0:00

Welcome to Fall Through a

0:02

podcast about software, technology, and

0:04

computing. I'm your host, Chris Brando, also

0:06

known as scriptable, and on today's episode,

0:09

we are talking about whether we think

0:11

you should learn to code. Now you might

0:13

be thinking, Chris, I already code. Yes,

0:15

we're aware that most of our listeners

0:17

are people that are already well-versed in

0:19

coding, but this episode is not just

0:22

for you, it's also for those friends

0:24

and family members who come and ask

0:26

you. Should I learn to code? Should

0:28

I consider a career in this? Is

0:30

there any use in learning this for

0:33

me? This episode is a guide for

0:35

them and a guide for you, so

0:37

you can navigate those conversations. Now, don't

0:39

worry, there's still plenty of nerdery and

0:41

some really in-depth tangents because this is

0:43

fall through after all. And this is just

0:46

part one of a two-part series. In

0:48

the second part, we'll be talking with

0:50

a recruiter who has nearly 30 years

0:52

of experience. He's seen everything from the

0:54

dot-com boom and bust, to the Great

0:56

Recession, to you know, whatever happened in

0:58

the 2010s. We're super excited for that

1:00

episode as well, so make sure you

1:03

subscribe so you'll be notified when we

1:05

ship that. As always, I'm joined by

1:07

my wonderful panel of co-host that include

1:09

In Wester Lopsire, Matthew Sinabria and Dylan

1:11

and Dylan and Dylan Burke. Before we

1:13

get into the episode, I just want

1:16

to remind you that we are on

1:18

social media. You can find us pretty

1:20

much anywhere at Fall Through FM. And

1:22

if you want to see our lovely

1:25

faces instead of just hearing our lovely

1:27

voices, you can subscribe to us over

1:29

on YouTube. We would really appreciate

1:31

it. And with that, let's get into the

1:34

episode. Dylan. How are you doing today?

1:36

I'm doing well. Holidays were

1:38

relaxing, getting back into doing real

1:40

work now that we're into the

1:43

new year. Brand new year. It

1:45

feels the same as it did

1:47

last year. There's always that

1:49

challenge of everyone else took off

1:51

for the holidays. The new guy,

1:54

only two months in. So you

1:56

still, you got stuck there. You're

1:58

like, I gotta be here. free time

2:00

to do random things because I don't

2:02

have anyone to consult with because they're

2:05

all out on vacation. I love the

2:07

time when everyone else is out on

2:09

vacation. Like that last week before Christmas

2:11

I got so much done. Oh yeah.

2:13

It was I don't know it was

2:15

like meditative. It was great. No one

2:18

bothering you. The productivity. Not getting stuff

2:20

out. How are you doing? Good. Holidays

2:22

are great. I also have been at

2:24

my new job for about almost two

2:26

months and I also felt... weird taking

2:28

time off but I saw most people

2:30

were out and I just kind of

2:33

copied their out of office schedule and

2:35

I was like I guess I'm out

2:37

too. So it was good. It's a

2:39

good time. That's good. Yeah. Ian you've

2:41

been at the same job a while

2:43

so like yeah five years now. How

2:46

are you doing? I'm doing great you

2:48

know you're not the new guy. I

2:50

still didn't take much time off but

2:52

like I said I love that pre-holiday

2:54

time where no one's bothering you. Did

2:56

hurt my back over the break, so

2:58

I'm recovering from that and not great,

3:01

but we do what we can. Yeah,

3:03

it was, it's been an interesting few

3:05

weeks getting into this New Year. It

3:07

like snowed in Christmas for the first

3:09

time in a while in New York.

3:11

I was like, oh, and then it

3:13

was a crazy thunderstorm on New Year's

3:16

Eve in New York. And I was

3:18

like, oh, those poor people in Times

3:20

Square. Also, the fact you're in Times

3:22

Square is just annoying. So my dog

3:24

is terrified of fireworks but not bothered

3:26

by thunder at all. Oh, and so

3:29

it started like thunderstorming and he just

3:31

thought everything was thunder after that and

3:33

it was not nervous at all. It

3:35

was great. It should thunderstorm every new

3:37

year. The random fireworks in the street

3:39

like. Too much. Oh, they were they

3:41

were going until like 2.20 in the

3:44

morning by me and I was like,

3:46

what are we doing? Like, come on,

3:48

20 minutes after the New Year, fine.

3:50

Two hours? No, no, no. They went

3:52

till about 1.30 here. I've also reached

3:54

the age where we don't go out

3:57

and party. So I spent New Year's

3:59

Eve on my sofa with my dog

4:01

under my feet cowering in fear from

4:03

Armageddon happening. outside. Y'all should have had

4:05

a thunderstorm. I would have solved everything.

4:07

No, I definitely stayed home because you

4:09

have people. Oh, my friends were like,

4:12

oh, you're not going to go out?

4:14

And I'm like, no, too much proximity

4:16

to Midtown. I don't want to be

4:18

out and have to go near a

4:20

train station that is in or around

4:22

Times Square. Just like, no, thank you.

4:25

Like, I'm good. Maybe if I love

4:27

another borough of another borough, I'd be

4:29

fine. For like uptown. for being in

4:31

Manhattan night. I'm like, now I'm gonna

4:33

stay inside. Unless I got like, had

4:35

a party in my place and like

4:37

I got more drunk or something like

4:40

that, then maybe I'd be out and

4:42

about. But I was just like, now

4:44

I'm just gonna sit here, just ring

4:46

in the new year, chilling on my

4:48

couch. It was nice. So on today's

4:50

episode, we are talking about whether we

4:53

think you should code. And this is

4:55

part one of a two-part mini series

4:57

if it's only two episodes two episodes.

4:59

I mean, we will have a follow

5:01

up. It's a dual half. Yeah, it's

5:03

the first half. It's a dual two-part

5:05

episode, I guess. Two episode, two episode

5:08

series. Ah, we'll call two episode series.

5:10

That's first act. First act of a

5:12

two-act. Podcast. Episode. Thing. Yes. Naming. One

5:14

of those tough things in our industry.

5:16

So yeah, anyway, this is part one

5:18

of part of two parts, where we're

5:20

going to be talking about coding and

5:23

careers in coding and all of that.

5:25

And in this episode, we're going to

5:27

be talking about, do we think you

5:29

should code? Or do we think you

5:31

should learn how to code? And so

5:33

before we jump into that, we're going

5:36

to talk about why we decided to

5:38

learn how to code. So who wants

5:40

to go first? Who wants to tell

5:42

their little short story about why they

5:44

learn to code? I feel like you

5:46

never go first. So maybe you should

5:48

go first. That's true, Chris. Put you

5:51

in the, put you in the seat.

