
he's a great
[57:51] (3471.84s)
communicator um very data driven he does
[57:54] (3474.92s)
a lot of you know he's a Str there's a
[57:56] (3476.92s)
strength with
[57:58] (3478.36s)
interviewing um great coder cool uh
[58:02] (3482.48s)
feedback oh well he's not scaling
[58:04] (3484.08s)
through others uh he could be a better
[58:06] (3486.96s)
Mentor um he doesn't communicate upward
[58:10] (3490.84s)
very well to directors or
[58:13] (3493.24s)
VPS um so let's work on that you don't
[58:16] (3496.56s)
really have to put so much emphasis on
[58:19] (3499.20s)
the strengths just make sure that they
[58:21] (3501.28s)
don't regress and turn into problems but
[58:23] (3503.76s)
I think you can just focus on the delta
[58:26] (3506.36s)
because that's what the promo panel is
[58:29] (3509.00s)
going to do when you're you know we try
[58:30] (3510.92s)
to make the the promo packet sticky to a
[58:34] (3514.52s)
particular set of individuals and so
[58:36] (3516.84s)
it's like okay well Ryan you know
[58:38] (3518.88s)
rejected you get the big red Stamper
[58:41] (3521.92s)
thing on a piece of paper and you know
[58:45] (3525.56s)
six months later it's like oh Ryan he's
[58:48] (3528.36s)
not promoted yet okay like let's dig in
[58:51] (3531.76s)
again with humans just like the talent
[58:53] (3533.72s)
review
[58:54] (3534.76s)
process you're you're going to look at
[58:56] (3536.60s)
the Delta you're going to look at the
[58:58] (3538.04s)
outliers right and so you're going to be
[59:00] (3540.08s)
like okay well what changed right and
[59:01] (3541.96s)
just like let's look at the like the
[59:03] (3543.80s)
evidence that's there and so if you're
[59:06] (3546.96s)
able to really focus in on the the areas
[59:10] (3550.28s)
for growth the places where there aren't
[59:12] (3552.24s)
as many data points then uh I think
[59:15] (3555.00s)
you'll be pretty successful when you get
[59:16] (3556.72s)
that packet back you're saying there's
[59:18] (3558.40s)
the strengths and then there's things
[59:19] (3559.76s)
that blocked it and you're saying
[59:22] (3562.16s)
strengths they're good don't you don't
[59:23] (3563.96s)
need to worry about those just focus on
[59:26] (3566.16s)
on the weaknesses and closing those gaps
[59:28] (3568.52s)
I would just say prioritize the
[59:30] (3570.48s)
weaknesses and gaps and you just I think
[59:32] (3572.96s)
about it like uh you're in a kitchen
[59:34] (3574.80s)
with a lot of pots and pans everywhere
[59:36] (3576.52s)
it's like your strengths you can put
[59:38] (3578.32s)
that on the back burner mhh right but um
[59:42] (3582.20s)
you know this uh this risoto like you're
[59:45] (3585.16s)
going to sit here and make sure that the
[59:47] (3587.00s)
risoto is good right it's like it's like
[59:49] (3589.76s)
you're adding broth you you just can't
[59:51] (3591.36s)
you have to make sure that you got that
[59:52] (3592.80s)
right and so you said you were at Amazon
[59:54] (3594.56s)
for 18 years their Amazon's culture is
[59:57] (3597.96s)
very specific they have the leadership
[60:00] (3600.48s)
principles it's its own yeah culture
[60:04] (3604.12s)
what's your favorite parts of Amazon
[60:06] (3606.76s)
culture and then we'll also talk about
[60:08] (3608.52s)
the worst Parts too the worst Parts is
[60:11] (3611.40s)
it you know I think there's some amount
[60:13] (3613.36s)
of Stockholm syndrome for me being there
[60:15] (3615.48s)
for so long I'm drinking the Kool-Aid
[60:17] (3617.80s)
you know I still say I we even though
[60:19] (3619.60s)
it's been a while since I work what's
[60:21] (3621.00s)
your favorite Kool-Aid then well I just
[60:23] (3623.52s)
the big thing is uh customer obsession
[60:26] (3626.12s)
oh yeah I I think especially when Bezos
[60:28] (3628.72s)
was there
[60:30] (3630.32s)
um nobody ever gave uh lip service to
[60:36] (3636.40s)
the customer experience that was the
[60:38] (3638.56s)
highest
[60:39] (3639.64s)
priority from interns to
[60:42] (3642.08s)
VPS you were always going to be doing
[60:45] (3645.64s)
the right thing if you had the customer
[60:47] (3647.40s)
in mind absolutely
[60:49] (3649.88s)
100% um and I just I think that's a
[60:53] (3653.00s)
great North
[60:54] (3654.28s)
Star and so you know I think if you
[60:57] (3657.24s)
chase profits or you focus on
