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when you're a new nrad I don't know it's
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just you don't expect to see like
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venuses at work or any nudity at work
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eaing all these cool things whatever and
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I leave all of that to realized I don't
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know a damn thing today's conversation
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is with Evan King he's a software
[00:12] (12.16s)
engineer who grew to staff by the age of
[00:14] (14.04s)
25 he had a lot of things to share when
[00:16] (16.60s)
it came to Growing your career quickly
[00:18] (18.60s)
we also thought it'd be interesting to
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interview both ways because his career
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growth matches mine very closely and so
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for each leg of the career not only does
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he go over what he learned but also I
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provide context on my as well I hope
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this conversation is helpful let's get
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into it today's interview is going to be
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a little bit different from the ones
[00:37] (37.04s)
that I normally do we have Evan on the
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podcast I actually don't know of anyone
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who's got promoted to staff faster than
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Evan absolute rocket ship trajectory got
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to meta and got promoted to staff in
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three years which just means he got to
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promo every single year so he has a lot
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to to say I'm really looking for the
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conversation and one thing that we're
[00:55] (55.16s)
going to do today that is different from
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a normal podcast is because his
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trajectory is similar to mine as well we
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both grew very quickly very lucky in in
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our trajectories we will do kind of a
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back and forth where every time Evan
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answers I'll also kind of give my
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perspective on how it was for me yeah
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totally I'm really looking forward to
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this round this is going to be a lot of
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fun and I'm especially excited to hear
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about your journey because that's
[01:18] (78.64s)
something that even offline you and I
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haven't chatted about yet so yeah yeah
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absolutely and I think there's some
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stuff in here I've haven't set anywhere
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before so we can uh see where it goes
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nice that'll be exciting so okay let's
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let's get in the first thing first thing
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is like the beginnings of your career
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even before you got into the industry
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when we put out that content showing how
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quickly you grew there was conversation
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about are you this brilliant person
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who's been coding since you were 5 years
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old or were you someone who started
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studying at a normal time so I'm kind of
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curious how did you get into studying
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computer science I had computer science
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offered in my High School AP Computer
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Science which compared to most this is
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certainly early but it I felt late like
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most of the people in that AP Computer
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Science class I grew up in the Seattle
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area around the Seattle area most people
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in that class had a dad or a mom that
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worked at Microsoft and so they had all
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been programming since they were super
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super young and I was horrible like I
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knew nothing and it was incredibly
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complex and I was like I was so down on
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myself and up until that point i' had
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been a straight A student um so it
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really stressed me out it made me feel
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like this wasn't something that actually
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clicked for me but you know I was
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resilient enough to make sure that I
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didn't lose that a streak and worked
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really hard in order to do well enough
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in that in that course
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but then when we got to college I didn't
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think I was going to do computer science
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I just joined the engineering school and
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you have an intro to computer science
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class and because I had more of a
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background than the majority of others
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who had no CS background now all of a
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sudden I was good and better than other
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people and it's like that human nature
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that when you're good at something it's
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exciting and and you want to keep going
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that that was the beginning my high
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school so I grew up in Orange County in
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Southern California we actually didn't
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even have apcs I actually didn't even
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know what CS was until I got to colge
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yeah so yeah I guess it shows you don't
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really need to be like a a prodigy to
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succeed in in Industry cuz you said you
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weren't like naturally um you know super
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into CS from a from a young age I didn't
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know what CS was until I got to UCLA and
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even there I started as an Undeclared
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engineer just cuz I knew I liked Math
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and Science but I didn't know exactly
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what I wanted to do and then when I took
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our our intro CS classes I thought it
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was fun but I still actually I declared
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as an electrical engineer I didn't go
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into CS um and my reasoning was that I
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like video games and I like computers
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and I just thought that was you know how
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I'm going to get into that later when I
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got into like you know Finding
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internships and things I realized
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actually electrical engineering is maybe
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not the way to set myself up for Career
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Success so then I ended up switching
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into CS which there's a lot of overlap
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between e and CS so I it didn't need to
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take year with that switch that was
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actually in junior year of college so
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pretty late that's surprisingly late
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yeah but I switched into um computer
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science and engineering so I all those e
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upper divs I had taken kind of like got
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reused and I can go into CS with the
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last two years of my college but yeah so
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I switched into it pretty late don't
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have like a you know storied long tenure
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in in CS prior to getting into it in
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college yeah I guess we're both proof of
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the the contrary of what most people
[04:29] (269.80s)
look back there yeah exactly I I don't
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think you need to be like a programming
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Prodigy for most stuff in industry and
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so I saw you you know once you got into
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CS you started getting really involved
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like you did the uh Cornell hacking Club
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what made you want to to start that so
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actually I played soccer at Cornell in
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college and then my junior year I came
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to the realization that like you know
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when you're playing the division one
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sport you're spending a ton of time on
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it so you're up early you're working out
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you're training you're on the bus on
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weekends you're traveling whatever and I
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finally came to this realization is I
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was like Landing internships that I'm
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not going to be a professional soccer
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player I have no aspirations to be but I
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am going to be a professional software
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engineer and so why am I dedicating so
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much time to the soccer stuff as opposed
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to the thing that's actually going to be
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fruitful for the rest of my life so I I
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quit soccer my junior year and then all
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of a sudden I had so much time and so
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like at least in a relative sense I had
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so much time compared to what I was used
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to and so I had been doing a lot of
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hacking on the side just building things
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that I thought was fun and I decided
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this could be a cool thing to try to
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expand and so I had done a couple of
[05:29] (329.72s)
Capture the Flag competitions myself and
[05:32] (332.12s)
like entered teams through Reddit and I
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figured Cornell's got a bunch of smart
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people this could probably be something
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that we could do so I set up a handful
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of Flyers around the the engineering
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quad and next thing you know I had calls
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conversations with about 25 people
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grabbed a couple of them to kind of be
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like the founding quote unquote officers
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and then from there we really scaled it
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up and had a core team of like 25 people
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that competed in ctfs but then had at
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some points as many as 200 people who
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showed up to weekly like call it
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lectures to talk about hacking stuff
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that was a ton of fun and I guess as we
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see and we might get into later like
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with the hello interview stuff I've
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always just really loved teaching so
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that was a maybe a Genesis for that as
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well you know when I was in college or
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just in general in my education I feel
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like people always told me this advice
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of you should get into these leadership
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opportunities and oftentimes in high
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school it was to just make your college
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application look better yeah totally but
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I think actually looking back if you if
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I look through all the behaviors that
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you had to do to start that club get all
[06:34] (394.84s)
the alignment with all the people
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communicate and Market it Etc and kind
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of be a leader in that space that's
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actually a lot of what I think you know
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more senior Engineers need to do like
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those all those soft skills so I feel
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like actually it is a good thing to do
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in the long term and I I did some um
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leadership stuff as well in college
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because I thought it was good for for
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interviews but also cuz I I enjoyed
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meeting all the other officers in those
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clubs and getting involved so and I
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think in that experience too beyond all
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the leadership stuff which was super
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important most of the kids in the club
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with me were technically brilliant more
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so than me like significantly more so
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than me but like we spent all day
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hacking and writing code and Building
[07:15] (435.68s)
Things that that were pretty
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sophisticated and like even to this day
[07:18] (438.96s)
like you know pretty awesome I look back
[07:20] (440.92s)
at some of those repos and and find it
[07:22] (442.44s)
pretty amazing but you always hear
[07:23] (443.64s)
people recommend doing side projects and
[07:26] (446.08s)
I guess that was my example of that
[07:27] (447.64s)
where it's like I was just working on
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something that was fun
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with friends who were brilliant and I
[07:32] (452.00s)
feel like that set me up pretty well
[07:34] (454.04s)
eventually going into meta did you have
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a side project experiences much going
[07:39] (459.08s)
into I had a few side projects they were
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like little things though for instance
[07:43] (463.88s)
there was this one thing that I built I
[07:45] (465.76s)
was in this e club called i e and the
[07:49] (469.32s)
club's lab is only open when an officer
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is present you know how do you know if
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it's open well maybe you ping people you
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have group chats or something see if
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it's open but that was kind of
[08:01] (481.84s)
unreliable and slow I wanted there to be
[08:04] (484.44s)
like this status indicator so I built
[08:07] (487.96s)
this occupancy sensor which was
[08:10] (490.28s)
basically just it was like a Raspberry
[08:12] (492.68s)
Pi connected to the Wi-Fi of that lab
[08:16] (496.00s)
sweet if any of the officer's devices I
[08:18] (498.40s)
had like a manual mapping of the Mac
[08:20] (500.12s)
addresses of all their devices if any of
[08:22] (502.20s)
them connected to the Wi-Fi that bot
[08:24] (504.28s)
knew that someone's in the lab and so
[08:26] (506.68s)
you could just ping that slackbot say
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hey I think the command was like who is
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or something and it'll just give you
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like all the officers that are there and
[08:34] (514.56s)
so like yeah that is something that I
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did build that I felt like was useful
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and it was like a nice side project and
[08:40] (520.28s)
I did remember talking about it in
[08:42] (522.28s)
interview conversations and I feel like
[08:43] (523.96s)
that's such a perfect example because my
[08:45] (525.88s)
suggestion to especially like new grads
[08:47] (527.64s)
nowadays as it pertains to doing a side
[08:49] (529.80s)
project like choosing from some of those
[08:51] (531.28s)
random lists which you see always going
[08:52] (532.96s)
around is like cool but you're not
[08:55] (535.52s)
nearly going to have like you're not
[08:56] (536.64s)
going to be as passionate about it or
[08:58] (538.32s)
want to be working on it later as you
[08:59] (539.84s)
would be something like what you just
[09:00] (540.88s)
describe it's like and so maybe that
[09:02] (542.08s)
would be the concrete advice to to
[09:03] (543.48s)
anybody listening it's in that phase is
[09:04] (544.76s)
like just observe the problems around
[09:06] (546.04s)
you and then build some software to
[09:07] (547.16s)
solve it that's the side project you
[09:08] (548.40s)
should be working on 100% agree I think
[09:10] (550.40s)
there's all this advice on doing side
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projects and if you just build one
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that's like redis clone or something
[09:16] (556.92s)
like that but no one uses it I guess
[09:18] (558.96s)
it's better than nothing but it's not
[09:21] (561.32s)
letting you do that full end to-end path
[09:23] (563.40s)
of learning and it's essentially the
[09:25] (565.44s)
same as like a college class project or
[09:28] (568.20s)
something that you put on your resume me
[09:29] (569.84s)
you're not going to get nearly as much
[09:31] (571.28s)
out of it highly agree with what you're
[09:33] (573.52s)
saying you did CTF when I think of
[09:36] (576.40s)
really really good technically brilliant
[09:38] (578.92s)
Engineers I think of CTF I think of like
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top coder and these competitive coding I
[09:45] (585.04s)
feel like that probably helped you with
[09:46] (586.64s)
leak code what was your experience when
[09:48] (588.36s)
you were interviewing did you feel like
[09:49] (589.88s)
it was pretty smooth when you
[09:51] (591.40s)
interviewed to get your meta job
[09:53] (593.24s)
honestly like not in the beginning
[09:54] (594.88s)
anyway like everybody knows that you
[09:56] (596.08s)
have to leode at school I was surrounded
[09:58] (598.64s)
by a bunch of computer science Majors we
[09:59] (599.96s)
all knew that we had to Le Cod but like
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I found it really hard I felt like
[10:02] (602.64s)
people around me found it easier that
[10:04] (604.20s)
might have just been projecting some
[10:05] (605.80s)
insecurities there it might not have
[10:07] (607.00s)
actually been the case but it felt like
[10:08] (608.68s)
that and we would just spend so many
[10:10] (610.20s)
hours every single day in the library
[10:11] (611.80s)
just practicing different problems and
[10:13] (613.64s)
eventually I felt like I got in the
[10:14] (614.68s)
groove but actually maybe funny story
[10:16] (616.76s)
and this is where the first tick of luck
[10:18] (618.44s)
pops in and I'm sure that'll be a
[10:19] (619.56s)
reoccurring theme throughout but meta
[10:22] (622.16s)
came to my campus to interview I think
[10:24] (624.00s)
this still happens periodically but it
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certainly happened more then and so they
[10:27] (627.32s)
came to campus I showed up to do my
[10:29] (629.04s)
interview
[10:30] (630.08s)
and the first question that I got was
[10:32] (632.68s)
one that I really would never have been
[10:34] (634.96s)
able to do really struggled with it was
[10:36] (636.36s)
Elite code hard it was super difficult
[10:38] (638.00s)
but the night before when I was studying
[10:39] (639.52s)
I was like let me just look at one more
[10:41] (641.20s)
and I looked at that one and I skimmed
[10:42] (642.88s)
it I didn't do it I just skimmed it but
[10:44] (644.96s)
like I knew the trick and so that
[10:46] (646.68s)
question popped up and had I not skimmed
[10:48] (648.44s)
it I certainly wouldn't have passed
[10:50] (650.12s)
certainly wouldn't have gone on site
[10:51] (651.60s)
wouldn't work at meta you and I probably
[10:53] (653.00s)
wouldn't be having this conversation so
[10:55] (655.00s)
certainly a factor of luck there it's
[10:56] (656.76s)
crazy how much luck can make a