5:53

Sure fine okay you're always so kind

5:55

you're like you know you let it

5:57

let the round robin go and you're

5:59

his last one so we can start

6:01

with you proper host to you okay

6:04

so yeah I I come from a

6:06

household of programmers my mom was a

6:08

programmer for a decade my dad is

6:10

to this day a software engineer low-level

6:12

software engineer so I kind of grew

6:14

up with the kind of ethos of

6:16

like lots of computers lots of tech

6:19

going on in my house so I

6:21

first learned to code when I was

6:23

13, I want to say. That's why

6:25

I forgot my first programming book. And

6:27

I took, you know, permanent courses in

6:29

high school, never really got any of

6:32

it. So I was like, I'm not

6:34

going to do this. And then when

6:36

I was in college, we had this

6:38

thing where I need to build a

6:40

website. And I was like, you know

6:42

what? I think I have enough skills

6:44

to build a website. So I learned

6:47

how to build a website. And I'm

6:49

like, I kept doing it and kept

6:51

doing it and kept doing it. went

6:53

to graduate and I was like I

6:55

have career opportunities and I was like

6:57

I think I want to learn how

7:00

to code I think I want to

7:02

be a programmer let's try this out

7:04

and I sat down and I learned

7:06

how to actually write PhD instead of

7:08

just quaboring together random snippets of code

7:10

I found on the internet and I

7:12

just kind of kept going from there

7:15

I never really stopped from that point

7:17

so I think the decision was mostly

7:19

like I need a job and I

7:21

need a career and I felt like

7:23

programming software engineering was the career that

7:25

at the moment felt like the best

7:27

fit for me. So that's why I

7:30

learned a program. I had no idea

7:32

that both your parents were programmers. Yeah,

7:34

that's awesome. Yeah. I come from a

7:36

programmer from a computing lineage I guess.

7:38

I have like some aunts and uncles

7:40

that were also computer people. I think

7:43

I come from the opposite end of

7:45

that. My dad was a school bus

7:47

mechanic and my mom was a school

7:49

bus driver. There was... yeah, I don't

7:51

know where to go from there. But

7:53

I learned to code first because I

7:55

thought I wanted to be like a

7:58

designer. Maybe like... a front end developer.

8:00

So I learned HTML and CSS, you

8:02

know, and probably like 13 or 14

8:04

started putting together websites. At one point

8:06

I had my own e-commerce store that

8:08

I used to pay for college, which

8:11

was pretty cool. But I did find

8:13

out I was a garbage designer, but

8:15

I was pretty good at the coding

8:17

part. And I just found it a

8:19

lot of fun. I picked up a

8:21

PhD book at a garage sale and

8:23

kind of went from there. And then

8:26

I got to college and I did

8:28

not want to. do software engineering as

8:30

a job. It was like one of

8:32

my favorite things to do. So I

8:34

kind of wanted to keep it as

8:36

a hobby, right? Like I had that

8:39

naive idea that if I made it

8:41

a career, I would not like it

8:43

anymore. And so far that hasn't happened,

8:45

so I'm good. But so I went

8:47

to school for math. Just ended up

8:49

falling into a computer science internship and

8:51

just haven't looked back. I finally got

8:54

into doing it professionally and it professionally

8:56

and I just haven't stopped since. But

8:58

I do love it, so. I guess

9:00

I also sort of fell into it.

9:02

First, learn a code in middle school.

9:04

We had a program where we got,

9:06

they called it the Talented and Gifted

9:09

Program. They replaced our English class and

9:11

we got to do advanced grammar, but

9:13

because we were skipping ahead, we also

9:15

got to play around with art and

9:17

music and computers. So I got to

9:19

play on a Radio Shack, TRS TRS,

9:22

T. took Pascal in high school and

9:24

actually went to college for mechanical engineering.

9:26

I was convinced I was going to

9:28

be a rocket scientist and build spaceships

9:30

for NASA. Fast forward three and a

9:32

half years and several Ds and drops

9:34

in thermodynamics and fluid dynamics and I

9:37

needed to do something else. For about

9:39

a year before then, I had been

9:41

working as a lab monitor. and the

9:43

Petroleum Engineering Department at LSU, basically helping

9:45

people come and figure out why they

9:47

can't protect their Word document. But they

9:50

were doing a project across the hall

9:52

and they needed some help coding and

9:54

I was capable because I don't... done

9:56

it as kind of a background hobby.

9:58

So when I needed to change majors

10:00

I was like oh I should give

10:02

this computer science thing of a world.

10:05

And three semesters later I graduated with

10:07

a computer science degree. Started off fixing

10:09

Y2K bugs and spent a long time

10:11

in health care and various other places

10:13

and here I am. So it's I

10:15

was never big on the hobby project

10:18

side of it. Past... being a teenager.

10:20

So it's always been a professional thing,

10:22

but at the same time, it's always

10:24

fun to learn the new things and

10:26

keep up with the industry and find

10:28

new problems to solve. I think that

10:30

puts it on to me then. Much

10:33

like Ian, I kind of didn't have

10:35

parents for that, right? Like opposite of

10:37

Chris. My parents were as far away

10:39

from technology as you can possibly imagine.

10:41

In fact... only one of them actually

10:43

graduated high school. And so like my

10:46

my siblings and I were the first

10:48

like generation of college kids in our

10:50

in our family, which is cool. But

10:52

I had no idea what I wanted

10:54

to do heading into college. Right? Like

10:56

growing up, our first computer was like

10:58

some Delaware gateway maybe running like XP

11:01

or something. And I was like, I

11:03

don't know what this is. You can

11:05

use AOL. Great. Okay. So I can

11:07

just chat with my friends on AOL.

11:09

That's all I really did with my

11:11

friends on AOL. That's all I really.