[60:59] (3659.04s)
competitors or you know there's a lot of
[61:01] (3661.20s)
other trappings that are there you might
[61:03] (3663.36s)
optimize for the wrong thing right if
[61:05] (3665.24s)
you optimize for shortterm next quarter
[61:07] (3667.68s)
profits it's going to bite you in the
[61:09] (3669.52s)
long run um if you optimize for you know
[61:14] (3674.44s)
if you're just sort of chasing that's
[61:16] (3676.20s)
another problem right and so if you if
[61:19] (3679.08s)
you actually work backward from the
[61:20] (3680.76s)
customer you know Jeff Bezos has that
[61:22] (3682.64s)
saying they're like hey long-term
[61:24] (3684.80s)
profits and and customers those are the
[61:27] (3687.92s)
same thing there's no difference there I
[61:30] (3690.48s)
think that's wonderful another thing
[61:31] (3691.88s)
that I
[61:33] (3693.28s)
absolutely I think is a superpower for
[61:35] (3695.60s)
Amazon is their writing culture you know
[61:37] (3697.64s)
I think um the ability to write a
[61:39] (3699.52s)
six-page doc that was that was
[61:41] (3701.96s)
accelerated by the fact that I have a
[61:43] (3703.20s)
writing degree and so I didn't realize
[61:45] (3705.64s)
that I had the precursor to a
[61:48] (3708.12s)
superpower um when I joined I I was
[61:50] (3710.92s)
worried about like learning Java right
[61:53] (3713.44s)
or or learning how to to deploy to
[61:57] (3717.96s)
man I wish people would have a college
[62:00] (3720.36s)
class to figure out how to like send an
[62:03] (3723.28s)
email or to be clear about like the work
[62:06] (3726.28s)
that's in front of them and so what
[62:09] (3729.08s)
comes with a a wonderful writing culture
[62:11] (3731.16s)
is a wonderful reading culture like we
[62:13] (3733.04s)
literally will spend the first 30
[62:15] (3735.04s)
minutes of a meeting reading the
[62:17] (3737.48s)
document and then we will have a
[62:20] (3740.32s)
discussion afterwards there's no this
[62:22] (3742.56s)
never works it's like oh I sent you the
[62:24] (3744.32s)
document
[62:26] (3746.00s)
so after you've read the document we're
[62:27] (3747.36s)
all going to get in the no nobody does
[62:28] (3748.96s)
that right like they should it's like a
[62:32] (3752.76s)
best intention sort of thing right but
[62:35] (3755.08s)
the fact that you're forced to read it
[62:36] (3756.48s)
at the same time and everybody's just
[62:38] (3758.60s)
sort of fast forwarded to the same place
[62:40] (3760.28s)
and then you can have a discussion like
[62:42] (3762.52s)
that's actually super powerful so if
[62:44] (3764.32s)
someone was on boarding to Amazon they
[62:46] (3766.64s)
really want to make sure they hit the
[62:47] (3767.84s)
ground running and plug into the
[62:50] (3770.28s)
culture would you say that's one of the
[62:52] (3772.72s)
most important things yeah if if they if
[62:55] (3775.00s)
they are curious about how we know we're
[62:58] (3778.20s)
doing right by the
[63:00] (3780.12s)
customer yeah I think that's a you if
[63:03] (3783.20s)
you have a curiosity about that you will
[63:05] (3785.04s)
do you will do really well um the
[63:08] (3788.60s)
writing culture I think that's just the
[63:10] (3790.60s)
medium by which we express our ideas
[63:13] (3793.08s)
that's
[63:14] (3794.16s)
learnable um that's something that I
[63:16] (3796.28s)
wouldn't necessarily focus on before you
[63:17] (3797.84s)
joined you said you're drinking the
[63:19] (3799.24s)
Kool-Aid but there's got to be something
[63:21] (3801.72s)
that you don't like about Amazon culture
[63:23] (3803.68s)
what would be the number one thing
[63:27] (3807.28s)
uh I know mine what's that I remember
[63:32] (3812.04s)
this was uh this was like a joke among
[63:35] (3815.08s)
my friends and I Amazon I there's the
[63:36] (3816.84s)
leadership principles right and you know
[63:39] (3819.64s)
there a list of what 11 or 12 things
[63:44] (3824.00s)
that yeah everyone's kind of basing
[63:46] (3826.64s)
everything off of and there's one there
[63:49] (3829.48s)
that was just like the recurring inside
[63:51] (3831.68s)
joke among our friend group which was
[63:54] (3834.44s)
frugality basically anything anytime
[63:57] (3837.24s)
something was crappy or cheap or
[64:00] (3840.08s)
whatever we would just say oh frugality
[64:03] (3843.76s)
so you know no free food no uh there was