[10:58] (658.64s)
difference there's there's so many
[11:00] (660.08s)
little things that were just
[11:01] (661.28s)
opportunities that happen I'm sure like
[11:03] (663.24s)
the team that you picked or this for
[11:05] (665.72s)
instance just completely change your
[11:07] (667.72s)
trajectory so yeah that resonates and I
[11:10] (670.04s)
think for me for for elak code I was
[11:13] (673.04s)
kind of mid at leak code not very
[11:15] (675.68s)
good I remember my interview season for
[11:19] (679.84s)
junior year I didn't have a great resume
[11:22] (682.04s)
so I I had like one or two companies I
[11:25] (685.04s)
think and the one I ended up getting was
[11:26] (686.68s)
Bloomberg which was in New York yeah and
[11:29] (689.28s)
that was probably a fun experience yeah
[11:30] (690.56s)
it was it was pretty fun although at
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that time I was really young so you
[11:33] (693.28s)
can't do a whole lot if you're like a
[11:35] (695.24s)
19-year-old in yeah New York I got
[11:37] (697.72s)
through elak code survived but I
[11:39] (699.56s)
remember that internship the project was
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really easy and that I don't mean that
[11:43] (703.96s)
is a bragging thing but it was like a I
[11:45] (705.92s)
don't know only like two weeks of work
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even for someone who didn't have context
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on the code base so I got it done really
[11:51] (711.20s)
quick and I spent the rest of the time
[11:52] (712.80s)
just grinding leak code CU think okay
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I'm going to make sure that that return
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that full-time offer that I get is going
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to give this amazing company and be so
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satisfied with it I'd been practicing
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leak code aggressively all day every day
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for the entire summer and then I go into
[12:08] (728.44s)
the interviews and I was able to get
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interview opportunities with all the
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biggest companies because at that point
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Bloomberg was a decent name to have UCLA
[12:18] (738.24s)
yeah yeah and UCLA so I was able to get
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my foot in the door everywhere but I
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failed every single onsite that I got
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like I think like when I when I look
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back I at the end of the day is just a
[12:30] (750.16s)
wasteland I had two offers one was the
[12:32] (752.56s)
Bloomberg return offer which I didn't
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need to interview for and then the other
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one was Amazon and that interview Loop
[12:41] (761.40s)
was not an interview Loop it was some
[12:43] (763.16s)
weird sat oh did did you have the online
[12:46] (766.08s)
like simulation thing I did that for
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Amazon whereas you're in a full
[12:49] (769.60s)
simulation portal with like a person
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telling you to check your email kind of
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thing I remember that I don't remember
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if that was the year after the one I did
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the one that I remember is like they
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came to our school and they had a they
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booked out a room that could fit
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hundreds of people and they all gave us
[13:06] (786.64s)
essentially an SAT like it was uh just
[13:09] (789.76s)
logic puzzles you know that would be
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like it would be like a b c d colon
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blank and then the multiple choice would
[13:17] (797.40s)
be like is it e fgh h or is it like you
[13:22] (802.20s)
just like complete the pattern kind of
[13:24] (804.00s)
stuff anyway so I I got the offer
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through that like weird logic puzzle
[13:28] (808.28s)
thing and anyway at the end of the day I
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completely failed all my le code even
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though I was grinding and really trying
[13:35] (815.20s)
still not sure what happened in that in
[13:37] (817.16s)
that case but uh yeah ended up accepting
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Amazon because I wanted to stay in the
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west coast in that case that's so funny
[13:43] (823.92s)
I had a bunch of the interview rounds
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too maybe slightly different the
[13:46] (826.60s)
majority went well but there's one that
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I failed miserably and I still remember
[13:49] (829.68s)
it to this day because of kind of how
[13:51] (831.44s)
much it shook me up and it was the one I
[13:52] (832.80s)
wanted more than anything it was paler
[13:54] (834.56s)
which at the time in particular like
[13:55] (835.92s)
paler was so cool for whatever reason it
[13:58] (838.20s)
maybe it was just the Cornel thing or
[13:59] (839.56s)
maybe this UCLA paler was so cool and I
[14:03] (843.36s)
went in the interview Loop and they say
[14:04] (844.92s)
you do a first Loop for the on-site and
[14:06] (846.84s)
then they regroup and they call some
[14:08] (848.68s)
names to either like go to the next
[14:10] (850.32s)
round or be released and what they say
[14:12] (852.08s)
is that if your name is called to be
[14:13] (853.52s)
released either you crushed it and
[14:14] (854.84s)
you're just hired or you know you failed
[14:17] (857.04s)
obviously it's probably only true that
[14:18] (858.80s)
you failed but I was convinced by that I
[14:20] (860.80s)
thought I crushed my interview I was in
[14:22] (862.16s)
the first group of names no so I was
[14:24] (864.76s)
like I nailed it and then I just waited
[14:26] (866.48s)
for the call I was so confident and then
[14:27] (867.96s)
two weeks later it told me didn't get it
[14:29] (869.56s)
and I was so heartbroken but oh God the
[14:32] (872.36s)
difference in expectations must have
[14:34] (874.08s)
been crazy totally totally and now in
[14:36] (876.24s)
hindsight it's like oh man I must have
[14:38] (878.24s)
totally just blown it and they were nice
[14:39] (879.76s)
to me making me think Ed did well so
[14:41] (881.52s)
what you're saying about paler
[14:43] (883.08s)
absolutely s tier uh company to go to at
[14:46] (886.36s)
the time this was you were 2017 for
[14:49] (889.12s)
Cornell yeah yeah yeah so I was 2017 for
[14:52] (892.24s)
UCLA and yeah I remember paler was one
[14:55] (895.56s)
company that was absolutely s tier which
[14:58] (898.00s)
I feel like people it's no longer that
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prestigious and another one that I
[15:02] (902.24s)
remember was Kora Kora was like oh that
[15:05] (905.04s)
one was really good you should go to
[15:06] (906.72s)
that one that's funny I didn't hear much
[15:08] (908.36s)
about Kora I don't think that was top
[15:09] (909.92s)
the mind for me okay maybe it was like a
[15:11] (911.80s)
California thing the Jane Street Jane
[15:14] (914.16s)
Street yeah Jane Street's always been
[15:15] (915.84s)
all the all of the Quant firms were
[15:17] (917.44s)
really really big I'm sure that probably
[15:19] (919.08s)
still true where you were too but
[15:20] (920.12s)
especially the proximity to to New York
[15:22] (922.16s)
that was really true Cornell at UCLA as
[15:24] (924.44s)
well and when i' I've looked at some
[15:26] (926.32s)
recent day tier lists and aside from the
[15:28] (928.72s)
AI companies coming in those finance
[15:30] (930.84s)
companies are are still you know yeah
[15:32] (932.84s)
they still pay handsomely in cash from
[15:34] (934.40s)
what I understand oh yeah yep I remember
[15:36] (936.68s)
it was like o camel was like the thing
[15:38] (938.68s)
for Jan Street like a little bit yeah
[15:40] (940.40s)
exactly we had an O camel class in
[15:42] (942.40s)
school yeah yeah y y probably just for
[15:44] (944.84s)
that reason okay so you got the meta job
[15:47] (947.76s)
and you graduated and you know so you
[15:50] (950.04s)
started as a newr in ic3 you know I
[15:52] (952.48s)
think one of the first things that
[15:53] (953.48s)
you're faced with is what team do you
[15:55] (955.28s)
pick how' you pick the team that you
[15:57] (957.08s)
ended up going with yeah So Meta used to
[15:58] (958.76s)
Bo Camp they don't have this anymore now
[16:00] (960.44s)
it's team match which is a shame I
[16:02] (962.84s)
understand why they would have gotten
[16:03] (963.64s)
rid of it maybe logistically there's a
[16:05] (965.16s)
lot of overhead you know this well I
[16:07] (967.80s)
love boot both iterations of it but for
[16:09] (969.68s)
those who don't know boot camp was that
[16:11] (971.52s)
you entered kind of Undeclared if you
[16:13] (973.40s)
will to use like college terminology and
[16:15] (975.52s)
you just started by doing a bunch of
[16:16] (976.64s)
tasks and then you eventually started to
[16:18] (978.64s)
whittle down to a handful of teams that
[16:20] (980.16s)
were hiring that you were interested in
[16:21] (981.36s)
you would do some tasks for each of them
[16:22] (982.64s)
respectively and then you got to make
[16:24] (984.28s)
the decision obviously they needed to
[16:26] (986.20s)
also want you it was a bit two-way but
[16:27] (987.84s)
it really felt like you were were in
[16:29] (989.16s)
control you got to try a bunch of things
[16:30] (990.80s)
determine which one you preferred and
[16:32] (992.04s)
then and then join that team and so that
[16:33] (993.40s)
was the case with me and I thought that
[16:34] (994.84s)
I would go the cyber security route
[16:36] (996.36s)
certainly with the the hacking club like
[16:37] (997.96s)
that's what I was passionate about
[16:38] (998.88s)
that's what I was excited about I spent
[16:40] (1000.16s)
all summer hacking doing all these
[16:41] (1001.76s)
things I thought for sure one of the
[16:43] (1003.08s)
reasons I chose meta was boot camp would
[16:44] (1004.60s)
allow me to choose a cyber security team
[16:46] (1006.92s)
and so I thought I would go that route I
[16:48] (1008.44s)
was boot camping with those sorts of
[16:49] (1009.92s)
teams and like it just didn't it didn't
[16:52] (1012.76s)
feel right cyber secur is really low in
[16:54] (1014.56s)
the stack you get a different type of
[16:56] (1016.24s)
folk on the teams in those areas they
[16:58] (1018.36s)
felt less welcoming to me it felt all a
[17:00] (1020.32s)
little bit like more stoic less friendly
[17:02] (1022.60s)
I don't know it didn't resonate and then
[17:04] (1024.08s)
I came across a team that was nothing i'
[17:06] (1026.56s)
had ever considered before but was
[17:07] (1027.72s)
working on things that I found so
[17:09] (1029.16s)
interesting and this was the General org
[17:11] (1031.36s)
was called content integrity and the
[17:12] (1032.96s)
org's mission was to build machine
[17:14] (1034.88s)
learning models to identify and take
[17:17] (1037.00s)
action on violating content and so this
[17:18] (1038.40s)
goes from everything from like hate
[17:19] (1039.52s)
speech to graphic violence to Sude to
[17:22] (1042.40s)
you name it at the time the team that I
[17:24] (1044.00s)
joined and was boot camping with was
[17:26] (1046.12s)
terrorism and it was a new team it was
[17:27] (1047.72s)
being moved from the London office but
[17:29] (1049.12s)
at least to the Seattle office where I
[17:30] (1050.28s)
was it was a brand new team it didn't
[17:31] (1051.36s)
have any Engineers yet it had one
[17:32] (1052.76s)
manager and they were the manager of a
[17:35] (1055.16s)
different team as well so they were kind
[17:36] (1056.48s)
of just standing it up until they hired
[17:38] (1058.12s)
a real manager or a full-time manager
[17:40] (1060.28s)
and then there was one engineer who was
[17:41] (1061.64s)
like half Tech leading it while also
[17:43] (1063.16s)
working on another another team I
[17:45] (1065.68s)
thought who doesn't want to fight that
[17:47] (1067.60s)
sounds that sounds pretty awesome
[17:49] (1069.40s)
machine learning Cutting Edge cool
[17:51] (1071.36s)
content Integrity had a bunch of young
[17:52] (1072.76s)
people that I felt like I could really
[17:54] (1074.36s)
relate to made the decision to go that
[17:55] (1075.72s)
way was your boot camp in mpk at menla
[17:58] (1078.12s)
Park or was it in uh Seattle so the way
[18:00] (1080.52s)
that we did it cuz I was out of the
[18:01] (1081.36s)
Seattle office we did two two week
[18:04] (1084.00s)
stints in mpk and then the rest of it
[18:05] (1085.96s)
was out of Seattle so I guess half and
[18:08] (1088.36s)
half how did you go about cuz I remember
[18:10] (1090.36s)
at the time they gave us a few different
[18:12] (1092.32s)
things you could choose from in terms of
[18:14] (1094.64s)
you could be an Android engineer you
[18:16] (1096.68s)
could be iOS you could be systems which
[18:18] (1098.92s)
is just generic term for backend there's
[18:21] (1101.44s)
also the other distinction of like do
[18:23] (1103.28s)
you want to work on product or do you
[18:25] (1105.04s)
want to work on I guess more
[18:26] (1106.64s)
infrastructure stuff so were you
[18:28] (1108.28s)
thinking about where you wanted to place
[18:30] (1110.24s)
yourself in terms of tech stack I think
[18:32] (1112.00s)
not Beyond I came in just like thinking
[18:33] (1113.96s)
of myself as a backend engineer and so I
[18:36] (1116.32s)
just sort of gravitated to the problems
[18:38] (1118.16s)
that were like that and I know that now
[18:39] (1119.68s)
meta like draws the distinction between
[18:41] (1121.60s)
when you interview even sweet products s
[18:44] (1124.24s)
generalists obviously there's always
[18:45] (1125.96s)
been the front-end iOS you know versions
[18:47] (1127.92s)
as well or categories as well yeah I
[18:49] (1129.24s)
don't know it wasn't a conscious
[18:50] (1130.68s)
decision for me was that something that
[18:51] (1131.96s)
that you thought a lot about I think yes
[18:53] (1133.76s)
so my team matching situation I mean I
[18:55] (1135.92s)
went through through boot camp as well
[18:57] (1137.64s)
because I was also at meta I remember
[18:59] (1139.64s)
thinking of a few things one was like
[19:02] (1142.16s)
the product versus infrastructure
[19:04] (1144.16s)
decision and at the time as a newr I
[19:07] (1147.28s)
didn't really know what type of work to
[19:09] (1149.80s)
expect or what it even meant down the
[19:12] (1152.32s)
the road I was just kind of making
[19:13] (1153.64s)
decisions without a whole lot of context
[19:16] (1156.32s)
based on what I thought sounded cool so
[19:18] (1158.04s)
I was thinking oh okay product is it's
[19:21] (1161.28s)
like fun and it's like it's like front
[19:23] (1163.64s)
end was my understanding and front end
[19:25] (1165.68s)
did not appeal to me I was wrong I mean
[19:28] (1168.12s)
product can be very deeply Technical and
[19:30] (1170.04s)
interesting I was wrong but I ended up
[19:32] (1172.88s)
choosing infrastructure even the word
[19:34] (1174.88s)
itself sounds Technical and cool totally
[19:37] (1177.52s)
yeah yeah I mean there is that sign yeah
[19:39] (1179.36s)
exactly so I was like okay I'm I'm going
[19:41] (1181.76s)
towards infrastructure teams you know
[19:43] (1183.52s)
when you think about infrastructure you
[19:44] (1184.76s)
also think about systems a lot of times
[19:46] (1186.68s)
and then the other distinction that kind
[19:48] (1188.36s)
of like led me to where I was was what
[19:52] (1192.76s)
organization that I want to be a part of
[19:54] (1194.76s)
so you know there's WhatsApp teams you
[19:56] (1196.96s)
could work on the Blue app it's Facebook
[19:59] (1199.28s)
you could work on Instagram and
[20:01] (1201.28s)
Instagram at the time was the relatively
[20:03] (1203.96s)
new acquisition uh Founders were still
[20:06] (1206.52s)
there yeah and it was it was hot it was
[20:09] (1209.20s)
this cool product you know people people
[20:11] (1211.12s)
generally liked Instagram then and the
[20:13] (1213.72s)
Facebook ad was kind of this bloated
[20:15] (1215.20s)
thing that old people use I don't know I
[20:17] (1217.40s)
was thinking okay I want to go to
[20:18] (1218.44s)
Instagram and so that's how I ended up
[20:20] (1220.28s)
picking an Instagram infra team and I
[20:24] (1224.04s)
remember at the time the manager that I
[20:26] (1226.80s)
reached out to actually did didn't have
[20:29] (1229.04s)
headcount for me but I I begged him
[20:31] (1231.28s)
because I said I really want to go to uh
[20:34] (1234.48s)
an infrastructure to I really want to
[20:35] (1235.92s)
work at Instagram I promise you I'm
[20:37] (1237.52s)
going to really work as hard as I can
[20:39] (1239.48s)
please please please and he had some
[20:41] (1241.56s)
flexibility he was able to I guess
[20:43] (1243.60s)
borrow uh headcount from someone or
[20:45] (1245.80s)
something because when I met with him he
[20:48] (1248.12s)
really felt uh how how Earnest I was
[20:51] (1251.36s)
there I think that's one thing that I
[20:52] (1252.80s)
learned in my career journey is
[20:55] (1255.12s)
oftentimes the best opportunities are
[20:57] (1257.52s)
not the ones that seek you out but the
[20:59] (1259.56s)
ones that you seek out because the ones
[21:01] (1261.48s)
that are seeking you out often times
[21:03] (1263.20s)
they're in a you know position of less
[21:05] (1265.24s)
strength they just need someone and the
[21:07] (1267.16s)
ones that are really great they have all
[21:08] (1268.92s)
these people coming to them so you
[21:10] (1270.28s)
really got to like battle your way into
[21:11] (1271.92s)
them but it was totally worth it and I
[21:13] (1273.88s)
absolutely loved that team and I stayed
[21:15] (1275.84s)
at it the whole time and that that
[21:17] (1277.20s)
moment of agency I'm sure like
[21:18] (1278.80s)
translated throughout your your whole
[21:20] (1280.52s)
career and that definitely resonated
[21:21] (1281.84s)
with me it's it's sort of this aspect of
[21:24] (1284.00s)
like you got to go take it it's not
[21:25] (1285.52s)
necessarily going to fall on your lap
[21:26] (1286.88s)
and so if that seemed like the right fit
[21:28] (1288.16s)
for you and you went in and and you sort
[21:30] (1290.12s)
of demanded that you take it and it
[21:31] (1291.68s)
worked out which is huge yeah yeah
[21:33] (1293.40s)
definitely agency is a huge part of
[21:36] (1296.84s)
actually capitalizing on opportunity so
[21:39] (1299.04s)
much of this stuff is luck and
[21:40] (1300.72s)
opportunity and if you have that extra
[21:43] (1303.40s)
agency to go and take initiative and
[21:45] (1305.48s)
seek things out you can turn things that
[21:47] (1307.68s)
were NOS into yeses oh in this case yeah
[21:51] (1311.24s)
someone might not have you know might
[21:52] (1312.96s)
have politely said oh okay you don't
[21:54] (1314.24s)
have head count and like search
[21:55] (1315.44s)
somewhere else but I was I was
[21:56] (1316.84s)
aggressive starting at meta you're
[21:59] (1319.28s)
you're on the team I think you mentioned
[22:01] (1321.72s)
to me something all it says in our
[22:03] (1323.92s)
outline is penis story I lit I laughed
[22:07] (1327.36s)
when I saw that what what is this and
[22:09] (1329.72s)
how is this relevant to to your
[22:11] (1331.56s)
onboarding at meta so when I when I
[22:14] (1334.32s)
first joing the team one of the largest
[22:16] (1336.16s)
portions of content integrity was
[22:17] (1337.64s)
pornography it was the main thing that
[22:20] (1340.60s)
that started Mak sense right making sure
[22:23] (1343.68s)
that the site didn't have any
[22:24] (1344.44s)
pornography and so like when you're a
[22:26] (1346.68s)
new nrad I don't know it's just you
[22:28] (1348.60s)
don't expect to see like penises at work
[22:31] (1351.48s)
or any nudity at work right um and I
[22:34] (1354.00s)
have this distinct memory of the first
[22:35] (1355.48s)
time where I had just joined the team I
[22:36] (1356.88s)
was trying to get up to speed and I went
[22:38] (1358.32s)
up to one of my colleagues who worked on
[22:41] (1361.04s)
the porn team again I was the only one
[22:42] (1362.40s)
at this point on the terrorism team so I
[22:43] (1363.72s)
was kind of relying on them for
[22:44] (1364.80s)
expertise and I went over there and sat
[22:46] (1366.20s)
next to him to try to ask some questions
[22:47] (1367.60s)
and he's got his two big monitors and
[22:49] (1369.32s)
one of them's got all the code that he's
[22:50] (1370.60s)
been working on and the other one is
[22:51] (1371.80s)
just the entire screen filling the
[22:55] (1375.32s)
entire screen and I'm like trying not to
[22:57] (1377.76s)
look it's incredible shocking and like
[22:59] (1379.52s)
jarring to me but this is his every day
[23:02] (1382.88s)
you know so to him he didn't even think
[23:04] (1384.52s)
twice or notice it I don't know but
[23:06] (1386.20s)
there was something about it that was
[23:07] (1387.68s)
just like I loved that story afterwards
[23:09] (1389.40s)
I went home I told all my friends I
[23:10] (1390.76s)
thought it was you know so hysterical
[23:12] (1392.92s)
and then it kind of became I don't know
[23:15] (1395.68s)
indicative of like the organization and
[23:18] (1398.12s)
the team as a as a whole that like you
[23:21] (1401.28s)
become desensitized to that stuff you're
[23:22] (1402.84s)
doing your job it's it's no longer silly
[23:24] (1404.60s)
it's no longer funny but it was a it was
[23:26] (1406.44s)
a shocking and memorable moment from my
[23:28] (1408.16s)
first stays there that's for sure that's
[23:30] (1410.40s)
hilarious just seeing that on the screen
[23:32] (1412.76s)
in like a work environment it's kind of
[23:34] (1414.32s)
crazy it was really funny and they they
[23:35] (1415.68s)
hide Us in that Seattle office they hit
[23:37] (1417.56s)
us in the second floor in the corner oh
[23:39] (1419.28s)
really you think that was intentional
[23:40] (1420.72s)
yeah totally at least that's what the
[23:42] (1422.08s)
people before me said was the case so
[23:44] (1424.04s)
that nobody ever had to walk past those
[23:45] (1425.80s)
desks oh that's so funny and just be
[23:48] (1428.20s)
shocked because the nudity is the nudity
[23:49] (1429.96s)
is you know Silly and and largely funny
[23:52] (1432.28s)
but you know there are plenty of things
[23:53] (1433.80s)
that are much more jarring that's
[23:55] (1435.24s)
hilarious okay so sounds like your team
[23:56] (1436.68s)
had a pretty good like social VI on it
[23:59] (1439.56s)
yeah totally when you got there you
[24:01] (1441.28s)
mentioned that you were working on the
[24:03] (1443.16s)
terrorist side of things um can you tell
[24:05] (1445.68s)
a little bit about like the technical
[24:07] (1447.00s)
side just in case someone's curious in
[24:08] (1448.52s)
the audience like what what exactly you
[24:10] (1450.56s)
were working on is like some backend
[24:12] (1452.20s)
system or yeah exactly so was backend
[24:14] (1454.16s)
system this was mostly hacked is you
[24:16] (1456.56s)
know Facebook's types safe PHP maybe not
[24:18] (1458.84s)
directly my first project but like my
[24:20] (1460.72s)
first substantial project was to work on
[24:23] (1463.16s)
this thing that we we named Estuary and
[24:25] (1465.20s)
Estuary is the point where multiple
[24:27] (1467.00s)
Rivers kind of come and join together um
[24:30] (1470.08s)
and ultimately what it was was the
[24:31] (1471.68s)
infrastructure in order to detect
[24:34] (1474.16s)
terrorist content and so it's this
[24:36] (1476.04s)
multi-staged funnel you initially run
[24:38] (1478.16s)
some kind of crude checks on content
[24:39] (1479.84s)
that are really quick in order to
[24:41] (1481.04s)
determine whether they're worth further
[24:42] (1482.64s)
considering and running your expensive
[24:43] (1483.96s)
models on some photo matching happens at
[24:46] (1486.76s)
that point you make a determination
[24:48] (1488.12s)
based on the scores the models the photo
[24:49] (1489.96s)
matching if you need to take any given
[24:51] (1491.48s)
actions if something needs to go to
[24:53] (1493.04s)
human review how many human
[24:55] (1495.32s)
reviews uh you know combination of those
[24:57] (1497.56s)
reviews ultimately to an action as well
[24:59] (1499.72s)
and so this was the infrastructure to
[25:01] (1501.96s)
facilitate that process and try to make
[25:03] (1503.88s)
it as easy as possible for us as the
[25:06] (1506.24s)
team to experiment plugging in playing
[25:08] (1508.68s)
different models changing thresholds
[25:10] (1510.68s)
running AB tests all of these things
[25:12] (1512.72s)
kind of getting into the promos like
[25:14] (1514.08s)
your first promo was super fast I think
[25:17] (1517.12s)
one thing that's interesting though to
[25:18] (1518.88s)
to think about is was that something
[25:21] (1521.00s)
that you asked your manager about and
[25:23] (1523.40s)
you were in touch the whole way or did
[25:25] (1525.08s)
it kind of just happen it definitely
[25:27] (1527.24s)
just happened that wouldn't be my advice
[25:28] (1528.68s)
to people normally but like looking back
[25:30] (1530.88s)
at that point in my career I was still I
[25:32] (1532.48s)
was new and I was like shy and had my
[25:34] (1534.44s)
insecurities like everybody else and
[25:36] (1536.32s)
that was a a big moment that stuck with
[25:38] (1538.04s)
me there were a couple moments of like
[25:39] (1539.68s)
