WEBVTT

00:00:00.001 --> 00:00:05.000
What if you could take the experience and insight from 100 job interviews and use them to find

00:00:05.000 --> 00:00:09.320
just the right job? You'd be able to weed out the bad places that are not a right fit.

00:00:09.320 --> 00:00:13.000
You'd see that lowball offer coming a mile away and move right along.

00:00:13.000 --> 00:00:18.320
But no one could really do 100 consecutive interviews, right? That'd be like a full-time

00:00:18.320 --> 00:00:23.400
job in and of itself. Well, this week you'll meet Susan Tan, who did just that.

00:00:23.400 --> 00:00:27.440
This is Talk Python To Me, recorded June 5th, 2017.

00:00:28.720 --> 00:00:31.080
Developers, developers, developers, developers.

00:00:31.080 --> 00:00:36.400
I'm a developer in many senses of the word because I make these applications, but I also

00:00:36.400 --> 00:00:41.900
use these verbs to make this music. I construct it line by line, just like when I'm coding another

00:00:41.900 --> 00:00:48.060
software design. In both cases, it's about design patterns. Anyone can get the job done. It's

00:00:48.060 --> 00:00:51.840
the execution that matters. I have many interests. Sometimes it can flex.

00:00:51.840 --> 00:00:57.360
Welcome to Talk Python To Me, a weekly podcast on Python, the language, the libraries, the ecosystem,

00:00:57.440 --> 00:01:02.100
and the personalities. This is your host, Michael Kennedy. Follow me on Twitter where I'm at

00:01:02.100 --> 00:01:07.360
mkennedy. Keep up with the show and listen to past episodes at talkpython.fm and follow the

00:01:07.360 --> 00:01:11.600
show on Twitter via at Talk Python. Susan, welcome to Talk Python.

00:01:11.600 --> 00:01:12.620
Hi. Hi, Michael.

00:01:12.620 --> 00:01:17.580
Hi. Yeah, it's great to have you here. You had such a fun PyCon talk and I'm looking forward

00:01:17.580 --> 00:01:18.980
to sharing your story with everyone.

00:01:18.980 --> 00:01:19.360
Cool.

00:01:19.560 --> 00:01:24.440
Yeah. So before we get into that though, maybe introduce yourself really quick and let's

00:01:24.440 --> 00:01:26.820
talk about your story. How did you get into programming in Python?

00:01:26.820 --> 00:01:33.820
Yeah, sure. My name is Susan and I moved from New York City, Brooklyn, New York City to San

00:01:33.820 --> 00:01:40.440
Francisco back in fall 2012, specifically to part of tech industry. And so I've been here

00:01:40.440 --> 00:01:45.900
ever since for the past couple of years. And I really love everything in San Francisco.

00:01:45.900 --> 00:01:49.520
The weather's amazing and lots of really good people here.

00:01:49.520 --> 00:01:53.860
It's a really special city, but I've heard that New York has a pretty good startup scene

00:01:53.860 --> 00:01:58.200
and a pretty good tech scene and whatnot. But you think San Francisco is where it's at, huh?

00:01:58.200 --> 00:02:03.740
I feel like when I was in New York, the startup scene was like tech industry was just starting.

00:02:03.740 --> 00:02:06.020
So it's still like in its input stages at the time.

00:02:06.020 --> 00:02:06.400
I see.

00:02:06.560 --> 00:02:11.060
Like the early 2010s. And so I said, Hey, like, there's a lot of like really cool stuff

00:02:11.060 --> 00:02:15.720
happening in San Francisco as well. Explore. And it was like pretty much like my first thing I did,

00:02:15.720 --> 00:02:20.160
like right after college, I wanted to like explore and like see the other side of the coast.

00:02:20.160 --> 00:02:23.640
Yeah, that's definitely a different city. Awesome. Okay. So how about programming?

00:02:23.640 --> 00:02:27.280
Like take a little bit of a step back. Like how'd you get into programming in the first place?

00:02:27.280 --> 00:02:34.340
So I was doing an internship, a very large biomedical diagnostic company. So I was a little bit bored

00:02:34.340 --> 00:02:38.780
with my internship. And so like during the off hours, like in the evenings, I was working,

00:02:38.780 --> 00:02:44.520
I was exploring this online, massively online class called machine learning taught by professor Andrew

00:02:44.520 --> 00:02:49.520
Ng from Stanford University. And that was when I really like, that was my first introduction to

00:02:49.520 --> 00:02:53.860
artificial intelligence and machine learning. And it was a really good class. Like he's able to break

00:02:53.860 --> 00:02:59.380
down complicated concepts with something that's like bite sized, and easy to understand. So use

00:02:59.380 --> 00:03:04.540
Octave, which is a word domain specific language. And it was a really good experience, like applying

00:03:04.540 --> 00:03:09.940
linear algebra into like actual programming examples. And so I was like, when I really got hooked into

00:03:09.940 --> 00:03:14.300
programming, like, hey, I want to do more of this. Like, how do I get started to do more of this?

00:03:14.300 --> 00:03:18.040
That's really cool. Like, I want to, I want to control the machines. I want to build the machines.

00:03:18.040 --> 00:03:23.500
It's amazing. And was that you said Octave was Python involved in that so far?

00:03:23.700 --> 00:03:29.220
So that was all in Octave, which is an open source version of MATLAB. That's something I use in

00:03:29.220 --> 00:03:34.860
school. So I got my degree in general engineering from a very small liberal arts slash engineering

00:03:34.860 --> 00:03:39.240
school called Harvey Mudd College. It's a very technical school, but they also consider themselves

00:03:39.240 --> 00:03:44.560
a good liberal arts undergraduate school as well. And so I come from a pretty technical background.

00:03:44.560 --> 00:03:50.600
As part of like the first semester, everyone had to take the introductory programming class. So that was

00:03:50.600 --> 00:03:55.520
like my, like even years before that was like my first real step into programming, where they,

00:03:55.520 --> 00:04:00.220
by requirement, they had everyone, regardless of their major, take their first programming class in

00:04:00.220 --> 00:04:04.760
the first semester. And everyone was pretty much like on the same page in terms of like,

00:04:04.760 --> 00:04:08.920
and if you're brand new to programming, you would understand like what's going on. Or if you're

00:04:08.920 --> 00:04:13.720
already advanced, like, they'll put you in a different class, or you'll be able to more people with more

00:04:13.720 --> 00:04:17.980
advanced knowledge, they can go for that class. So it was a really good way to get into programming.

00:04:17.980 --> 00:04:21.780
And they got a lot of new, like CS majors, the introductory program.

00:04:21.780 --> 00:04:27.520
Oh, that's really nice. You said all the people, all the majors take that even if I was like,

00:04:27.520 --> 00:04:29.820
like studying literature, I'd have to take a programming course?

00:04:29.820 --> 00:04:35.800
Yeah, pretty much. Well, just for some context, a lot of the people who are coming into the school

00:04:35.800 --> 00:04:40.880
are pretty much set on like doing something of STEM, or they're like bio majors or chemistry majors.

00:04:40.880 --> 00:04:45.200
It's already kind of an engineering school anyway. So it leans that way. Okay. Yeah, yeah.

00:04:45.200 --> 00:04:51.040
Yeah, well, that sounds really cool. So that first course was in Python, but it was really this

00:04:51.040 --> 00:04:54.820
experience at your internship, you're like, okay, this is actually what I want to be doing.

00:04:54.820 --> 00:05:00.420
Right. So I was doing that class in addition to like doing the internship, which is more on the

00:05:00.420 --> 00:05:06.480
electronics and hardware side, as opposed to like the, like more programming. So it was a different

00:05:06.480 --> 00:05:11.120
side, like I switched over from working with like programming with Arduinos and working with winners

00:05:11.120 --> 00:05:18.820
and like PCBs to like working with software entirely. Sure. All right, cool. So given the topic that we're

00:05:18.820 --> 00:05:23.260
going to cover today, which I think is really fun, like I said, I think it's especially interesting to

00:05:23.260 --> 00:05:30.180
ask, what are you doing day to day now? So I'm a software engineer at a software as a service company

00:05:30.180 --> 00:05:35.920
called Berkeley Electronic Press. The short name is VPress. They're located in downtown Berkeley,

00:05:35.920 --> 00:05:42.380
and they offer a suite of products for universities. So all of the customers are universities. So let's

00:05:42.380 --> 00:05:50.000
say if you are like Harvard, and you want to have an academic profile for various faculty members and

00:05:50.000 --> 00:05:55.060
researchers, you can pretty much use our tools to be able to show off the works of students and faculty.

00:05:55.060 --> 00:06:01.840
That's really cool. I'm always blown away when I go to university websites to academics websites and

00:06:01.840 --> 00:06:08.880
researchers websites, how often they're like really bad, like really, like from 1994 straight out of like

00:06:08.880 --> 00:06:15.480
the web is one year old, you know, and which the reason it surprises me is these people are really

00:06:15.480 --> 00:06:20.780
dedicated. They've got like five papers and two research projects, and they've like dedicated 10 years

00:06:20.780 --> 00:06:24.980
of their life to this. Like surely it needs a better showcase than what it's getting, right?

00:06:24.980 --> 00:06:30.700
Yeah. Library science is a pretty big thing. A lot of librarians are university administrators are

00:06:30.700 --> 00:06:37.100
modernizing their systems. They're pushing ahead, like the digital agenda, like let's like modernize

00:06:37.100 --> 00:06:42.860
these websites, like make it so that it's easy to use for everybody. And we get more users to use the

00:06:42.860 --> 00:06:47.740
platform. And so a lot of like the librarians who are our customers, they're advocating for this on their own

00:06:47.740 --> 00:06:53.980
campuses. Okay. Yeah. So you see a lot of like librarians learning technology skills to be able to

00:06:53.980 --> 00:06:58.140
handle lots of data pretty quickly and be able to have this digital literacy.