[64:08] (3848.12s)
some other things too like a hardware
[64:09] (3849.56s)
wasn't particularly good or yeah you
[64:12] (3852.08s)
know I think free food that's a
[64:14] (3854.40s)
perk if if a company doesn't provide you
[64:16] (3856.92s)
food like that doesn't mean it's a bad
[64:19] (3859.00s)
company so it's it's it's great on the
[64:21] (3861.48s)
upside but I don't think there's it says
[64:23] (3863.20s)
very much on the other side I do think
[64:25] (3865.76s)
think you know frugality uh we we have a
[64:28] (3868.80s)
term called being Frid where you are
[64:32] (3872.16s)
right so Frugal that it's kind of stupid
[64:35] (3875.00s)
I had to beg borrow and plead for
[64:36] (3876.92s)
Hardware right like I'm I'm trying to
[64:39] (3879.00s)
get a trying to get a MacBook Pro with
[64:42] (3882.56s)
like some Ram so that it doesn't like
[64:44] (3884.92s)
like the fan doesn't overheat when I'm
[64:47] (3887.04s)
running like building my code it's
[64:50] (3890.40s)
like if you're going to hire you know
[64:52] (3892.68s)
tens of thousands of software developers
[64:54] (3894.36s)
you won't like get them a computer that
[64:55] (3895.88s)
work now I'm not saying like I need the
[64:57] (3897.36s)
top-of-the-line thing I just I just need
[64:59] (3899.88s)
a computer I'm a software developer give
[65:01] (3901.44s)
me a you know give me a computer that
[65:02] (3902.88s)
works you know when intern season would
[65:04] (3904.96s)
come and then the interns would leave
[65:07] (3907.12s)
and then the vultures would come to try
[65:09] (3909.28s)
to steal the
[65:11] (3911.60s)
monitors right and so it's just like you
[65:14] (3914.96s)
know it just it just reminds me of like
[65:16] (3916.76s)
Oliver Twist like you know it's like
[65:18] (3918.28s)
more please it's like you just want a
[65:19] (3919.88s)
little bit more
[65:21] (3921.96s)
GRL yeah one thing that I wanted to dig
[65:24] (3924.60s)
into uh and I guess this is switching to
[65:27] (3927.72s)
another topic is in your time at Amazon
[65:31] (3931.84s)
you had 17 managers over 18
[65:36] (3936.28s)
years so you've seen a lot when it comes
[65:38] (3938.88s)
to managers what was it that made your
[65:42] (3942.08s)
best manager the best manager out of 17
[65:45] (3945.76s)
I think I had more than 17 managers
[65:47] (3947.80s)
actually really yeah okay than it was in
[65:50] (3950.08s)
the 20s last time I checked I took a
[65:51] (3951.84s)
screenshot of my phone tool you know I
[65:53] (3953.92s)
think a lot about this you know uh
[65:56] (3956.84s)
sometimes people would complain about a
[65:58] (3958.96s)
micromanager but there's a class of of
[66:02] (3962.48s)
folks that kind of like a micromanager
[66:05] (3965.24s)
like they they kind of need to be led
[66:06] (3966.72s)
they kind of need things broken down for
[66:08] (3968.56s)
them I do think that a lot of what makes
[66:10] (3970.44s)
a good manager is personal the ones that
[66:13] (3973.80s)
I resonated with um they tended to be
[66:16] (3976.96s)
principles based right so not just the
[66:19] (3979.48s)
leadership principle stuff but like the
[66:21] (3981.04s)
way that they operated um they sort of
[66:23] (3983.64s)
reasoned through you think of these
[66:25] (3985.60s)
principles as
[66:26] (3986.96s)
axioms and um you know so you fix
[66:29] (3989.96s)
certain things and and those things have
[66:32] (3992.76s)
implications and so the best managers I
[66:36] (3996.00s)
think they fixed customer Obsession they
[66:39] (3999.56s)
fixed uh things that I value like sort
[66:41] (4001.44s)
of thinking ahead in the future so they
[66:43] (4003.96s)
were maybe willing to entertain some you
[66:47] (4007.28s)
know some stuff that in the short term
[66:48] (4008.84s)
like a hack but it was always within the
[66:51] (4011.88s)
context of like what should we do what's
[66:53] (4013.56s)
the right thing to do in the future okay
[66:55] (4015.16s)
so like let's made a tradeoff for that
[66:57] (4017.28s)
instead of you know maybe some managers
[66:59] (4019.64s)
that I didn't like are folks that are
[67:03] (4023.16s)
maybe too delivery oriented right so
[67:06] (4026.00s)
it's just a constant Death March it's
[67:08] (4028.16s)
about delivery it's about near-term
[67:10] (4030.68s)
delivery um so folks that kind of