confidence building that happened early
[25:41] (1541.12s)
in my career which I think were super
[25:42] (1542.52s)
necessary for me to go on and and maybe
[25:45] (1545.12s)
kind of achieve the promotions that they
[25:46] (1546.52s)
were ultimately achieved and at least in
[25:48] (1548.56s)
this case that promo happened my first
[25:50] (1550.64s)
half you know six months or so after
[25:52] (1552.40s)
after being at the company I never
[25:53] (1553.88s)
talked about promo I didn't know how
[25:55] (1555.20s)
well I was doing I thought I was doing a
[25:56] (1556.68s)
good job but like I don't know relative
[25:58] (1558.36s)
to everybody else I figure everyone
[25:59] (1559.76s)
around me is really smart and they
[26:00] (1560.80s)
certainly were um and then I got pulled
[26:03] (1563.72s)
into a room with my manager he gave me a
[26:05] (1565.52s)
bunch of compliments tell me I was doing
[26:06] (1566.92s)
great I felt really good and then he
[26:08] (1568.64s)
said you're promoted and it's nothing I
[26:11] (1571.00s)
had even considered he showed me the new
[26:13] (1573.40s)
salary the new equity and I was like oh
[26:15] (1575.68s)
my gosh holy smokes what just happened
[26:19] (1579.36s)
like this is insane I was like shaking
[26:22] (1582.28s)
with giddiness uh it was it was a it was
[26:25] (1585.24s)
a pretty cool experience but it was a as
[26:28] (1588.52s)
I said it was a huge confidence gaining
[26:30] (1590.24s)
moment because from that moment on I had
[26:31] (1591.96s)
the assurance that I was good and I was
[26:34] (1594.08s)
capable and then now I was like sort of
[26:35] (1595.56s)
freed of that anxiety questioning
[26:37] (1597.40s)
whether or not I was good enough and was
[26:39] (1599.20s)
free to just kind of continue to to grow
[26:41] (1601.96s)
at that pace and did you intern that
[26:43] (1603.96s)
Facebook but beforehand no so I interned
[26:46] (1606.28s)
at Zillow beforehand okay the other
[26:49] (1609.00s)
confidence gaining moment that really
[26:50] (1610.96s)
comes to my mind was actually at Zillow
[26:52] (1612.60s)
and so that I entered Zillow now it's
[26:55] (1615.20s)
even before meta so I'm like maybe more
[26:56] (1616.88s)
insecure working work on on what I need
[26:59] (1619.04s)
to work on got my project done quickly
[27:00] (1620.72s)
like you said you did with yours at
[27:02] (1622.28s)
Bloomberg worked on a bunch of things
[27:03] (1623.84s)
that had nothing to do with my product
[27:05] (1625.48s)
but were really fun and then I remember
[27:07] (1627.24s)
distinctly my manager at the end of at
[27:10] (1630.08s)
the end of The Internship both getting
[27:12] (1632.08s)
the return offer and then him who had
[27:13] (1633.92s)
worked at Google for a long time and
[27:15] (1635.20s)
then I was at Zillow saying that I was
[27:17] (1637.00s)
the the best intern he had ever worked
[27:18] (1638.84s)
with Wow and that was just like the I
[27:21] (1641.52s)
think to this day probably the biggest
[27:22] (1642.76s)
one of the biggest compliments I ever
[27:24] (1644.08s)
got like I was just beaming and I felt
[27:26] (1646.36s)
like I felt so good and so confident
[27:27] (1647.96s)
coming out of that and so I was able to
[27:29] (1649.76s)
ride that confidence into meta and then
[27:31] (1651.24s)
of course you still have a bit of the
[27:32] (1652.24s)
insecurity and then this moment with my
[27:34] (1654.00s)
manager really kind of solidified that
[27:35] (1655.52s)
confidence so what is the thing that you
[27:37] (1657.88s)
were doing so early in your career that
[27:40] (1660.48s)
made both of these
[27:42] (1662.64s)
managers you know say you were the best
[27:45] (1665.08s)
intern or best you know one of the best
[27:47] (1667.80s)
early people they were working with I
[27:49] (1669.44s)
think the biggest thing was that I was
[27:50] (1670.60s)
just like inquisitive and didn't feel
[27:52] (1672.64s)
bounded by what I was told to do and so
[27:55] (1675.00s)
at least at Zillow I finished my project
[27:56] (1676.84s)
pretty quickly and then I was working on
[27:59] (1679.04s)
the rental steam it had nothing to do
[28:00] (1680.40s)
with security but security stuff was
[28:02] (1682.00s)
interesting to me and I saw all these
[28:03] (1683.36s)
posters around the office about how
[28:05] (1685.16s)
people shouldn't leave their computers
[28:06] (1686.72s)
unlocked when they go to the bathroom or
[28:08] (1688.32s)
go to lunch or anything like this people
[28:09] (1689.60s)
would leave their screens open security
[28:11] (1691.48s)
concern and so I threw together a fun
[28:13] (1693.72s)
game where if somebody's screen was open
[28:16] (1696.00s)
then you could go to a certain website
[28:17] (1697.76s)
hosted internally and then like kind of
[28:19] (1699.92s)
get them if you will and so then you had
[28:22] (1702.52s)
like a leaderboard and you had like cute
[28:24] (1704.08s)
graphs about who left their screen open
[28:25] (1705.64s)
and who have been got more than anyone
[28:26] (1706.80s)
else and who was getting people and like
[28:28] (1708.24s)
became this fun little thing in the
[28:29] (1709.52s)
office and that's what I spent most of
[28:31] (1711.08s)
my time doing and then I would hang out
[28:32] (1712.88s)
a bunch with the cyber security folks
[28:35] (1715.08s)
and like they took me to Defcon in Las
[28:37] (1717.36s)
Vegas um totally not my team nothing to
[28:39] (1719.92s)
do with rentals or anything um but like
[28:42] (1722.72s)
I was just looking for other
[28:43] (1723.68s)
opportunities to seek out stuff that was
[28:45] (1725.64s)
fun to me and the same was true when
[28:47] (1727.84s)
first joining meta I think actually the
[28:49] (1729.60s)
the article that you published on on
[28:51] (1731.08s)
your substack I'm sure we'll link that
[28:53] (1733.64s)
below or something talks about my very
[28:55] (1735.56s)
first project at meta or again I I
[28:57] (1737.64s)
finished it is pretty quickly and then
[28:59] (1739.04s)
had all this time to improve it do
[29:01] (1741.24s)
things that I thought were fun and
[29:02] (1742.24s)
outside of the scope of the original
[29:03] (1743.52s)
task you know when we published that
[29:05] (1745.28s)
article there was that was probably the
[29:07] (1747.40s)
thing people asked the most about which
[29:09] (1749.40s)
was you said hey do your work fast and
[29:12] (1752.12s)
that gives you this budget of time to
[29:14] (1754.68s)
Excel and do all these other things
[29:16] (1756.96s)
which lead to the career growth but that
[29:18] (1758.92s)
was the big thing that people wanted to
[29:20] (1760.76s)
know more about which was how do you get
[29:23] (1763.60s)
through your assigned projects and your
[29:26] (1766.56s)
initial code and all the things that
[29:28] (1768.24s)
expected of you so fast is there
[29:30] (1770.32s)
anything that you might say to the
[29:32] (1772.92s)
audience for that I understand where the
[29:34] (1774.24s)
question is coming from I I hate it
[29:36] (1776.48s)
largely because like I don't know and it
[29:38] (1778.84s)
almost makes me feel like held up in
[29:40] (1780.36s)
this status that I I don't know doesn't
[29:42] (1782.36s)
doesn't feel all that deserved I feel
[29:43] (1783.76s)
like it just happen I'm interested to
[29:45] (1785.92s)
hear your thoughts because I know this
[29:47] (1787.40s)
was true for you as well and then maybe
[29:50] (1790.28s)
as you're answering it I'll I'll come up
[29:52] (1792.12s)
with something that that could be useful
[29:54] (1794.40s)
but I know you had the same experience
[29:56] (1796.12s)
yeah so I definitely had a similar
[29:58] (1798.44s)
experience when I joined Instagram I was
[30:02] (1802.56s)
an absolute Workhorse and I was just
[30:05] (1805.36s)
churning out anything that anyone gave
[30:07] (1807.76s)
me there's two aspects to this one is
[30:11] (1811.08s)
doing the work quickly and I think that
[30:13] (1813.32s)
to some extent you know having all my
[30:14] (1814.92s)
key bindings be super fast and you know
[30:17] (1817.60s)
making sure my workflow is really dialed
[30:19] (1819.64s)
in like I have everything memorized I
[30:21] (1821.80s)
can you know fire off a diff in like 10
[30:24] (1824.32s)
minutes or something and really know
[30:26] (1826.44s)
where everything is in the code base
[30:28] (1828.48s)
and that comes with just spending a lot
[30:30] (1830.92s)
of time in like really knowing your area
[30:33] (1833.20s)
and becoming kind of like the go-to
[30:34] (1834.80s)
person there you know when you first
[30:36] (1836.32s)
start someone tells you something you
[30:37] (1837.84s)
don't know where it is and you're kind
[30:39] (1839.16s)
of just trying to figure out what's
[30:40] (1840.12s)
going on but at some point you get so
[30:42] (1842.32s)
dialed in that someone says we need to
[30:44] (1844.76s)
make that tweak and you know exactly
[30:46] (1846.60s)
where is the exact line of code and you
[30:49] (1849.24s)
just you can just fire it off so at some
[30:51] (1851.52s)
point I got that so dialed in that I was
[30:54] (1854.40s)
I looked at my old diff count and it was
[30:57] (1857.04s)
like 10 diffs a day at some point cuz I
[30:59] (1859.24s)
had a very coding heaving project at
[31:00] (1860.96s)
some point I think it's like the second
[31:02] (1862.88s)
half of my junior engineer stint um so
[31:06] (1866.04s)
there's that aspect but the other thing
[31:07] (1867.80s)
too is like if you want an extra 30% of
[31:10] (1870.80s)
time you can also just work an extra 30%
[31:13] (1873.64s)
um that's the answer nobody ever wants
[31:15] (1875.92s)
to hear yeah you don't need to be
[31:18] (1878.32s)
brilliant I I'll say um and I definitely
[31:21] (1881.20s)
did that I was an absolute monster I
[31:23] (1883.52s)
would get in not too early I don't know
[31:25] (1885.08s)
like 10:00 a.m. or something but I leave
[31:27] (1887.08s)
on the absolute latest shuttle which I
[31:28] (1888.96s)
still remember to this day it was like
[31:30] (1890.28s)
9:27 p.m. the important thing there must
[31:32] (1892.56s)
have been that you were enjoying it
[31:33] (1893.80s)
right cuz I think that's the fine line
[31:35] (1895.24s)
and that's where the advice becomes kind
[31:36] (1896.96s)
of dangerous maybe for sure I think like
[31:39] (1899.28s)
because everything was so new and you're
[31:40] (1900.72s)
in like this big area and it's you're
[31:43] (1903.04s)
it's just fun kind of like getting
[31:44] (1904.76s)
really dialed in and firing out all that
[31:46] (1906.92s)
code you know as a byproduct whether you
[31:48] (1908.60s)
enjoyed it or not if you do spend an
[31:50] (1910.92s)
extra 30% a time yeah you can use that
[31:54] (1914.28s)
to grow it's almost like this budget of
[31:56] (1916.44s)
extra stuff that you can do yeah I guess
[31:58] (1918.24s)
there's two ways to it you can you can
[32:00] (1920.60s)
really dial in and like you know submit
[32:02] (1922.88s)
code more quickly which comes with time
[32:05] (1925.16s)
and like really thinking critically
[32:06] (1926.88s)
about your workflow but the other thing
[32:08] (1928.72s)
too is you can you know work work extra
[32:11] (1931.12s)
and it's it's way better working extra
[32:13] (1933.20s)
when you enjoy it yeah you're going to
[32:15] (1935.12s)
hate your life if you hate submitting
[32:17] (1937.00s)
the code but you're doing it anyways
[32:18] (1938.44s)
totally totally I think the the two
[32:20] (1940.16s)
things that came to mind for me there as
[32:21] (1941.88s)
you were sharing all that was the first
[32:24] (1944.00s)
one the workflow is so important and for
[32:26] (1946.32s)
me it was a memory thing actually don't
[32:28] (1948.08s)
I don't have the best memory but I'm
[32:29] (1949.48s)
good at using resources in order to tell
[32:31] (1951.40s)
me remember things so at my time at
[32:33] (1953.76s)
Zillow and at school like I had a I
[32:35] (1955.92s)
built a fun little project I think it
[32:37] (1957.68s)
was a variant of Lucine at the time I'm
[32:40] (1960.00s)
not sure but it was my own like little
[32:41] (1961.56s)
personal hosted search engine and I
[32:43] (1963.32s)
would just put mark down stuff in there
[32:44] (1964.92s)
that I need to remember and then I could
[32:46] (1966.08s)
like quickly search it and and find it
[32:48] (1968.08s)
fun enough right you can't use that at
[32:49] (1969.84s)
meta but it's not all too difficult to
[32:51] (1971.88s)
like recreate some variation of that
[32:53] (1973.60s)
even with just like a control F and and
[32:55] (1975.28s)
some markdown files anytime I solved the
[32:57] (1977.08s)
problem I would write it down
[32:58] (1978.68s)
and then I never needed to struggle to
[33:00] (1980.76s)
solve a problem twice which was really
[33:02] (1982.52s)
important and that speeds things up
[33:04] (1984.28s)
significantly and then the other thing
[33:06] (1986.20s)
that stood out and this I more observed
[33:08] (1988.68s)
with mentees that I had or other folks
[33:11] (1991.12s)
on the team was that I guess naturally I
[33:14] (1994.04s)
just I had the ability to not let things
[33:17] (1997.16s)
stop me and so I'm sure this will
[33:18] (1998.40s)
resonate with you too but there's plenty
[33:19] (1999.72s)
of times for which I would see a mentee
[33:21] (2001.48s)
and they got stuck and they'd like try
[33:23] (2003.00s)
to research it they would be a little
[33:24] (2004.20s)
nervous like do I ask the senior
[33:25] (2005.88s)
engineer now or are they busy do I do
[33:27] (2007.84s)
this do I do that and I felt pretty
[33:29] (2009.64s)
comfortable just spending like an hour
[33:31] (2011.04s)
trying to answer the question and then
[33:32] (2012.96s)
asking someone you don't want to be that
[33:34] (2014.24s)
annoying guy that's always asking things
[33:36] (2016.00s)
but like the ability to find the person
[33:37] (2017.64s)
at the company that knows and get the
[33:39] (2019.32s)
answer from them and this isn't just
[33:40] (2020.44s)
true a junior this is true staff and
[33:42] (2022.48s)
Beyond I'm sure is a super powerful
[33:44] (2024.08s)
skill and that's just like kind of
[33:45] (2025.08s)
having the confidence to know it's
[33:46] (2026.52s)
reasonable I don't know this let me ask
[33:48] (2028.32s)
someone who does and let me write it
[33:50] (2030.08s)
down and keep moving that second one is
[33:52] (2032.36s)
is huge it can be so impactful because
[33:55] (2035.16s)
if you get blocked it could take you
[33:56] (2036.92s)
days to do something that someone else
[33:59] (2039.00s)
can do in an hour or something you know
[34:01] (2041.20s)
if you go to the senior person that
[34:02] (2042.92s)
really already knows the code base you
[34:04] (2044.56s)
the exact code pointer tell you exactly
[34:06] (2046.92s)
what to change instead of you doing like
[34:09] (2049.28s)
a blind Brute Force search you can speed
[34:11] (2051.64s)
up by days and that is actually way more
[34:14] (2054.52s)
impactful than small workflow
[34:16] (2056.92s)
improvements and things like that so and
[34:19] (2059.16s)
yeah that is kind of like a soft skill
[34:21] (2061.16s)
thing where knowing that it's reasonable
[34:23] (2063.52s)
to ask knowing how to ask in a way that
[34:26] (2066.24s)
is uh welcomed I think that's that's
[34:28] (2068.92s)
huge especially for for the early levels
[34:31] (2071.36s)
and then maybe the last one here not to
[34:33] (2073.72s)
kind of beat a dead horse on this topic
[34:35] (2075.56s)
but being able to search the code base I
[34:37] (2077.68s)
think that was something that I wasbe
[34:39] (2079.72s)
uniquely Adept at early too you know a
[34:42] (2082.60s)
meta it's monolith we have the entire
[34:44] (2084.92s)
code base at your fingertips and the
[34:46] (2086.56s)
chances that you're solving something
[34:47] (2087.84s)
for the first time is almost none
[34:50] (2090.28s)
somebody has almost certainly done it or
[34:52] (2092.00s)
done something similar and so knowing
[34:53] (2093.56s)
what to be able to search for and
[34:55] (2095.08s)
sometimes this is just like guessing as
[34:56] (2096.76s)
to what people might have named
[34:58] (2098.08s)
functions or variables and you're
[34:59] (2099.96s)
hunting for just that piece of code that
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resembles a similar challenge to what
[35:04] (2104.16s)
you have in front of you and being good
[35:05] (2105.28s)
at that searching process is is honestly
[35:07] (2107.40s)
a huge accelerate 100% And if you're
[35:09] (2109.80s)
really good at code search it is so
[35:11] (2111.92s)
impactful for the later levels too
[35:13] (2113.76s)
because often times the later levels
[35:15] (2115.24s)
you're just trying to figure out where
[35:16] (2116.68s)
to make changes and how to make changes
[35:18] (2118.56s)
and figure out ambiguity and like
[35:20] (2120.20s)
where's the problem understanding qu
[35:22] (2122.00s)
bookly yeah exactly and code search is
[35:24] (2124.28s)
like one of the absolute Peak skills to
[35:27] (2127.20s)
to really B so yeah that was pretty good
[35:29] (2129.32s)
for for the junior side of things moving
[35:31] (2131.32s)
on to the next one in terms of promo
[35:33] (2133.40s)
from midlevel to senior I'm curious what
[35:36] (2136.12s)
is the what were the main differences in
[35:38] (2138.60s)
this one and what is the story behind
[35:40] (2140.36s)
that promotion I guess the first place
[35:41] (2141.80s)
that I would start is that the team had
[35:43] (2143.32s)
grown now so we were talking about how I
[35:44] (2144.80s)
was the first engineer on the team it
[35:46] (2146.40s)
only took a week or two until we hired
[35:48] (2148.08s)
the first senior engineer on the team
[35:50] (2150.00s)
couple weeks later we had another one
[35:51] (2151.72s)
now the team's 8 n it's got the
[35:53] (2153.40s)
full-time manager that came in I think
[35:55] (2155.28s)
because even though like you know the
[35:57] (2157.32s)
team at one point was three senior
[35:58] (2158.80s)
engineers and me as the junior engineer
[36:00] (2160.48s)
because I was there first even if it was
[36:01] (2161.88s)
just a couple weeks I felt like I had
[36:03] (2163.84s)
the context and I was like helping them
[36:06] (2166.44s)
ramp up sort of was probably more in my
[36:09] (2169.08s)
head than anything else but at least
[36:10] (2170.12s)
helping them with with context and that
[36:12] (2172.00s)
was super valuable like both in terms of
[36:13] (2173.88s)
having the confidence and just like
[36:15] (2175.80s)
really understanding the the code base
[36:17] (2177.60s)
more than more than most people and so
[36:19] (2179.16s)
the teamate continue to grow and content
[36:20] (2180.96s)
integrity was growing like crazy and we
[36:23] (2183.00s)
have more and more violation types that
[36:24] (2184.64s)
we needed to support the terrorism team
[36:26] (2186.56s)
had been morphed and changed and now
[36:28] (2188.40s)
like split into at the time three teams
[36:30] (2190.40s)
terrorism child exploitation imagery the
[36:33] (2193.00s)
really bad stuff and then graphic
[36:34] (2194.56s)
violence and graphic violence was sort
[36:36] (2196.68s)
of like the lowest priority of the group
[36:38] (2198.96s)
and so it kind of got carved off and my
[36:41] (2201.64s)
manager asked me if I wanted to be the
[36:43] (2203.76s)
tech lead for the graphic violence team
[36:45] (2205.48s)
and I didn't know what tech lead was I
[36:47] (2207.12s)
didn't know what that mean it sounded
[36:48] (2208.20s)
cool it sounded fancy it turns out it's
[36:50] (2210.28s)
not actually even a real thing at meta
[36:52] (2212.56s)
like it's a it's not a title that shows
[36:54] (2214.80s)
up anywhere it's not formal it's uh you
[36:57] (2217.76s)
know it's largely made up in Optics but
[36:59] (2219.76s)
like to me it felt so big and cool and
[37:02] (2222.48s)
and Powerful I don't I don't love saying
[37:04] (2224.80s)
that word but you know it felt it felt
[37:06] (2226.44s)
that way and so the team had three
[37:07] (2227.96s)
Engineers myself a junior engineer and a
[37:11] (2231.16s)
and a mid-level PhD research scientist
[37:13] (2233.64s)
and it was the three of us tasked with
[37:15] (2235.80s)
solving quote unquote graphic violence
[37:17] (2237.64s)
problems at meta and this was the
[37:19] (2239.24s)
process of detecting if things were
[37:20] (2240.48s)
graphic in most cases putting a warning
[37:22] (2242.20s)
screen or an intertial over it uh in the
[37:24] (2244.48s)
extreme cases deleting the content and
[37:26] (2246.52s)
so like I really took to this this
[37:27] (2247.80s)
leadership role so I got to kind of lean
[37:30] (2250.60s)
on some of those skills learn during the
[37:32] (2252.00s)
hacking Club days and now I'm
[37:34] (2254.08s)
proactively setting up weekly meetings
[37:36] (2256.04s)
for the team helping management with
[37:37] (2257.76s)
laying out our road map even having
[37:39] (2259.64s)
one-on ones with both of my teammates
[37:41] (2261.60s)
weekly which was a cool and new
[37:43] (2263.16s)
experience for me and like this was
[37:44] (2264.64s)
really the transformative moment in my
[37:46] (2266.04s)
career where I grew more of those
[37:47] (2267.20s)
leadership skills and if not grow I was
[37:49] (2269.56s)
able to at least Express those
[37:50] (2270.96s)
leadership skills and of course there
[37:52] (2272.04s)
was a ton of growth in here as well and
[37:53] (2273.76s)
then graphic violence like continued to
[37:55] (2275.04s)
do pretty well our our stats looked good
[37:57] (2277.20s)
and so we took a project that was like
[37:59] (2279.40s)
it wasn't dying it was just
[38:00] (2280.32s)
underinvested in and we increased our
[38:02] (2282.56s)
precision and recall numbers to to to
[38:04] (2284.28s)
something I wouldn't be able to quote
[38:05] (2285.28s)
now because I don't remember well enough
[38:06] (2286.84s)
but we did a great job and I think that
[38:08] (2288.24s)
it was on account of my leadership there
[38:11] (2291.08s)
and the fact that I was directly leading
[38:12] (2292.80s)
other Engineers doing one-on-one setting
[38:14] (2294.84s)
team directions road map these are all
[38:16] (2296.36s)
qualities of of senior Engineers I can't
[38:18] (2298.96s)
remember well enough if we expanded as
[38:21] (2301.00s)
well at this point to have more than
[38:22] (2302.24s)
just two Engineers before the promotion
[38:23] (2303.96s)
it's quite possible that was the case
[38:25] (2305.56s)
but I can't remember yeah I think that's
[38:26] (2306.76s)
the tldr the promo pack there that's an
[38:28] (2308.96s)
absolute no-brainer ic5 promo or senior
[38:32] (2312.12s)
promo and that is really interesting cuz
[38:34] (2314.56s)
you were just just a year out of college
[38:36] (2316.76s)
at that point to be able to step into a
[38:39] (2319.44s)
leadership role like that is pretty
[38:41] (2321.36s)
extraordinary one thing that I'm curious
[38:43] (2323.20s)
about is your manager gave you the
[38:46] (2326.80s)
opportunity so it's not like you found
[38:49] (2329.00s)
this new thing and said hey we got to do
[38:51] (2331.88s)
graphic violence stuff your manager said
[38:54] (2334.24s)
hey I got this thing I'm going to trust
[38:56] (2336.00s)
this guy with leading this what did you
[38:58] (2338.84s)
do to get someone to trust you so early
[39:01] (2341.96s)
in your career with you know a more
[39:04] (2344.08s)
senior leadership role good
[39:07] (2347.00s)
question I'm not sure what I can say is
[39:09] (2349.84s)
that it was incredible management and my
[39:12] (2352.08s)
manager was was exactly that he was an
[39:14] (2354.04s)
incredible leader his his path kind of
[39:16] (2356.28s)
up the chain was was fast as well his
[39:18] (2358.88s)
influence was was fantastic and I think
[39:21] (2361.04s)
this was a moment of him identifying
[39:23] (2363.40s)
somebody who had capabilities and giving
[39:26] (2366.68s)
them the encourage in the space to be
[39:28] (2368.80s)
able to grow into a more full form and
[39:32] (2372.32s)
there was plenty of like Hands-On
[39:33] (2373.52s)
management as well of course each
[39:34] (2374.88s)
one-onone with him I was getting plenty
[39:36] (2376.20s)
of tips on on how to become this leader
[39:38] (2378.52s)
but at least for me having someone
[39:40] (2380.88s)
recognize an ability and then giving me
[39:43] (2383.92s)
something that at the time was outside
[39:45] (2385.64s)
of my scope and felt Grand was like a
[39:48] (2388.60s)
challenge that I felt I I I needed to
[39:51] (2391.12s)
repay them and I I needed to kind of
[39:52] (2392.92s)
grow into that role and be successful I
[39:54] (2394.60s)
think this is really just like a lesson
[39:56] (2396.48s)
and fantastic ttbook management of
[39:58] (2398.64s)
identify people who maybe have the
[40:00] (2400.04s)
capabilities give them more than they
[40:01] (2401.76s)
can they can chew maybe I wouldn't say
[40:03] (2403.52s)
it that way but give them give them a
[40:05] (2405.56s)
larger scope make them feel empowered
[40:07] (2407.88s)
and then support them while empowering
[40:09] (2409.68s)
them this manager must have seen
[40:11] (2411.72s)
something in you that let him think that
[40:15] (2415.60s)
you could handle it prior to that
[40:17] (2417.64s)
there's something that you did when you
[40:19] (2419.08s)
were Junior I guess maybe that's also
[40:21] (2421.56s)
why you got promoted so quickly to even
[40:24] (2424.04s)
the the mid levels yeah the the the
[40:25] (2425.80s)
stepping stone was probably that we
[40:27] (2427.32s)
onboarded so many people and like I was
[40:29] (2429.20s)
the authority I'd been on the team the
[40:30] (2430.60s)
longest and so every person that we
[40:32] (2432.04s)
onboarded like I was significant in
[40:33] (2433.56s)
their onboarding regardless of their
[40:34] (2434.96s)
level and then even beyond their
[40:36] (2436.44s)
onboarding you know like I had the
[40:38] (2438.12s)
contact so I was the person that people
[40:39] (2439.56s)
would come to with questions in order to
[40:41] (2441.72s)
to help and to one of the things that
[40:43] (2443.60s)
was in the article on your substack like
[40:45] (2445.84s)
I was never shy with favors and helping
[40:48] (2448.40s)
people and so if anyone came to my desk
[40:50] (2450.04s)
with a problem or they needed help with
[40:51] (2451.68s)
something then I was eager and willing