11:13

What should I do? And this was

11:16

around a time when Iron Man was

11:18

like coming out, right? And I was

11:20

like, oh, I'll be a mechanical engineer,

11:22

I'll be Iron Man. That's what I'm

11:24

going to do. And my friend convinced

11:26

me to play video games on a

11:29

computer. He's like, hey, you should build

11:31

a computer, go to microcenter, and build

11:33

a computer, and play games. I was

11:35

like, you can do that? You can

11:37

actually play games on the computer, no

11:39

way. And that's kind of what got

11:41

me using using computers, using computers, using

11:44

computers, using computers, using computers, using computers,

11:46

more, word of the time, like you

11:48

can get a degree in IT and

11:50

you can make money and da da

11:52

da. So I was like, oh, I

11:54

guess I can do that. And I

11:57

went to college for IT. And what

11:59

brought me to like coding was I

12:01

hated my coding class in college. I

12:03

hated it. I was like, Java, what

12:05

is this? Like, is this an outprint

12:07

line? What? No, no. public static void

12:09

mean? No, no, I'm good. But as

12:12

I like got into the industry and

12:14

used more like computers, I started to

12:16

realize like, oh, there's layers to this

12:18

stuff and the things that I'm using

12:20

to do my job are written in

12:22

in programming languages. Like it's software under

12:25

the hood. So if I wanted to

12:27

get better, I should learn what's underneath.

12:29

And that's how I kind of went

12:31

into the coding aspect. It's one of

12:33

the things that always strikes me how

12:35

separate like the IT side of I

12:37

mean, like, I guess I kind of

12:40

just popped on my head that not

12:42

only were both my parents' software people,

12:44

they met in college studying computer science,

12:46

like that's what they were both studying.

12:48

That's what they were both studying. That's

12:50

awesome. But also my dad from a

12:53

very young age was just like, yeah,

12:55

that's awesome. But also my dad from

12:57

a very young age was just like,

12:59

yeah, this degree doesn't mean anything anymore,

13:01

so don't get one. Like, there's no.

13:03

with building computers and always having multiple

13:05

computers, which I think people in their

13:08

minds usually equate these two things together.

13:10

They're like, oh, if you're a software

13:12

person, then you must be really good

13:14

at computers. And I remember a few,

13:16

I guess this was a while ago

13:18

now, at one of my previous jobs,

13:20

where it's a whole bunch of very

13:23

smart software engineers, people are very competent

13:25

in building things. one of them wanted

13:27

to upgrade their their SSD and their

13:29

computer. They wanted more space for something,

13:31

I wanted a faster drive. I don't

13:33

remember what it was. But I was

13:36

talking about IT guys, like, oh yeah,

13:38

I brought it over to this person,

13:40

and I handed it to them, and

13:42

they just looked at me, and the

13:44

guy was like, oh, do you want

13:46

me to install this for you? And

13:48

they were like, yes, please, because they

13:51

didn't know how to put a hard

13:53

drive in a computer, which is like,

13:55

which is like, like, like, just because

13:57

you can build software doesn't mean you

13:59

know how computers work or how to

14:01

put one together or anything like that.

14:04

I mean, Chris, you work on computers,

14:06

can you come and fix my printer?

14:08

My smartphone's out there, please. Well, I

14:10

mean, there's that too. And it's like,

14:12

I mean, no one can fix your

14:14

printer. It's a demon machine. And we

14:16

keep them in dark places for reasons

14:19

because we don't want them to, you

14:21

know, you're worried about AI. We're all

14:23

worried about our printers and what they

14:25

might do. Oh, yeah. I do work

14:27

with computers. I do not work on

14:29

computers. Yeah. Yes, but I think that's

14:32

like an important thing, listener, if you're

14:34

like, oh man, I'm sort of interested

14:36

in like, maybe doing some coding or

14:38

anything, but I don't, I don't know

14:40

how to like put a computer to

14:42

go, I don't know what a hard

14:44

drive, it's like, you know, you don't

14:47

really need to know that stuff to

14:49

get started, like if you can't build

14:51

your own custom PC, you're fine, you

14:53

can learn to code, you don't need

14:55

to know that stuff to be, Java

14:57

and Python. So I learned to code

14:59

in college in C. Mm. I wish

15:02

I would have learned C instead of

15:04

Java. That would have been probably more

15:06

interesting because I like to be closer

15:08

to what's happening. You definitely, and even

15:10

then, C was tricky to learn once

15:12

second year I took assembly, like four

15:15

loops and pointer arithmetic became very easy.

15:17

once you can write it in a

15:19

simpler. Like, okay, now I understand what

15:21

the machine is doing, so it's no

15:23

longer tricky to figure out what this

15:25

nasty expression with parentheses and stars and

15:27

ampersands is doing. Perhaps they didn't offer

15:30

it on my degree track, because I

15:32

took an IT degree in college rather

15:34

than a CS degree, because that was

15:36

the term that I was hearing more.

15:38

I didn't know computer science, like, what

15:40

it really was at that time. But

15:43

the IT degree covered zero assembly. It

15:45

was just like Java. And there was

15:47

like a MAT lab course because some

15:49

reason, but it just was Java. And

15:51

I was like, looking back, I'm like,

15:53

we didn't really touch how this stuff

15:55

actually works under the hood. I saw

15:58

Java in the history of computer languages.

16:00

class, but all of my coursework was

16:02

in C and X86 similar and C++.

16:04

Yeah. I want to go back to

16:06

the point Chris was getting at where

16:08

you don't need to know how to

16:11

build a computer or whatnot to code,

16:13

right? And it's true. And I've seen

16:15

this. This maps pretty well to other

16:17

professions too, right? You don't really need

16:19

to know how the car is perfectly

16:21

built or whatever to be a good

16:23

race car driver and train for that.

16:26

It doesn't matter if you. can take

16:28

apart the engine or change tires or

16:30

whatever, that doesn't matter. You can suck

16:32

at that as long as you're a

16:34

good race car driver. And similar in

16:36

coding, like you don't have to know

16:39

exactly how the hardware and everything works

16:41

under the hood, it can help you

16:43

obviously be better and be more efficient.

16:45

But it's not like a hard requirement

16:47

where it's like, I couldn't put rem

16:49

and ram slot. I'm a failure. It's

16:51

like, no, you're not a failure, okay?

16:54

It's okay, I swear. It's like USB

16:56

plugs, turn it around. It still doesn't

16:58

work, turn it around again, and now

17:00

it'll be fine. Yeah. Although the new

17:02

version of that is, what does this

17:04

USB cable have support? Does it do

17:06

charging? Does it do fast charging? Does

17:09

it, I think, what's it gonna, is

17:11

it a thunderable cable? Is it not

17:13

like what? You're so not wrong, I

17:15

literally had to buy a specific down

17:17

the roll-for cable for this device I

17:19

had, and I was like, and I

17:22

was just, I went down the rabbit

17:24

hole of standards, and I was like,

17:26

why, where did, okay, never mind, purchase,

17:28

purchase. You're not universal, universal serial bus.