[67:13] (4033.04s)
thought a little bit ahead in the future
[67:15] (4035.80s)
and um were maybe not so constrained by
[67:19] (4039.12s)
what we had in front of us I see and
[67:21] (4041.56s)
then what about the worst manager you
[67:23] (4043.12s)
had out of 20 something managers yeah I
[67:26] (4046.04s)
don't want to name names or anything but
[67:29] (4049.24s)
um you know sometimes I think about how
[67:32] (4052.24s)
did we get
[67:34] (4054.16s)
here right and so like we live in a in a
[67:37] (4057.12s)
moment right now and so I'm talking to
[67:39] (4059.48s)
you and so I I I can see it you know a
[67:41] (4061.48s)
year ago he was here and a year before
[67:43] (4063.40s)
that he was here and I I can kind of see
[67:45] (4065.76s)
the progression of how you get from you
[67:49] (4069.16s)
know maybe a university student at
[67:52] (4072.20s)
UCLA to where you are right now like
[67:55] (4075.08s)
that aggression makes sense I think some
[67:57] (4077.92s)
people that I worked with you're like
[68:00] (4080.24s)
how did you get
[68:02] (4082.20s)
here like it's it's sort of like the
[68:04] (4084.48s)
Silicon Valley thing I forget the name
[68:06] (4086.00s)
of the guy that uh bigh head yeah yeah
[68:09] (4089.00s)
it had to have been some sort of big
[68:11] (4091.36s)
scenario where you know he fell up right
[68:15] (4095.12s)
luck happened and everything just sort
[68:17] (4097.48s)
of landed in their lap so you know um I
[68:22] (4102.60s)
think the worst managers I had would be
[68:25] (4105.56s)
combination of like not my style right
[68:27] (4107.88s)
so again you know micromanager one
[68:29] (4109.80s)
person is a really caring and engaged
[68:31] (4111.64s)
manager to another person and then um
[68:35] (4115.48s)
just a little bit of like WTF like how
[68:38] (4118.44s)
did you get here I thought that the
[68:40] (4120.88s)
whole performance and promotion process
[68:42] (4122.96s)
and the hiring process was supposed to
[68:45] (4125.36s)
filter a certain set of folks out and
[68:48] (4128.32s)
here we are at the end of each interview
[68:50] (4130.52s)
I like to go over just general
[68:52] (4132.64s)
reflections of people um kind of looking
[68:55] (4135.64s)
over the career what are the things that
[68:57] (4137.72s)
you learned and and various other things
[69:01] (4141.16s)
um one thing that I'm curious about
[69:03] (4143.08s)
because you were at Amazon for 18 years
[69:06] (4146.32s)
and in this industry that is
[69:08] (4148.88s)
extraordinary people already call me
[69:11] (4151.40s)
fossil for being at meta for greater
[69:14] (4154.20s)
than four or five years so you know what
[69:16] (4156.64s)
kept you at Amazon so long I think that
[69:19] (4159.40s)
you know we had talked about the number
[69:20] (4160.64s)
of managers that I had reported
[69:26] (4166.32s)
I had many careers many many careers at
[69:29] (4169.36s)
Amazon right so I worked on the first
[69:31] (4171.24s)
Kindle and I worked on the precursor to
[69:33] (4173.36s)
Prime video before I went back to Prime
[69:35] (4175.60s)
video I and I worked on in payments so
[69:40] (4180.48s)
you know I think the fact that Amazon
[69:43] (4183.36s)
does so many different things um has
[69:46] (4186.68s)
allowed me to work on a variety of
[69:49] (4189.52s)
different things you know and didn't
[69:52] (4192.20s)
feel like I've been on one team it's not
[69:54] (4194.28s)
like I worked in the accounting
[69:55] (4195.76s)
department for 25 years and they handed
[69:58] (4198.24s)
me a gold watch right um and so you know
[70:03] (4203.12s)
there's a there's a VP I think he's
[70:05] (4205.04s)
still a VP at in advertising Paul cotus
[70:07] (4207.76s)
he he told me one day he said I've never
[70:11] (4211.00s)
switched
[70:12] (4212.08s)
teams wow right like Amazon just kind of
[70:17] (4217.28s)
you know refactored itself around him
[70:19] (4219.28s)
until he was BP of ads right and so
[70:22] (4222.40s)
great guy and so um you know I don't
[70:25] (4225.08s)
think it's gets to that extreme but um
[70:27] (4227.80s)
you know I had a wide variety of
[70:29] (4229.16s)
experiences there and so it does it
[70:31] (4231.04s)
doesn't feel like one 18-year contiguous
[70:34] (4234.24s)
sort of experience so it sounds like you
[70:36] (4236.32s)
were still challenged learning I think