00:06:58.140 --> 00:07:04.220
Yeah. Do you feel like that's kind of the story of like all jobs these days that this thing that used

00:07:04.220 --> 00:07:10.980
to be pretty low tech in terms of computer skills required is now like almost requires programming to

00:07:10.980 --> 00:07:15.200
like really take it to the next level? Yeah, I think so. Where, especially in this space,

00:07:15.340 --> 00:07:20.060
there's a lot of opportunity where like, whereas before, like people weren't thinking about like,

00:07:20.060 --> 00:07:25.420
how, how do we use technology to like better improve, to make our lives easier? So this is

00:07:25.420 --> 00:07:29.820
like a space where I found out about it. And I thought this is such a cool like product,

00:07:29.820 --> 00:07:33.500
a suite of products that librarians use. So I just like went into it.

00:07:33.500 --> 00:07:37.020
Oh yeah, that's great. Yeah. You can definitely make a big difference in this space.

00:07:37.900 --> 00:07:44.460
So let's take a step back. How long ago did you start this whole project of looking for,

00:07:44.460 --> 00:07:47.500
for doing a bunch of interviewing and looking for this job?

00:07:47.500 --> 00:07:56.380
So I left my job at Cisco back in mid late August of 2016. So I left a full time job to do the full

00:07:56.380 --> 00:08:02.540
time job searching. And that was like quite an adventure that I do want to talk more about in

00:08:02.540 --> 00:08:07.660
depth. Yeah, absolutely. So I think it's worth pointing out that you worked at a couple of major

00:08:07.660 --> 00:08:14.300
San Francisco style companies before this. This is not your, your first job, your first time looking

00:08:14.300 --> 00:08:18.860
for a job or anything like that, right? You, so you just said you were at Cisco and the way you got to

00:08:18.860 --> 00:08:24.700
Cisco was through a acquisition sort of aqua hire type thing at what was that piston or what was the name

00:08:24.700 --> 00:08:31.100
of this place? So I used to work at a small 40 person cloud computing store called piston where, and

00:08:31.100 --> 00:08:36.620
the product itself is an operating system and it enabled companies that happen to have on-site

00:08:36.620 --> 00:08:43.820
servers to be able to coordinate the resources on those servers. So it's pretty much like orchestration

00:08:43.820 --> 00:08:48.780
and like, it's what people, yeah, DevOps, automated DevOps for people who are in the

00:08:48.780 --> 00:08:53.980
apps business. And so I was working primarily on the web application side. So I was usually one of

00:08:53.980 --> 00:08:58.300
the only applications engineers in a room full of distributed systems engineers.

00:08:58.300 --> 00:09:00.380
A lot of auto operating system people around, huh?

00:09:00.380 --> 00:09:00.780
Yeah.

00:09:00.780 --> 00:09:08.700
So you had a, I'll link to your PyCon talk, but you had like a pretty amazing stylistic photo

00:09:08.700 --> 00:09:11.500
taking the people that work there. Tell me about what it was like to be at that place.

00:09:11.500 --> 00:09:16.380
Yeah. So it's a very chaotic, quirky environment, lots of like energetic

00:09:16.380 --> 00:09:21.580
people. And what really struck me the most was the people around me. I feel like they were not

00:09:21.580 --> 00:09:26.220
the stereotypical type of like, oh, like they're wearing hoodies or jeans. Like these are people

00:09:26.220 --> 00:09:33.340
like from all across various age groups. And especially the men who in the startup were like

00:09:33.340 --> 00:09:39.420
very much into like the steampunk style and like the golden age of Hollywood, like menswear style.

00:09:39.420 --> 00:09:44.300
So like sometimes you'll see them in like three piece suits or like amazing bow ties.

00:09:44.300 --> 00:09:48.780
And they kind of want to like change things up and they don't want to look like something from

00:09:48.780 --> 00:09:49.500
stereotype.

00:09:49.500 --> 00:09:53.100
Not all about the hoodies and the ripped jeans or whatever, huh?

00:09:53.100 --> 00:09:56.700
Yeah. They, they like having, you know, an aesthetic style that, you know,

00:09:56.700 --> 00:10:01.420
and I feel like the entire culture is, is around that as well. Like there's a lot of people

00:10:01.420 --> 00:10:07.500
who like love design and marketing and the arts. It's like, it's a good group of folks.

00:10:07.500 --> 00:10:07.900
Yeah.

00:10:07.900 --> 00:10:12.220
And they're pretty quirky. And I feel that of all the companies, I feel like of all the past

00:10:12.220 --> 00:10:17.180
companies, it's my favorite workplace because I felt like really comfortable in this sort of environment

00:10:17.180 --> 00:10:22.220
where like, I'm not afraid to just be me. And I'm pretty quirky as well.

00:10:22.220 --> 00:10:28.860
And so I had a lot of fun with the culture of the company. And it's just also my first workplace

00:10:28.860 --> 00:10:33.980
where I was coding in Python and I got to learn from like really great, smart people.

00:10:33.980 --> 00:10:38.620
I learned how to do unit testing, learned how to like write idiomatic Python. So that's a really

00:10:38.620 --> 00:10:39.900
good intro for me.

00:10:39.900 --> 00:10:42.780
Yeah, for sure. And the web app you're working on, is that Django?

00:10:42.780 --> 00:10:49.740
Yeah, it's built in Django. So a lot of the code base is upstream code base from the OpenStack

00:10:49.740 --> 00:10:54.300
Horizon code base. So a lot of like the code is actually from, from OpenStack. And then we

00:10:54.300 --> 00:10:58.860
pretty much repackage OpenStack into something that's a lot more manageable to people in terms of

00:10:58.860 --> 00:11:00.940
like the UI and the design.

00:11:00.940 --> 00:11:03.820
Sure. Okay, cool. And so you

00:11:03.820 --> 00:11:08.940
you went from there to working at Cisco and Cisco is a slightly larger company than 40 people.

00:11:08.940 --> 00:11:17.020
I personally have spent 17 years of my career at small companies. And by small, I mean, 10 people,

00:11:17.020 --> 00:11:23.260
30 people, 40 people, something like that. And I really enjoyed working in those places. You got to

00:11:23.260 --> 00:11:28.860
have lots of leeway in the technology. You got to have, you got to be able to make a pretty big impact

00:11:28.860 --> 00:11:33.660
in the company with what you were doing. And I've also worked at companies that had like

00:11:33.660 --> 00:11:38.460
thousand people. And that's a different experience. So did you find when you went to Cisco that you're

00:11:38.460 --> 00:11:40.780
kind of like, I kind of need to change after a while?

00:11:40.780 --> 00:11:46.060
Yeah. So I think the biggest change, like when I first joined versus like a year and a half later,

00:11:46.060 --> 00:11:50.780
was that I was on an all remote team. So that was like a really different experience because

00:11:50.780 --> 00:11:54.300
pretty much throughout my career, I was pretty much like an all in person team.

00:11:54.300 --> 00:11:58.780
And then all of a sudden I was on like all remote team where like there are seven people and

00:11:58.780 --> 00:12:03.740
they're from like Texas and Canada and Hawaii. So things got, it wasn't something I was expecting,

00:12:03.740 --> 00:12:04.460
like walking in.

00:12:04.460 --> 00:12:08.620
Yeah, sure. Okay. So eventually for whatever reason you decided that's it,

00:12:08.620 --> 00:12:13.820
I'm going to go look for something new. And then how did you decide that like,

00:12:13.820 --> 00:12:20.860
I'm going to go and just start interviewing full time and like really try to find that perfect fit?

00:12:20.860 --> 00:12:26.860
I think after a while, like I decided, well, like I was working on a very small component of a very

00:12:26.860 --> 00:12:31.260
large system. So after a while I was like, okay, maybe I should really do something different. Like

00:12:31.260 --> 00:12:36.460
do something where it's completely outside of this industry where something that's not DevOps related

00:12:36.460 --> 00:12:42.860
or not operating system related. And I really wanted to go to work on a product where people really need to

00:12:42.860 --> 00:12:46.860
use that product, where it's a place where they really need software engineers.

00:12:46.860 --> 00:12:52.780
Right. The level of benefit you can bring to like helping librarians do more technology is a much

00:12:52.780 --> 00:12:57.820
bigger impact than like making that one button do its feature slightly better or whatever that is.

00:12:57.820 --> 00:12:58.060
Right?

00:12:58.060 --> 00:13:01.980
Yeah. Yeah. That's part of working in a large company. There's a lot of different teams and

00:13:01.980 --> 00:13:04.220
lots of different people, lots of different projects.

00:13:04.220 --> 00:13:05.900
A lot of different meetings as well.

00:13:05.900 --> 00:13:08.780
Yeah. Yeah, that is true. I've seen that.

00:13:08.780 --> 00:13:15.500
All right. So, so your talk was basically lessons learned from going through a hundred

00:13:15.500 --> 00:13:20.620
interviews. And at one point you showed your calendar and you're like, look at this. I'm

00:13:20.620 --> 00:13:25.180
like 20 interviews scheduled or 10 interviews scheduled this week. It's like crazy, right? You

00:13:25.180 --> 00:13:26.540
were really going after it.

00:13:26.540 --> 00:13:30.220
Yeah. That was like one of the busiest times in my life probably.