[40:53] (2453.56s)
to to help out and I'm sure that like
[40:55] (2455.24s)
some of these qualities are what kind of
[40:57] (2457.48s)
led to to him feeling like he could put
[40:59] (2459.08s)
that faith in me yeah yeah exactly
[41:00] (2460.88s)
because I've seen people who have the
[41:03] (2463.20s)
exact same opportunity they were early
[41:05] (2465.00s)
on a team and they even told me they
[41:07] (2467.36s)
said this is a good opportunity for me
[41:09] (2469.16s)
all the new people coming in I'm going
[41:10] (2470.64s)
to onboard them and I this is going to
[41:12] (2472.52s)
help I'll be in a a good position and
[41:15] (2475.08s)
rather than them riding the wave with
[41:17] (2477.16s)
the team growing you know the team goes
[41:19] (2479.92s)
uh over them you know they're kind of
[41:21] (2481.84s)
they're just Junior engineer that knew
[41:24] (2484.44s)
where some of the code was but that's it
[41:26] (2486.24s)
but in this case you had the leadership
[41:28] (2488.28s)
ability to remain a leader and naturally
[41:31] (2491.16s)
too it doesn't sound like you were
[41:32] (2492.88s)
really like power hungry and saying I
[41:34] (2494.60s)
got to I got to stay on top and you know
[41:36] (2496.64s)
you kind of just helped people you knew
[41:39] (2499.56s)
everything and you naturally were put in
[41:42] (2502.28s)
a leadership positions there were as you
[41:44] (2504.00s)
were saying that one thing came to mind
[41:45] (2505.40s)
which might be interesting to folks and
[41:46] (2506.64s)
that was that there were tensions there
[41:48] (2508.28s)
um the one tension that I remember was a
[41:50] (2510.56s)
senior engineer who joined the team who
[41:51] (2511.96s)
actually ended up being to this day one
[41:53] (2513.32s)
of my my best friends in any relative
[41:56] (2516.64s)
professional cont context he was a
[41:57] (2517.80s)
senior engineer incredibly brilliant guy
[42:00] (2520.64s)
a current manager at meta still and I
[42:03] (2523.32s)
felt a little like territorial I was
[42:05] (2525.08s)
like this is like my project and my
[42:06] (2526.56s)
things and like I'm the Little Junior
[42:07] (2527.76s)
engineer and he's a sophisticated senior
[42:09] (2529.88s)
engineer at the time coming from
[42:11] (2531.20s)
Microsoft it didn't last long I remember
[42:13] (2533.52s)
I think I had one conversation with my
[42:14] (2534.96s)
manager about it but like I I needed to
[42:17] (2537.28s)
slap myself across the face and like be
[42:19] (2539.20s)
humbled a little bit and he was teaching
[42:20] (2540.92s)
me so much so much about like in all of
[42:24] (2544.20s)
my code reviews and all of my you know
[42:27] (2547.20s)
design meetings design reviews like he
[42:29] (2549.28s)
helped me grow so significantly
[42:30] (2550.84s)
technically and if I wasn't open to that
[42:33] (2553.44s)
I my career likely would have gone in a
[42:35] (2555.56s)
different direction and it very well
[42:36] (2556.92s)
could have if I didn't kind of a
[42:39] (2559.00s)
self-realize that I was having that kind
[42:41] (2561.68s)
of negative negative feeling and then to
[42:43] (2563.64s)
I'm sure get a a slight slapping across
[42:46] (2566.20s)
the face and a polite way from my
[42:47] (2567.44s)
manager as well so you felt territorial
[42:50] (2570.00s)
but rather than like going and clawing
[42:52] (2572.04s)
for and saying this is mine you shared
[42:54] (2574.28s)
the scope and actually you two combined
[42:57] (2577.16s)
it was like 1+ 1 equals you know three
[42:59] (2579.92s)
or something more than yeah and I think
[43:01] (2581.52s)
that we had like such an amazing
[43:02] (2582.80s)
relationship and he helped me
[43:05] (2585.04s)
grow I won't speak for him to any extent
[43:07] (2587.76s)
that that that I helped him I think that
[43:09] (2589.44s)
might be too large to say but like yeah
[43:11] (2591.84s)
well one plus one equal equal three and
[43:13] (2593.60s)
we were able to go on and accomplish
[43:15] (2595.68s)
great things over the next couple of
[43:17] (2597.04s)
years I would also agree I mean in my
[43:19] (2599.80s)
career as well I had people who were
[43:23] (2603.48s)
working with me that were more senior
[43:26] (2606.92s)
they knew way more than me and those
[43:30] (2610.04s)
relationships I feel like I owe
[43:32] (2612.08s)
everything to those relationship I was
[43:33] (2613.52s)
so lucky that these people would spend
[43:36] (2616.64s)
the time to work closely with me I would
[43:38] (2618.68s)
go and put all this work into the docks
[43:41] (2621.08s)
they would eat it alive and you know the
[43:43] (2623.68s)
end result is so much better and I
[43:45] (2625.88s)
learned so much from them I didn't
[43:47] (2627.72s)
really think too much about this is my
[43:50] (2630.60s)
thing or whatever and I don't know
[43:52] (2632.08s)
exactly what was in each of our
[43:54] (2634.00s)
performance reviews like you know did
[43:55] (2635.52s)
they get credit for leading and I just
[43:57] (2637.64s)
got credit for execution I don't I don't
[43:59] (2639.32s)
even know I just put my head down and
[44:01] (2641.72s)
said I love working with this guy I'm
[44:03] (2643.64s)
learning so much from them and this
[44:05] (2645.36s)
project is going amazingly I could point
[44:07] (2647.60s)
to a specific person at each promo and
[44:10] (2650.00s)
say this person I couldn't have done it
[44:11] (2651.84s)
without them and they're they're so
[44:13] (2653.80s)
impactful in my growth but also we just
[44:15] (2655.84s)
did so much more as a result so that
[44:17] (2657.96s)
makes a lot of sense I think whenever
[44:19] (2659.64s)
it's getting territorial I think you
[44:22] (2662.04s)
know you can think more about how it's
[44:24] (2664.84s)
not a zero sum game and you can actually
[44:26] (2666.76s)
create way more by not caring about who
[44:30] (2670.28s)
does the work but that the work gets
[44:31] (2671.80s)
done and it's amazingly high quality
[44:33] (2673.96s)
exactly and it's all through a lens of
[44:35] (2675.20s)
like self-growth you have to be able to
[44:37] (2677.08s)
realize that there's so many things that
[44:38] (2678.80s)
you don't know and all of these people
[44:40] (2680.84s)
can teach you these things and you have
[44:41] (2681.84s)
to be eager to do so as you just said
[44:43] (2683.80s)
absolutely one last thing that you said
[44:45] (2685.60s)
in this area you talked a little bit
[44:47] (2687.72s)
about tech leading and how that was like
[44:49] (2689.44s)
a critical part and you define deck
[44:51] (2691.36s)
leading is kind of driving the road map
[44:54] (2694.24s)
uh you know coordinating with everyone
[44:55] (2695.96s)
having one-on ones and working through
[44:57] (2697.76s)
others it sounds like I'll just say that
[45:00] (2700.00s)
that was also a huge part in my
[45:01] (2701.92s)
promotion to senior as well I was not
[45:04] (2704.52s)
given it sounds like in your case you
[45:06] (2706.20s)
had your manager said hey this scope go
[45:09] (2709.60s)
for it and here's people working with
[45:11] (2711.80s)
you on it in my case I got a taste of it
[45:15] (2715.28s)
with there was some work stream that
[45:16] (2716.76s)
we're working on which I kind of became
[45:18] (2718.92s)
the backend lead on it naturally it was
[45:21] (2721.28s)
just something that was coming together
[45:23] (2723.20s)
and there was client we needed client
[45:24] (2724.72s)
Engineers we need backend engineers and
[45:27] (2727.08s)
I was there first and then as it grew in
[45:29] (2729.48s)
importance I was a guy that knew
[45:31] (2731.36s)
everything on the back end so there were
[45:33] (2733.32s)
you know other teams getting involved
[45:35] (2735.16s)
and I was the go-to person and I I was
[45:37] (2737.96s)
leading be being a tech lead in that
[45:40] (2740.00s)
that space even though I felt it was
[45:42] (2742.20s)
kind of stretching my leadership
[45:43] (2743.52s)
capabilities I remember a few core
[45:45] (2745.72s)
memories of certain meetings where I was
[45:48] (2748.00s)
leading it but I didn't feel like a
[45:49] (2749.60s)
leader and you I was just doing it
[45:52] (2752.08s)
though cuz I knew what I had to do and I
[45:53] (2753.96s)
just kind of buckled down and did it but
[45:56] (2756.00s)
there's definitely some you know Growing
[45:57] (2757.72s)
Pains but uh growing into that role
[46:00] (2760.60s)
being a tech lead was a huge part of it
[46:03] (2763.24s)
and also I had a intern at some point
[46:05] (2765.88s)
which honestly this intern was amazing I
[46:09] (2769.04s)
got super lucky this intern basically
[46:11] (2771.36s)
showed me the power of I guess like
[46:14] (2774.04s)
Leverage or working through others cuz I
[46:17] (2777.00s)
I was always a Workhorse and I was
[46:18] (2778.84s)
taking on you know three work streams at
[46:20] (2780.80s)
the same time and then this guy came
[46:23] (2783.56s)
along and I realized oh I can entrust
[46:27] (2787.12s)
him with some of this and I can go take
[46:29] (2789.40s)
on more stuff and so now I felt like I
[46:32] (2792.52s)
was two people at once and I was
[46:35] (2795.00s)
shipping twice as much impact and I was
[46:38] (2798.28s)
kind of getting the credit for all of it
[46:39] (2799.80s)
too because he was like an intern and
[46:41] (2801.72s)
you know he'd just be there for a little
[46:42] (2802.92s)
bit of time so that kind of got me a uh
[46:45] (2805.68s)
a little taste of of like Leverage and I
[46:48] (2808.36s)
I something that I I liked a lot for the
[46:50] (2810.92s)
rest of my career two things that really
[46:52] (2812.28s)
stood out there for me was that the
[46:53] (2813.80s)
first one was the power of contact that
[46:55] (2815.44s)
seems to be a through line in in both of
[46:57] (2817.08s)
ours and there's like that classic
[46:58] (2818.64s)
advice of become an expert in something
[47:00] (2820.96s)
um so that you're that go-to person in
[47:02] (2822.60s)
something and I think that that's that's
[47:04] (2824.88s)
great advice for anyone in in their
[47:06] (2826.12s)
career if you're the go-to person on
[47:07] (2827.36s)
something ideally something valuable and
[47:09] (2829.68s)
something growing then that context is
[47:11] (2831.44s)
going to be worth so much and then to to
[47:14] (2834.84s)
the delegation aspect that's something
[47:16] (2836.68s)
that honestly was probably the first
[47:18] (2838.12s)
point in my career where things stopped
[47:19] (2839.80s)
coming naturally and I remember many
[47:21] (2841.48s)
conversations with my manager about like
[47:23] (2843.00s)
you need to be able to delegate cuz I
[47:24] (2844.24s)
was just like you we like I could just
[47:25] (2845.48s)
do it and I could do it quickly so like
[47:27] (2847.08s)
why do I need anyone else around to to
[47:29] (2849.40s)
help and it was at this moment kind of
[47:31] (2851.36s)
around that five promotion just before
[47:33] (2853.56s)
just after where that was really getting
[47:35] (2855.56s)
beaten into me and similarly to you that
[47:38] (2858.12s)
was kind of a huge eye openening
[47:40] (2860.68s)
learning when I finally was able to get
[47:42] (2862.52s)
that to click like you don't have to do
[47:44] (2864.16s)
everything yourself in fact at the
[47:45] (2865.36s)
higher levels you can't do everything
[47:46] (2866.64s)
yourself and you need to figure out how
[47:48] (2868.40s)
to empower people you need to figure out
[47:49] (2869.76s)
how to delegate and you need to figure
[47:51] (2871.00s)
out how to kind of increase your scope
[47:52] (2872.92s)
through others definitely I think that
[47:54] (2874.96s)
was the biggest feedback back that I got
[47:57] (2877.48s)
once I was senior on how do I get to
[47:59] (2879.60s)
staff yeah it was like the buzz word was
[48:02] (2882.76s)
scaling yourself like you you got to
[48:04] (2884.84s)
scale yourself I'm really thankful that
[48:07] (2887.40s)
I had that experience with the intern as
[48:09] (2889.40s)
a senior or growing into senior because
[48:12] (2892.60s)
that was like the name of the game to
[48:14] (2894.56s)
kind of be able to take on more scope
[48:17] (2897.28s)
than I could physically deliver okay
[48:19] (2899.60s)
before we go to the staff stuff I guess
[48:21] (2901.52s)
last thing on the five stuff at this
[48:23] (2903.28s)
point you're kind of more plugged into
[48:24] (2904.80s)
the industry did you start talking to
[48:26] (2906.48s)
your manager about promo this time or
[48:28] (2908.84s)
yeah yeah now like I had a great
[48:30] (2910.40s)
relationship with my manager he was
[48:32] (2912.32s)
always looking out for me and trying to
[48:34] (2914.28s)
push me to move as quickly as possible
[48:35] (2915.64s)
but similarly like we'd have those open
[48:37] (2917.04s)
conversations you know like we're
[48:38] (2918.60s)
looking for a promotion by this day
[48:40] (2920.56s)
let's make it happen here's what has to
[48:41] (2921.76s)
happen in order to accomplish it and so
[48:43] (2923.84s)
it was like a much more honest and open
[48:45] (2925.32s)
conversation at that point I talked to a
[48:46] (2926.96s)
lot of my friends when I was at meta in
[48:48] (2928.80s)
my boot camp class who didn't have the
[48:49] (2929.92s)
same experience they didn't have the
[48:51] (2931.00s)
same promotion growth and largely they
[48:52] (2932.96s)
didn't have a manager that was
[48:54] (2934.16s)
advocating for them to the same degree
[48:55] (2935.68s)
that I had and so my advice to them
[48:58] (2938.12s)
which was maybe a little bit silly
[48:59] (2939.40s)
because I don't know that I even did all
[49:00] (2940.56s)
this all that much certainly not the
[49:01] (2941.96s)
beginning but was like that they really
[49:03] (2943.08s)
needed to self- Advocate and like you
[49:04] (2944.56s)
have to have those conversations with
[49:05] (2945.56s)
your managers this is when I want to be
[49:07] (2947.04s)
promoted to five by and this is what I
[49:09] (2949.04s)
think I need to do do you agree where
[49:11] (2951.28s)
are the gaps and it's like an awkward
[49:13] (2953.12s)
conversation cuz it's setting yourself
[49:14] (2954.68s)
up it's vulnerable like but you have to
[49:16] (2956.44s)
have it you have to have that
[49:17] (2957.40s)
conversation and you want to hear the
[49:18] (2958.84s)
bad news if there is bad news you'd
[49:20] (2960.24s)
rather hear it now then come promo day
[49:22] (2962.24s)
when you're expecting something 100% my
[49:24] (2964.04s)
manager at this point was you know one
[49:26] (2966.16s)
of my absolute favorite managers love
[49:28] (2968.76s)
him and learn so much from him he was
[49:32] (2972.44s)
never pushing me hard for promo but he
[49:35] (2975.84s)
was very supportive when I asked for it
[49:38] (2978.16s)
and so I guess in my experience I was
[49:40] (2980.84s)
more of like the I advocated for myself
[49:44] (2984.12s)
pretty aggressively and it it definitely
[49:45] (2985.80s)
made a difference and it's not that my
[49:47] (2987.92s)
manager was ever not supportive it's
[49:51] (2991.24s)
just that he wasn't coming to me and
[49:52] (2992.84s)
saying hey let's let's do the promo
[49:54] (2994.68s)
here's the date I would come into the
[49:56] (2996.28s)
conversation say hey what do I have to
[49:58] (2998.64s)
do to get promoted I'm super motivated
[50:01] (3001.04s)
I'm loving this work what does it even
[50:03] (3003.32s)
look like at the next level and me just
[50:05] (3005.28s)
constantly going in and because I was a
[50:08] (3008.00s)
high performer I think that also helped
[50:11] (3011.36s)
me a lot because my manager had strong
[50:13] (3013.48s)
reason to kind of you know make sure
[50:15] (3015.28s)
that I was happy with my growth and and
[50:17] (3017.24s)
everything and you know as I'm growing
[50:19] (3019.20s)
too I'm I'm helping them get way more
[50:21] (3021.04s)
stuff done so there's just like a lot of
[50:23] (3023.56s)
alignment and incentive um there totally
[50:26] (3026.76s)
I think that your experience there is
[50:28] (3028.28s)
definitely the one that most people can
[50:30] (3030.36s)
try to to learn from there and what you
[50:32] (3032.88s)
just described I didn't put into action
[50:34] (3034.80s)
until later on it wasn't until I have a
[50:36] (3036.40s)
different manager when I was like
[50:37] (3037.44s)
shooting for the the seven path that we
[50:39] (3039.48s)
were really that I was more advocating
[50:41] (3041.40s)
for myself as opposed to and my manager
[50:43] (3043.88s)
was still great and and on my team of
[50:45] (3045.56s)
course but it wasn't being as led by my
[50:47] (3047.68s)
manager at that point yeah definitely
[50:49] (3049.40s)
and also I think the you know some
[50:52] (3052.08s)
managers are just more they have more
[50:54] (3054.52s)
things on their plates it's not like
[50:56] (3056.44s)
they they don't want you to they just
[50:58] (3058.68s)
aren't focused on it potentially it just
[51:01] (3061.48s)
makes you get a lot more lucky with your
[51:03] (3063.72s)
promos if you're you're focused on it
[51:05] (3065.60s)
yeah and by the way to luck I think that
[51:07] (3067.60s)
manager that you had that was also like
[51:10] (3070.12s)
opportunity and luck to some extent
[51:12] (3072.40s)
right like you could have had a manager
[51:14] (3074.40s)
that actively disliked you and even
[51:17] (3077.00s)
though you're a killing it you might
[51:19] (3079.20s)
have been delayed on the promos or might
[51:22] (3082.08s)
not have got the opportunity to begin
[51:23] (3083.64s)
with so 100% yeah that's it that's a
[51:25] (3085.84s)
huge portion of it having the right
[51:27] (3087.16s)
manager is is is huge and I think
[51:29] (3089.76s)
there's there's probably there's two
[51:30] (3090.72s)
pieces there you certainly need to have
[51:31] (3091.96s)
the right manager it's also true that
[51:33] (3093.60s)
managers are taught to like invest in
[51:35] (3095.00s)
their High performers both of those
[51:36] (3096.28s)
things need to be true you need to be a
[51:37] (3097.60s)
high performer so your manager wants to
[51:39] (3099.08s)
invest in you and then your manager
[51:40] (3100.20s)
needs to be fantastic in order to kind
[51:42] (3102.36s)
of push that rate of acceleration if
[51:44] (3104.04s)
you're finding that you're not
[51:45] (3105.08s)
performing high and you're not getting
[51:46] (3106.48s)
attention from your manager that's
[51:48] (3108.32s)
probably why as maybe hurtful as that is
[51:51] (3111.40s)
to say and it's like you need that
[51:52] (3112.56s)
self-recognition to realize the first
[51:54] (3114.08s)
thing I need to fix is to become a high
[51:55] (3115.52s)
performer in order to kind of deserve
[51:58] (3118.12s)
that that attention and then you know
[52:00] (3120.88s)
then you can be a little bit more
[52:01] (3121.72s)
forceful with them about their about the
[52:04] (3124.04s)
next steps I don't know too many people
[52:06] (3126.56s)
who are high performers that are having
[52:10] (3130.04s)
maybe not getting a whole lot of
[52:11] (3131.40s)
attention unless there's some crazy
[52:13] (3133.48s)
thrash situation where people keep
[52:16] (3136.04s)
leaving and yeah which which also does
[52:18] (3138.84s)
happen so but like managers are
[52:20] (3140.32s)
incentivized to grow their team if the
[52:22] (3142.36s)
more promotions they give that are
[52:23] (3143.88s)
warranted obviously and it meta they
[52:25] (3145.40s)
have to be warranted they go through it
[52:26] (3146.68s)
a pretty rigorous process but like
[52:28] (3148.32s)
they're rewarded for growth within their
[52:31] (3151.04s)
team and how many higher levels are
[52:32] (3152.76s)
within their team and so like they're
[52:34] (3154.48s)
looking for the ones that are excelling
[52:36] (3156.12s)
so they can invest their resources in
[52:37] (3157.56s)
those in order to also help themselves
[52:39] (3159.68s)
like it's it's the reality and it's a
[52:41] (3161.48s)
it's the right incentive structure too I
[52:43] (3163.00s)
don't think that it's devious so talking
[52:45] (3165.52s)
about staff promotions and I think this
[52:47] (3167.96s)
is the part that I think a lot of people
[52:50] (3170.08s)
are most interested in cuz it's
[52:51] (3171.72s)
ambiguous I guess the thing that I'm I'm
[52:53] (3173.60s)
curious about to start is what kept you
[52:56] (3176.24s)
at the company on the same team because
[52:58] (3178.92s)
when I think to my peers a lot of them
[53:01] (3181.04s)
had left their initial team within 2
[53:03] (3183.88s)
years or they switched companies uh so
[53:06] (3186.40s)
what kept you there yeah I guess the
[53:08] (3188.84s)
short of it was that I just really loved
[53:10] (3190.48s)
it actually I wasn't hyper optimizing
[53:12] (3192.12s)
for growth like the growth stuff was
[53:13] (3193.68s)
happening and it was fun it was great
[53:14] (3194.88s)
and I loved it and I was trying to push
[53:16] (3196.28s)
for promotions but like I was just
[53:18] (3198.64s)
really enjoying what I was doing we were
[53:19] (3199.68s)
working on really cool things and I felt
[53:22] (3202.04s)
like deeply like I was having an impact
[53:23] (3203.64s)
in the world whether it was terrorism
[53:24] (3204.96s)
graphic violence I worked for smaller on
[53:26] (3206.76s)
the CI stuff like it was deeply
[53:28] (3208.64s)
fulfilling and it was exciting and then
[53:30] (3210.48s)
at least the fact that the team was
[53:31] (3211.72s)
growing so quickly and that content
[53:33] (3213.20s)
Integrity the organization kept growing
[53:35] (3215.20s)
and it meant that despite the fact that
[53:36] (3216.72s)
I never switched teams I went from
[53:37] (3217.96s)
working on terrorism to CI to graphic
[53:40] (3220.12s)
violence to we'll talk about here in six
[53:41] (3221.72s)
some other stuff and so I never made a
[53:43] (3223.72s)
conscious change but I had three
[53:45] (3225.36s)
managers I had different teams the
[53:47] (3227.92s)
engineers around me were all coming and
[53:49] (3229.52s)
going like there was enough dynamy to
[53:51] (3231.20s)
keep me interested I think that started
[53:52] (3232.68s)
to fade towards towards the end of my
[53:54] (3234.56s)
career at meta and then obviously a
[53:55] (3235.80s)
change was made but at this point I was
[53:58] (3238.40s)
just loving what I was doing so there
[53:59] (3239.52s)
was no there's no consideration I think
[54:01] (3241.28s)
for me you know I stayed much longer
[54:03] (3243.64s)
than uh all of my friends I think a lot
[54:05] (3245.92s)
of my friends they went off to do
[54:07] (3247.28s)
startups or or whatever I'm I'm curious
[54:10] (3250.12s)
to hear from you and I don't know if
[54:11] (3251.16s)
it's now or if you want to talk about
[54:12] (3252.44s)
this later but at least fairly recently
[54:14] (3254.80s)
you made the change I did I wonder how
[54:16] (3256.92s)
you reflect on that if if you wish you
[54:18] (3258.56s)
made it earlier kind of how the change
[54:20] (3260.28s)
how the change went in terms of your
[54:21] (3261.60s)
growth not just in your career growth
[54:23] (3263.36s)
your technical growth all those things
[54:24] (3264.68s)
yeah and we can definitely talk about
[54:26] (3266.00s)
that I think up until the Staff point I
[54:29] (3269.72s)
was hyper optimizing for for career
[54:32] (3272.68s)
growth and I I loved my work at the same
[54:35] (3275.32s)
time too don't get me wrong but I was
[54:37] (3277.24s)
always thinking you know how how can I
[54:38] (3278.96s)
grow faster I think I was pretty
[54:40] (3280.84s)
ambitious when it comes to to that sort
[54:43] (3283.20s)
of thing every year I would think you
[54:45] (3285.20s)
know what can I do to grow faster what
[54:46] (3286.64s)
is the next thing and the answer was
[54:48] (3288.60s)
always well stay here that there's
[54:50] (3290.60s)
another promo right on the table all
[54:52] (3292.32s)
right the opportunity is clear yeah the
[54:53] (3293.84s)
opportunity was clear and I was loving
[54:56] (3296.08s)
the people I was working with and the
[54:57] (3297.76s)
work so I actively thought about it and
[55:01] (3301.32s)
decided to stay and I felt like that was
[55:04] (3304.44s)
also uh powerful in making me feel uh
[55:08] (3308.36s)
satisfied and fulfilled in my work was
[55:10] (3310.28s)
that every time I consider I was
[55:11] (3311.60s)
thinking yeah this is I'm doing the
[55:13] (3313.04s)
right thing in the right place and so
[55:14] (3314.92s)
that's kind of what kept me working on
[55:16] (3316.96s)
the same team for so long it makes sense
[55:18] (3318.80s)
and I think that that's actually it's
[55:20] (3320.00s)
like I was the same way and it's and
[55:21] (3321.60s)
it's a blessing and it was right and it
[55:23] (3323.40s)
was great for our careers but in
[55:25] (3325.40s)
hindsight like there is a a slight
[55:26] (3326.68s)
negative to it it's almost like this
[55:28] (3328.76s)
trap of that next thing is so close so
[55:31] (3331.04s)
keep going to it and I wonder if at
[55:33] (3333.80s)
least like as a meta Point that's meta
[55:37] (3337.08s)
not as in the company but you know what
[55:38] (3338.60s)
I'm saying it's better to switch like a
[55:39] (3339.96s)
little bit sooner for for technical
[55:42] (3342.00s)
growth I don't know it's a balance as
[55:43] (3343.80s)
trade-offs at least reflector on myself
[55:45] (3345.28s)
there is a lot of trade-offs that come
[55:47] (3347.04s)
with it I will say staying until ic6
[55:49] (3349.80s)
especially with the trajectory I have I
[55:52] (3352.16s)
I don't have a whole lot of regret with
[55:54] (3354.12s)
it I look back and I I AB absolutely
[55:56] (3356.72s)
loved being plugged into this maybe it's
[55:59] (3359.08s)
just my personality but knowing that
[56:00] (3360.56s)
there's something right in front of me
[56:02] (3362.28s)
grinding towards it there's all these
[56:03] (3363.84s)
things I'm growing towards the next ring
[56:05] (3365.84s)
in the ladder right yeah I felt like I
[56:07] (3367.72s)
was playing a video game or something
[56:09] (3369.36s)
and it was just so you know you talked
[56:11] (3371.48s)
about that first fromo you got and you
[56:13] (3373.08s)
felt so giddy yeah I was I was chasing
[56:15] (3375.52s)
that high all the time no totally I
[56:18] (3378.32s)
definitely think like to ic6 it was a no
[56:20] (3380.16s)
verer especially with the trajectory I