[70:38] (4238.68s)
when I was at Amazon for my short
[70:41] (4241.08s)
stunt it was difficult for me to not
[70:44] (4244.88s)
have wandering eyes because there were
[70:47] (4247.28s)
these other hot companies recruiters
[70:48] (4248.92s)
were messaging me and you know I was
[70:51] (4251.52s)
just seeing that oh maybe I can get more
[70:54] (4254.40s)
somewhere else
[70:55] (4255.96s)
um did did you ever consider leaving
[70:58] (4258.24s)
Amazon yeah yeah absolutely I think
[71:02] (4262.32s)
um you know especially early career it
[71:05] (4265.08s)
makes a lot of sense to jump
[71:07] (4267.44s)
companies uh you know everybody hears
[71:10] (4270.08s)
the the common advice it's like hey you
[71:12] (4272.20s)
want to maximize your total comp you
[71:14] (4274.32s)
should be job hopping I think that works
[71:17] (4277.60s)
until you get to the equivalent of
[71:20] (4280.32s)
senior after that I think you know
[71:23] (4283.00s)
you're an outlier here but I think after
[71:24] (4284.96s)
that it makes sense to put Roots down
[71:27] (4287.88s)
right the the levels that at the highest
[71:29] (4289.92s)
levels I I don't think you're going to
[71:31] (4291.40s)
find a lot of distinguished Engineers or
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principal Engineers or staff senior
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staff Engineers that haven't been on the
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team like the like the jump the thing
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that got them to that level I think you
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what you'll find is that you know there
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there was like five years you know at
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least like at least three but more like
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five or so where they really stayed on
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the same team on the same problem right
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right and so you know I think if you
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want to min max it what I would say is
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you know job hop every two years till
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you get to to Mid maybe a little bit
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before and then go to um you know and
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then try to put Roots down if you want
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to become a highle tech IC for me I
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think that because I was able to to go
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to different teams and you know because
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I don't have that computer science
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background I think staying put made a
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ton of sense because I feel like I
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didn't there was so much to learn right
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you know there was so many there was so
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much code that you had access to there
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were all of these wikis you know these
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internal videos and so I felt like I
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could still grow in the ways that I
[72:45] (4365.16s)
wanted to by staying at Amazon I
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remember even when I was at Amazon the
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stock was climbing like crazy did you
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have any years where you were just super
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overcome ated and if so how much were
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you making in that year so here's the
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I I would uh you know I I was basically