00:13:30.220 --> 00:13:31.100
Yeah.

00:13:31.100 --> 00:13:35.020
And going through that many interviews, I felt like it gave me a good experience of

00:13:35.020 --> 00:13:39.420
different tech products and really understanding what are recruiters looking for? What are engineers

00:13:39.420 --> 00:13:44.860
looking for? It's gave me a really good overview of the industry in particular. So I think that

00:13:44.860 --> 00:13:50.060
in with all like that, I talk a lot about the bad, frustrating aspects about interviewing in my talk,

00:13:50.060 --> 00:13:55.580
but there are some like shining light in the tunnel in this whole process and that you get to go

00:13:55.580 --> 00:13:59.500
and look at cool like tech offices that normally the public would never see.

00:13:59.500 --> 00:14:00.540
Yeah. Yeah. Yeah.

00:14:00.540 --> 00:14:05.420
Yeah. That's really neat. And, and sometimes you get to see demos of some products that are in

00:14:05.420 --> 00:14:08.460
like beta version or alpha version that haven't been released yet to the public.

00:14:08.460 --> 00:14:11.260
So that's cool. And with the chance to maybe be part of that team, right?

00:14:11.260 --> 00:14:16.540
Yeah. Yeah. Yeah. Very nice. So when you started, did you think this is going to take me

00:14:16.540 --> 00:14:21.660
three or four months and a hundred interviews, or did you think it would not be so intense?

00:14:21.660 --> 00:14:27.100
I thought it would finish pretty quickly when I first like really got into the interviewing. And

00:14:27.100 --> 00:14:31.660
then like, if someone asked me last year, if I would do like a hundred interviews, like I was like,

00:14:31.660 --> 00:14:37.180
no way. Like I did not think I would do as many interviews, but strangely, this is how life turned

00:14:37.180 --> 00:14:41.580
out for me. And I just like, you know, was like focused on the next thing, the next company,

00:14:41.580 --> 00:14:43.100
kept moving forward.

00:14:43.100 --> 00:14:47.260
So do you feel like you got like this really interesting life experience or would you,

00:14:47.260 --> 00:14:49.900
like, if you could change it, would just go, I'd rather just have that,

00:14:49.900 --> 00:14:51.580
find that good job after the first week.

00:14:51.580 --> 00:14:55.100
It's hard for me to answer that because like, wow, like I think I felt, I felt that really grown

00:14:55.100 --> 00:14:58.700
and like really learned a lot from this whole process. And like, I've seen ways that interviews

00:14:58.700 --> 00:15:05.820
are so broken and, and I've met some really great people along the process. And like, I've seen

00:15:05.820 --> 00:15:10.780
really kind people, for example, there's this one time when I was talking to a dirty party recruiter

00:15:10.780 --> 00:15:16.140
and she knew I didn't have like a quiet, like space at home. And so she was like, Hey,

00:15:16.140 --> 00:15:20.780
like, why don't you go to the office and you can use the conference room to take like phone calls

00:15:20.780 --> 00:15:25.580
and interviews there. And that was like really kind of her. And so I did that for a good number

00:15:25.580 --> 00:15:27.260
of mornings for a few hours.

00:15:27.260 --> 00:15:31.420
Oh yeah. That's really nice. Did you work with one person that was trying to get you a job or

00:15:31.420 --> 00:15:37.260
was it just like randomly reaching out and connecting with like the recruiters on the other side or?

00:15:37.260 --> 00:15:42.380
So I know a lot of people recommend that it's better to like the easiest way is like,

00:15:42.380 --> 00:15:47.980
go for a friend. If you know a friend, just have the door. That's an easy way in. But for me, like I,

00:15:47.980 --> 00:15:51.980
I knew a lot of people in the tech industry who are working at the larger companies. And I was like,

00:15:51.980 --> 00:15:57.340
pretty much like set on like networking at more of the larger companies. I was like, okay, like I,

00:15:57.340 --> 00:16:01.260
I should, so I couldn't really ask my friends for connection.

00:16:01.260 --> 00:16:03.580
Yeah. You would get a job where you didn't want to be.

00:16:03.580 --> 00:16:07.020
Right. Yeah. And so it was pretty much me like applying like straight code,

00:16:07.020 --> 00:16:11.580
emails and applications to various tech companies that I found were pretty interesting.

00:16:11.580 --> 00:16:15.660
Yeah. You must've learned a lot of interesting ways to reach out to people you don't know.

00:16:15.660 --> 00:16:21.980
Oh yeah. A lot of it is from like 90% of the time is from the normal application process. There's like

00:16:21.980 --> 00:16:25.660
a number of fields and a lot of them look pretty much the same. There's like,

00:16:25.660 --> 00:16:31.260
fill out the resume, fill out like cover letter and technology makes that easy for applicants to

00:16:31.260 --> 00:16:34.140
like all fill out complete a lot of different fields.

00:16:34.140 --> 00:16:39.900
Yeah. Yeah. For sure. So your comment on the big companies, maybe that's worth going into

00:16:39.900 --> 00:16:46.140
your list of no criteria, because if you would just take any job out there, you probably could have

00:16:46.140 --> 00:16:49.820
gotten one quicker, but like you were saying, you were kind of looking for what you felt would be a

00:16:49.820 --> 00:16:56.300
really good fit. So you had six things, six rules. You're like, I'm not even going to talk to companies

00:16:56.300 --> 00:17:00.060
that fit into one of these areas, one or more of these areas, maybe two areas, right?

00:17:00.060 --> 00:17:04.540
Pretty much if they meet, I try to avoid companies that are any of the above.

00:17:04.540 --> 00:17:05.020
Okay.

00:17:05.020 --> 00:17:08.540
And there's also, I have another list too, where there's like, okay, things I do want to,

00:17:08.540 --> 00:17:12.780
criteria is definitely looking for. So I had like two sets of criteria, the no criteria and then like,

00:17:12.780 --> 00:17:17.100
okay, things I'm definitely looking for, like a good strong culture, a good like culture of code

00:17:17.100 --> 00:17:21.500
review and a good like testing infrastructure and other things like that. But at the same time,

00:17:21.500 --> 00:17:25.660
like I was also, you know, the no criteria is like, was something that it was definitely a

00:17:25.660 --> 00:17:29.420
do for good for me because I didn't want to be in a place where I might get frustrated or

00:17:29.420 --> 00:17:33.020
the top, maybe the culture would be more toxic than I imagined.

00:17:33.020 --> 00:17:39.740
Yeah, sure. So you had no large companies, no homogeneous culture. What does that mean?

00:17:39.740 --> 00:17:44.940
So one of the things I care about is that it's about like diversity in terms of like age, gender,

00:17:44.940 --> 00:17:49.260
race, like all of them, all of the things. And that's something I care deeply about. And I,

00:17:49.260 --> 00:17:55.260
and if I see that a company, they may be like a few years out in business and they don't have

00:17:55.260 --> 00:17:59.740
a diverse workforce. I feel like that may be a warning sign. And there's certain recruiters

00:17:59.740 --> 00:18:04.060
who have been really honest about the fact that I like, if I work there, I may be the first female

00:18:04.060 --> 00:18:06.700
engineer there. And that's kind of scary to me.

00:18:06.700 --> 00:18:11.660
That was not a thrilling concept to you to be the first person to break that ice.

00:18:11.660 --> 00:18:13.100
It is. It is pretty scary.

00:18:13.100 --> 00:18:18.700
Yeah, I would think it would be as well. I mean, I've talked to other women in tech who were like,

00:18:18.700 --> 00:18:23.740
I totally fit and fine. It's no big deal. But just, you know, I didn't connect in the same way,

00:18:23.740 --> 00:18:29.980
like maybe a bunch of young white guys who are programmers who just came out of, you know,

00:18:29.980 --> 00:18:35.820
college or whatever. Like I wasn't interested in land parties. So there goes a big part of my,

00:18:35.820 --> 00:18:42.460
my connecting with my coworkers and whatnot. So yeah. Did you find that it was easy enough to find

00:18:42.460 --> 00:18:47.100
places that were heterogeneous cultures or was it really challenging?

00:18:47.100 --> 00:18:52.700
Well, that's one of the questions I asked recruiters on the first conversation. And I also pretty much ask

00:18:52.700 --> 00:18:59.180
more or less the same question to the engineering director or like the tech lead to see like,

00:18:59.180 --> 00:19:04.780
oh, like what are the ratio, women engineers, male engineers in the environment. So that's like one

00:19:04.780 --> 00:19:07.020
thing amongst many other things I'm looking for.

00:19:07.020 --> 00:19:12.700
Yeah. Yeah. You said also no stupid apps, which is a kind of cut ties back to like,

00:19:12.700 --> 00:19:15.180
you want to make a difference with what you create. Right.

00:19:15.180 --> 00:19:17.580
Yeah. I've seen a lot of stupid apps. Oh God.

00:19:17.580 --> 00:19:22.780
I mean, I've seen apps that like seem pretty implausible. And like, once I think about it,

00:19:22.780 --> 00:19:25.340
I was like, wait, like, why, why would you do this?

00:19:25.340 --> 00:19:29.980
Yeah. I'm a big fan of a lot of stuff happening in San Francisco, but there are certainly some

00:19:29.980 --> 00:19:36.860
companies just like, well, the world does not need this. Come on. I find one of the

00:19:36.860 --> 00:19:43.900
more frustrating things, like maybe near the top of my list of frustrating things in a job as a

00:19:43.900 --> 00:19:50.460
programmer is nobody uses the thing that I built. You put your heart and soul into writing software and

00:19:50.460 --> 00:19:56.700
coming up with something and just, it's like a creation of art almost as a team. And if you

00:19:56.700 --> 00:20:01.820
launch that and then just nobody comes, it's just like, I find that really frustrating. So I think the

00:20:01.820 --> 00:20:05.420
stupid apps may also like tie back to unused apps.