[56:22] (3382.00s)
think it would be different if it was
[56:24] (3384.20s)
grueling and there was a lot of
[56:26] (3386.40s)
uncertainty and things but I do feel
[56:29] (3389.00s)
like locking in the ic6 growth so
[56:31] (3391.96s)
quickly well it definitely helped
[56:34] (3394.68s)
financially there's no doubt but also I
[56:36] (3396.76s)
think a lot of the higher level
[56:37] (3397.88s)
behaviors are the most satisfying for me
[56:41] (3401.08s)
personally like I I enjoy working
[56:43] (3403.24s)
through others and leverage and as an
[56:45] (3405.36s)
ic6 you define the direction and that's
[56:47] (3407.84s)
very satisfying to me rather than taking
[56:50] (3410.00s)
Direction yeah let's talk a little bit
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about the ic6 promo for you I'm curious
[56:54] (3414.60s)
what was the anchor project that got you
[56:57] (3417.08s)
promoted maybe you can tell us a little
[56:58] (3418.64s)
about the story at the time I guess the
[57:00] (3420.72s)
turning point was so I'm still the the
[57:03] (3423.24s)
tech leader of the graphic violence team
[57:04] (3424.88s)
so I guess timing wise let's see the
[57:06] (3426.28s)
first promotion was a half from four to
[57:08] (3428.72s)
five then was two halves a year and then
[57:11] (3431.24s)
this one was three half so it went one
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two three and so we're probably halfway
[57:15] (3435.04s)
through at this point maybe a little bit
[57:16] (3436.48s)
before halfway so maybe the first of
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those three halves and um the tragic
[57:20] (3440.64s)
incidents in New Zealand the Christ
[57:22] (3442.40s)
Church shooting I don't know if this is
[57:23] (3443.88s)
something that you remember from the
[57:24] (3444.72s)
news at all but it was March 19th or
[57:26] (3446.76s)
March 15th 2019 and somebody live
[57:29] (3449.04s)
streamed the shooting of a mosque in
[57:30] (3450.76s)
Christ Church New Zealand killed 51
[57:32] (3452.88s)
people on live stream and as the tech
[57:34] (3454.80s)
lead for the graphic violence team I was
[57:36] (3456.64s)
heavily involved in in Facebook's
[57:38] (3458.96s)
technical response to this it was all
[57:40] (3460.64s)
over the news it was a horrible
[57:41] (3461.92s)
atrossity and we blew it we missed it
[57:43] (3463.84s)
like we allowed this to be live on the
[57:45] (3465.24s)
platform for n and a half minutes as
[57:47] (3467.04s)
opposed to detecting it much sooner and
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then beyond that copies of it kept
[57:51] (3471.12s)
spreading like crazy so people would
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download the full video I think he also
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streamed was it twitch something else um
[57:58] (3478.32s)
anyway you know the videos just
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continued to be spread around our
[58:02] (3482.24s)
platform and this was bad and so I think
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that this happened my memory serves me
[58:07] (3487.12s)
correctly sometime in the evening 5 or 6
[58:09] (3489.40s)
p.m. I think I'd already gone home at
[58:10] (3490.68s)
this point and I got the phone call that
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it was an emergency probably from my pm
[58:14] (3494.48s)
at that time and like we were in the war
[58:16] (3496.68s)
room and so I'm sitting in the war room
[58:18] (3498.28s)
with the the VP of Integrity with head
[58:21] (3501.12s)
of content policy at Facebook and like I
[58:23] (3503.80s)
was the technical head here my manager
[58:26] (3506.32s)
at the time if I remember correctly was
[58:27] (3507.44s)
on paternity leave so it was like you
[58:29] (3509.80s)
know there were plenty of people around
[58:30] (3510.92s)
to support don't get me wrong but I kind
[58:33] (3513.12s)
of had a significant role to play there
[58:35] (3515.16s)
and so there were many nights staying up
[58:37] (3517.52s)
through most of them figuring out what
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to do training models kind of overnight
[58:42] (3522.24s)
on the spot in order to detect different
[58:43] (3523.80s)
variations of these things making
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adjustments to our content detection
[58:47] (3527.64s)
algorithms in our photo Banks video
[58:49] (3529.36s)
Banks respectively and like that was
[58:51] (3531.80s)
that was significant it gave me a lot of
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visibility and I wasn't thinking about
[58:54] (3534.80s)
promotions obviously at the time I was
[58:56] (3536.16s)
thinking about like the families of the
[58:58] (3538.80s)
people who had this video being
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circulated and the atrocity that it was
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and everybody that we were working with
[59:03] (3543.48s)
was thinking about you know that context
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just how awful the situation was and
[59:07] (3547.36s)
that we wanted to be a part of the
[59:08] (3548.80s)
solution so I spent a lot of time on
[59:10] (3550.56s)
that and then ultimately we came to the
[59:13] (3553.68s)
conclusion as a company and my manager
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is now back from paternity leave and I I
[59:17] (3557.84s)
only learned how strongly he petitioned
[59:19] (3559.48s)
for this afterwards at the time I
[59:21] (3561.20s)
thought I had a larger role in this at a
[59:22] (3562.96s)
n side I did but regardless the
[59:25] (3565.48s)
recognition for the company was that we
[59:26] (3566.80s)
were underinvested in our ability to
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detect these sorts of worst of the worst
[59:30] (3570.44s)
atrocities in real time on live video
[59:32] (3572.44s)
and so my team in graphic violence put
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most of our resources onto photos and
[59:36] (3576.00s)
videos that were not live and this is
[59:37] (3577.92s)
just a it's a different fundamental
[59:39] (3579.52s)
challenge so we decided to create a new
[59:41] (3581.08s)
team and this team was called realtime
[59:42] (3582.48s)
integrity and its goal was to detect in
[59:44] (3584.36s)
real time things like murders and
[59:46] (3586.68s)
suicides on live video which is a
[59:48] (3588.52s)
horrible thing that you even need to do
[59:49] (3589.60s)
in the first place but unfortunately it
[59:51] (3591.56s)
was necessary and so the team was
[59:53] (3593.68s)
created and at the time of creation it
[59:55] (3595.88s)
was was me and the PM and they basically
[59:58] (3598.80s)
said this is your guys's problem figure
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out the scope figure out how many
[60:02] (3602.56s)
Engineers you need figure out what you
[60:03] (3603.92s)
need to do figure out the road map and
[60:05] (3605.76s)
like have at it and so this was totally
[60:07] (3607.28s)
Green Field and it was a super fun
[60:08] (3608.84s)
challenging thing to work on it was
[60:09] (3609.96s)
super fulfilling it was super exciting
[60:11] (3611.64s)
we started to higher up slowly uh for
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the first half or so we only had two
[60:17] (3617.08s)
other Engineers other than me so three
[60:18] (3618.44s)
engineers in total and our progress was
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really slow actually like we were having
[60:22] (3622.44s)
a really hard time detecting any of this
[60:24] (3624.72s)
content it's it happens so infrequently
[60:27] (3627.84s)
and so you know you're caught in these
[60:30] (3630.00s)
terrible situations of what do you do
[60:31] (3631.28s)
you train on the couple of examples that
[60:32] (3632.96s)
you have and then obviously they were in
[60:34] (3634.56s)
your training data so you're overfitting
[60:35] (3635.92s)
to them so the fact that you detect them
[60:37] (3637.52s)
now is not representative of anything
[60:39] (3639.60s)
but we don't have any other examples to
[60:41] (3641.56s)
evaluate ourselves on so like it's a
[60:43] (3643.48s)
measurement Nightmare and then the only
[60:45] (3645.24s)
way that we can know if we're doing a
[60:46] (3646.24s)
good job or not is that the next
[60:47] (3647.60s)
atrocity happens and we get the phone
[60:49] (3649.24s)
call that we blew it again so it was
[60:50] (3650.76s)
like it was stressful and progress
[60:52] (3652.68s)
wasn't being made at the pace that we
[60:54] (3654.16s)
wanted it to be made at but then two
[60:57] (3657.28s)
large things came that changed that the
[60:59] (3659.48s)
first was the need to solve the
[61:00] (3660.76s)
measurement problem and so in order to
[61:03] (3663.04s)
do this this was sort of my largest
[61:04] (3664.72s)
project at the time and it grew even to
[61:07] (3667.24s)
an an organization wide project later on
[61:09] (3669.72s)
an Integrity wide project later on and
[61:11] (3671.52s)
we called it golden set recall and it
[61:12] (3672.96s)
was basically the idea that like we we
[61:14] (3674.48s)
went through a bunch of effort in order
[61:15] (3675.80s)
to curate a set a golden set of content
[61:18] (3678.48s)
that we needed to be able to evaluate
[61:19] (3679.64s)
ourselves on this was all of the past
[61:21] (3681.52s)
atrocities that have happened since live
[61:23] (3683.32s)
video went live in 2007 or whatever it
[61:27] (3687.04s)
was 2011 uh 12 maybe anyway all of those
[61:31] (3691.00s)
and then like this is the set that we're
[61:33] (3693.16s)
going to evaluate ourselves on by way of
[61:35] (3695.76s)
actually restreaming content so we'll
[61:37] (3697.44s)
have holdout content that needs to uh
[61:39] (3699.72s)
that we need to evaluate against and
[61:41] (3701.16s)
we're going to set up the infrastructure
[61:42] (3702.40s)
since that such that Bots will
[61:44] (3704.08s)
legitimately restream this content in
[61:45] (3705.92s)
order to test holistically our
[61:47] (3707.24s)
infrastructure not just our models we'll
[61:49] (3709.36s)
legitimately restream this content on
[61:51] (3711.08s)
Facebook comments will come in at the
[61:52] (3712.80s)
right time all of these different things
[61:55] (3715.00s)
and then importantly this needs to be
[61:56] (3716.36s)
like fully isolated it needs to be on
[61:58] (3718.08s)
real Facebook so that it tests our real
[62:00] (3720.12s)
infrastructure but obviously if anybody
[62:02] (3722.52s)
saw any of this it would be an absolute
[62:04] (3724.60s)
Nightmare and so that was the challenge
[62:07] (3727.92s)
and once we had eyes we knew how we were
[62:11] (3731.40s)
doing and what we learned was that like
[62:13] (3733.44s)
our recall at the time was 9% this was
[62:15] (3735.60s)
for suicide specifically for which we
[62:17] (3737.20s)
had more data for and so we had 9%
[62:18] (3738.76s)
recall on live suicides on Facebook this
[62:20] (3740.76s)
is this is bad this is this is not good
[62:22] (3742.92s)
at all so we contined to iterate from a
[62:24] (3744.80s)
modeling perspective we're doing like
[62:26] (3746.44s)
fancy things from modeling perspectives
[62:27] (3747.88s)
is's a lot of uh assistants from the AI
[62:30] (3750.40s)
org as well like they're doing a lot of
[62:31] (3751.88s)
the core embeddings and then you know
[62:33] (3753.36s)
we're doing the applied ML on top of it
[62:34] (3754.96s)
you know we're doing sophisticated
[62:36] (3756.56s)
sequencing temporal modeling and
[62:37] (3757.84s)
nothing's really happening and then I
[62:39] (3759.88s)
had the idea which is so obvious in
[62:42] (3762.52s)
hindsight but I looked at enough of
[62:44] (3764.04s)
these examples that we were missing as
[62:45] (3765.48s)
they were coming in every day and I
[62:46] (3766.72s)
realized that you look at the comments
[62:47] (3767.92s)
and the comments read don't do it your
[62:50] (3770.16s)
family loves you like please no these
[62:52] (3772.36s)
comments are indicative and the people
[62:53] (3773.80s)
who are posting the comments know of the
[62:55] (3775.28s)
atrocity long before our sophisticated
[62:57] (3777.52s)
models were able to figure it out and at
[62:58] (3778.96s)
the time we were so focused on pinching
[63:01] (3781.40s)
pixels and Audio Waves that we weren't
[63:04] (3784.04s)
focused on the thing that was obvious
[63:05] (3785.24s)
and right there kind of beneath our nose
[63:06] (3786.92s)
the entire time and so we updated the
[63:09] (3789.28s)
models to take into consideration these
[63:11] (3791.40s)
kind of temporal comment signals and it
[63:14] (3794.64s)
was a revelation like we went from 9 to
[63:16] (3796.64s)
50 55% recall almost overnight and then
[63:20] (3800.04s)
now we had a feedback loop now the model
[63:22] (3802.48s)
is better and it's actually detecting
[63:24] (3804.40s)
these things far more than you would
[63:26] (3806.08s)
ever imagine would actually be on these
[63:27] (3807.68s)
platforms and now we have more training
[63:29] (3809.24s)
data and now we can continue to iterate
[63:30] (3810.84s)
and we have a foothold and by the time I
[63:33] (3813.12s)
left we were into the mid 90% on recall
[63:36] (3816.84s)
which was which was a huge success and
[63:38] (3818.84s)
so to tit all back to the to the promo
[63:41] (3821.52s)
the promo came kind of maybe halfway
[63:43] (3823.76s)
through that story where we were just
[63:45] (3825.64s)
starting to see progress we had a metric
[63:47] (3827.56s)
we had a way to evaluate comments were
[63:49] (3829.20s)
successful and so I think my promo
[63:51] (3831.12s)
packet was something on the back of was
[63:52] (3832.56s)
able to step up in a time of need for
[63:54] (3834.12s)
the company do all of these fantastic
[63:55] (3835.56s)
things to help us when we were in crisis
[63:57] (3837.76s)
and then created largely and led a new
[64:00] (3840.04s)
team in order to solve this problem
[64:01] (3841.48s)
moving forward and has up until this
[64:03] (3843.44s)
point the point of the promotion made
[64:05] (3845.52s)
significant progress and I think at that
[64:06] (3846.76s)
point it was you know like the 9% to 60%
[64:08] (3848.80s)
or something I mean that's huge impact
[64:10] (3850.52s)
so the ic6 scope in terms of the impact
[64:14] (3854.36s)
side of things was absolutely clear you
[64:17] (3857.28s)
said something there about your you were
[64:19] (3859.88s)
just given the opportunity to create a
[64:22] (3862.44s)
team from scratch as an IC how big did
[64:25] (3865.08s)
that team end up being and how was that
[64:27] (3867.08s)
process by the time I left the team had
[64:29] (3869.16s)
just recently split into two two of
[64:31] (3871.68s)
eight each so 16 total at the at it at
[64:34] (3874.60s)
its peak real time integrity was
[64:35] (3875.92s)
something around 12 to 14 engineers at
[64:38] (3878.68s)
this point I you know I was two years
[64:40] (3880.16s)
into being staff or so so this isn't as
[64:42] (3882.20s)
close to the promo path by promo time
[64:44] (3884.48s)
maybe the team was four or five
[64:46] (3886.16s)
Engineers but it continued to grow and
[64:49] (3889.16s)
at first it well we weren't sure if it
[64:50] (3890.28s)
was going to be like a dud project you
[64:52] (3892.16s)
know for through the first six to eight
[64:54] (3894.16s)
months six months maybe but once we
[64:56] (3896.04s)
started to get that acceleration then it
[64:57] (3897.56s)
was something that the company and
[64:58] (3898.52s)
Leadership wanted to invest resources in
[65:00] (3900.60s)
and fortunately it was sort of a pet
[65:02] (3902.12s)
project of like the VP and director of
[65:04] (3904.72s)
the org because of you know Mark was
[65:07] (3907.08s)
breathing down their neck about how
[65:08] (3908.96s)
horrible this was that we allowed this
[65:10] (3910.24s)
to happen we can't allow it to happen
[65:11] (3911.48s)
again so we were getting resources
[65:14] (3914.04s)
accordingly man for an ic5 to just be
[65:16] (3916.48s)
trusted with this blue ocean of build
[65:19] (3919.72s)
this team for like a top priority for
[65:22] (3922.28s)
the org I like that a directors paying
[65:24] (3924.68s)
attention to is definitely uh a huge a
[65:28] (3928.80s)
huge opportunity who was the decision
[65:31] (3931.52s)
maker that that gave you that
[65:33] (3933.04s)
opportunity it was that the director or
[65:34] (3934.88s)
was that your your direct manager be
[65:37] (3937.52s)
honest I don't know so there's like the
[65:39] (3939.08s)
visibility that I had and to which this
[65:41] (3941.20s)
felt so cool I felt like I was just
[65:42] (3942.52s)
given so much scope I felt like I
[65:43] (3943.96s)
advocated for it based on what happened
[65:47] (3947.08s)
you know during the incident and I think
[65:49] (3949.08s)
all of this was true in part but as I
[65:51] (3951.04s)
said I learned that behind the scenes my
[65:52] (3952.48s)
manager was doing a ton of advocating
[65:54] (3954.52s)
for this new team and my guess would be
[65:56] (3956.40s)
that in part of his advocating or
[65:58] (3958.36s)
advocacy it was let's kind of let Evan
[66:01] (3961.52s)
and the pm at the time like have a shout
[66:03] (3963.52s)
at this and of course he's there and
[66:06] (3966.04s)
close by and helping it's not like you
[66:08] (3968.36s)
know your manager is certainly involved
[66:10] (3970.44s)
yeah like I said I think he did far more
[66:11] (3971.68s)
behind the scenes than I appreciated at
[66:13] (3973.04s)
the time but it felt to me and as it was
[66:15] (3975.24s)
written in my promo packet like this was
[66:17] (3977.44s)
a moment of proactivity uh for me to
[66:20] (3980.60s)
like kind of largely suggest the
[66:22] (3982.28s)
creation of a team and Lead its
[66:24] (3984.08s)
Inception got it okay and so would have
[66:25] (3985.92s)
been a case of uh I guess creating this
[66:28] (3988.00s)
scope then as as the IC uh Tech lead
[66:31] (3991.04s)
involved when you look back on that I
[66:33] (3993.00s)
guess what was like the most important
[66:35] (3995.72s)
behavior that kind of got you promoted
[66:37] (3997.92s)
because I think you've laid out the
[66:39] (3999.48s)
facts of what happened but you know what
[66:41] (4001.76s)
was like the skill that you kind of
[66:43] (4003.92s)
needed that maybe made it the biggest
[66:45] (4005.72s)
difference the biggest thing was the not
[66:48] (4008.88s)
being afraid to try the simple and
[66:50] (4010.20s)
obvious thing this or in general and all
[66:52] (4012.12s)
the teams that I was on and certainly
[66:53] (4013.40s)
real time Integrity like I was
[66:54] (4014.44s)
surrounded by MLP s and it was
[66:56] (4016.68s)
interesting on these teams and that
[66:57] (4017.68s)
there was like a ton of ambiguity you
[66:59] (4019.40s)
know like I largely did a lot of the
[67:01] (4021.52s)
infrastructure but I spent a lot of time
[67:03] (4023.00s)
training models too and fine-tuning
[67:04] (4024.72s)
Hyper parameters and doing feature
[67:06] (4026.32s)
engineering just alongside and them and
[67:09] (4029.24s)
they would do infrastructure things too
[67:10] (4030.56s)
like when you were on the team your
[67:11] (4031.56s)
title didn't really matter we all did
[67:12] (4032.92s)
things you know you lean towards your
[67:14] (4034.16s)
expertise but nonetheless and so I just
[67:16] (4036.92s)
had this really unique opportunity where
[67:18] (4038.48s)
I was surrounded by brilliant people who
[67:21] (4041.00s)
they absolutely were brilliant but they
[67:23] (4043.44s)
sort of had like horse Blinder to the
[67:26] (4046.36s)
effect of focusing on how to optimize
[67:28] (4048.52s)
the model in the most sophisticated
[67:30] (4050.56s)
technical means possible so that they
[67:32] (4052.88s)
could write a research paper and make
[67:34] (4054.88s)
progress in that way and this was like
[67:36] (4056.80s)
really fun cuttingedge modeling that we
[67:39] (4059.16s)
were doing it was interesting but I
[67:41] (4061.40s)
obviously by the nature of having less
[67:43] (4063.40s)
expertise there was less focused on
[67:45] (4065.48s)
those things and I had only one thing on
[67:47] (4067.64s)
my mind get this number from nine to
[67:49] (4069.56s)
something higher and what is it going to
[67:51] (4071.40s)
take to do that and while most people
[67:53] (4073.24s)
were focused narrowly on the model
[67:54] (4074.88s)
improvements I was focused on the
[67:57] (4077.40s)
holistic problem and this allowed me to
[67:59] (4079.00s)
see those Simple Solutions like for
[68:01] (4081.04s)
example the comments and so in hindsight
[68:03] (4083.80s)
it's a no-brainer but I think this is
[68:06] (4086.60s)
kind of Representative of much of big
[68:09] (4089.80s)
Tech at times that the people that are
[68:12] (4092.24s)
there are brilliant and want to solve
[68:13] (4093.60s)
hard complex technical challenges and
[68:15] (4095.68s)
those who are able to take a step back
[68:17] (4097.32s)
view the problem more holistically and
[68:18] (4098.88s)
then propose the solutions that
[68:20] (4100.72s)
regardless of their technical
[68:21] (4101.84s)
sophistication are going to make the
[68:23] (4103.56s)
largest progress on the goal of times
[68:25] (4105.84s)
Excel and I think that was true not just
[68:27] (4107.80s)
in this moment but but throughout much
[68:29] (4109.28s)
of my career is that is that something
[68:30] (4110.56s)
that resonates with you yes that that
[68:32] (4112.64s)
definitely resonates and when I think
[68:35] (4115.04s)
about my staff promotion I ended up
[68:37] (4117.80s)
writing a blog post um about it which I
[68:40] (4120.16s)
can kind of Link in the show notes about
[68:42] (4122.36s)
the optimization but the tldr is on a
[68:45] (4125.96s)
high level the optimization that I I
[68:48] (4128.28s)
actually did was trivial it was I I was
[68:52] (4132.36s)
kind of I guess maybe uh you know in a
[68:54] (4134.60s)
tech lead role trying to figure out
[68:57] (4137.00s)
what's the best way to optimize our
[69:00] (4140.04s)
compute efficiency for for everything
[69:02] (4142.80s)
for all the workloads that were being
[69:04] (4144.36s)
spent on uh processing Instagram video
[69:07] (4147.24s)
en codings that was an area where we
[69:09] (4149.08s)
didn't look for a long time because as a
[69:11] (4151.40s)
growing small company is like Instagram
[69:14] (4154.08s)
you just throw more machines at it and
[69:15] (4155.72s)
it's usually fine but at some point I
[69:18] (4158.20s)
think this was around covid there was
[69:21] (4161.88s)
too much demand for our platforms
[69:25] (4165.00s)
because people were using it so much
[69:27] (4167.04s)
while they were all Sheltering in place
[69:29] (4169.40s)
and so actually it became critical that
[69:31] (4171.92s)
we needed to uh improve our computer
[69:34] (4174.36s)
efficiency and I got lucky because I was
[69:36] (4176.80s)
looking into that when it became
[69:39] (4179.16s)
business critical and I was kind of
[69:40] (4180.80s)
already there and kind of playing around
[69:42] (4182.80s)
tinkering in an area where no one had
[69:45] (4185.04s)
looked at it just because I thought it
[69:46] (4186.72s)
would be fun I that it just sounds cool
[69:49] (4189.28s)
you know compute efficiency I was like
[69:50] (4190.80s)
yeah this is awesome let's make it
[69:52] (4192.24s)
better and then so there's so much money
[69:54] (4194.92s)
to be saved
[69:55] (4195.96s)
exactly I just thought oh there's this
[69:57] (4197.28s)
big opportunity and this work is going
[69:58] (4198.80s)
to be so cool and so I just started
[70:00] (4200.88s)
looking into the area and kind of
[70:02] (4202.52s)
digging into like what what would it
[70:04] (4204.60s)
look like to make this sufficient
[70:06] (4206.56s)
because this is something that we've
[70:07] (4207.60s)
never really looked at and I you know
[70:10] (4210.40s)
listed out all the ideas and I booked
[70:12] (4212.80s)
meetings with the most brilliant
[70:15] (4215.20s)
Engineers that I was working with that
[70:17] (4217.44s)
also contributed to these brainstorms as
[70:19] (4219.36s)
well and when we put everything out the
[70:22] (4222.68s)
the most impactful idea was the most
[70:26] (4226.08s)
obvious easy thing to do it absolutely
[70:28] (4228.56s)
trivial it was like on a high level I
[70:30] (4230.96s)
could just explain it as we just didn't
[70:34] (4234.36s)
do some redundant work that we were
[70:36] (4236.32s)
already
[70:38] (4238.00s)
doing and it probably wasn't the first
[70:40] (4240.04s)
thing people considered yeah there's
[70:41] (4241.92s)
there's a lot of other things we could
[70:43] (4243.08s)
definitely be doing yeah this this
[70:44] (4244.96s)
project didn't seem that cool yeah it
[70:46] (4246.48s)
definitely resonates that you know as an
[70:48] (4248.40s)
ic6 engineer or just generally as an
[70:50] (4250.56s)
engineer you focusing on actually what
[70:54] (4254.12s)
matters and what's impact ful is the
[70:56] (4256.56s)
absolute number one thing that's going
[70:57] (4257.80s)
to grow your career and it's not always
[71:00] (4260.12s)
the uh technically complex solution that
[71:03] (4263.28s)
is the shortest path to having impact
[71:05] (4265.56s)
and the people who have the initiative
[71:07] (4267.32s)
to drive the impact regardless of what
[71:09] (4269.84s)
it takes to do it are going to be the
[71:12] (4272.28s)
people who are rewarded because
[71:15] (4275.52s)
everything is proportional to your
[71:16] (4276.84s)
impact so yeah that definitely resonates
[71:18] (4278.96s)
to me in terms of doing the simple thing
[71:21] (4281.88s)
it's actually it's it's a benefit this
[71:23] (4283.88s)
simpler the optimization is the way that
[71:26] (4286.96s)
I look at prioritization is it's kind of
[71:30] (4290.28s)
like the the impact throughput that
[71:33] (4293.36s)
you're having where you can think of
[71:35] (4295.12s)
this as like a fraction and the the
[71:37] (4297.20s)
numerator is like how much impact is
[71:39] (4299.16s)
there but obviously the denominator is
[71:41] (4301.36s)
like how much effort and time and
[71:43] (4303.84s)
complexity is this thing going to be and
[71:46] (4306.72s)
actually if someone tells me this is I'm