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divesting and then you know putting
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money into other
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Investments and I won't say that I
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missed a lot of like the Amazon's climb
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because a lot of it was was sort of
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unvested right
[73:19] (4399.68s)
um I don't know I think uh 2020 or
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something like that I probably got like
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an extra 350k that I didn't
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deserve you know just from from the
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market returns and and extra rsus that
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were given to me um when I left so 2024
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I you know if on the on the vesting
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schedule that I was on I would have made
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750k which is not a lot compared to like
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the upper end of the salary ranges but
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quite a bit just sort of objectively as
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a number to make in the US at this point
[73:54] (4434.72s)
in time I decided around I think 2018 or
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2019 to to maybe like not divest my
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Amazon shares cuz it was always like
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you're dumb like you shouldn't put all
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of your eggs in one basket but every
[74:10] (4450.24s)
time I sold stock just if you just look
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at the stock price it was just it was
[74:15] (4455.12s)
just the wrong move right and so I was
[74:17] (4457.00s)
like I'm done I'm done I'm not going to
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keep every single little bit but um I'm
[74:22] (4462.72s)
going to keep some and so that turned
[74:24] (4464.88s)
out to be okay you said extra Equity did
[74:27] (4467.68s)
does Amazon have a uh for high
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performers uh like a discretionary
[74:32] (4472.52s)
Equity or additional Equity um not that
[74:36] (4476.76s)
I know of I think um I compensation is
[74:41] (4481.24s)
largely you're talking about like
[74:42] (4482.60s)
Refreshers then yeah yeah it's at the
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discretion of managers and so you know
[74:47] (4487.76s)
one of my one of my best managers he was
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basically
[74:51] (4491.20s)
like YOLO YOLO he was like I'm out and
[74:54] (4494.80s)
so so he hooked me up you know and and
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left me go but it's not like these
[74:58] (4498.68s)
insane like million-dollar things that I
[75:00] (4500.44s)
ever got how how big of a difference to
[75:02] (4502.60s)
that it was that 350 Delta oh I see I
[75:05] (4505.56s)
see just like that was over four years
[75:07] (4507.48s)
or no it was it was just sort of all at
[75:10] (4510.20s)
once it just here's
[75:11] (4511.92s)
350 okay that's pretty good yeah yeah it
[75:14] (4514.96s)
was it was the equivalent of that he was
[75:16] (4516.72s)
he was basically on his way out and he
[75:18] (4518.20s)
he gave it to me and then he left and
[75:19] (4519.48s)
then that appreciated essentially the
[75:21] (4521.92s)
next year like immediately so oh that's
[75:24] (4524.16s)
amazing it wasn't it wasn't like here's
[75:25] (4525.96s)
he didn't write me a check it was just a
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combination of the um of sort of getting
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an outsized um performance bonus and and
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the stock price just doing really well
[75:37] (4537.12s)