17:30

You're like, oh, why is this thing

17:32

cost $70? And then you like, I

17:34

actually look at the tech inside, you're

17:37

like, like, oh. It's really impressive. I

17:39

feel like that's quite a bit like

17:41

how like different programming languages and things

17:43

of like what what is this language

17:45

supposed to be used for how is

17:47

this supposed to work and I feel

17:50

like that's like so much of the

17:52

time people want to pigeonhole like I

17:54

guess like I'm trying to say like

17:56

in the old days right you have

17:58

like specific cables that you use for

18:00

specific things like a huge Java one

18:02

thing and you'd use maybe objective C

18:05

for another and C for another and

18:07

C plus plus for another and I

18:09

feel like all of that has now

18:11

gone away and now it's just like

18:13

all of these languages can pretty much

18:15

do everything every other language can do

18:18

and I feel like that causes a

18:20

lot of confusion for people that do

18:22

like want to learn how to code

18:24

and want to get into this industry.

18:26

Do you mean confusion of like where

18:28

to begin? Yeah, like where to begin

18:30

or even like I feel like it's

18:33

easy to get nerd-snipes into like language

18:35

wars like language wars have always been

18:37

around but like I mean you're not

18:39

going to build an operating system in

18:41

PhD right so it's like there there

18:43

were things that were just like no

18:46

of course you're not going to use

18:48

this tool for that so the if

18:50

you like the the breadth of nerd

18:52

snipey things which is much smaller you

18:54

know like back in the day it

18:56

was like them and E Max and

18:58

now it's just like I still see

19:01

a lot of I'm new to this

19:03

looking to get into a career in

19:05

programming, what's the best way to learn,

19:07

go, or rust, or whatever the thing

19:09

may be, and kind of to your

19:11

point. Maybe that's not the best thing

19:13

at all. Don't go into it thinking,

19:16

I want to learn language acts. It's

19:18

more, I want to solve a problem.

19:20

Yeah, it's usually the advice is, the

19:22

best way to learn whatever language you're

19:24

diving into is to go. Think of

19:26

a problem you have that you know

19:29

how to solve and go solve it

19:31

with that language. Yeah, or probably mean

19:33

you don't know how to solve and

19:35

then go figure out, you know, what

19:37

do I need to solve it? Yeah.

19:39

Yeah, or explore the space in that

19:41

language and you'll learn it as a

19:44

side effect rather than going in with

19:46

the idea of, I'm going to go

19:48

learn, go. Yeah, counterpoint to that though,

19:50

like... Say I'm just getting started in

19:52

software and I'm like, I don't even

19:54

know if I like programming yet, you

19:57

know, I'm trying to learn. And if

19:59

I pick up rust, I'm probably gonna

20:01

hate programming, right? Or you're gonna love

20:03

it. Rust as your first language seems

20:05

difficult. Maybe I'm wrong, right? But picking

20:07

up something like, even like Java might

20:09

make more sense, right? Yeah, I feel

20:12

like Rust is not a great gateway

20:14

drug. But I feel like there are

20:16

a decent amount. Like, say you pick

20:18

up Java and you're trying to solve

20:20

a problem and you hate it. Do

20:22

you think switching to go or PhD

20:25

is gonna change that? Is giving one

20:27

a solid go enough to decide if

20:29

you like programming or not? Maybe not,

20:31

because there are some drastically different paradigms

20:33

as well. Like solving a problem in

20:35

go is a vastly different exercise than

20:37

solving the same problem in a dynamic

20:40

language like Python or JavaScript. I mean,

20:42

for me, right, if I look at

20:44

my own journey of how I became

20:46

a software person. But I learned to

20:48

program when I was younger. My first

20:50

programming book was like a program for

20:53

numbies and I'm telling you Q Basic.

20:55

So I did that. And I was

20:57

just like, oh, this is cool. You

20:59

can make the computer do things. Then

21:01

I just kind of lost interest in

21:03

it. And then in high school, I

21:05

learned to make the computer do things.

21:08

Then I just kind of lost interest

21:10

in it. And then in high school,

21:12

I learned C and C and C

21:14

and C plus plus. And I was

21:16

really good. that I needed to do.

21:18

When I was like, I got to

21:20

build a website. Or I think like

21:23

the very first website I built was

21:25

there was this whole thing we did

21:27

at the TV station on campus where

21:29

we'd have like these movies. We did

21:31

this thing called Moving Marathon. People would

21:33

vote. And I built a little web

21:36

app to allow people to vote online.

21:38

And I just kind of cobbled that

21:40

together with a bunch of PhD. And

21:42

I was like, OK, this is cool.

21:44

And then even more to that point,

21:46

like the first time I tried to

21:48

pick up go was like super early

21:51

in my career and it was just

21:53

kind of like, I don't understand this,

21:55

like I don't understand what this is,

21:57

this syntax looks weird to me, what

21:59

does this colon equals thing, this makes

22:01

them sense, and like put it immediately

22:04

back down and went back to PhD.

22:06

And it wasn't until I had a

22:08

problem that go fit more of like

22:10

my desire. to have more simplicity instead

22:12

of so much complexity, that I was

22:14

able to pick go back up and

22:16

be like, oh no, this is beautiful,

22:19

this is exactly what I wanted. So

22:21

I think, especially when it comes to

22:23

programming languages, you need to have a

22:25

problem you're trying to solve before you

22:27

try and learn the language. I think

22:29

if you just try and learn the

22:32

thing, you're going to have a much

22:34

rougher time than if you have a

22:36

specific thing you're trying to do. And

22:38

I think you should have multiple things

22:40

over time. you're going to be able

22:42

to guide yourself properly. Finally you mention

22:44

colon equals because for me that was

22:47

a throwback to learning turbo Pascal in

22:49

high school where you also had allocate

22:51

and assign via colon equals. Chris I

22:53

kind of think your point leads well

22:55

into something I've been thinking about which

22:57

is you're saying you need to have

22:59

that problem to solve with the programming

23:02

language you're learning but like to me

23:04

the programming language is the tool not

23:06

the skill right like like you don't

23:08

if you want to get good at

23:10

Digging holes, you don't learn shovel, right?

23:12

You. That's the worst example I've ever

23:15

made, you know. No, that's a great

23:17

example. Especially with the internet memes of

23:19

like, be the one selling shovels. That's

23:21

spot on. The question should you learn

23:23

to program isn't the one. It's like,

23:25

do you want to solve problems? Should

23:27

you learn this tool to solve problems?