[71:48] (4308.80s)
going to have the biggest impact with
[71:50] (4310.88s)
like a oneline change that is just not
[71:53] (4313.44s)
doing some additional work it's amazing
[71:55] (4315.40s)
I prefer that to the crazy you know
[71:58] (4318.00s)
year-long project that's like super
[71:59] (4319.96s)
complex and adds all this maintenance
[72:01] (4321.84s)
that that was one place that was one
[72:03] (4323.24s)
place where meta's culture excelled and
[72:06] (4326.44s)
I don't know to the extent that this has
[72:07] (4327.52s)
changed since I've left of course you're
[72:08] (4328.80s)
still there so you can speak to this but
[72:10] (4330.48s)
I know at other companies if you're the
[72:11] (4331.88s)
guy who made the oneline change and it
[72:13] (4333.32s)
had huge impact you're going to be
[72:15] (4335.16s)
rewarded proportional to the difficulty
[72:18] (4338.52s)
the oneline change right whereas at meta
[72:20] (4340.56s)
that wasn't the case like it was like
[72:22] (4342.20s)
you had huge impact and nobody else
[72:24] (4344.76s)
thought to that one mind but you did and
[72:27] (4347.40s)
so you're rewarded for it and that
[72:29] (4349.36s)
creates this culture that's so important
[72:31] (4351.44s)
of go find the impact it doesn't have to
[72:33] (4353.80s)
be the hard crazy thing it doesn't have
[72:35] (4355.12s)
to be a lot of work find the impact and
[72:37] (4357.04s)
have positive impact for the company and
[72:38] (4358.32s)
you're rewarded and so that's always
[72:39] (4359.96s)
been a fantastic thing about medic
[72:41] (4361.16s)
culture yeah absolutely that's the
[72:43] (4363.84s)
number one thing that I enjoy about meta
[72:46] (4366.56s)
culture and I think no matter where I'm
[72:48] (4368.32s)
working I'm always going to take that
[72:49] (4369.80s)
with me for the rest of my career just
[72:52] (4372.12s)
that impact is everything I don't care
[72:54] (4374.52s)
how it happens who does it it's just
[72:57] (4377.20s)
let's just get the job done and make
[72:59] (4379.64s)
things better and in that case sounds
[73:01] (4381.32s)
like you you were trusted with the scope
[73:03] (4383.48s)
the team grew to something where it's
[73:05] (4385.68s)
you're basically doing an ic's job and
[73:08] (4388.52s)
you delivered massively more than anyone
[73:11] (4391.60s)
expected so I think the ic6 promo made a
[73:15] (4395.08s)
lot of sense one thing that I think is
[73:17] (4397.00s)
unique about your career path as
[73:20] (4400.00s)
especially starting from four and onward
[73:22] (4402.56s)
or midlevel to staff is it seems like
[73:25] (4405.20s)
like your management Shane was trusting
[73:26] (4406.60s)
you almost as a manager they were
[73:28] (4408.56s)
telling you to give us how many
[73:30] (4410.52s)
headcount you need and you're having
[73:32] (4412.04s)
one-on ones with people and you were
[73:34] (4414.28s)
growing people in that sense did that
[73:36] (4416.24s)
come naturally to you and am I seeing
[73:38] (4418.20s)
that uh right like that you were not
[73:40] (4420.80s)
purely doing IC stuff you were also kind
[73:43] (4423.08s)
of an extension of your manager and
[73:45] (4425.24s)
doing some management stuff yeah I think
[73:46] (4426.92s)
that's fair and actually I wanted to
[73:48] (4428.00s)
jump in and mention this so I'm glad
[73:49] (4429.12s)
that you brought it back like
[73:50] (4430.12s)
Technically when defining well I guess
[73:52] (4432.24s)
you can't say technically cuz Tech lead
[73:54] (4434.00s)
isn't a Define role but traditionally
[73:56] (4436.96s)
Tech lead is that you're setting the
[73:58] (4438.16s)
technical direction for the team and so
[73:59] (4439.60s)
as you just described my role had like a
[74:02] (4442.04s)
lot more of a people aspect maybe than
[74:04] (4444.52s)
was traditionally the case and of course
[74:06] (4446.88s)
these Engineers were still having one-on
[74:08] (4448.00s)
ones with their real manager their real
[74:09] (4449.64s)
manager was determining their promos and
[74:11] (4451.72s)
whatnot but certainly when I was senior
[74:14] (4454.24s)
and absolutely when I was at staff
[74:15] (4455.96s)
absolutely when I was at staff I was
[74:17] (4457.16s)
like kind of explicitly in those
[74:18] (4458.76s)
conversations to help my manager have
[74:21] (4461.60s)
visibility and make determinations about
[74:24] (4464.40s)
the given engineer on the team's
[74:25] (4465.56s)
performance reviews even to the point
[74:27] (4467.24s)
where at least we attempted to have me
[74:30] (4470.40s)
attend a uh a calibrations and an
[74:33] (4473.04s)
ultimately ended up getting shut down
[74:34] (4474.28s)
for whatever reason from from the
[74:35] (4475.40s)
director as an ic5 or as an IC as an ic6
[74:38] (4478.72s)
as an ic6 but yeah why that ended up
[74:40] (4480.40s)
happening I'm not sure I think I really
[74:42] (4482.28s)
enjoyed it and like I took it so
[74:44] (4484.40s)
seriously like I I really wanted to be
[74:46] (4486.52s)
good at it and so I was really observing
[74:48] (4488.00s)
what my manager was doing I read the
[74:49] (4489.56s)
making of a manager when I became when I
[74:52] (4492.96s)
became the tech lead of graphic violence
[74:54] (4494.48s)
I read that book thinking like I really
[74:56] (4496.40s)
got to learn how to kind of lead right
[74:58] (4498.32s)
and it was a great book and yeah I don't
[74:59] (4499.72s)
know I just I took it seriously and I
[75:01] (4501.16s)
think the fact that I excel did it and
[75:02] (4502.76s)
importantly I don't want to speak for
[75:04] (4504.32s)
any of the engineers that I worked with
[75:05] (4505.84s)
but I was never aware of any time where
[75:08] (4508.08s)
people felt uneasy with my leadership or
[75:11] (4511.12s)
like I wasn't on their team and
[75:12] (4512.56s)
supporting them and I think that's where
[75:14] (4514.40s)
those things will typically go wrong is
[75:16] (4516.40s)
there's either like components of
[75:18] (4518.52s)
competitiveness jealousy aggression
[75:21] (4521.36s)
whatever it is where it's like why are
[75:22] (4522.80s)
you in between me and my manager and why
[75:24] (4524.76s)
do you say what is going on and do you
[75:26] (4526.76s)
have my best interests like why am I
[75:28] (4528.76s)
navigating with this person now and I
[75:30] (4530.68s)
think probably subconsciously cuz I
[75:32] (4532.24s)
didn't do this explicitly necessarily
[75:34] (4534.28s)
but I just understood the value of being
[75:36] (4536.52s)
on everyone's team and on everyone's
[75:38] (4538.16s)
side and so to the favor stuff that we
[75:40] (4540.52s)
were talking about to just generally
[75:42] (4542.00s)
being nice and wanting to come to work
[75:44] (4544.00s)
like I thought and some people listening
[75:46] (4546.04s)
to this that were my old colleagues May
[75:47] (4547.40s)
disagree with some of these statements
[75:48] (4548.60s)
but I don't know of any that would like
[75:50] (4550.36s)
I was everyone's best friend and I was
[75:52] (4552.20s)
trying to help everyone and they knew
[75:53] (4553.52s)
that I had their best intentions in and
[75:55] (4555.32s)
that was genuinely true there was nobody
[75:57] (4557.28s)
that I felt kind of sour about in any
[75:59] (4559.24s)
way and I think that allowed me to
[76:02] (4562.20s)
continue to have that role without there
[76:04] (4564.40s)
being any significant tension because I
[76:05] (4565.92s)
could imagine any engineer feeling
[76:07] (4567.28s)
uncomfortable with it would raise that
[76:08] (4568.60s)
to a manager and then the manager would
[76:10] (4570.68s)
recognize that and kind of pull back
[76:12] (4572.00s)
that responsibility I gu was able to to
[76:13] (4573.80s)
navigate it cautiously enough they all
[76:16] (4576.00s)
had trust in you it sounds like because
[76:18] (4578.64s)
I mean not only were you genuinely
[76:20] (4580.48s)
caring and thinking about their growth
[76:22] (4582.60s)
but also you were someone who was very
[76:24] (4584.52s)
technical competent and I'm sure they
[76:27] (4587.12s)
had seen that you had demonstrated
[76:28] (4588.76s)
yourself repeatedly so because I've seen
[76:31] (4591.24s)
the case where someone who doesn't do
[76:33] (4593.92s)
all that soft skills stuff or the behind
[76:36] (4596.24s)
the scenes stuff and they have trouble
[76:38] (4598.40s)
with the transition into a more
[76:39] (4599.76s)
leadership role and so I think that's
[76:41] (4601.12s)
something that you did that was
[76:43] (4603.00s)
outstanding and I think was a large part
[76:44] (4604.88s)
of your success in these leadership
[76:46] (4606.36s)
roles maybe maybe the the last thing on
[76:48] (4608.08s)
this point that's really interesting
[76:49] (4609.20s)
that just came to mind for those
[76:50] (4610.80s)
listening at meta your level isn't
[76:53] (4613.28s)
public and so often times it's known
[76:55] (4615.28s)
within teams and on different teams it's
[76:57] (4617.08s)
known to varing degrees at my team at
[76:59] (4619.52s)
least like it wasn't it wasn't really
[77:02] (4622.20s)
talked about of course you knew the
[77:04] (4624.40s)
levels of the people like I knew the
[77:06] (4626.84s)
levels of the people on my team for
[77:08] (4628.32s)
example because I was involved in their
[77:09] (4629.52s)
promo packets or whatever else it may be
[77:11] (4631.32s)
of course but like I at least was under
[77:13] (4633.96s)
the impression often times that those
[77:16] (4636.84s)
that I was leading or those on my teams
[77:18] (4638.56s)
did not know my level and so there's no
[77:20] (4640.92s)
fall back of like I'm ic6 you you should
[77:23] (4643.28s)
listen to me it needed to be earned
[77:25] (4645.08s)
every day right like they didn't know
[77:27] (4647.48s)
what I was and they could guess or not
[77:29] (4649.44s)
guess but like they're probably doing
[77:30] (4650.68s)
the math and at times I had my own
[77:32] (4652.16s)
insecurity of like people are looking at
[77:33] (4653.80s)
my profile and saying that I've been at
[77:35] (4655.04s)
the company three years like and I have
[77:38] (4658.04s)
all of this responsibility they're
[77:39] (4659.44s)
probably writing me off or feeling some
[77:41] (4661.20s)
type of way about it or whatever else
[77:43] (4663.20s)
and it kind of kept me hungry because I
[77:45] (4665.24s)
couldn't rely on this like oh just look
[77:47] (4667.00s)
at my title and see that I have a bigger
[77:49] (4669.04s)
title than you so now listen and I think
[77:50] (4670.60s)
that's another thing that that is
[77:51] (4671.72s)
fantastic within meta culture I agree
[77:54] (4674.00s)
100% And I I think prior to me
[77:56] (4676.56s)
transitioning to management and actually
[77:58] (4678.76s)
knowing everyone's levels you just have
[78:02] (4682.20s)
this gauge this this high level thinking
[78:04] (4684.96s)
of like you know let's say I had joined
[78:06] (4686.80s)
your team and you're just outspoken in
[78:08] (4688.44s)
all the meetings these get a sense of
[78:10] (4690.04s)
okay this person knows what they're
[78:11] (4691.04s)
doing and I start to get credibility if
[78:12] (4692.76s)
you say things that are right all the
[78:14] (4694.08s)
time like okay this guy you know I trust
[78:17] (4697.00s)
this guy this is good and if he has
[78:19] (4699.44s)
proposed an idea I'm more likely to
[78:21] (4701.52s)
believe it and that sort of thing when I
[78:23] (4703.56s)
became a manager and I knew everyone's
[78:26] (4706.84s)
levels afterwards there was no surprises
[78:30] (4710.00s)
on my end even though I didn't know
[78:31] (4711.44s)
anyone's level I think if I you asked me
[78:33] (4713.28s)
to guess it I might have been off by
[78:34] (4714.92s)
plus or minus a level but when I became
[78:37] (4717.56s)
it I was thinking that makes sense this
[78:39] (4719.52s)
guy is amazing he deserves that level
[78:42] (4722.28s)
and you know these people yeah so I I I
[78:45] (4725.44s)
kind of I like that and I think one
[78:47] (4727.08s)
large part of growing the ic6 too is
[78:49] (4729.44s)
also being able to influence without
[78:52] (4732.00s)
Authority you people don't know your
[78:53] (4733.60s)
level so that's one thing you also they
[78:55] (4735.56s)
don't report to you you're not their
[78:56] (4736.88s)
manager directly in any way you know to
[78:59] (4739.00s)
get five people to go in your direction
[79:01] (4741.36s)
you got to convince them that you know
[79:03] (4743.44s)
what you're doing that you have a good
[79:05] (4745.08s)
idea that they can trust you and you
[79:08] (4748.12s)
have to do all of that without relying
[79:10] (4750.04s)
on some contrived thing that's like hey
[79:12] (4752.64s)
I'm a higher level than you you need to
[79:14] (4754.40s)
do what I say you just need to be right
[79:17] (4757.16s)
a lot and that's how you build trust
[79:20] (4760.04s)
totally yeah exactly exactly right about
[79:22] (4762.68s)
management by the way so sounds like you
[79:24] (4764.92s)
you were considering ic7 I guess before
[79:27] (4767.16s)
we talk about you leaving meta did at
[79:28] (4768.88s)
any point you consider going to
[79:30] (4770.60s)
management so I actually thought that's
[79:31] (4771.92s)
what I would do I thought I would go to
[79:32] (4772.88s)
six and then switch over to management
[79:34] (4774.40s)
and then for whatever reason maybe
[79:35] (4775.44s)
similar to what you were describing
[79:36] (4776.44s)
before like the opportunity to seven
[79:37] (4777.96s)
seemed clear enough and there's a lot of
[79:41] (4781.08s)
work that comes from being a manager I
[79:43] (4783.28s)
talked to a lot of my friends who had
[79:44] (4784.32s)
recently made that transition actually
[79:46] (4786.84s)
that first engineer that I had described
[79:48] (4788.56s)
earlier the senior engineer uh who I had
[79:50] (4790.88s)
built a built a good relationship with
[79:52] (4792.36s)
after kind of our initial
[79:53] (4793.28s)
competitiveness or my received
[79:55] (4795.00s)
competitiveness uh he certainly did not
[79:56] (4796.88s)
have the competitiveness he had recently
[79:58] (4798.28s)
transitioned to be a manager and I was
[80:00] (4800.08s)
hearing from him and like this stresses
[80:02] (4802.80s)
that come with the manager you know like
[80:04] (4804.28s)
you're you're directly responsible for
[80:06] (4806.08s)
people you have to take care of their
[80:08] (4808.44s)
issues and the BS that comes up and it's
[80:10] (4810.80s)
a large weight and I all of a sudden
[80:12] (4812.24s)
found myself in this like amazing place
[80:13] (4813.96s)
where my organization had grown
[80:15] (4815.76s)
tremendously I was sort of like the
[80:17] (4817.60s)
entry point of knowledge in many ways to
[80:20] (4820.00s)
the organization I had VP and director
[80:22] (4822.48s)
visibility and all these cool projects
[80:24] (4824.24s)
that I could work on across not just
[80:26] (4826.64s)
content Integrity my or but Integrity
[80:28] (4828.72s)
the the larger org of several thousand
[80:30] (4830.60s)
people yeah I decided that let me get to
[80:32] (4832.44s)
seven and then I'll think about
[80:33] (4833.96s)
switching maybe over to to M2 because
[80:37] (4837.60s)
then I would avoid the petty problems
[80:41] (4841.04s)
because m1's who are reporting to you
[80:42] (4842.92s)
typically have less small problems than
[80:46] (4846.36s)
you know Junior and mid-level folk
[80:47] (4847.72s)
reporting to you yeah for me I was faced
[80:50] (4850.40s)
with a similar decision I think I got to
[80:53] (4853.84s)
six and I was think thinking okay do I
[80:55] (4855.28s)
do seven or do I go to management and my
[80:59] (4859.44s)
manager told me and he was absolutely
[81:02] (4862.04s)
right in that he said if you stay as IC
[81:05] (4865.68s)
there's a path for ic7 I I can see it
[81:08] (4868.40s)
it's not that ambiguous you just it's
[81:10] (4870.92s)
continuation of your existing role and
[81:13] (4873.52s)
we need it if you become a manager it's
[81:16] (4876.68s)
a lot more based on opportunity and I
[81:19] (4879.48s)
just don't know like there there's a you
[81:22] (4882.12s)
you may get promoted you may not like
[81:24] (4884.12s)
there's just no not a whole lot of uh
[81:27] (4887.00s)
deterministic control in your your promo
[81:29] (4889.84s)
that being said I went to management
[81:32] (4892.60s)
anyways because you you stayed at ic6
[81:35] (4895.08s)
for a bit right you didn't immediately
[81:36] (4896.36s)
make the change for a bit not
[81:37] (4897.76s)
immediately but I also after some time I
[81:41] (4901.20s)
switched to tlm which was still kind of
[81:44] (4904.00s)
uh you know icy for a bit and I had a
[81:46] (4906.88s)
small team of maybe a few people may
[81:49] (4909.16s)
four five maybe for people who don't
[81:51] (4911.12s)
know Define tlm yeah tlm is a tech Le
[81:54] (4914.80s)
manager which is a role that some
[81:57] (4917.92s)
companies have where you are I'll
[82:01] (4921.08s)
describe it on a high level you're 70%
[82:03] (4923.56s)
IC 30% manager where you your
[82:06] (4926.56s)
contributions are still carried as being
[82:08] (4928.72s)
an IC but you have a small team of
[82:10] (4930.36s)
people that report to you often they're
[82:12] (4932.60s)
a team of Specialists or something like
[82:14] (4934.60s)
that where everyone's like kind of
[82:16] (4936.16s)
focused on like a very narrow
[82:18] (4938.00s)
technically challenging problem and so
[82:20] (4940.04s)
that's kind of like what I was doing and
[82:22] (4942.40s)
then I told my manager that you know
[82:24] (4944.60s)
kind of want to grow more as a manager
[82:26] (4946.88s)
and eventually uh pivoted a little more
[82:29] (4949.68s)
into a org leader which is just a
[82:32] (4952.00s)
traditional manager but yeah I I
[82:33] (4953.88s)
switched to manager well one because my
[82:36] (4956.44s)
intrinsic desire was let's learn this
[82:39] (4959.24s)
new set of behaviors I feel like this
[82:40] (4960.80s)
will be cool learn a lot but the other
[82:42] (4962.84s)
thing is I felt like if I grew to ic7 I
[82:46] (4966.04s)
would become a snowflake or like I
[82:49] (4969.16s)
become this this very unique tool for
[82:53] (4973.72s)
very very big companies and I'm always
[82:57] (4977.24s)
thinking about the long term and I just
[82:58] (4978.92s)
thought that okay I go to seven and then
[83:01] (4981.36s)
what now I'm I I kind of like narrowed
[83:03] (4983.88s)
the opportunities that I can fit into
[83:06] (4986.56s)
and I'm only useful in a handful of very
[83:10] (4990.92s)
very big companies and even more so if I
[83:13] (4993.52s)
were to grow to ic8 and at that point
[83:15] (4995.48s)
you kind of the the show ends there some
[83:18] (4998.36s)
people get to ic9 but it's for the most
[83:20] (5000.76s)
part that's the end of your your growth
[83:22] (5002.96s)
and at a certain point you've handcuffed
[83:24] (5004.68s)
to that given company yes like in meta's
[83:26] (5006.60s)
case if you make it to IC not only do
[83:28] (5008.56s)
you have so much Equity that to leave
[83:29] (5009.88s)
would be crazy but you're not going to
[83:32] (5012.24s)
get hired especially you know at our
[83:33] (5013.92s)
trajectories let's just say
[83:35] (5015.32s)
hypothetically I don't know the number
[83:36] (5016.92s)
of years but eight years or something to
[83:39] (5019.56s)
to IC to be eight years into your career
[83:41] (5021.76s)
and go over to Google or whomever else
[83:43] (5023.32s)
and say I'd like an ic8 they'd they
[83:45] (5025.76s)
laugh at you right so and you wouldn't
[83:48] (5028.36s)
want to go take the the huge decrease in
[83:50] (5030.88s)
pay and lose all that Equity so you're
[83:52] (5032.84s)
just like you're kind of stuck is an I8
[83:54] (5034.80s)
at meta forever yep definitely and
[83:57] (5037.44s)
because a lot of your impact is coming
[83:58] (5038.88s)
from your credibility within this or you
[84:01] (5041.28s)
go to Google you don't necessarily have
[84:03] (5043.40s)
that and so I just felt like although I
[84:05] (5045.92s)
might have been happier in the short
[84:07] (5047.24s)
term going to ic7 and all of that I
[84:11] (5051.60s)
decided let's try out this new path and
[84:14] (5054.76s)
let's learn management and I felt like I
[84:16] (5056.88s)
had a unique opportunity to do so not
[84:19] (5059.00s)
always easy to transition to management
[84:21] (5061.20s)
especially as such a young IC at the
[84:23] (5063.20s)
time so I felt like okay let's let's go
[84:25] (5065.48s)
for it and what what what stands out as
[84:27] (5067.84s)
the of single biggest learning so far
[84:30] (5070.52s)
well first thing I'll say is for the
[84:32] (5072.04s)
people out there who are thinking about
[84:33] (5073.32s)
career growth and all that what my
[84:35] (5075.16s)
manager said was right my career my your
[84:38] (5078.52s)
career as a manager is kind of
[84:39] (5079.96s)
proportional to the number of recursive
[84:41] (5081.92s)
reports you have and you know unless
[84:43] (5083.76s)
your team is growing quickly you're not
[84:46] (5086.04s)
going to get to that next thing so you
[84:47] (5087.96s)
kind of couple yourself to the growth of
[84:50] (5090.32s)
your org which can be a good or bad
[84:52] (5092.32s)
thing especially now at metan across all
[84:53] (5093.96s)
the big companies with the age of
[84:55] (5095.20s)
efficiency exactly exactly the or CH got
[84:57] (5097.88s)
squeezed yeah yeah yeah exact opportun
[85:00] (5100.44s)
there five years ago the trees were just
[85:02] (5102.68s)
growing and growing and growing y y
[85:05] (5105.48s)
exactly so I've gotten very lucky in my
[85:08] (5108.32s)
career I could say this is uh me giving
[85:10] (5110.76s)
back a little bit I switched to
[85:11] (5111.96s)
management at the time where it was
[85:13] (5113.96s)
maybe an unlucky time to do so but yeah
[85:16] (5116.44s)
other than that I mean a lot of the
[85:18] (5118.00s)
things that you hear stereotypically are
[85:19] (5119.56s)
also true I think what you mentioned
[85:21] (5121.44s)
about dealing with people problems like
[85:23] (5123.72s)
a lot of the I guess sevs or like major
[85:26] (5126.44s)
incidents that I think about now are
[85:28] (5128.64s)
this person is you know has some issue
[85:31] (5131.52s)
with that team and he's unhappy or
[85:33] (5133.32s)
something like that and then another
[85:34] (5134.72s)
interesting thing is your your work
[85:36] (5136.72s)
hours become like a solid block of
[85:39] (5139.20s)
meetings from like 9 to5 as a as a tech
[85:42] (5142.00s)
lead or as an IC I would you have like
[85:45] (5145.00s)
dis fragmented meetings along the day
[85:47] (5147.60s)
and then I would work like kind of later
[85:49] (5149.64s)
Into the Night On My IC stuff so maybe I
[85:52] (5152.72s)
worked a larger number of hours but I
[85:55] (5155.48s)
had more flexibility and control as a
[85:57] (5157.72s)
manager is just you know you you log in
[86:00] (5160.48s)
you attend those meetings you log out
[86:02] (5162.56s)
because I can't really do a whole lot
[86:04] (5164.96s)
without people and so I kind of you know
[86:07] (5167.64s)
it's not like I can just grind into the
[86:09] (5169.16s)
night get things done so and if you are
[86:11] (5171.72s)
doing that you're filling out
[86:13] (5173.04s)
performance reviews or something which
[86:14] (5174.44s)
isn't exactly fun to be doing L yeah
[86:16] (5176.92s)
yeah that's that's coming up soon
[86:18] (5178.52s)
performance re that's the chore that you
[86:21] (5181.08s)
that's definitely maybe the grindi time
[86:23] (5183.48s)
of my career is when there's performance
[86:25] (5185.92s)
reviews you just non-stop meetings all
[86:28] (5188.72s)
day writing all night meetings all day
[86:31] (5191.16s)
writing all night brutal um yeah so
[86:35] (5195.04s)
there's the manager I don't I don't envy
[86:37] (5197.96s)
sir yeah I'll say uh being an IC does
[86:41] (5201.60s)
give you that flexibility that makes
[86:44] (5204.04s)
life a little more you have more control
[86:45] (5205.76s)
of your own stuff okay so you you got to
[86:48] (5208.00s)
staff and then you left what uh what
[86:51] (5211.80s)
made you want to leave meta so I stayed
[86:53] (5213.76s)
for another
[86:55] (5215.24s)
a little over year and a half which felt
[86:56] (5216.56s)
significant like I I feel like I mean
[86:58] (5218.52s)
almost half of my time not quite but uh
[87:01] (5221.84s)
a third of my time was spent there and
[87:04] (5224.36s)
like the team continued to grow was
[87:05] (5225.96s)
doing all of that crossw workg stuff
[87:07] (5227.20s)
that I had mentioned as I said the team
[87:08] (5228.76s)
split into two a new manager had come in
[87:11] (5231.60s)
that was a really cool relationship
[87:13] (5233.16s)
because he came in and immediately it
[87:15] (5235.16s)
was like you know and he said this in
[87:17] (5237.52s)
his quotes like this is this is your
[87:19] (5239.56s)
team I'm not here to take it you know
[87:21] (5241.68s)
you and I are Partners let's figure out
[87:23] (5243.52s)
how we can grow this and do all of this
[87:25] (5245.00s)
together and that that was like a really
[87:26] (5246.40s)
cool opportunity where I saw more of
[87:27] (5247.80s)
that management angle in particular and
[87:29] (5249.84s)
we were shooting we were shooting for
[87:30] (5250.92s)
seven like I really wanted to continue
[87:32] (5252.88s)
at this point the one half two half
[87:34] (5254.48s)
three halves and then now four halves
[87:37] (5257.00s)
seven right and that was that was like
[87:38] (5258.92s)
our plan you know we were going to get
[87:40] (5260.32s)
try to go up for it and who knows if
[87:42] (5262.24s)
we'd come up just shy or not you know
[87:43] (5263.92s)
and if we did we'd go the next half so I
[87:45] (5265.84s)
thought that was going to be it like you
[87:47] (5267.44s)
make a ton of money at seven life's
[87:49] (5269.00s)
great you making a ton of money of
[87:50] (5270.16s)
course at six and all these things
[87:51] (5271.52s)
that's what I thought the path was but
[87:52] (5272.80s)
that first manager who I had mentioned
[87:54] (5274.92s)
have mentioned a number of times now who
[87:56] (5276.32s)
I massively respected had the biggest
[87:58] (5278.28s)
influence in my career most brilliant
[88:00] (5280.44s)
person I've ever worked with respected
[88:03] (5283.24s)
infinitely um he started messaging me he