00:20:05.420 --> 00:20:11.180
And I was also pretty careful about companies that are more about like the hype and the marketing and

00:20:11.180 --> 00:20:17.340
the media. And you know, it's, they may not have like the product to be able to fulfill that hype.

00:20:17.340 --> 00:20:23.740
So, so I'm looking for like real companies that have real business value, like to have like proven business success for the long term.

00:20:23.740 --> 00:20:29.180
Yeah. Yeah. So speaking of proven business success, you said you didn't want to be the first,

00:20:29.180 --> 00:20:35.260
like the single technical co-founder or the first tech person, first engineer at a,

00:20:35.260 --> 00:20:38.060
at some kind of startup, somebody's wild dream.

00:20:38.060 --> 00:20:46.700
Oh yeah. I'm pretty sure that is like a dream from a lot of people in the Bay Area to be like the first like founder or CTO of their like first startup.

00:20:46.700 --> 00:20:53.580
But I feel like I like working on a team and on a team environment and like having all of the,

00:20:53.580 --> 00:20:58.620
the advantages of being on a team where like you're tracking people, you're discussing with other engineers.

00:20:58.620 --> 00:21:02.420
It's really important for growth and like technical growth, personal growth.

00:21:02.420 --> 00:21:04.560
Yeah. I think that is really important for personal growth.

00:21:04.560 --> 00:21:09.320
I think being the single tech person is probably okay.

00:21:09.320 --> 00:21:13.220
Once you're more established, you've already got connections with other people in the industry.

00:21:13.220 --> 00:21:14.780
You're pretty confident in yourself.

00:21:14.780 --> 00:21:17.460
You can go to like meetups and conferences and all that.

00:21:17.460 --> 00:21:23.540
But when you're, when you're pretty new, it's certainly, I think it's, it's a really tough place to be because you want that.

00:21:23.540 --> 00:21:31.620
I've always, at least personally wanted to be the least knowledgeable experienced person in the room because I felt like, all right, that,

00:21:31.620 --> 00:21:34.640
that is going to get me in a place where I can just like learn more.

00:21:34.640 --> 00:21:35.820
I agree with that too.

00:21:35.820 --> 00:21:36.620
Yeah. Yeah. I mean,

00:21:36.620 --> 00:21:42.800
So my current company, I think I'm like more of the, I guess like mid-level younger engineers to give some context.

00:21:42.800 --> 00:21:48.460
Like the company working at has been around since 1999 and they've been profitable since then.

00:21:48.460 --> 00:21:54.140
And a lot of people, like a lot of the employees have been there on average of like seven to 10 years.

00:21:54.140 --> 00:21:57.480
And so to me, that's like, wow, like that's a, that's a long time.

00:21:57.480 --> 00:21:59.260
Yeah. That's a really, really good sign.

00:21:59.260 --> 00:22:02.560
Actually, it is a long time, especially in San Francisco, but it's also a good sign.

00:22:02.560 --> 00:22:06.280
That means like people who work there like to work there.

00:22:06.280 --> 00:22:07.140
Right.

00:22:07.140 --> 00:22:12.080
I went to work at a, like a trading company in New York, actually.

00:22:12.080 --> 00:22:19.080
And went there and it was a training gig that I was doing, teaching some stuff for those guys.

00:22:19.080 --> 00:22:21.580
And there's, there was a pretty big team of people.

00:22:21.580 --> 00:22:23.380
I think it was probably 30 people.

00:22:23.380 --> 00:22:27.600
And this guy came up to me and said, look, I'm the most senior person on this team.

00:22:27.600 --> 00:22:28.920
I've been here for two years.

00:22:28.920 --> 00:22:32.240
I thought, whoa, there might be something wrong in this company.

00:22:32.240 --> 00:22:37.080
It's like, you can't keep anyone out of a group of 30 more than two years.

00:22:37.080 --> 00:22:39.680
This is, this is like a, it was a pretty intense place to work.

00:22:39.680 --> 00:22:41.940
So I think the people being there longer is,

00:22:41.940 --> 00:22:43.220
generally a good sign.

00:22:43.220 --> 00:22:44.840
There's also drawbacks, but pretty good.

00:22:44.840 --> 00:22:46.760
So that was something I was looking forward to.

00:22:46.760 --> 00:22:47.160
All right.

00:22:47.160 --> 00:22:47.920
So great.

00:22:47.920 --> 00:22:51.720
And then the last one you said, you just didn't want to travel too far, which makes total sense.

00:22:53.160 --> 00:22:55.840
This portion of Talk Python To Me is brought to you by us.

00:22:55.840 --> 00:23:01.760
As many of you know, I have a growing set of courses to help you go from Python beginner to novice to Python expert.

00:23:01.760 --> 00:23:03.800
And there are many more courses in the works.

00:23:03.800 --> 00:23:08.040
So please consider Talk Python training for you and your team's training needs.

00:23:08.300 --> 00:23:14.460
If you're just getting started, I've built a course to teach you Python the way professional developers learn by building applications.

00:23:14.460 --> 00:23:19.540
Check out my Python jumpstart by building 10 apps at talkpython.fm/course.

00:23:19.540 --> 00:23:22.660
Are you looking to start adding services to your app?

00:23:22.660 --> 00:23:25.840
Try my brand new consuming HTTP services in Python.

00:23:26.200 --> 00:23:31.280
You'll learn to work with RESTful HTTP services, as well as SOAP, JSON, and XML data formats.

00:23:31.280 --> 00:23:33.160
Do you want to launch an online business?

00:23:33.160 --> 00:23:37.320
Well, Matt Makai and I built an entrepreneur's playbook with Python for Entrepreneurs.

00:23:37.320 --> 00:23:42.560
This 16-hour course will teach you everything you need to launch your web-based business with Python.

00:23:42.560 --> 00:23:46.100
And finally, there's a couple of new course announcements coming really soon.

00:23:46.100 --> 00:23:51.560
So if you don't already have an account, be sure to create one at training.talkpython.fm to get notified.

00:23:51.560 --> 00:23:55.340
And for all of you who have bought my courses, thank you so much.

00:23:55.440 --> 00:23:57.300
It really, really helps support the show.

00:23:57.300 --> 00:24:00.180
All right, so that was your no list.

00:24:00.180 --> 00:24:06.320
And then you went on all of these interviews, and you had a number of interesting stories.

00:24:06.320 --> 00:24:09.400
So maybe we could go through some of your stories.

00:24:09.400 --> 00:24:10.000
Sure.

00:24:10.000 --> 00:24:16.240
So a lot of my interviews are I would send out a job application, fill out the online forms, and click the send button.

00:24:16.240 --> 00:24:21.740
And then I would not hear back from most of the employers for a couple of days or weeks.

00:24:21.840 --> 00:24:25.840
And if I did hear back from them, it would be like this very impersonal email reply.

00:24:25.840 --> 00:24:27.700
Oh, sorry, dude, some of our candidates.

00:24:27.700 --> 00:24:29.180
We can't have you move forward.

00:24:29.180 --> 00:24:32.380
So I felt pretty mildly disappointed.

00:24:32.380 --> 00:24:38.980
But at the same time, I knew that they can't get back to me with a detailed personal response, even if I wanted them to.

00:24:39.220 --> 00:24:43.220
So that's when I go, okay, it's time to move on to the next opportunity.

00:24:43.220 --> 00:24:46.860
So it can get pretty grating at times and a little bit frustrating.

00:24:46.860 --> 00:24:50.340
But I understood where they're coming from, that they're pretty busy people.

00:24:50.340 --> 00:24:50.920
Yeah.

00:24:50.920 --> 00:24:52.760
So you get the serious silent treatment.

00:24:53.520 --> 00:24:59.880
Yeah, but you said one of the things that was kind of funny was like, people would pick it up later and like come back to you much later, right?

00:24:59.880 --> 00:25:00.580
Oh, yeah.

00:25:00.580 --> 00:25:02.480
That was really unusual.

00:25:02.480 --> 00:25:04.220
Like, that's something I was not expecting.

00:25:04.220 --> 00:25:10.360
Usually in the Bay Area, a lot of people get back to me if they're interested in like a few days or up to a week at most.

00:25:10.360 --> 00:25:12.420
But to get back to me like months later.

00:25:12.420 --> 00:25:20.580
And like literally, I once got this email from a company and they're like, oh, like we found your resume several months later and we wanted to be you.

00:25:20.580 --> 00:25:24.540
But they're like, I've already accepted a job months ago.

00:25:24.540 --> 00:25:25.040
Yeah, yeah.

00:25:25.040 --> 00:25:25.540
Too late.

00:25:25.540 --> 00:25:27.460
Yeah, this is a little bit weird.

00:25:27.460 --> 00:25:29.060
I certainly see how people get overwhelmed.

00:25:29.060 --> 00:25:33.640
Like I put up ads for jobs and, you know, got to so many applicants.

00:25:33.640 --> 00:25:36.160
It's like, oh, my gosh, I don't know if I could deal with all this.

00:25:36.160 --> 00:25:37.840
Certainly not like detailed responses.

00:25:37.840 --> 00:25:38.740
But yeah.

00:25:39.740 --> 00:25:43.660
So another one was this AI startup that you were talking about.