23:30

Right. But I think that, you know,

23:32

in that analogy you made, I think

23:34

there's a little hidden thing of like,

23:36

like, you're trying to. Learn how to

23:38

dig holes. And it's like, okay, shovel

23:40

is good for small holes. But if

23:43

I want to make a big hole,

23:45

then I need like a backo. So

23:47

I should probably like, maybe sometimes need

23:49

a shovel, sometimes I need a backo,

23:51

sometimes I need a drill of some

23:53

sort, right? Like what type of thing

23:55

you might try to do and you

23:58

learn this collection of tools, you can

24:00

put in a toolbox and then you

24:02

can use those. And I think that's

24:04

the same thing in programming and programming.

24:06

Or in. coding or software building in

24:08

general. It's like, don't just learn a

24:11

tool. Learn a tool for a type

24:13

of problem you're trying to solve. And

24:15

then you'll also be able to find

24:17

other tools that will help you actually

24:19

solve that problem. different levels. I've always

24:21

had this this mental image. First two

24:23

summers out of high school I worked

24:26

framing houses as a carpenter and did

24:28

some amateur woodworking for the next few

24:30

years and I kind of have this

24:32

mental image of woodworking jigs. It's like

24:34

I'm trying to make a thing and

24:36

you have all these various power tools

24:39

but you also have these various jigs

24:41

and setups and things that you put

24:43

together and it's like, oh, here's how

24:45

you make a door. You use this

24:47

thing and you cut it this way

24:49

and then you put it over here

24:51

and you use the router to round

24:54

over the edge and it's assembling all

24:56

these different tools and other pieces that

24:58

you've built over the years and have

25:00

in your toolbox to go make a

25:02

thing. And the toolbox is the language,

25:04

the libraries that you've learned. That's kind

25:06

of like Ian said, it's beside the

25:09

actual problem of I'm trying to do

25:11

a thing. It's funny you say that

25:13

as a hobbyist woodworker I think programming

25:15

and working are super analogous because it's

25:17

like it's not just oh I need

25:19

to make use this saw to make

25:22

this cut I need to make this

25:24

tool to make this saw that can

25:26

cut a straight line it's like the

25:28

same type of thinking I'm trying to

25:30

think of a good way to describe

25:32

that but if you like that type

25:34

of thinking you should you should learn

25:37

to code because you can put it

25:39

on I don't know there are definitely

25:41

a lot of parallels and a similar

25:43

mental pathways Yeah. I feel like there's

25:45

a lot of people that do programming

25:47

that wind up doing woodworking as like

25:50

a fun side hobby. Like, oh, I

25:52

actually want to work with my hands.

25:54

And then you just, yeah, why they're

25:56

doing woodworking? It really does end up

25:58

being like the same type of thinking.

26:00

It's like process, like order of operation.

26:02

How do I, what do I need

26:05

to cut first? You know, you have

26:07

to, like that same creative mind mapping

26:09

that you do when you program, you

26:11

have to do for woodworking. Congratulations, you've

26:13

just made a library. You are learning

26:15

to code. Yeah, congratulations, check. You're already

26:18

on the path. Yeah, and to answer

26:20

the question you asked way earlier in

26:22

about, is one language enough to like

26:24

know if you want to code? I

26:26

personally say no, because like if it

26:28

was up to me and I just

26:30

stuck with Java, I didn't like it,

26:33

right? And that was, that turned me

26:35

off. But I tried other languages, right?

26:37

I tried C. I looked at Python.

26:39

I even looked at scratch for a

26:41

little bit because I was like looking

26:43

at, okay, what does this even, what's

26:46

this logic? for me. And that kind

26:48

of got me back into it. And

26:50

that's what kind of jump started me.

26:52

So if I gave up just that

26:54

Java, I probably wouldn't be here today,

26:56

right? I wouldn't, like, here in this

26:58

podcast doing this thing, because I wouldn't

27:01

be in software, probably. To me, it

27:03

was never a language that drew me

27:05

into software. It was always that, like,

27:07

problem solving. Like, a lot of the

27:09

early stuff, like, something I did early

27:11

was make Yahoo Messenger messenger skins, right?

27:13

And it's like that, it's always like

27:16

that same type of thinking as like,

27:18

how do I make this happen? How

27:20

do I solve these problems? Yeah, I

27:22

love go, but I kind of enjoy

27:24

programming in whatever language I have to,

27:26

right? I've been doing a lot of

27:29

like Python and like Apache Spark, and

27:31

even that like scratches that same itch,

27:33

right? So to me, if you have

27:35

that itch, all right, you should learn

27:37

to program. I think my first kind

27:39

of carrot of carrot of, oh, this

27:41

is really cool graphics graphics in logo.

27:44

way back when like go forward 100

27:46

yeah you're gonna have to explain both

27:48

of those things for for at least

27:50

me. Turtle graphics is the idea you

27:52

have this little cursor and you move

27:54

it around the screen and it draws

27:57

a line as it moves and logo

27:59

was this logic language it would amount

28:01

to move forward 80 units turn right

28:03

25 degrees move forward this many units

28:05

turn left this many degrees and you

28:07

kind of wait I can write this

28:09

code and out pops a flower. At

28:12

the time I was in middle school

28:14

like 10-11 years old so like this

28:16

was an amazing thing. Wow I can

28:18

make the computer. The coolest spirograph ever.