[88:06] (5286.04s)
had moved to a different team at this
[88:07] (5287.32s)
point he was an M2 elsewhere and this
[88:10] (5290.80s)
was when web 3 was becoming all over
[88:12] (5292.44s)
agage a little fun yeah exactly exactly
[88:16] (5296.48s)
so people who bought into it as I it at
[88:18] (5298.32s)
the time this was like and it may still
[88:20] (5300.00s)
happen but like the next iteration of
[88:21] (5301.68s)
the internet a decentralized better
[88:23] (5303.72s)
internet right with all the benefits
[88:25] (5305.32s)
that come from it and so in college I
[88:28] (5308.60s)
really liked crypto Ean goon Seer was my
[88:32] (5312.08s)
the adviser of our hacking Club I was
[88:34] (5314.24s)
also a TA for him and he's really
[88:36] (5316.44s)
influential in the crypto Community um
[88:38] (5318.84s)
he's the current CEO and founder of of
[88:41] (5321.04s)
avalanche one of one of the the larger
[88:42] (5322.88s)
blockchains as well now and at the time
[88:44] (5324.96s)
he was working a lot on on bitcoin and
[88:47] (5327.00s)
other similar Pro uh projects and he had
[88:49] (5329.44s)
research assistants in there working on
[88:50] (5330.80s)
it so I was kind of prived all of that I
[88:52] (5332.64s)
was excited by it I was close to while
[88:54] (5334.32s)
he was doing it I was investing all of
[88:55] (5335.88s)
those things and so when I joined meta I
[88:57] (5337.60s)
was like kind of the crypto guy sounds
[89:00] (5340.24s)
funny now and so my manager at that time
[89:03] (5343.76s)
now fast forward back to when he was on
[89:05] (5345.88s)
the different team he started messaging
[89:07] (5347.52s)
me about crypto stuff and about web 3
[89:09] (5349.28s)
because he knew that I had interests
[89:10] (5350.60s)
there and so him and I were just talking
[89:11] (5351.84s)
a little bit on messenger outside of a
[89:14] (5354.36s)
professional context and we were
[89:17] (5357.32s)
brainstorming ideas and eventually it
[89:19] (5359.60s)
got to a point where we've we built
[89:21] (5361.04s)
something for fun just the two of us
[89:22] (5362.56s)
outside of work and we launched it and
[89:25] (5365.12s)
it got a you know 10,000 users or so in
[89:28] (5368.12s)
relatively quick order and then we found
[89:29] (5369.68s)
ourselves in a position where he was
[89:32] (5372.00s)
ready he was ready to do startups he
[89:34] (5374.52s)
always wanted to I never thought that
[89:36] (5376.12s)
was going to be something that I was
[89:37] (5377.12s)
going to do and I saw my path to
[89:38] (5378.72s)
promotion I was like why would I ever
[89:39] (5379.88s)
leave this this place is great I'm going
[89:41] (5381.08s)
to stay here until I'm a VP and just
[89:42] (5382.48s)
like retire into the sunset But
[89:43] (5383.84s)
ultimately there was this opportunity
[89:45] (5385.88s)
where I had the person who I respected
[89:47] (5387.60s)
more than anybody in the world
[89:48] (5388.96s)
professionally and we could go leave and
[89:50] (5390.92s)
try to do something and we had something
[89:53] (5393.92s)
that that had some traction I initially
[89:55] (5395.76s)
said like I'm not going to leave until
[89:58] (5398.28s)
uh we get funding ultimately I don't
[90:01] (5401.36s)
know it was just it was too fun and too
[90:03] (5403.36s)
big of an opportunity to give up and so
[90:05] (5405.88s)
I left I left all the equity I left all
[90:07] (5407.84s)
the opportunities and all of these
[90:09] (5409.32s)
things uh in order to start a startup
[90:11] (5411.92s)
and there were certainly regrets
[90:13] (5413.76s)
throughout the last it's now been over
[90:15] (5415.28s)
two years I think it's going to be 3
[90:16] (5416.44s)
years in March sheesh but in hindsight
[90:18] (5418.68s)
now I don't regret it for a moment so
[90:20] (5420.56s)
what is the thing that made you want to
[90:22] (5422.44s)
leave because you had this this golden
[90:24] (5424.68s)
ticket to probably seven figure plus
[90:27] (5427.20s)
earnings yeah even thinking back to it
[90:29] (5429.00s)
in hindsight it was kind of crazy um but
[90:32] (5432.28s)
there was no convincing from my manager
[90:34] (5434.56s)
and now co-founder at that time he was
[90:36] (5436.12s)
super respectful of kind of my needs and
[90:37] (5437.68s)
my decision and all that ultimately it
[90:39] (5439.68s)
was that the things that we were talking
[90:41] (5441.28s)
about after hours the things that we
[90:43] (5443.00s)
were tinkering with after hours ended up
[90:45] (5445.40s)
becoming more fun than my day-to-day job
[90:47] (5447.96s)
and ultimately I would wake up in the
[90:49] (5449.04s)
morning and I would I would go to meta
[90:50] (5450.88s)
work from you know my 7 to 5 7 to 4
[90:53] (5453.16s)
whatever it was and I would be thinking
[90:54] (5454.76s)
about when work ended being able to
[90:57] (5457.12s)
think about those different problems and
[90:59] (5459.60s)
so it got to a point where I would have
[91:01] (5461.08s)
rather been doing that and I wanted to
[91:02] (5462.40s)
spend my time doing that and so without
[91:04] (5464.56s)
funding without any of these things just
[91:06] (5466.84s)
a little bit of traction who took the
[91:08] (5468.16s)
lead you left and then you went and you
[91:09] (5469.84s)
said you worked on startups for for two
[91:11] (5471.92s)
years now what what's the high level
[91:14] (5474.08s)
road map so far yeah so the really high
[91:16] (5476.20s)
Lev tldr is that we left with this web3
[91:18] (5478.20s)
company we don't need to get into too
[91:19] (5479.24s)
much detail at a high level it was like
[91:21] (5481.04s)
we called it a social intelligence layer
[91:23] (5483.00s)
so combining activities that people were
[91:24] (5484.88s)
doing in quotee unquote web 2 largely on
[91:27] (5487.56s)
Twitter where people interact with
[91:29] (5489.20s)
crypto nfts Etc with what was happening
[91:31] (5491.28s)
on chain and then being able to do like
[91:32] (5492.84s)
some rankings and predictions and
[91:35] (5495.32s)
whatnot based on those combined
[91:36] (5496.56s)
movements that was the the first company
[91:38] (5498.72s)
and it went well enough like it it grew
[91:40] (5500.56s)
significantly got to I guess
[91:42] (5502.16s)
significantly in quote it's 100,000
[91:43] (5503.68s)
users which is like a significant
[91:45] (5505.00s)
portion of the active space at that time
[91:47] (5507.16s)
we raised money we were growing great
[91:50] (5510.04s)
things and then there was a lot of
[91:51] (5511.16s)
interest in acquisition and we
[91:52] (5512.72s)
entertained that interest in acquisition
[91:54] (5514.12s)
unfortunately for us it ended up being
[91:56] (5516.00s)
about the time when the market took a
[91:57] (5517.92s)
downturn ironically now here we are
[91:59] (5519.84s)
having this conversation and Bitcoin and
[92:01] (5521.24s)
crypto is back up to the moon but there
[92:03] (5523.12s)
was kind of a lull there right and so we
[92:05] (5525.60s)
ended up we ended up selling selling
[92:07] (5527.32s)
that company and then we found ourselves
[92:08] (5528.80s)
in this awkward position where it's like
[92:10] (5530.56s)
we left our jobs for this like big web 3
[92:13] (5533.16s)
Vision thing that's not working out what
[92:15] (5535.84s)
do we do now we we have each other I had
[92:18] (5538.76s)
my questions of like should I just go
[92:20] (5540.04s)
back to Big Tech I think that was never
[92:21] (5541.32s)
really in the cards for him he was ready
[92:22] (5542.76s)
to continue to move on and I figured
[92:25] (5545.52s)
whatever like here we are two people I
[92:27] (5547.44s)
trust him I trust us we have some money
[92:29] (5549.64s)
from the sale let's let's shoot and so
[92:32] (5552.20s)
we ended up in this period of just
[92:33] (5553.32s)
trying so many different things and this
[92:34] (5554.92s)
was probably like a six eight month
[92:36] (5556.40s)
period of just like trying ideas and
[92:38] (5558.80s)
these were ideas from like truck
[92:40] (5560.32s)
factoring and invoicing uh to things in
[92:43] (5563.56s)
the design space to things literally all
[92:45] (5565.60s)
over the map and nothing was totally
[92:47] (5567.68s)
clicking and then throughout that
[92:49] (5569.64s)
Journey we built another product which
[92:51] (5571.00s)
was pretty fun it allowed you to go to
[92:52] (5572.80s)
any website you click one button to copy
[92:55] (5575.16s)
that website and directly paste it
[92:56] (5576.72s)
contrl V into figma and you would have
[92:58] (5578.80s)
fully editable figma frames that you can
[93:00] (5580.76s)
move around and edit and what not so a
[93:02] (5582.08s)
great tool for designers to able to do
[93:03] (5583.48s)
that and this was cool there's a lot of
[93:04] (5584.96s)
technical sophistication to it we had to
[93:06] (5586.52s)
reverse engineer and and my co-founder
[93:08] (5588.56s)
to his credit did did the majority of
[93:10] (5590.04s)
this reverse engineering the ability to
[93:12] (5592.68s)
paste things in in the first place CU
[93:14] (5594.40s)
that was encrypt encrypted and so that
[93:16] (5596.92s)
was hugely valuable and there were other
[93:18] (5598.28s)
companies in the space that wanted that
[93:19] (5599.44s)
technology and so after only a couple of
[93:20] (5600.92s)
months they came knocking on the door
[93:22] (5602.16s)
and then they ended up buying that
[93:23] (5603.16s)
technology call it two Acquisitions hand
[93:25] (5605.56s)
wavy a little bit loose and then we find
[93:27] (5607.16s)
ourselves in that same position again
[93:29] (5609.12s)
okay we have a little bit more money now
[93:30] (5610.56s)
in each other but no ideas and we tried
[93:33] (5613.04s)
a bunch of more things and ultimately
[93:35] (5615.00s)
what we wanted to do was like let's just
[93:36] (5616.24s)
do something that a we know really
[93:37] (5617.80s)
really well and B that we're passionate
[93:39] (5619.80s)
about and ultimately what that was was
[93:41] (5621.76s)
interviewing and hiring and helping
[93:44] (5624.16s)
candidates prepare for interviews and so
[93:46] (5626.24s)
this is like now the beginning of kind
[93:47] (5627.84s)
of chat DPT wave and so we're like can
[93:51] (5631.24s)
we make AI mock interviews like why
[93:53] (5633.80s)
people have to practice with a human why
[93:54] (5634.96s)
can't they just practice with an AI
[93:56] (5636.36s)
let's make this good and so we tried and
[93:59] (5639.28s)
it wasn't very good um some people paid
[94:01] (5641.76s)
for it but not many and so we started to
[94:04] (5644.00s)
do inperson mock interviews in order to
[94:05] (5645.80s)
get training data and we would do these
[94:07] (5647.20s)
for free with our paying users in order
[94:09] (5649.12s)
to get training data and after every
[94:10] (5650.12s)
single one of them they would look at us
[94:11] (5651.24s)
and they would be like please let me pay
[94:12] (5652.80s)
you to do more of that like that was
[94:14] (5654.20s)
huge for me and we would say no no no
[94:16] (5656.12s)
we're not an inperson mock interview
[94:17] (5657.48s)
business that's crazy like we're we're
[94:19] (5659.36s)
technologists we're building cool AI
[94:21] (5661.16s)
mock interviews whatever and then
[94:22] (5662.28s)
eventually after the the two dozenth
[94:25] (5665.12s)
person has asked that you learn as a
[94:27] (5667.44s)
startup founder that you have to do what
[94:29] (5669.04s)
people are willing to pay for and so we
[94:31] (5671.08s)
put on the side of the website in small
[94:33] (5673.12s)
inperson mock interviews and big was AI
[94:35] (5675.72s)
interviews and then quickly it was just
[94:37] (5677.56s)
Stephan and I that that's my co-founders
[94:39] (5679.76s)
name it was just Stephan and I and we
[94:41] (5681.04s)
were booked like three four five soon
[94:43] (5683.56s)
six seven mocks a day um and we were
[94:46] (5686.52s)
like oh smokes people people want this
[94:48] (5688.92s)
and people want to pay for this and so
[94:51] (5691.20s)
that continued to grow tldr hello
[94:54] (5694.16s)
interview is the current company uh we
[94:56] (5696.24s)
do in-person mock interviews with
[94:58] (5698.96s)
current senior engineers and managers
[95:01] (5701.96s)
from your target company as well as now
[95:04] (5704.28s)
we've brought back some of the AI guided
[95:06] (5706.40s)
learning stuff in a much improved
[95:08] (5708.00s)
capacity that people are really enjoying
[95:09] (5709.96s)
as well as a lot of free and paid
[95:11] (5711.84s)
resources you know from an educational
[95:13] (5713.48s)
perspective content so when you look
[95:15] (5715.24s)
back on
[95:16] (5716.40s)
yourent startups or your current lag in
[95:19] (5719.12s)
startups from a financial perspective do
[95:21] (5721.80s)
you did you out earn what you would have
[95:23] (5723.92s)
earned in big Tech because that no okay
[95:27] (5727.64s)
not yet anyway I mean there's there's
[95:29] (5729.36s)
there's time still yet right but right
[95:31] (5731.28s)
right not yet but but what I will say
[95:33] (5733.16s)
and this might have been your next
[95:34] (5734.16s)
question but I'll beat you to the punch
[95:35] (5735.56s)
it's been far worth it the value in
[95:37] (5737.72s)
terms of the monetary compensation has
[95:39] (5739.88s)
not equated yet certainly not um but the
[95:42] (5742.72s)
value in terms of experiences and purely
[95:45] (5745.60s)
technical knowledge has far outpace that
[95:48] (5748.68s)
of what I would have learned at meta and
[95:50] (5750.36s)
so when I think about my projected
[95:52] (5752.12s)
earnings over the lifetime of my career
[95:54] (5754.60s)
I think that my projected earnings will
[95:56] (5756.72s)
be significantly higher than if I had
[95:58] (5758.36s)
even stayed and gone to 78 Etc and the
[96:01] (5761.44s)
reason for this is that now I've learned
[96:03] (5763.80s)
a ton of things that I otherwise
[96:05] (5765.48s)
wouldn't have known I've learned how to
[96:07] (5767.24s)
learn and I've learned all sorts of
[96:09] (5769.04s)
these skills outside of Technology about
[96:10] (5770.84s)
how to build a company and these things
[96:12] (5772.52s)
are invaluable it hasn't gotten there
[96:13] (5773.88s)
yet it's all a ways to go until it gets
[96:15] (5775.68s)
there but I'm optimistic that kind of
[96:18] (5778.24s)
the compensation will catch up to the
[96:19] (5779.88s)
value of increased learning when you
[96:21] (5781.68s)
mentioned the stuff that you don't learn
[96:23] (5783.84s)
in big Tech that you only learn in
[96:25] (5785.40s)
startups that are going to pay dividends
[96:27] (5787.92s)
can you talk a little bit about that
[96:29] (5789.48s)
yeah totally this is this is one that
[96:30] (5790.84s)
I'm I'm pretty passionate about so this
[96:32] (5792.32s)
is at least true in my experience this
[96:33] (5793.68s)
doesn't extrapolate to everybody of
[96:34] (5794.92s)
course but like in starting startups I
[96:36] (5796.68s)
realized that I was an idiot like I left
[96:38] (5798.48s)
big Tech with a relative ego all these
[96:41] (5801.44s)
past promotions I'm the man I'm good I'm
[96:43] (5803.92s)
good on my team my team's grown 16
[96:46] (5806.00s)
people leading all these cool things
[96:47] (5807.28s)
whatever and I leave all of that to
[96:49] (5809.28s)
realize I don't know a damn thing at
[96:51] (5811.16s)
meta you work on the narrowest not only
[96:53] (5813.16s)
had I really coded significantly in a
[96:55] (5815.84s)
year and a half at this point because it
[96:57] (5817.20s)
was mostly you know ideation and and and
[96:59] (5819.56s)
Leadership at this point but to the
[97:00] (5820.92s)
extent that I was coding and I was the
[97:02] (5822.36s)
quote unquote quote unquote code machine
[97:04] (5824.80s)
it was narrowly on this small thing and
[97:07] (5827.52s)
so I work on my small thing and then I
[97:09] (5829.12s)
hit go and then within six hours that is
[97:11] (5831.60s)
affecting three billion people and every
[97:13] (5833.64s)
single post that comes into Facebook
[97:15] (5835.80s)
right but I didn't figure out how to
[97:17] (5837.36s)
make that happened I figured out how to
[97:18] (5838.76s)
do my little thing but everyone else did
[97:20] (5840.76s)
everything else around me and so like I
[97:22] (5842.92s)
had never set up a simple caching layer
[97:24] (5844.84s)
i' never configured my own database I
[97:26] (5846.68s)
had never stood up my own I suppose I
[97:29] (5849.24s)
had done some of these things at a small
[97:31] (5851.08s)
capacity in college but by and large and
[97:33] (5853.92s)
now I have to do it we have to do it
[97:36] (5856.80s)
right stepan and I and so at first like
[97:39] (5859.76s)
it was super humbling it was like crap
[97:42] (5862.48s)
this is really hard I don't know any of
[97:44] (5864.40s)
this and like we're doing a lot of front
[97:45] (5865.92s)
end stuff I'd never written a line of
[97:47] (5867.08s)
frontend code and I have to learn all of
[97:49] (5869.08s)
a sudden at the time like we were
[97:50] (5870.76s)
slinging raw jQuery we've now evolved in
[97:53] (5873.04s)
a you know using react but like I didn't
[97:55] (5875.20s)
know any of these things and it was
[97:56] (5876.96s)
incredibly stressful incredibly
[97:58] (5878.36s)
overwhelming and now here I am on the
[97:59] (5879.96s)
other side of it and I feel like I now
[98:03] (5883.20s)
have practical skills you can drop me
[98:06] (5886.16s)
into any situation and I can figure it
[98:08] (5888.16s)
out I can go to any other big tech
[98:09] (5889.64s)
company I can go to any other startup I
[98:11] (5891.00s)
can do whatever else and like I have the
[98:12] (5892.92s)
experiences that are transferable to our
[98:15] (5895.12s)
point about the ic8 at meta not being
[98:17] (5897.48s)
particularly transferable I think that's
[98:19] (5899.24s)
exactly the point here I've heard very
[98:21] (5901.28s)
similar opinion from most people that go
[98:23] (5903.60s)
to startups I've only heard one person
[98:25] (5905.68s)
that told me that they felt like the
[98:29] (5909.16s)
technical learning was not as fast at a
[98:33] (5913.60s)
startup because they felt like the
[98:35] (5915.40s)
problems that they were dealing with
[98:37] (5917.04s)
were smaller trivial you know like just
[98:40] (5920.52s)
setting things up you know going through
[98:42] (5922.08s)
tutorials getting the database up that's
[98:44] (5924.28s)
a solved problem that at meta which in
[98:47] (5927.40s)
it's a good thing that it's a solved
[98:48] (5928.76s)
problem because the fun and the deeply
[98:51] (5931.28s)
technical stuff is when you kind of are
[98:53] (5933.56s)
digging into the specialist problems
[98:55] (5935.12s)
that are on the the higher level I think
[98:57] (5937.12s)
probably the right thing is to do it in
[98:58] (5938.32s)
the inverse order than I did it oh so
[99:00] (5940.00s)
start at a startup and then go into big
[99:02] (5942.08s)
Tech I wouldn't recommend that for
[99:03] (5943.12s)
someone from a career perspective but I
[99:04] (5944.80s)
would recommend it from a learning
[99:05] (5945.84s)
perspective because then you get the
[99:06] (5946.84s)
bread you understand how to do all of
[99:08] (5948.32s)
these things and then the optimizations
[99:10] (5950.04s)
that you're doing in big Tech are within
[99:11] (5951.68s)
context and I think that that's that
[99:13] (5953.48s)
would be valuable I think yeah to
[99:14] (5954.72s)
generalize it I think big Tech Absol
[99:17] (5957.24s)
absolutely gets you the depth and
[99:19] (5959.48s)
startups absolutely gets you the bread
[99:21] (5961.68s)
you got to do everything even outside
[99:23] (5963.48s)
the technical you got to do all this
[99:25] (5965.16s)
random stuff that you might not and and
[99:27] (5967.04s)
and maybe the last point there is that
[99:28] (5968.76s)
what I wish I had done while I was at
[99:30] (5970.32s)
meta has been a bit more inquisitive
[99:32] (5972.40s)
about how things worked and so it was
[99:34] (5974.84s)
easy to focus on my day job and the
[99:36] (5976.16s)
reality is like you only have so much
[99:37] (5977.52s)
time in the day so I don't know if I
[99:38] (5978.80s)
would have been able to pull this off
[99:39] (5979.84s)
but like to Facebook's cashing layer to
[99:42] (5982.36s)
those who who aren't familiar like I
[99:44] (5984.84s)
used it every day as an abstraction
[99:47] (5987.88s)
right I I I called into it every single
[99:50] (5990.12s)
day by many layers of abstraction but
[99:53] (5993.52s)
didn't care to or know significantly
[99:55] (5995.68s)
about how it actually worked that's not
[99:57] (5997.24s)
what I worked on and it didn't matter to
[99:58] (5998.48s)
me in hindsight maybe even out of hours
[100:00] (6000.44s)
I wish I had been a bit more inquisitive
[100:01] (6001.96s)
there like Facebook publishes all of
[100:03] (6003.48s)
these different blogs and now that I do
[100:05] (6005.36s)
so much time you know Learning System
[100:08] (6008.00s)
design both to teach it for our YouTube
[100:10] (6010.68s)
channel for the content that we write I
[100:12] (6012.52s)
read all these blogs now and I wish I
[100:15] (6015.28s)
had done some of that while I was
[100:17] (6017.52s)
actually at meta yeah I mean curiosity
[100:19] (6019.48s)
is probably the biggest tool for
[100:23] (6023.36s)
actually driving learning technical
[100:24] (6024.92s)
learning so totally agree with that and
[100:27] (6027.12s)
so for someone who's let's say someone's
[100:29] (6029.52s)
a big Tech engineer in at a yeah one of
[100:33] (6033.44s)
these big companies and they're thinking
[100:35] (6035.88s)
about one day they'd like to try a
[100:37] (6037.60s)
startup but they you know are kind of
[100:40] (6040.56s)
thinking what do they need to see to
[100:42] (6042.88s)
actually think that okay now is the time
[100:45] (6045.16s)
and now it's a good time to go to a
[100:46] (6046.52s)
startup what advice would you have for
[100:47] (6047.88s)
them this is super hard I actually wrote
[100:49] (6049.72s)
I wrote a post two years ago or so and I
[100:51] (6051.64s)
posted it on blind and they got like a
[100:53] (6053.00s)
decent amount of attention and it was be
[100:54] (6054.56s)
basically convincing big Tech employees
[100:56] (6056.32s)
that like they should leave and and
[100:58] (6058.12s)
start a startup or join a startup and it
[100:59] (6059.56s)
was through the lens and i' had good
[101:01] (6061.64s)
intentions from what you and I are
[101:03] (6063.32s)
discussing now like you're going to
[101:04] (6064.44s)
learn more here was my experience now
[101:06] (6066.08s)
rightfully so I got ripped to shreds in
[101:07] (6067.92s)
the comments of the post blind is an
[101:09] (6069.68s)
aggressive place first of all but it was
[101:12] (6072.36s)
because you know I I I struck a nerve
[101:14] (6074.40s)
with many people and I was insensitive
[101:16] (6076.16s)
to the fortunate situation that I had
[101:18] (6078.08s)
which is that I was financially secure
[101:19] (6079.84s)
and I didn't have a family that I was
[101:21] (6081.00s)
supporting and like I could afford to
[101:22] (6082.56s)
take this risk and not get paid for a
[101:24] (6084.64s)
while and it was going to be okay so I
[101:26] (6086.28s)
recognize most people aren't in that
[101:27] (6087.44s)
situation and so the reality is only you
[101:30] (6090.36s)
know what makes sense for you
[101:31] (6091.76s)
financially if you're purely optimizing
[101:34] (6094.40s)
for your own learning your own technical
[101:37] (6097.12s)
learning and your own improvements from
[101:38] (6098.96s)
a technical perspective and I think
[101:40] (6100.28s)
Beyond a technical perspective then I
[101:42] (6102.08s)
would do it as soon as you can if you're
[101:44] (6104.16s)
brand new to your career I'd probably
[101:45] (6105.36s)
wait until you're at least a senior
[101:46] (6106.44s)
engineer like go go up the ranks of big
[101:48] (6108.76s)
Tech if you're if you're new to it and
[101:50] (6110.64s)
then consider making the switch I
[101:51] (6111.84s)
wouldn't do it before that but you're
[101:53] (6113.40s)
going to learn a significant degree more
[101:56] (6116.76s)
somewhere else is what I think you're
[101:59] (6119.36s)
going to learn a lot about how
[102:00] (6120.40s)
organizations work at Big Tech that's
[102:02] (6122.68s)
important you're going to learn a lot
[102:03] (6123.64s)
about people's skills and you will of
[102:05] (6125.12s)
course learn things technically but
[102:06] (6126.72s)
you'll learn more somewhere else and
[102:08] (6128.20s)
maybe the middle ground is to like go to
[102:10] (6130.16s)
a a series b or series C or something
[102:13] (6133.76s)
ASAP spend your time there and then
[102:16] (6136.32s)
consider starting your own thing if you
[102:18] (6138.72s)
can afford to financially of course it
[102:20] (6140.80s)
is a privilege to be to not have a
[102:23] (6143.96s)
family to be financially secure enough
[102:25] (6145.76s)
to to be able to do it so yeah that that
[102:28] (6148.16s)
that makes sense and I think like I said
[102:30] (6150.36s)
almost all of my friends at this point
[102:32] (6152.16s)
have gone off and done startups so um I
[102:34] (6154.80s)
think what you're saying makes sense and
[102:37] (6157.24s)
a lot of people do enjoy it and and it
[102:39] (6159.60s)
is like this fun thing to do and and now
[102:42] (6162.36s)
now is a cool time to do a startup with
[102:44] (6164.40s)
you know the the advancements of of llms
[102:46] (6166.72s)
not just in terms of making a generic AI
[102:49] (6169.96s)
this company but in terms of like
[102:51] (6171.44s)
accelerating your own rate of progress
[102:53] (6173.84s)
hello interview is still to this day
[102:55] (6175.40s)
just Stephan and I in terms of two
[102:56] (6176.60s)
full-time employees and we've slung a
[102:59] (6179.88s)
lot of code and a lot of that code has
[103:01] (6181.44s)
been accelerated based on the tools that
[103:03] (6183.12s)
we have at our disposal now and so like
[103:05] (6185.80s)
what would have been many weak Cycles at
[103:08] (6188.40s)
even a meta with a team of some number
[103:10] (6190.08s)
of Engineers if you have two highly
[103:11] (6191.88s)
capable engineers and Claude at your
[103:15] (6195.12s)
disposal you can move pretty quick and
[103:17] (6197.28s)
plenty of opinions about where Cloud's
[103:18] (6198.88s)
useful where it slows you down whatever