00:25:43.660 --> 00:25:46.760
And you said the interview went pretty well.

00:25:46.760 --> 00:25:51.460
But in the end, they decided to just hire their friend or something like this, right?

00:25:51.460 --> 00:25:56.700
Ironic to me was that they were working on like automating human resources, like the hiring component.

00:25:56.700 --> 00:26:05.160
And yet they decided, OK, well, we're just going to hire someone already now, which is like ironic because what is the purpose of the product that they're making?

00:26:05.160 --> 00:26:08.680
The machine says my friend.

00:26:09.520 --> 00:26:15.900
Oh, and again, like, you know, if you have a connection, a way in, that's great for you.

00:26:15.900 --> 00:26:17.620
And we're lucky for them.

00:26:17.620 --> 00:26:22.940
But a lot of times, like when I was doing a job search, like I didn't have a way in, like a direct connection or just me.

00:26:22.940 --> 00:26:29.340
And everyone else is very much like, you know, they reached out to me via email or the standard application process.

00:26:29.540 --> 00:26:29.920
Yeah, sure.

00:26:29.920 --> 00:26:41.720
So how much do you think like moving out there from New York and not growing up there sort of limits your connections to like the number of people in these positions maybe?

00:26:42.100 --> 00:26:47.540
So initially, it was harder for me because I didn't have like a network of people already in the Bay Area.

00:26:47.880 --> 00:26:52.860
So I had to reach out to people, like connect with other people.

00:26:52.860 --> 00:27:01.600
And that can get pretty frustrating sometimes, like especially for like the interviewing process, because sometimes people are hiring, sometimes they're not, especially for the meetups I would go to.

00:27:02.100 --> 00:27:03.720
So it's really hit or miss for me.

00:27:03.720 --> 00:27:10.440
And one of the questions I got from people after my talk was like, to what extent was I going to meetups and doing a networking thing?

00:27:10.440 --> 00:27:12.300
And I didn't really do a whole lot.

00:27:12.300 --> 00:27:16.020
I personally found that pretty draining, especially at the end of a long day of interviews.

00:27:16.020 --> 00:27:18.300
Like I kind of didn't want to go to like a meetup.

00:27:18.300 --> 00:27:20.440
And that was my personal.

00:27:20.440 --> 00:27:24.900
Maybe some people are really into like all the networking and meeting all the possible people.

00:27:24.900 --> 00:27:29.360
But as an introvert, I felt that it's a bit more draining to put myself out there.

00:27:29.640 --> 00:27:32.260
Yeah, it can be pretty hard to do that as well.

00:27:32.260 --> 00:27:33.420
Sure.

00:27:33.420 --> 00:27:42.220
It's definitely challenging, especially if you're, it's kind of hard to walk in completely by yourself into a room and start just randomly talking to strangers.

00:27:42.220 --> 00:27:52.040
I find it's a little easier in the tech space for me because I can just talk about tech, which is a pretty, is a pretty good common thing to talk about.

00:27:52.040 --> 00:27:54.740
But general networking is still pretty challenging.

00:27:54.740 --> 00:27:56.900
So what about Jelly?

00:27:56.900 --> 00:27:59.200
Initially, I was pretty excited about Jelly.

00:27:59.580 --> 00:28:04.540
And I was one of like, when I found out about Jelly, I was like one of the more avid users I was asking.

00:28:04.540 --> 00:28:06.760
So Jelly to backup is a Q&A app.

00:28:06.760 --> 00:28:10.080
You ask questions and then you can get answers that are-

00:28:10.080 --> 00:28:10.740
Like Quora?

00:28:10.740 --> 00:28:12.280
Yeah, it's pretty much like Quora.

00:28:12.280 --> 00:28:13.020
Okay.

00:28:13.020 --> 00:28:17.060
And their focus is about like providing quality answers.

00:28:17.380 --> 00:28:22.900
So they're pretty selective about like who gets to like answer the questions or trying to find like the best people for that.

00:28:22.900 --> 00:28:24.920
And it's all like crowdsourced.

00:28:24.920 --> 00:28:31.520
So it's really up to like a team of volunteers who are in the community of experts who are answering a lot of these questions.

00:28:31.940 --> 00:28:35.640
And they have like a Twitter integration where you get to put a hashtag, ask Jelly.

00:28:35.640 --> 00:28:40.720
So sometimes I would like ask questions in 140 characters and I get a response back.

00:28:40.720 --> 00:28:41.100
Okay.

00:28:42.360 --> 00:28:48.820
And you had an interview with Biz Stone, co-founder of Twitter, who asked you just one question, right?

00:28:48.820 --> 00:28:49.280
Yes.

00:28:49.280 --> 00:28:50.720
What was the question?

00:28:50.720 --> 00:28:54.840
So he asked me, what do you hope to accomplish in your life, Susan?

00:28:55.840 --> 00:28:59.980
And I was a little bit from back from this question because I wasn't sure how to answer it.

00:28:59.980 --> 00:29:02.880
Like this was not one of the questions I was prepared for.

00:29:02.880 --> 00:29:05.700
So I was totally ready for like other questions.

00:29:05.700 --> 00:29:08.060
Like, okay, like how does that jingle work?

00:29:08.060 --> 00:29:10.180
Or like how does the internet work?

00:29:10.180 --> 00:29:11.140
And I was ready for it.

00:29:11.140 --> 00:29:13.580
It was kind of like web-depth related questions.

00:29:13.580 --> 00:29:15.360
But this is like a really broad question to me.

00:29:15.360 --> 00:29:16.600
So I was a bit in trouble.

00:29:16.600 --> 00:29:21.800
What's the advantage of using a Q in such and such situation or something, right?

00:29:21.800 --> 00:29:24.600
Like that's not the same as what are you going to accomplish in your life?

00:29:24.600 --> 00:29:25.040
Yeah.

00:29:25.260 --> 00:29:27.400
So I was like really like taken aback.

00:29:27.400 --> 00:29:30.420
And so I basically had to come up with something really quickly on the spot.

00:29:30.420 --> 00:29:33.320
And I talked about like my passion for Jelly.

00:29:33.320 --> 00:29:35.660
Like it seems like it really has a lot of potential.

00:29:35.660 --> 00:29:40.540
And I want to work on the features and get more users to use this product.

00:29:40.540 --> 00:29:46.160
So it was like pretty like a standard response to something that's pretty generic, I think.

00:29:46.160 --> 00:29:49.540
So I think he liked the answer.

00:29:49.540 --> 00:29:54.240
Like, you know, he also gave me his answer, which seemed a little bit hippy-dippy.

00:29:54.580 --> 00:29:55.680
He gave like this.

00:29:55.680 --> 00:30:02.740
He gave me an answer about how he wants to connect the world and make everyone part of this like community of like-minded internet.

00:30:02.740 --> 00:30:03.660
It's very hippy-dippy.

00:30:03.660 --> 00:30:05.200
If I remember.

00:30:05.200 --> 00:30:05.880
Yeah.

00:30:05.880 --> 00:30:07.500
Sounds a little like Twitter Jelly.

00:30:07.500 --> 00:30:07.840
Okay.

00:30:09.420 --> 00:30:20.880
And you said you had this very awkward experience around like, hey, we know you don't really know Ruby that well, but why don't you implement a full stack solution in Ruby anyway?

00:30:20.880 --> 00:30:21.760
Now.

00:30:21.760 --> 00:30:23.620
Tell us about this one.

00:30:24.280 --> 00:30:24.460
Yeah.

00:30:24.460 --> 00:30:32.700
So I, so basically I walked into the office and the email that I got before the interview was like, hey, you should brush up on some Ruby and some Ruby on Rails.

00:30:33.200 --> 00:30:40.880
And so initially like when I walked into the office, I thought I was going to be pair programming with the interviewer on a full stack Ruby application and we'll go through the problem together.

00:30:41.360 --> 00:30:48.000
But it turned out that he wants me to implement a feature on an existing Ruby application from in like 15 minutes.

00:30:48.000 --> 00:30:51.360
And I was like, wait, like, are you sure you want me to do this in 15 minutes?

00:30:51.880 --> 00:30:53.260
And he was like, yeah, yeah, sure.

00:30:53.260 --> 00:30:53.840
Go for it.

00:30:53.840 --> 00:30:56.460
Since like he's in charge of this whole process.

00:30:56.460 --> 00:30:59.240
I was like, and I was following instructions.

00:30:59.240 --> 00:31:00.160
Like, okay, yeah, sure.

00:31:00.160 --> 00:31:00.700
Why not?

00:31:00.700 --> 00:31:02.380
And so I tried like going through the process.

00:31:02.380 --> 00:31:06.660
Like I was looking up the documentation, like going through the online Ruby tutorial.

00:31:06.660 --> 00:31:08.040
I was like, this is really awkward.

00:31:08.040 --> 00:31:12.660
Like I'm trying to like learn Ruby at the same time, trying to create something that would be a profession.

00:31:12.660 --> 00:31:13.640
Yeah.

00:31:13.640 --> 00:31:17.480
And so 15, there was also like my shortest interview, 15 minutes.

00:31:17.820 --> 00:31:25.980
And then like a few minutes later, he, he saw, I was like, not at all proficient with Ruby, which was, I told him that like a few minutes ago.

00:31:25.980 --> 00:31:29.880
And he stopped me saying, okay, Susan, you don't seem to know Ruby very well.

00:31:29.880 --> 00:31:33.920
So let's just hold off on this until you gain some experience in Ruby.

00:31:33.920 --> 00:31:35.540
Then we can reconsider.