28:20

Yes, I can make the computer do

28:22

things. We did spirographs like, what happens

28:25

if I just move forward and then

28:27

right turn one degree forever? Because it

28:29

would just cycle around the screen and

28:31

you would get these various patterns popping

28:33

out and it was like, that was

28:35

a cool thing. What else can I

28:37

make it do? That's kind of similar

28:40

to my idea is the curiosity. Like

28:42

what else is there? Or what's behind

28:44

this? Like what more is there? That's

28:46

what drove me. I didn't always have

28:48

a problem to solve that led me

28:50

to software, but I did have a

28:52

curiosity. I was like, how the heck

28:55

is this doing the thing that it's

28:57

doing? I've used that perspective to dive

28:59

into software. I feel like that's the

29:01

thing. So, you know, I think a

29:03

lot of people have asked me, like,

29:05

how did you, like, ascend to, like,

29:08

you know, such a short period of

29:10

time to, like, a high level within,

29:12

like, in the engineering field? I don't

29:14

know, not a lot of people become

29:16

like... How are you god-tier, Chris? What

29:18

did you do? How did you become

29:20

a principal engineer before 30? It's like,

29:23

like, I just found the answer. learning

29:25

how like so much more actually works

29:27

so then when it comes time when

29:29

it oh there's a problem and it's

29:31

like oh yeah that's how that thing

29:33

works this thing looks like x y

29:36

z and you can explain it to

29:38

everybody because you just found it on

29:40

your path traversing through a bunch of

29:42

other stuff and then everybody in the

29:44

rooms just like oh well you know

29:46

way more than anybody else here like

29:48

that's that's crazy but it comes from

29:51

that like that curiosity and that need

29:53

to understand I think it's Almost clinical

29:55

drive to not stop until I find

29:57

that thing that I'm looking for right

29:59

like guilty guilty That's the like obsessive

30:01

brain. Yes That does that has served

30:04

me very well because like you're saying

30:06

it's like your teams handed this project

30:08

that has this one little thing you

30:10

need to fix and you end up

30:12

doing a deep dive into it and

30:14

all of a sudden you know everything

30:16

about it and everyone's like well how

30:19

do you know how this works and

30:21

it's like well you know there was

30:23

that one thing wrong and I couldn't

30:25

stop until I knew everything so well

30:27

I pull the thread and it fell

30:29

over so then I had to put

30:32

it back together. Yeah computers they're just

30:34

gonna do what they're told to do

30:36

and at some point down the stack

30:38

something is responsible for making this thing

30:40

do whatever it's doing and I'm gonna

30:42

find it. I can't even count the

30:44

number of times I've used that quote.

30:47

How did you figure this out? It's

30:49

like, well, computers are dumb. They do

30:51

exactly what you tell them to do.

30:53

So if there's a problem, it's not

30:55

because your computer's broken. It's because there's

30:57

some instruction that you gave it somewhere

30:59

that it interpreted literally and then went

31:02

off on a tangent and did the

31:04

wrong thing. So to reiterate the curiosity

31:06

thing, it's... Where is the thing that

31:08

I put in wrong? How do I

31:10

follow the thread to find the thing

31:12

that caused it to go off the

31:15

rails? I want to answer the question,

31:17

do we think we should learn to

31:19

code? But before we actually answer that

31:21

question, we've been talking about like, learn

31:23

to program, learn to code, languages, this

31:25

problems, curiosity. What do you all mean

31:27

when you say learn to code? Like,

31:30

learn a language to hello world, check,

31:32

or like what do we mean? What

31:34

do we mean? when we say this.

31:36

Even better, what do we mean by

31:38

the word code? That's fair. When I

31:40

see Should You Learn to Code, my

31:43

mind immediately goes to like, should I

31:45

make a career in software engineering, right?

31:47

I don't think it's just like, oh,

31:49

I can dabble with JavaScript, right? I

31:51

don't think it's just like, oh, I

31:53

can dabble with JavaScript and like mess

31:55

around with things. But I don't think

31:58

that's what it means to learn to

32:00

learn to code. Maybe I'm showing my

32:02

curmudgeonness. a bit, but I always got

32:04

an Ick from the idea of learn

32:06

C++ in 21 days or like the

32:08

crash course. It's like, no, there's much

32:11

more to it than that. So learning

32:13

to code is to me, learn to

32:15

code has always had this connotation of

32:17

kind of similar to what she said,

32:19

E, and where it's like, hey, take

32:21

this crash course and you too can

32:23

be a software engineer. So it's always

32:26

kind of rubbed me. the wrong way

32:28

because it's like there's much more to

32:30

it than just learning to code. Yeah

32:32

I mean I think I mean of

32:34

course this is going to be my

32:36

answer but I kind of see you

32:39

know the word code there in the

32:41

same way that I see the word

32:43

writing or that I see math, right?

32:45

You know, should you learn to write?

32:47

Should you learn math? I think the

32:49

answer to that is obviously yes. Like

32:51

the way I think everybody should be

32:54

able to write, like, yeah, you should

32:56

be able to, like, put together an

32:58

email or, like, write a tweet. Like,

33:00

I think you should be able to,

33:02

like, put together an email or, like,

33:04

write a tweet. Like, I think, the

33:06

people I think the vast majority of

33:09

people in this world that are programmers

33:11

are people that can put together Excel

33:13

spreadsheets because that is programming like you

33:15

sit down and watch people build spreadsheets

33:17

that is absolutely programming and it's like

33:19

do I think you should be able

33:22

to do Excel professionally, I'd be like

33:24

absolutely. I think spreadsheets are extremely helpful

33:26

in basically every industry in pretty much

33:28

every job unless it's like very very

33:30

like, you know, I go into a

33:32

factory, I do a thing, I go

33:34

home at the end of the day,

33:37

if your job isn't that type of

33:39

thing, I think, yeah, Excel spreadsheets are

33:41

going to be very helpful for you.

33:43

So I think it's there's like levels

33:45

of it, but it's like do I

33:47

think everybody should be a professional software

33:50

developer? Like do I think it should

33:52

be your job to build software for

33:54

other people? I think probably not, but

33:56

I think that's like much higher on

33:58

the level of things for me. I

34:00

think there's like different tiers. I think

34:02

the lower two tiers are like, yes.

34:05

And I think all of that is

34:07

learning to code at the end of

34:09

the day. Yeah, I actually, you bring

34:11

up the Excel thing. Like I think

34:13

learning how to program in Excel is

34:15

probably the like, as far as like

34:18

the learning to code ethos. That's probably

34:20

the single easiest thing you can do

34:22

and get the most bang for your

34:24

buck, right? Well, I don't know about

34:26

easy, but it's easier than learning a

34:28

language, but you still. get a lot

34:30

of that functionality, you still start learning

34:33

how to think in the way, like

34:35

that very structured way. I would say

34:37

learning Excel is learning to code in

34:39

the non-career way. As far as ROI,

34:41

learning Excel is probably your biggest bang

34:43

for the buck also, because even if

34:45

you're in something fair, super artistic, like

34:48

you do abstract art, you still can

34:50

use Excel to go do invoices and

34:52

Like you said, track your bills, track

34:54

your spending, project how much money are

34:56

you going to have after six months.

34:58

And those things are still coding in

35:01

a sense that, like Ian said, you're

35:03

learning to break down a larger problem

35:05

and do calculations and assemble parts together.

35:07

So you're coding in a sense without

35:09

actually, compared to learning rust. Or learning

35:11

X86 is simpler. Those are different animals.