[103:20] (6200.28s)
but I'll I'll hold that for a different
[103:21] (6201.60s)
conversation I think that could be
[103:22] (6202.76s)
really interesting so for the last part
[103:24] (6204.44s)
of this interview and I think this is my
[103:26] (6206.32s)
favorite part always is just reflecting
[103:28] (6208.80s)
looking back on everything your career
[103:31] (6211.40s)
going into meta growing so quickly and
[103:33] (6213.96s)
then going into startups and you know
[103:36] (6216.20s)
through those Acquisitions and
[103:37] (6217.44s)
everything I'm curious to look at all of
[103:40] (6220.44s)
that and ask you some questions and so
[103:42] (6222.64s)
the first one that I'm curious about is
[103:44] (6224.96s)
and maybe this is similar to what we
[103:46] (6226.48s)
were just talking about but what periods
[103:48] (6228.88s)
of your career did you feel like you had
[103:51] (6231.04s)
the most skill growth the skill growth
[103:52] (6232.92s)
was certainly as we just alluded to the
[103:54] (6234.24s)
startup stuff undoubtedly of course
[103:55] (6235.72s)
there's a lot of skill growth in the
[103:56] (6236.72s)
early early days of your career as well
[103:59] (6239.40s)
but everything pales in comparison to
[104:01] (6241.28s)
the to the startup trainy from skill
[104:03] (6243.64s)
growth once you left to to do the
[104:05] (6245.20s)
startup that was like the you never felt
[104:08] (6248.04s)
growth that that uh fast yeah totally
[104:11] (6251.08s)
and it's all the things that they say
[104:12] (6252.28s)
growth should be it was uncomfortable
[104:14] (6254.28s)
certainly at first it was stressful it
[104:16] (6256.40s)
was like emotional at times credit to to
[104:19] (6259.08s)
my co-founder for putting up with some
[104:21] (6261.44s)
you know emotional moments for me where
[104:23] (6263.60s)
where things felt difficult but yeah
[104:25] (6265.44s)
here we are on the other side of it and
[104:27] (6267.20s)
it was all tremendously worth it I'm
[104:28] (6268.88s)
curious about because your career's
[104:30] (6270.52s)
grown so quickly when you think about
[104:32] (6272.52s)
how many hours a week that you were
[104:34] (6274.84s)
working throughout the different parts
[104:36] (6276.64s)
of your career yeah how much were you
[104:38] (6278.12s)
working during meta I usually tell
[104:39] (6279.60s)
people not a lot and that's generally my
[104:41] (6281.64s)
advice but like in a reflection it's
[104:44] (6284.40s)
it's probably not totally honest I loved
[104:46] (6286.80s)
what I was doing and so I got to work at
[104:50] (6290.00s)
8:00 or so maybe 8:30 and I left work at
[104:53] (6293.44s)
5:30 or 6 but I got home and I
[104:55] (6295.88s)
decompressed and I sat down I watched TV
[104:57] (6297.68s)
I did whatever and like I would open up
[104:58] (6298.84s)
my laptop and I would check an
[104:59] (6299.92s)
experiment or I would tweak something or
[105:01] (6301.52s)
I would do something because I was like
[105:02] (6302.76s)
passionate and excited about it to the
[105:04] (6304.16s)
point where sometimes I would wake up in
[105:05] (6305.48s)
the middle of the night because much of
[105:06] (6306.68s)
what we were doing was training models
[105:08] (6308.12s)
which training takes time I would wake
[105:10] (6310.12s)
up in the middle of the night being like
[105:12] (6312.52s)
did did my Run finish like let me go let
[105:14] (6314.48s)
me go check it CU I was just excited and
[105:16] (6316.64s)
so if you actually accounted for all of
[105:18] (6318.60s)
those hours certainly it's more than
[105:20] (6320.68s)
your average 40 hours a week but at at
[105:23] (6323.08s)
the same time and this part's important
[105:24] (6324.72s)
I love the snowboard Wednesdays I would
[105:27] (6327.24s)
leave work at like 2:00 and go drive up
[105:29] (6329.64s)
to the mountains being in Seattle they
[105:31] (6331.04s)
were only an hour and a half two hours
[105:32] (6332.00s)
away and I would I was no word until
[105:33] (6333.76s)
8:00 p.m. and then drive home um so like
[105:36] (6336.24s)
you can do both and you weren't working
[105:37] (6337.64s)
weekends or anything sounds like you
[105:39] (6339.28s)
were okay no if I if it was something I
[105:41] (6341.76s)
was passionate about but not really
[105:43] (6343.32s)
right right right okay so this sounds
[105:45] (6345.04s)
like I don't know maybe 50 hours a week
[105:46] (6346.60s)
or something um one of the more balanced
[105:49] (6349.48s)
uh career paths what about when you did
[105:51] (6351.40s)
startups though ex exactly EV it changed
[105:54] (6354.60s)
okay so so particularly with that first
[105:56] (6356.76s)
company when I was both struggling to
[105:58] (6358.96s)
learn and consume everything I needed to
[106:01] (6361.08s)
I didn't have my feet under me yet and
[106:03] (6363.12s)
it was a company that like it was doing
[106:05] (6365.12s)
a lot of face fast-paced realtime data
[106:07] (6367.80s)
analytics and so like a lot of things
[106:10] (6370.28s)
can break and when they do break because
[106:12] (6372.32s)
it's money people really care about it
[106:14] (6374.40s)
and it was stressful and so I was
[106:17] (6377.16s)
working all the time like I'd be waking
[106:19] (6379.56s)
up at 7 or 8: and I would stop working
[106:21] (6381.68s)
at midnight or 2:00 a.m. in many cases
[106:24] (6384.28s)
and like I couldn't leave my house
[106:25] (6385.64s)
without my laptop like I distinctly
[106:27] (6387.68s)
remember one instance where I felt like
[106:29] (6389.56s)
things were pretty good I was going to
[106:31] (6391.76s)
leave and go to a friend's birthday
[106:32] (6392.88s)
party that was just up the street from
[106:34] (6394.44s)
me and I went and I brought my laptop
[106:36] (6396.24s)
and I sat down and I ordered my food and
[106:38] (6398.68s)
then binging my pager Duty starts going
[106:40] (6400.44s)
off at the whole sight sound ah and I'm
[106:42] (6402.60s)
like God and I grab my laptop and I
[106:45] (6405.28s)
start running down the hill to try to
[106:48] (6408.36s)
because this was one particular moment
[106:49] (6409.64s)
where I think my co-founder was either
[106:50] (6410.92s)
on vacation or at something with his
[106:52] (6412.32s)
kids or you know like I was the the only
[106:53] (6413.96s)
one to do it and so that was stressful
[106:57] (6417.20s)
and then now we've sort of come full
[106:58] (6418.56s)
circle and that hello interview is
[107:01] (6421.24s)
starting to become much more stable
[107:03] (6423.88s)
things don't necessarily break it's
[107:05] (6425.96s)
fortunately in the nature of the
[107:07] (6427.32s)
business not something where people are
[107:08] (6428.76s)
like eagerly staring at the site every
[107:10] (6430.68s)
second there's less opportunities for
[107:12] (6432.12s)
things to go wrong and now my hours are
[107:14] (6434.36s)
still more than my metad days just
[107:16] (6436.12s)
because you're passionate about your own
[107:17] (6437.52s)
company and you want to make it
[107:18] (6438.32s)
successful but I go to friend's
[107:20] (6440.40s)
birthdays without my laptop okay okay
[107:22] (6442.56s)
that's good
[107:23] (6443.80s)
I remember you you telling me that you
[107:26] (6446.80s)
looking and you also wrote a post about
[107:28] (6448.96s)
it the work life balance and you know
[107:31] (6451.44s)
not but by you doing startups you're
[107:34] (6454.56s)
you're kind of contradicting that by
[107:36] (6456.08s)
working such an insane amount of hours
[107:38] (6458.08s)
so uh what do you say to that yeah so I
[107:40] (6460.24s)
was at this point I think you and I
[107:41] (6461.64s)
chatted about this a little bit I was at
[107:43] (6463.40s)
this point at the end of my meta career
[107:46] (6466.16s)
where I had kind of come to like this
[107:48] (6468.20s)
come to Jesus moment where I had been
[107:50] (6470.40s)
chasing the next ring in the ladder the
[107:51] (6471.80s)
whole time I had just been focused on
[107:53] (6473.40s)
that that was about to come to an end
[107:55] (6475.32s)
certainly if I got that seven promotion
[107:57] (6477.12s)
I need to kind of figure out what else
[107:58] (6478.36s)
matters in life I've been hyper
[107:59] (6479.84s)
optimizing for my career growth and like
[108:01] (6481.84s)
letting other things around Me Maybe
[108:05] (6485.08s)
consequentially um and I had convinced
[108:08] (6488.16s)
myself of this realization that like
[108:10] (6490.16s)
there's two paths in life one you make
[108:13] (6493.72s)
sure you're really passionate about work
[108:15] (6495.40s)
and you spend all your hours on that
[108:16] (6496.64s)
because that's what you love and it
[108:17] (6497.60s)
checks all of your boxes it checks your
[108:19] (6499.44s)
relationship boxes it checks your
[108:21] (6501.28s)
fulfillment boxes obviously the monetary
[108:23] (6503.56s)
boxes or you just look at work as
[108:27] (6507.96s)
something that supports your passions
[108:30] (6510.40s)
financially and so you go to work you do
[108:32] (6512.36s)
a good job you do a great job from 9: to
[108:34] (6514.56s)
5 and then you hang out with your
[108:36] (6516.12s)
friends and you travel the world and you
[108:37] (6517.80s)
live a great fulfilled life finding
[108:39] (6519.24s)
other things to find you passion and so
[108:41] (6521.28s)
I was excited to go for option b and I
[108:43] (6523.84s)
thought that's what I was transitioning
[108:44] (6524.96s)
to after hopefully a seven promotion and
[108:47] (6527.60s)
yeah here I am so be it things went in a
[108:49] (6529.76s)
different direction I think that I might
[108:51] (6531.36s)
be able to pull back out option b in a
[108:54] (6534.04s)
handful of years down the line at least
[108:55] (6535.96s)
I'm still in option A where I'm
[108:57] (6537.04s)
passionate and excited about what I do
[108:58] (6538.52s)
and helping people and you know that's
[109:01] (6541.20s)
fantastic you mentioned earlier I think
[109:03] (6543.36s)
uh a while ago when you're talking about
[109:06] (6546.24s)
starting a startup you talked a little
[109:08] (6548.52s)
bit about regrets is there anything when
[109:11] (6551.32s)
you look back on your career what's the
[109:13] (6553.48s)
biggest regret that you have something
[109:15] (6555.52s)
that others could learn from potentially
[109:17] (6557.44s)
yeah I think that I think that my
[109:18] (6558.84s)
biggest regret would be not slowing down
[109:21] (6561.48s)
and like I I took shortcuts and I I
[109:23] (6563.56s)
still have a tendency to do this
[109:25] (6565.24s)
sometimes now although I push myself to
[109:26] (6566.76s)
be much better here for what it's worth
[109:28] (6568.44s)
but like you need to understand how
[109:30] (6570.68s)
things work and so there are certain
[109:32] (6572.08s)
approaches that you can take in order to
[109:33] (6573.56s)
accomplish the task through iteration
[109:35] (6575.56s)
and you'll get there but once it works
[109:37] (6577.40s)
you might move on alternatively you get
[109:39] (6579.24s)
there and then you're inquisitive about
[109:40] (6580.68s)
why it actually worked and I think that
[109:42] (6582.24s)
this is just a much more sustainable
[109:43] (6583.96s)
foundation and so like at meta it was
[109:46] (6586.48s)
easy to kind of experiment see numbers
[109:48] (6588.56s)
go up I was in a very quantitative kind
[109:51] (6591.00s)
of field or team where we had metrics
[109:53] (6593.32s)
and those metrics would go up or they
[109:54] (6594.48s)
would not go up and if they went up
[109:56] (6596.36s)
success and you generally have an idea
[109:58] (6598.08s)
for why but I wasn't as inquisitive as I
[110:00] (6600.36s)
could have been about what like the
[110:01] (6601.92s)
actual underlying particularly technical
[110:03] (6603.68s)
cause and then the same was true in the
[110:05] (6605.68s)
early days of startups because I didn't
[110:07] (6607.60s)
feel like I had the time I was learning
[110:09] (6609.28s)
so much and I was trying to just get my
[110:11] (6611.16s)
feet under me and I was trying to move
[110:12] (6612.52s)
that like once I got it to work it was
[110:13] (6613.88s)
like okay that works now like next thing
[110:16] (6616.32s)
and then now only within the last year I
[110:18] (6618.48s)
feel like I've been able to make that
[110:19] (6619.80s)
transition kind of recognize that as an
[110:21] (6621.24s)
issue and I have more time now now I'm
[110:23] (6623.08s)
back to that like I can do you know my
[110:25] (6625.24s)
work in 70% of the time and I have a 30%
[110:27] (6627.28s)
of my time to dedicate to something else
[110:29] (6629.20s)
and now that it's not about career
[110:30] (6630.28s)
growth that 30% can go to actually
[110:31] (6631.92s)
learning and understanding and so this
[110:33] (6633.20s)
is a combination of like reading the
[110:34] (6634.52s)
engineering blogs from other companies
[110:36] (6636.36s)
that are coming out me being inquisitive
[110:38] (6638.36s)
about underlying kind of like libraries
[110:40] (6640.84s)
or platforms that we're using how they
[110:42] (6642.32s)
work why they work how they were built
[110:44] (6644.00s)
and I think this is a a valid and
[110:46] (6646.76s)
important shift in in the way that I
[110:48] (6648.76s)
think about technology got it so taking
[110:50] (6650.44s)
the time to rather than just pure impact
[110:53] (6653.96s)
machine launch something onto the next
[110:55] (6655.92s)
thing launch something on the next thing
[110:57] (6657.60s)
you wish that you took the time to
[111:00] (6660.60s)
deeply understand things after things
[111:03] (6663.08s)
are launched too just for the sake of
[111:04] (6664.64s)
your own technical growth which has
[111:06] (6666.60s)
long-term benefits exactly and I think
[111:08] (6668.72s)
that for all of the great things about
[111:10] (6670.48s)
meta that that you and I have talked
[111:11] (6671.92s)
about now that was probably the negative
[111:13] (6673.76s)
culturally is that it encouraged this
[111:15] (6675.72s)
culture of just like ship it and run and
[111:17] (6677.72s)
keep going impact impact impact impact
[111:19] (6679.76s)
and so I didn't need to ask those
[111:21] (6681.04s)
questions of like how does ta actually
[111:22] (6682.72s)
work this thing that I use every day
[111:24] (6684.88s)
right because it didn't matter to me but
[111:28] (6688.20s)
in terms of my growth as an engineer it
[111:30] (6690.28s)
would have been fantastic if I
[111:31] (6691.48s)
understood that and it would have been
[111:32] (6692.96s)
fantastic if I could then ask the
[111:34] (6694.64s)
engineers who were working on it
[111:35] (6695.72s)
questions as they were coming up that's
[111:37] (6697.24s)
something that that I regret on doing
[111:38] (6698.68s)
yeah the cultural I guess the other
[111:40] (6700.60s)
thing is move fast and break things so
[111:43] (6703.04s)
yeah yeah that's also kind of I was good
[111:44] (6704.40s)
at that yeah breaking things too but I
[111:47] (6707.28s)
can usually fix them fast enough that
[111:48] (6708.64s)
nobody notice or cared but yeah right
[111:50] (6710.76s)
right right right yeah I've had my fish
[111:52] (6712.60s)
sh breakages too okay and then the last
[111:54] (6714.76s)
thing that I like to ask everyone is if
[111:57] (6717.32s)
you could go back to Evan who's just
[112:01] (6721.12s)
graduating college and is entering the
[112:03] (6723.40s)
industry and you were to tell that Evan
[112:06] (6726.32s)
something what would be the advice that
[112:08] (6728.96s)
you give yourself just starting out in
[112:10] (6730.52s)
your career yeah I'm going to I'm going
[112:11] (6731.92s)
to take a more maybe emotional angle on
[112:14] (6734.00s)
this as opposed to technical or career
[112:16] (6736.40s)
or answerid but like I think the advice
[112:18] (6738.08s)
to me would be to really invest in
[112:19] (6739.96s)
relationships and the aspects outside of
[112:21] (6741.80s)
work like I'm only just now realizing in
[112:23] (6743.44s)
the last year and a half or so that like
[112:25] (6745.00s)
I was underinvested in in friendships
[112:27] (6747.96s)
and romantic relationships and things of
[112:30] (6750.32s)
this nature and it was largely because I
[112:32] (6752.40s)
was putting so much effort into work
[112:34] (6754.64s)
even if it wasn't an hours wise like
[112:36] (6756.32s)
that's where my optimizations were and
[112:38] (6758.48s)
you realize that like you spend all this
[112:39] (6759.76s)
time Road mapping goaling checking in
[112:41] (6761.64s)
with yourself about your career
[112:42] (6762.64s)
progression but in terms of like General
[112:44] (6764.72s)
Life progression I didn't apply nearly
[112:47] (6767.16s)
that same Vigor and so I think that that
[112:49] (6769.32s)
had a negative consequence and only
[112:50] (6770.76s)
moving to La now years ago did the shift
[112:54] (6774.80s)
and this is because I got pulled out of
[112:55] (6775.96s)
the tech bubble now a lot of my friends
[112:57] (6777.68s)
don't work in Tech and we invest a lot
[113:00] (6780.00s)
more in each other both financially and
[113:02] (6782.12s)
from a Time perspective and I have found
[113:04] (6784.00s)
that my life is so much more fulfilled
[113:06] (6786.96s)
because of this and so work continues to
[113:09] (6789.12s)
be a focus it continues to grow things
[113:11] (6791.04s)
are great there but now like I have all
[113:12] (6792.76s)
these people that I can rely on and like
[113:15] (6795.24s)
I'm moving apartments right now and and
[113:17] (6797.28s)
I have any number of people that I can
[113:18] (6798.92s)
call to help me move and these small
[113:20] (6800.60s)
things are like you know like I said
[113:22] (6802.68s)
it's a bit sentimental but they're
[113:24] (6804.00s)
they're really what matter in life U
[113:25] (6805.64s)
more so than your quick career
[113:27] (6807.28s)
progression so I wish I had learned to
[113:30] (6810.24s)
more fairly allocate time between those
[113:32] (6812.48s)
two and effort so if you could go back
[113:34] (6814.92s)
and grow slower yet retain more
[113:38] (6818.32s)
relationships and have done more outside
[113:40] (6820.32s)
of work would you make that change
[113:42] (6822.36s)
Looking Back Now that you know how
[113:44] (6824.60s)
things went if I was given that binary
[113:46] (6826.52s)
choice I think I would but I don't think
[113:48] (6828.44s)
that would have been the choice I had
[113:49] (6829.92s)
more than enough time I just didn't do
[113:51] (6831.36s)
it uh it just like it wasn't something
[113:53] (6833.84s)
that I was investing enough in and I
[113:55] (6835.36s)
just like didn't understand the
[113:56] (6836.64s)
importance of it until I got a little
[113:57] (6837.92s)
bit older and wiser in age so to anybody
[114:00] (6840.20s)
else I think you can absolutely do both
[114:02] (6842.16s)
hindsight if I had to make the binary
[114:03] (6843.92s)
decision of course your relationships
[114:07] (6847.04s)
matter more than anything else in the
[114:08] (6848.20s)
world so I would optimize for those as I
[114:10] (6850.96s)
as opposed to Career makes sense okay
[114:12] (6852.92s)
well that's all the questions that I had
[114:14] (6854.40s)
Evan I really enjoyed this conversation
[114:17] (6857.08s)
I loved how it had some back and forth
[114:18] (6858.84s)
and we could kind of both go over our
[114:20] (6860.72s)
our fast progressions to meta and show
[114:23] (6863.92s)
show everyone you know what they might
[114:25] (6865.64s)
be able to learn from that and so with
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that being said um you know this is
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opportunity to plug anything you'd like
[114:30] (6870.68s)
to do you want to shout out anything
[114:32] (6872.36s)
yeah totally well first off likewise
[114:34] (6874.40s)
this was a super super fun conversation
[114:35] (6875.76s)
I can't actually believe looking at the
[114:37] (6877.08s)
time L quickly it we moved through it
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because you I was certainly having a lot
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of fun chatting with you um in terms of
[114:42] (6882.76s)
plugs yeah absolutely hello
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interview.com that's the current startup
[114:46] (6886.08s)
that's the current company if you are
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preparing for software engineering
[114:49] (6889.28s)
interviews you should absolutely check
[114:51] (6891.12s)
us out we have everything from if you
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want just free resources to learn and of
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course I'm biased but we've heard over
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and over again from the community that
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these are some of the best free
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resources that exist on the internet to
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if you want kind of self-guided practice
[115:04] (6904.60s)
we've got you covered there and then all
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the way of course to the mock interviews
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and we go through extreme lengths to
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make sure that we only hire the absolute
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best coaches we make sure that if
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anybody drops below kind of our bar of
[115:14] (6914.32s)
expectations from a coach that that we
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part ways and we move on to to another
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coach that that can perform at the level
[115:20] (6920.16s)
required for our candidates to succeed
[115:22] (6922.00s)
and so so we hear a lot of great
[115:23] (6923.36s)
feedback check it out would love to be
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able to help you prepare for your
[115:25] (6925.92s)
interviews as well and maybe the last
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thing there since I'm assuming you're
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viewing this on YouTube you can also uh
[115:32] (6932.00s)
YouTube search for Hello interview we
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have a YouTube channel it's largely me
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talking about interviews and breaking
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down common system design problems so
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you can see how I think through these
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problems give that a watch too
[115:42] (6942.28s)
everything on there of course is is
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completely free yeah and I'll be putting
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links to everything in the in the
[115:46] (6946.88s)
description the show notes so you can
[115:48] (6948.28s)
take a look at that and yeah the last
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thing i' would add by the way about
[115:51] (6951.24s)
hello interview just to give you some
[115:53] (6953.40s)
unbiased feedback I can tell you a story
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that one of my roommates was recently
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interviewing and he didn't know that
[115:59] (6959.88s)
I've been talking to Evan and anything
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he's just been talking to me unbiasedly
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about mock interview services and what
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the resources are in terms of system
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design and he tried to interview IO and
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it was okay and then he didn't have
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super great results in his one of his
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first rounds so he had to re-evaluate
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everything and then he found hello
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interview and he remember specifically
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he credited the free resources he said
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that was really helpful for him to learn
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because he had read some other book on
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system design was not super helpful also
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he was overconfident when it came to
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system design because he felt like Oh
[116:37] (6997.16s)
I'm a senior engineer and I've been
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designing systems at work but actually
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the interview process is this contrived
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thing that you need to study
[116:45] (7005.68s)
specifically and hello interviews free
[116:48] (7008.20s)
resources as well as doing mocks
[116:50] (7010.76s)
themselves were the critical thing that
[116:53] (7013.04s)
actually like helped my my roommate a
[116:55] (7015.84s)
lot so although I haven't used the the
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interview service I would say this is
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like a very strong recommendation that I
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could personally recommend because
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someone I trust uh had such a good
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review with it yeah recommend you take a
[117:09] (7029.32s)
look at hello interview hello your
[117:10] (7030.56s)
friend that's awesome yeah appreciate
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that cool all right well thanks so much
[117:13] (7033.68s)
Evan yeah that's that's all we got