okay so over the course of your career
[75:38] (4538.56s)
18 years at Amazon one thing that I'm
[75:40] (4540.52s)
curious is what was your biggest regret
[75:44] (4544.56s)
um yeah certain teams I think just just
[75:48] (4548.16s)
reading the the the writing on the wall
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and making a sober decision about
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whether to stay or whether to leave I
[75:55] (4555.40s)
think there was a lot of inertia I think
[75:58] (4558.72s)
your default mode is to just stay put
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for some amount of time and I don't know
[76:05] (4565.24s)
if that's useful the uh I guess the
[76:07] (4567.24s)
career regret is noticing when you're in
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a bad situation or a bad team and just
[76:13] (4573.28s)
taking the initiative to change that
[76:15] (4575.16s)
situation just leave the regret is just
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did you make it a decision or not did
[76:21] (4581.88s)
you take in all of the considerations
[76:24] (4584.36s)
and then said said okay I am going to
[76:26] (4586.84s)
continue to stay it's the deferral of a
[76:30] (4590.28s)
decision and so the default becomes just
[76:32] (4592.72s)
staying put that's the regret it's just
[76:35] (4595.68s)
like just turn it into an explicit
[76:38] (4598.28s)
decision and the last question I like to
[76:40] (4600.84s)
ask and I ask everyone this question is
[76:44] (4604.16s)
if you could go back to you or you just
[76:47] (4607.44s)
graduated college you're right about to
[76:49] (4609.72s)
enter the industry you could tell
[76:51] (4611.76s)
yourself something what would be the
[76:54] (4614.04s)
thing that you want to tell yourself um
[76:58] (4618.16s)
I think I
[77:00] (4620.56s)
think maybe saying something
[77:04] (4624.28s)
around people pleasing right um you know
[77:08] (4628.52s)
in the the culture that I was raised in
[77:13] (4633.12s)
and you know there are these tracks that
[77:15] (4635.44s)
you get on and it's like okay we'll do
[77:18] (4638.64s)
well in school and then go get a job and
[77:20] (4640.92s)
then go get married and like you know
[77:23] (4643.36s)
you have this feeling of
[77:25] (4645.48s)
being ahead or behind right so that
[77:27] (4647.64s)
relative
[77:28] (4648.80s)
comparison um but then also after you do
[77:31] (4651.88s)
a thing after you make some sort of
[77:34] (4654.16s)
achievement you're kind of looking for
[77:36] (4656.68s)
to someone else for
[77:38] (4658.76s)
validation and
[77:41] (4661.44s)
um I don't know if my younger self would
[77:43] (4663.76s)
have like listened to be quite honest
[77:46] (4666.44s)
with you but you know just if I could
[77:49] (4669.40s)
somehow learn this lesson that like the
[77:51] (4671.92s)
person that you really need to please is
[77:53] (4673.60s)
yourself
[77:55] (4675.48s)
like just just being like are is are you
[77:58] (4678.20s)
doing what you want to do or are you
[77:59] (4679.84s)
doing it because that's the expectation
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of somebody else are you climbing the
[78:05] (4685.64s)
ladder because you want to get to the
[78:06] (4686.92s)
top or are you climbing a ladder because
[78:08] (4688.52s)
the ladder was put in front of you just
[78:10] (4690.68s)
examining that um that makes sense cool
[78:14] (4694.20s)
well thanks so much for your time Steve
[78:16] (4696.48s)
I really enjoyed the conversation and uh
[78:19] (4699.72s)
yeah I guess now would be the time if we
[78:22] (4702.16s)
if you want to shout out anything that
[78:23] (4703.88s)
you're working on um I have my uh
[78:26] (4706.36s)
YouTube channel it's called a life
[78:27] (4707.80s)
engineered um so go and subscribe to
[78:30] (4710.20s)
that I have a Weekly Newsletter um that
[78:33] (4713.40s)
gets sent out so you know it takes a
[78:36] (4716.04s)
long time to make a YouTube video and so
[78:38] (4718.44s)
you know if you want more from me the
[78:40] (4720.24s)
newsletters there and then if you want
[78:41] (4721.44s)
to chat um just join my Discord awesome
[78:45] (4725.04s)
cool all right well thanks so much for
[78:46] (4726.36s)
your time Steve really appreciate it
[78:47] (4727.80s)
absolutely