00:31:35.540 --> 00:31:35.960
Yeah.

00:31:35.960 --> 00:31:39.380
And you didn't follow up a few months later after you had done a bootcamp in Ruby.

00:31:39.380 --> 00:31:42.420
I kind of understood where he was coming from.

00:31:42.420 --> 00:31:47.060
Like, okay, this is like a, he wanted, maybe he did actually want people who are experienced in Ruby.

00:31:47.380 --> 00:31:52.000
And not like he, maybe he wasn't willing to look at beginners or teach newbies.

00:31:52.000 --> 00:31:52.380
Yeah.

00:31:52.380 --> 00:31:53.260
And that's totally reasonable.

00:31:53.260 --> 00:31:55.620
Like to say, look, I want somebody who already knows this technology.

00:31:55.620 --> 00:32:00.120
You can just come in on the first day, start being productive, but that should be like clear.

00:32:00.120 --> 00:32:01.100
Yeah.

00:32:01.100 --> 00:32:01.780
Beforehand.

00:32:01.780 --> 00:32:02.040
Right.

00:32:02.040 --> 00:32:03.940
Like it should just like, that should be more obvious.

00:32:03.940 --> 00:32:05.660
So that's kind of awkward.

00:32:05.660 --> 00:32:06.200
I'm sure.

00:32:06.200 --> 00:32:06.500
Right.

00:32:06.500 --> 00:32:06.680
Yeah.

00:32:06.680 --> 00:32:10.300
So there's a pattern of like a lot of interviewers may not know what they're looking for.

00:32:10.300 --> 00:32:14.960
And so they ask a lot of these questions that may, may not be relevant or they give you code

00:32:14.960 --> 00:32:19.140
challenges that may not have pertinence to the job description.

00:32:19.140 --> 00:32:19.760
Sure.

00:32:19.760 --> 00:32:23.260
So let's actually talk about code challenges since you brought that up a little bit.

00:32:23.260 --> 00:32:28.060
Like that seemed to be like one of your really biggest pet peeves of the whole experience.

00:32:28.060 --> 00:32:28.500
Yeah.

00:32:29.000 --> 00:32:33.620
So code challenges to give an intro, sometimes you may get code challenges and that can take

00:32:33.620 --> 00:32:36.900
anywhere from like 60, 30 minutes, 60 minutes, 90 minutes.

00:32:36.900 --> 00:32:42.060
And sometimes it can be timed where you answer a number of questions and it's either like a

00:32:42.060 --> 00:32:44.840
right answer or a wrong answer, depending on what they're looking for.

00:32:44.840 --> 00:32:50.160
Or sometimes there are open-ended questions where you have to build an application from scratch

00:32:50.160 --> 00:32:54.760
or you have to like create the models and the views and controllers, the whole thing.

00:32:54.760 --> 00:32:58.980
If you're a web application developer, I particularly really harp on like the open-ended

00:32:58.980 --> 00:33:03.860
open-ended code challenges in particular, because there's like no time constraints or sometimes

00:33:03.860 --> 00:33:05.900
there's no time constraints or like no feature constraints.

00:33:05.900 --> 00:33:10.680
So you don't have an idea if this will take like an hour or it's like a whole weekend project.

00:33:10.680 --> 00:33:10.980
Yeah.

00:33:10.980 --> 00:33:11.840
Give us an example.

00:33:11.840 --> 00:33:19.540
So one example is build a full stack application that uses the Twitter API in some way.

00:33:19.540 --> 00:33:23.120
And so it's just open-ended because you can use the Twitter API in any number of ways.

00:33:23.120 --> 00:33:28.160
This particular is challenging because you're not sure like what exactly are you looking for?

00:33:28.220 --> 00:33:29.200
Like, are you looking for design?

00:33:29.200 --> 00:33:33.640
Are we looking for how well I can write the test for this feature or how?

00:33:33.640 --> 00:33:37.080
So it's really hard to tell, especially if that code challenge doesn't come with really clear

00:33:37.080 --> 00:33:38.040
and specific guidelines.

00:33:38.040 --> 00:33:38.960
Like what is the input?

00:33:38.960 --> 00:33:39.920
What is the output?

00:33:39.920 --> 00:33:40.200
Yeah.

00:33:40.200 --> 00:33:41.940
So certainly you mentioned design.

00:33:41.940 --> 00:33:43.580
That's obviously one of them.

00:33:43.580 --> 00:33:48.080
But even on just the programming side, like you could go to either end of a spectrum.

00:33:48.200 --> 00:33:55.360
You could say, look, I want to see the most properly designed, layered, design pattern type

00:33:55.360 --> 00:33:57.480
of testable architecture.

00:33:57.480 --> 00:33:59.760
And that's what you could be graded on.

00:33:59.760 --> 00:34:05.600
Or you could be graded on, I want to see the most complete, full implementation of a cool

00:34:05.600 --> 00:34:06.040
app.

00:34:06.040 --> 00:34:10.280
In which case you should throw that out the window and just write crap as fast as you can,

00:34:10.280 --> 00:34:13.920
because it's not going to have to work really other than just to prove the concept.

00:34:13.920 --> 00:34:14.240
Right?

00:34:14.240 --> 00:34:14.540
Yeah.

00:34:14.740 --> 00:34:16.080
And so what should you do, right?

00:34:16.080 --> 00:34:16.600
You don't know.

00:34:16.600 --> 00:34:16.860
Yeah.

00:34:16.860 --> 00:34:21.880
And sometimes when I would go and spend time on the open-ended code challenges, one of the

00:34:21.880 --> 00:34:25.440
things I fell into is that, okay, like one of the feedback I got was like, maybe I didn't

00:34:25.440 --> 00:34:29.280
write unit tests or maybe I didn't use the right library that they expected me to.

00:34:29.280 --> 00:34:33.620
So it's really hard to know what you're expecting because you're not given those instructions.

00:34:33.620 --> 00:34:34.300
Yeah.

00:34:34.300 --> 00:34:34.560
Yeah.

00:34:34.560 --> 00:34:39.880
And you can spend days on it and maybe not even get anything out of it.

00:34:39.880 --> 00:34:40.080
Right?

00:34:40.080 --> 00:34:40.800
Right.

00:34:40.800 --> 00:34:41.180
Yeah.

00:34:41.180 --> 00:34:43.660
I suspect the most frustrating part is the ambiguity.

00:34:44.280 --> 00:34:48.080
Like, I don't know what criteria I'm being evaluated on.

00:34:48.080 --> 00:34:52.940
So I just got to like, what, go implement some brand new app from scratch.

00:34:52.940 --> 00:34:54.100
And it's part of my exam.

00:34:54.100 --> 00:34:54.400
Right?

00:34:54.400 --> 00:35:01.460
So the last story you had was about this genetic biochemistry company that uses the CRISPR algorithm.

00:35:01.460 --> 00:35:02.100
Right?

00:35:02.100 --> 00:35:03.080
What's the story there?

00:35:03.080 --> 00:35:03.380
Yeah.

00:35:03.380 --> 00:35:05.260
So on paper, it sounds really great.

00:35:05.260 --> 00:35:09.600
Like they're a very mission oriented company and the website has all these information,

00:35:09.600 --> 00:35:14.200
like papers they've published and the team looks like really solid, like lots of experienced

00:35:14.200 --> 00:35:14.620
people.

00:35:14.620 --> 00:35:16.060
Lots of PhDs probably.

00:35:16.060 --> 00:35:16.520
Yeah.

00:35:16.520 --> 00:35:16.940
Yeah.

00:35:16.940 --> 00:35:17.280
Yeah.

00:35:17.280 --> 00:35:19.140
So this is like the biotech space.

00:35:19.420 --> 00:35:23.120
And there's a lot of chemistry people, mechanical engineers, electrical engineers, and software

00:35:23.120 --> 00:35:25.900
engineers all working in a lab environment.

00:35:25.900 --> 00:35:26.400
Yeah.

00:35:26.400 --> 00:35:27.080
Sounds really fun.

00:35:27.080 --> 00:35:27.540
Yeah.

00:35:27.540 --> 00:35:32.820
And so I got to explore and did a tour of the lab and that was pretty neat.

00:35:33.080 --> 00:35:38.780
And in that interview process, I did a live coding challenge where I was making, I made

00:35:38.780 --> 00:35:40.440
a Django app that went pretty well.

00:35:40.440 --> 00:35:44.740
And I answered a lot of questions and asked a lot of questions to a lot of the engineers

00:35:44.740 --> 00:35:49.260
there and including the two co-founders who also happened to be brothers.

00:35:49.260 --> 00:35:51.280
So that was pretty interesting.

00:35:51.280 --> 00:35:57.620
So at the end, I really enjoyed the process and everything seemed like really swell and good.

00:35:57.760 --> 00:36:02.480
And I got the job offer with like the number and I was like, and I was pretty disappointed.

00:36:02.480 --> 00:36:06.380
And I said, well, and I told the CEO and the co-founder that, well, this is like way

00:36:06.380 --> 00:36:11.660
below the average salary for what a software engineer of my level experience should be making.

00:36:11.660 --> 00:36:13.580
I said, no, I went on 50 interviews.

00:36:13.580 --> 00:36:15.440
Yeah.

00:36:15.440 --> 00:36:20.840
And his response was very like, he was very stubborn and he didn't want to negotiate.

00:36:20.840 --> 00:36:23.900
Like I can tell that he was being very defensive on the other end of the phone.

00:36:24.360 --> 00:36:29.460
So to me, like that didn't seem like everything on when I visited in person, it seems good.