35:13

Both are coding. So I guess I'll

35:16

concede, yes, you should learn to code

35:18

in that you should learn enough to

35:20

be able to do your monthly bills

35:22

in a spreadsheet if that's something that's

35:24

convenient to you. You know, I feel

35:26

like I want to push back on

35:29

the idea that like Excel is easier

35:31

than other programming languages. I think Excel

35:33

is is hard. Right. I think it's

35:35

because you know, other one to call

35:37

it easier. I would call it more

35:39

accessible. Yeah, I think the barita entry

35:41

is lower. Yeah, I think it's like

35:44

if you look at the, I mean,

35:46

A, A. There's a whole, like people

35:48

give talks, and I think there's even

35:50

competitions about the ridiculous things you can

35:52

do with Excel, with the ridiculous things

35:54

you can model and build and create,

35:57

and you're like, how can you even

35:59

do that? That doesn't make any sense.

36:01

There's a lot of magic and declarative

36:03

programming that I absolutely love. I specifically

36:05

want to say that Excel is harder

36:07

than programming languages, because I think that...

36:09

framing it that way makes it more,

36:12

makes other programming languages more accessible to

36:14

people. Right, like I think imperative programming

36:16

languages are easy for a lot of

36:18

people to understand how they work, because

36:20

it's just this thing, then this thing,

36:22

then this thing, then this thing, then

36:25

this thing, then this thing, then this

36:27

thing, then this thing, then this thing,

36:29

then this thing, then this thing, then

36:31

this thing, then this thing, then this

36:33

thing, then this thing, then this thing,

36:35

and this thing, and this thing, and

36:37

this, and this. distributed systems thinking or

36:40

even like large systems thinking that I

36:42

think like learning a imperative programming language

36:44

probably doesn't give you. So I just

36:46

want to like kind of push that

36:48

idea down a little bit more to

36:50

people that are considering doing this of

36:52

like if you're really good at Excel,

36:55

you're probably going to be really good

36:57

at building software in general. And don't

36:59

be discouraged because you're like, oh, it's

37:01

just Excel, it's not something that's like

37:03

that important or that hard. It's like,

37:05

no, it is hard. There's a lot

37:08

of good skills you learn in how

37:10

to build a good spreadsheet and how

37:12

to model and make a good spreadsheet

37:14

that are applicable to the rest of

37:16

software development. So like hard and easy

37:18

are probably not the ways to quantify

37:20

it. to go and learn rust or

37:23

C++ plus. Like you have to invest

37:25

a lot more time to get something

37:27

concrete and practical out of it. Yeah,

37:29

I would say like if, like I

37:31

think the people that should learn to

37:33

code, like it should, do I think

37:36

people to learn to code? I'm like,

37:38

if there's problems in your life that

37:40

you're trying to solve and you can

37:42

figure out how to solve them with

37:44

code, then yes, please get a learn

37:46

to code. It's like I was even

37:48

doing some stuff with Excel or the

37:51

unknowing almost like Excel numbers like numbers

37:53

is just I need to actually get

37:55

Excel because numbers are driving me crazy.

37:57

Mac users make me outing themselves already.

37:59

I need I need I need Excel

38:01

so bad. But anyway I was doing

38:04

a whole bunch of stuff and just

38:06

the amount of things you can get

38:08

in a CSV format is just truly

38:10

crazy right you can go to like

38:12

like I got all of my Uber

38:14

Eat's orders from in a CSV. I

38:16

got all of my Amazon orders in

38:19

a CSV. And then you can take

38:21

that CSV and dump it into Excel

38:23

and then you can go do a

38:25

whole bunch of other stuff to like

38:27

pull that information and put it on

38:29

other things and then display and aggregate

38:32

and do all this that just made

38:34

the thing I was doing so much

38:36

easier than if I had to like

38:38

look at some web interface or create

38:40

the web interface. Very large segments of

38:42

society operate by exchanging. comma or pipe

38:44

or tag delimited text files. Yeah. And

38:47

then also there was a point too

38:49

where I just was like, oh no,

38:51

like, this date format isn't right and

38:53

it's like making like numbers bar for

38:55

some reason or like, oh, this, I

38:57

kept getting this thing where like the

38:59

records are in the wrong order and

39:02

I was like, how do I reverse

39:04

this? I was like, looking for some

39:06

function inside of numbers. I couldn't find

39:08

what. I'm like, wait a minute, this

39:10

is a C. This is a C.

39:12

brought in the whole CSB, flipped the

39:15

slice around and spit it back out,

39:17

and it was done. Or it went

39:19

in that sucked it in, looked at

39:21

the date, and spit it out another

39:23

form, another column, and spit it back

39:25

out. And I'm like, oh, combining these

39:27

little tools together, like writing a little

39:30

bit of go and having numbers, and

39:32

I got exactly what I wanted at

39:34

the end of the day. That to

39:36

me is the learn to code. So

39:38

like, to give my answer to learn

39:40

to code thing, definition, when I see

39:43

should you learn to code. I read

39:45

learn to code as should you learn

39:47

how to configure the computer to do

39:49

things and then from there that's at

39:51

the start and then from there it's

39:53

should you do that with some you

39:55

know like Excel or some graphical thing

39:58

or should you learn like more powerful

40:00

programming languages and be like a software

40:02

engineer to make software. That's where it

40:04

diverges. But for me, the very basic

40:06

is, can you configure the computer to

40:08

do something? And Excel spreadsheets and CSV

40:11

files are hugely important. And I think

40:13

it's a great starting point for anyone.

40:15

For Meetup.com, they export their, you can

40:17

export their attendees for your meetup as

40:19

CSV. And then every building that we

40:21

have to host to meetups at, they

40:23

want their own specific CSV format for

40:26

guests. Great, export, right, go, switch it

40:28

up, import it somewhere else, done. That's

40:30

coding, right? But that's not software engineering,

40:32

that's not like creating software, but that's

40:34

coding, and that's a valuable skill. Like

40:36

go do that manually, and it'll take

40:39

forever. Here I thought I was the

40:41

dinosaur in the group, and you guys

40:43

are talking about exchanging CSBs instead of

40:45

Jason files. Oh, that's because Jason is

40:47

terrible. It's the new hotness. So I

40:49

have a friend that does R&D for,

40:51

he makes like the lighters for grills

40:54

basically, right? You know, the things that

40:56

light the gas. And, you know, there's

40:58

a bunch of, during R&D, you know,

41:00

they do a bunch of measurements and

41:02

stuff. And every once in a while

41:04

he'll call me and be like, hey,

41:06

I have this set of measurements and

41:09

be like, hey, I have this set

41:11

of measurements and I need to make

41:13

this transform, but maybe not everyone should.