00:36:29.460 --> 00:36:34.960
But then like the company wasn't really willing to pay competitive salary to their engineers.

00:36:34.960 --> 00:36:39.220
Well, and there's one thing is like, if this company is kind of just getting started and

00:36:39.220 --> 00:36:43.940
they're, they're looking for VC money and they're thinking that this is going to blow up

00:36:43.940 --> 00:36:47.160
and they say, look, we'll just take care of you when everything starts to take off and

00:36:47.160 --> 00:36:48.400
it's going to be amazing for everyone.

00:36:48.400 --> 00:36:52.400
We just all got to kind of come together to help launch this idea.

00:36:52.400 --> 00:36:55.580
That's one thing, but they had like $40 million in VC funding already.

00:36:55.580 --> 00:36:55.940
Right.

00:36:55.940 --> 00:36:57.080
Yeah.

00:36:57.080 --> 00:37:00.180
And they're ready and they're like fifth or fourth year.

00:37:00.180 --> 00:37:03.400
So it's, they're not like a baby startup just getting started.

00:37:03.400 --> 00:37:04.120
Yeah.

00:37:04.120 --> 00:37:07.320
So they have a lot of money and that was like an automatic note to me.

00:37:07.320 --> 00:37:09.140
Like I'm not willing to compromise.

00:37:09.140 --> 00:37:12.360
You know, I think it's interesting is there are two, well, there are more than two types.

00:37:12.360 --> 00:37:18.100
There are two categories of companies that come to mind that really, and I don't know if

00:37:18.100 --> 00:37:19.140
this is the situation here.

00:37:19.280 --> 00:37:20.040
Tell me your thoughts.

00:37:20.040 --> 00:37:24.320
Like on one hand, there's companies, this could be in San Francisco and tech companies,

00:37:24.320 --> 00:37:28.800
or it could be in Kansas city in, you know, like a cable company.

00:37:28.800 --> 00:37:29.640
It doesn't really matter.

00:37:29.640 --> 00:37:34.640
But that where the company sees their software team and their software people, their technology

00:37:34.640 --> 00:37:38.640
people as like, like a sword that they can wield in business.

00:37:38.640 --> 00:37:38.820
Right.

00:37:38.820 --> 00:37:41.980
Like something that is super powerful and is like, should be respected.

00:37:42.240 --> 00:37:47.720
And then there's other companies that just see it as like an expense, like that just drags

00:37:47.720 --> 00:37:48.300
on the business.

00:37:48.300 --> 00:37:52.920
And so maybe these guys, they had that mindset where it's like, well, these developers, they're

00:37:52.920 --> 00:37:53.700
necessary, evil.

00:37:53.700 --> 00:37:54.560
We have to pay them.

00:37:54.560 --> 00:37:56.420
It's hard to tell.

00:37:56.420 --> 00:37:56.940
Yeah.

00:37:56.940 --> 00:37:57.120
Yeah.

00:37:57.120 --> 00:38:00.020
I'm sure you didn't go into the philosophy too much with the guy.

00:38:00.540 --> 00:38:05.060
Anyway, I definitely been in some companies where they, they don't seem to realize like,

00:38:05.060 --> 00:38:06.440
Hey, we have this amazing software team.

00:38:06.440 --> 00:38:08.420
Like, what could we do if we really inspired them?

00:38:08.420 --> 00:38:12.200
And they just seem to like, you know, not, not put a lot of credit in what they say or

00:38:12.200 --> 00:38:13.020
do or whatever.

00:38:13.020 --> 00:38:13.800
And that's not amazing.

00:38:13.800 --> 00:38:14.060
Yeah.

00:38:14.060 --> 00:38:17.900
And this often comes from say, like if the founders aren't technical themselves, they

00:38:17.900 --> 00:38:20.760
may not understand like, Oh, why do we have to have an ops team?

00:38:20.820 --> 00:38:23.620
Why do we even have to have people working on like the front end?

00:38:23.620 --> 00:38:28.100
I can even see if you were like a super high end scientist, theoretically, you might go,

00:38:28.100 --> 00:38:30.880
well, the science is what's important, not the programming.

00:38:30.880 --> 00:38:32.220
That's a dime a dozen, right?

00:38:32.220 --> 00:38:36.280
I suspect that's less common, but it still could be the case.

00:38:36.280 --> 00:38:37.220
All right.

00:38:37.220 --> 00:38:41.240
So you gave us the talk.

00:38:41.240 --> 00:38:44.480
You gave some numbers about how long it took you to find your first job, your second job

00:38:44.480 --> 00:38:48.040
and this last job and maybe some takeaways.

00:38:48.040 --> 00:38:50.180
Can you maybe run that down for us?

00:38:50.180 --> 00:38:55.120
Overall, it was a pretty frustrating experience because I talked to a lot of different companies.

00:38:55.120 --> 00:39:00.640
Sometimes I expected more positive responses and a lot of them turned out to be like, okay,

00:39:00.640 --> 00:39:02.880
like more frustrating experiences than I expected.

00:39:02.880 --> 00:39:04.380
Yeah, I'm sure.

00:39:04.380 --> 00:39:08.640
So I've gone through, talked to a lot of different engineers and learned a lot about different

00:39:08.640 --> 00:39:09.060
products.

00:39:09.060 --> 00:39:12.100
So it's really, I feel like the whole process is like a crap shoot.

00:39:12.100 --> 00:39:13.100
Like you, you have no idea.

00:39:13.100 --> 00:39:13.860
It's so unpredictable.

00:39:13.860 --> 00:39:18.320
Like you don't know how long the interview process may take and like what kind of questions

00:39:18.320 --> 00:39:18.900
you might get.

00:39:19.540 --> 00:39:25.360
And it can get pretty frustrating at times because getting a lot of no's can be like,

00:39:25.360 --> 00:39:28.480
you can lose your self-confidence when you're going through this process.

00:39:28.480 --> 00:39:33.760
But to me, like the way I got through it, like I tried to like take a step back and you know,

00:39:33.760 --> 00:39:38.720
the next day after taking breaks in between the next days, there's always like a new opportunity

00:39:38.720 --> 00:39:39.160
for me.

00:39:39.220 --> 00:39:42.140
And there's always like a new door, lots of new people to talk to.

00:39:42.140 --> 00:39:45.220
So like every day it was like a blank slate, like start fresh.

00:39:45.320 --> 00:39:50.100
Yeah, that probably takes putting yourself in the right mindset somewhat.

00:39:50.100 --> 00:39:54.160
So you're like, because you've got to show up with a good attitude.

00:39:54.160 --> 00:39:58.320
You can't just show up like looking worn out and like dejected, right?

00:39:58.320 --> 00:39:59.520
No one's going to hire you then.

00:39:59.520 --> 00:40:01.560
So yeah, it's good to take some breaks.

00:40:01.560 --> 00:40:05.760
And if you need to take like the afternoon off, just to like to clear ahead.

00:40:05.760 --> 00:40:06.440
I did that.

00:40:06.540 --> 00:40:10.980
Like there's lots of places where I would walk to just to take some walks.

00:40:10.980 --> 00:40:11.780
It's very therapeutic.

00:40:11.780 --> 00:40:13.560
And yeah, yeah.

00:40:13.560 --> 00:40:15.380
And I also drink a lot of tea as well.

00:40:15.380 --> 00:40:16.760
It's kind of like keeping calm.

00:40:16.760 --> 00:40:18.660
That's really cool.

00:40:18.660 --> 00:40:19.860
Nice.

00:40:19.860 --> 00:40:20.180
Okay.

00:40:20.180 --> 00:40:24.800
So did people ask about like, what did they ask about your prior work?

00:40:24.800 --> 00:40:26.560
Like, did they check out your GitHub profile?

00:40:26.560 --> 00:40:28.180
Did they talk about open source?

00:40:28.180 --> 00:40:29.980
What you did at other companies?

00:40:29.980 --> 00:40:31.460
What did they seem to focus on?

00:40:31.460 --> 00:40:35.800
So the reason I'm asking is people who are out there looking for a job, like, you know,

00:40:35.820 --> 00:40:37.000
where should they spend their energy?

00:40:37.000 --> 00:40:40.700
I think having a good project you can focus on.

00:40:40.700 --> 00:40:45.160
So a lot of questions that I've gotten are about previous favorite projects.

00:40:45.160 --> 00:40:46.320
Like what's been your favorite project?

00:40:46.320 --> 00:40:48.240
What's been the most challenging project?

00:40:48.240 --> 00:40:53.100
So these are going to be questions that are going to be like pretty common if you go to

00:40:53.100 --> 00:40:54.240
eventually to the on-site interview.

00:40:54.240 --> 00:40:59.200
So it's good to be pretty prepared and be able to show off like your strengths and be able

00:40:59.200 --> 00:41:03.460
to talk at length about different decisions that you've made or challenges that you faced

00:41:03.460 --> 00:41:04.620
and how you overcome them.

00:41:04.620 --> 00:41:05.060
Sure.

00:41:05.100 --> 00:41:08.260
Did anybody ever ask you what your favorite open source project was?

00:41:08.260 --> 00:41:11.620
Or was it always focused on like what you had done personally?

00:41:11.620 --> 00:41:13.080
I don't think I've gotten that question.

00:41:13.080 --> 00:41:15.860
It was primarily focused on like previous work.

00:41:15.860 --> 00:41:20.780
So sometimes I would get questions where I need to like diagram or like whiteboard what the

00:41:20.780 --> 00:41:23.100
architecture was for this past project.

00:41:23.100 --> 00:41:24.120
So yeah.

00:41:24.120 --> 00:41:25.080
So that's pretty typical.

00:41:25.080 --> 00:41:25.700
Yeah, sure.

00:41:25.700 --> 00:41:27.160
Okay.

00:41:27.460 --> 00:41:29.740
Well, this is very, very interesting.

00:41:29.740 --> 00:41:35.840
Let me ask you two more questions before I let you go and then we'll do a quick wrap up.

00:41:36.480 --> 00:41:40.460
So if you're going to write some Python code, what editor do you open up?

00:41:40.460 --> 00:41:41.300
It depends.

00:41:41.300 --> 00:41:43.760
I switch between sublime text and Vim.

00:41:44.520 --> 00:41:49.640
So the past two years I've been working on Vim, using Vim primarily because I had to SSH,

00:41:49.640 --> 00:41:53.040
vagrant SSH into a good Linux environment.

00:41:53.040 --> 00:41:53.820
Yeah.

00:41:54.040 --> 00:42:01.140
So I learned how to use a lot of Vim packages like c tags, a lot of the common Vim packages installed.

00:42:01.140 --> 00:42:05.920
But then what's frustrating about Vim personally is that sometimes when I destroy my environment

00:42:05.920 --> 00:42:10.920
accidentally, I have to like reset up all of the packages again and like reinstall those packages.

00:42:10.920 --> 00:42:12.360
And that gets a little bit annoying.

00:42:12.360 --> 00:42:13.980
How do I get this thing working again?

00:42:13.980 --> 00:42:14.340
Yeah.

00:42:14.340 --> 00:42:15.820
I saw a picture.

00:42:15.820 --> 00:42:16.980
It was some kind of meme.

00:42:16.980 --> 00:42:21.540
It was a picture of a bus and it had VIM written like in huge letters on the side.

00:42:21.660 --> 00:42:25.280
there were people in it and the meme was, how do I get off this bus?

00:42:25.280 --> 00:42:26.320
How do I quit this bus?

00:42:26.320 --> 00:42:26.760
Basically.

00:42:26.760 --> 00:42:28.280
It was really funny.

00:42:28.280 --> 00:42:29.240
All right.

00:42:29.240 --> 00:42:33.780
So favorite PyPI package or most notable one that you've come across that maybe people haven't

00:42:33.780 --> 00:42:34.260
heard of.

00:42:34.260 --> 00:42:36.340
In Django, I really like Shell Plus.

00:42:36.340 --> 00:42:42.400
You can use Shell Plus to load pretty much the database models into the shell.

00:42:42.400 --> 00:42:44.440
So that's been really useful for debugging.

00:42:44.440 --> 00:42:45.280
Oh yeah.

00:42:45.280 --> 00:42:45.880
That's cool.

00:42:45.880 --> 00:42:49.480
Because you have everything already preloaded for you when you open up the Django shell.

00:42:49.480 --> 00:42:50.180
Yeah.

00:42:50.180 --> 00:42:50.540
Nice.

00:42:50.540 --> 00:42:50.860
Okay.

00:42:51.320 --> 00:42:51.920
Very cool.

00:42:51.920 --> 00:42:52.680
That's a good one.

00:42:52.680 --> 00:42:53.480
All right.

00:42:53.480 --> 00:42:55.640
So last thing, final call to action.

00:42:55.640 --> 00:42:59.380
You've gone through this whole experience of all these interviews.

00:42:59.380 --> 00:43:05.280
You even like were fairly retrospective or introspective about the process because you

00:43:05.280 --> 00:43:07.720
did this PyCon talk, which I'll link to in the show notes.

00:43:07.720 --> 00:43:13.160
So with all that, can you give people out there who may be looking for a job, like a couple

00:43:13.160 --> 00:43:14.160
of pieces of advice?

00:43:14.160 --> 00:43:17.800
What can you tell them to make it a little bit easier given what you've gone through?

00:43:17.800 --> 00:43:20.660
Don't be afraid to say no when you think that.

00:43:20.980 --> 00:43:24.860
Things may not be working out during any part of the interview process.

00:43:24.860 --> 00:43:27.300
And I know I have a list of no criteria.

00:43:27.300 --> 00:43:31.500
If you can be selective and feel free to do that.

00:43:31.500 --> 00:43:35.080
And also you don't have to go for like, say, 20 interviews in a week.

00:43:35.080 --> 00:43:36.620
Not a lot of people want to do that.

00:43:36.620 --> 00:43:40.940
So take your time and take breaks in between.

00:43:40.940 --> 00:43:46.020
Some people may get their first job at the first onsite or they may take a while.

00:43:46.020 --> 00:43:46.820
So it really depends.

00:43:46.820 --> 00:43:47.920
So it's really unpredictable.

00:43:47.920 --> 00:43:50.400
So be mentally prepared for this process.

00:43:50.400 --> 00:43:50.780
Yeah.

00:43:50.780 --> 00:43:52.260
So one more question, I guess.

00:43:52.260 --> 00:43:53.480
Like, how did you keep going?

00:43:53.480 --> 00:43:57.440
Like, how do you just not get really frustrated and go, ah, I'm just going to go work at a

00:43:57.440 --> 00:43:57.900
big company.

00:43:57.900 --> 00:43:59.840
I'm going to go do something different or change my plan.

00:44:00.380 --> 00:44:02.640
I really want to stay in San Francisco.

00:44:02.640 --> 00:44:07.180
So it's just, it's a really good place to be in terms of like the environment.

00:44:07.180 --> 00:44:08.260
And I really love the city.

00:44:08.260 --> 00:44:10.560
So that's something I want to keep going.

00:44:10.560 --> 00:44:12.100
And I didn't want to move back to New York City.

00:44:12.100 --> 00:44:12.980
Yeah.

00:44:12.980 --> 00:44:17.320
I guess it sounds like you were really clear about what your priorities were and that

00:44:17.320 --> 00:44:18.140
kind of helped guide you.

00:44:18.140 --> 00:44:18.520
Yeah.

00:44:18.520 --> 00:44:21.480
So I have like a pretty clear list of like certain days I'm looking for.

00:44:21.480 --> 00:44:26.080
And I was pretty excited when I found like a new company, a new product that I want to

00:44:26.080 --> 00:44:29.020
contact the people behind that product and talk to them about it.

00:44:29.020 --> 00:44:33.900
So that's something that kept me going because I like reading news articles and new product

00:44:33.900 --> 00:44:34.260
releases.

00:44:34.260 --> 00:44:38.880
So that's something, if there's like a new thing that gets me excited, yeah, that's, I want

00:44:38.880 --> 00:44:39.260
to talk to them.

00:44:39.260 --> 00:44:39.840
That's awesome.

00:44:39.840 --> 00:44:44.280
So thank you so much, Susan, for sharing your journey and congratulations on finding

00:44:44.280 --> 00:44:46.340
a place where you're happy after all this work.

00:44:46.340 --> 00:44:47.100
That's, that's excellent.

00:44:47.100 --> 00:44:47.380
Great.

00:44:47.380 --> 00:44:48.420
Thanks for having me.

00:44:48.420 --> 00:44:48.960
You're welcome.

00:44:48.960 --> 00:44:49.260
Bye.

00:44:49.260 --> 00:44:49.600
All right.

00:44:49.600 --> 00:44:49.780
Bye.

00:44:49.780 --> 00:44:54.200
This has been another episode of Talk Python To Me.

00:44:54.200 --> 00:44:56.780
Our guest this week has been Susan Tan.

00:44:56.780 --> 00:44:59.800
Are you or a colleague trying to learn Python?

00:44:59.800 --> 00:45:04.460
Have you tried books and videos that just left you bored by covering topics point by point?

00:45:04.460 --> 00:45:08.500
Well, check out my online course, Python Jumpstart by Building 10 Apps at

00:45:08.500 --> 00:45:13.100
 talkpython.fm/course to experience a more engaging way to learn Python.

00:45:13.100 --> 00:45:17.860
And if you're looking for something a little more advanced, try my Write Pythonic Code course

00:45:17.860 --> 00:45:20.420
at talkpython.fm/pythonic.

00:45:20.420 --> 00:45:23.140
Be sure to subscribe to the show.

00:45:23.140 --> 00:45:25.340
Open your favorite podcatcher and search for Python.

00:45:25.340 --> 00:45:26.580
We should be right at the top.

00:45:26.580 --> 00:45:32.700
You can also find the iTunes feed at /itunes, Google Play feed at /play and direct

00:45:32.700 --> 00:45:35.900
RSS feed at /rss on talkpython.fm.

00:45:35.940 --> 00:45:40.980
Our theme music is Developers, Developers, Developers by Corey Smith, who goes by Smix.

00:45:40.980 --> 00:45:45.680
Corey just recently started selling his tracks on iTunes, so I recommend you check it out at

00:45:45.680 --> 00:45:47.680
 talkpython.fm/music.

00:45:47.680 --> 00:45:52.100
You can browse his tracks he has for sale on iTunes and listen to the full length version

00:45:52.100 --> 00:45:53.020
of the theme song.

00:45:53.660 --> 00:45:55.100
This is your host, Michael Kennedy.

00:45:55.100 --> 00:45:56.400
Thanks so much for listening.

00:45:56.400 --> 00:45:57.580
I really appreciate it.

00:45:57.580 --> 00:45:59.720
Smix, let's get out of here.

00:45:59.720 --> 00:45:59.720
Smix, let's get out of here.

00:45:59.720 --> 00:46:21.720
Outro Music.

00:46:21.720 --> 00:46:21.960
you

00:46:21.960 --> 00:46:22.460
you