41:15

make it their career. Yeah, totally agree

41:17

with that. Like there's so many professions

41:19

out there that learning to code can

41:22

aid you in your profession, but you're

41:24

not software engineering, right? Like you said

41:26

with your friend there, or even my

41:28

wife, like she's a chocolatier. And she

41:30

knows nothing about computers or whatever, but

41:32

she's had to learn how to use

41:34

Excel and code up formulas and do

41:37

her budgeting and her accounting and also

41:39

social media. She has to learn how

41:41

to automate some of those processes. That's

41:43

not strictly software engineering skills or programming

41:45

languages. But she's coding. She's telling the

41:47

system what to do for her to

41:50

make her business better. And like that.

41:52

For me, when I read Should you

41:54

learn a code, I'm always going to

41:56

answer yes from that perspective. Then the

41:58

secondary question, should you be a software

42:00

engineer? I'm more on the, I don't

42:02

know, maybe. It depends. That's where I

42:05

lean that way. If you interpret code

42:07

literally, as in, take some information and

42:09

encode it into some structured format so

42:11

that you can do something with it,

42:13

then yes, everyone should learn to code.

42:15

You should invest effort into... learning how

42:18

to break down a complex problem into

42:20

parts and organize them in a way

42:22

that you can get to the next

42:24

step in whatever it is that you're

42:26

trying to do. And very often, using

42:28

a computer to do that is the

42:30

best thing, the best step. And they're

42:33

prevalent. At this point, everything is a

42:35

computer. You have more computer in your

42:37

pocket today than flew to the moon

42:39

in Apollo 13. Allegedly flew to... Come

42:41

I gotta have a little bit of

42:43

fun. Or I mean, the Voyager interstellar

42:45

spacecraft is running a few hundred bytes

42:48

of code and we have gigabyte hard

42:50

drives on our phones and our pockets.

42:52

So learning to code is kind of

42:54

part of society these days. Everyone needs

42:56

to learn how to code. But I'll

42:58

definitely agree that should you take it

43:01

to the next step and do it

43:03

professionally, do it full-time, become a software

43:05

engineer, that's a different bar. Yeah. I

43:07

also think, if you do want to

43:09

become a professional software engineer, I think

43:11

one of the things that I definitely

43:13

experienced a lot when I was early

43:16

in my career is I, you know,

43:18

talked to my friends. You like, most

43:20

of them were not like computer people.

43:22

They weren't doing software. doing other things,

43:24

and they'd be like, oh man, that

43:26

sounds like a lot of math you

43:29

gotta do. And at first, I would

43:31

say, there's like no math needed. But

43:33

then I'd realize in my mind, I

43:35

had made the same mistake that lots

43:37

of people do, where it's like, yes,

43:39

coding and software. engineering is very math

43:41

heavy, but it is very discrete math

43:44

heavy, not continuous math heavy. So it's

43:46

not a lot of like, you don't

43:48

even know calculus or any of that.

43:50

You need to know like the logic

43:52

side of math in order to be

43:54

programmed. You need algebra. You need algebra.

43:57

But also I don't think people understand

43:59

like what, algebra is like a very

44:01

interesting. like subject because you know SQL

44:03

is also an algebra and there's like

44:05

but anyway anyway I don't want to

44:07

go off topic you need you need

44:09

some algebra right you need some basic

44:12

arithmetic you need logic you need some

44:14

you know all of that but it's

44:16

not like there's not giant formulas that

44:18

you're writing at the end of the

44:20

day but I also think it's important

44:22

to understand like all of those movies

44:25

that everybody watches that everybody watches that

44:27

are like oh the hacker or like

44:29

remember I saw this one like clip

44:31

and he's just like I know one

44:33

language and it's one zero one zero

44:35

one and I'm like absolutely not like

44:37

no that's not you are incorrect when

44:40

people say like oh all computers understand

44:42

is ones and zeros and I'm like

44:44

a that's Not correct. Computers don't understand

44:46

anything. That's not how computers work. But

44:48

B, saying that computers or like programming

44:50

or coding or any of this is

44:52

about once in zeros is kind of

44:55

like saying writing is about the 26

44:57

letters of the alphabet. It's like that's

44:59

that's how we encode the information. That's

45:01

like the very base level thing that

45:03

we're doing, but like that's not. the

45:05

breadth of it and you don't need

45:08

to understand like how did we get

45:10

this alphabet or how does the alphabet

45:12

work to be able to to be

45:14

a good writer and you don't need

45:16

to know how binary works to be

45:18

a good programmer or a good software

45:20

engineer. So. I even have the t-shirt.

45:23

There are one zero types of people,

45:25

those who understand binary and those who

45:27

don't. I think that's where we get

45:29

like the gatekeeping coming from Chris, not

45:31

from the t-shirt from what Chris was

45:33

getting at. That's where I think we

45:36

get the gate gatekeeping from. It's like,

45:38

oh, if you don't know how the

45:40

CPU works or how binary, you're not

45:42

a program, or you're not anything. It's

45:44

like, well, no, there's so many layers

45:46

to this that you can kind of,

45:48

that you can kind of, you can

45:51

be, you can be, you can be,

45:53

you can be, you can make coding,

45:55

you can make coding, you can make

45:57

coding and software. engineering your career and

45:59

not have to go low level or

46:01

not have to go high level. There's

46:04

these niches that you can fill that

46:06

are there in life that you can

46:08

do this as a professional like career.

46:10

That's not strictly like, oh I'm writing

46:12

software every day. Like you can just

46:15

update. themes for people and that's coding

46:17

as a hobby or as coding as

46:19

a profession too. You can do that

46:21

all day and there's need and you

46:24

can probably never run out of work

46:26

the same way a general contractor comes

46:28

around to like replace your toilet or

46:30

something or like some plumber comes

46:32

around to replace your toilet or

46:35

something or like some plumber comes

46:37

around to replace your toilet or

46:39

something. Same idea that that can keep

46:41

you employed and you can do it. And

46:43

I think people have this in

46:46

this mind where they're like, oh,

46:48

if I'm going to be a

46:50

software engineer, I have to be

46:52

the principal engineer before 30, if

46:54

I'm going to do this. It's

46:56

like, no, you don't. The same

46:58

way you don't have to be LeBron

47:00

James playing basketball, or the same

47:03

way you don't have to be

47:05

a CEO of a company. Like,

47:07

you can be in the general

47:09

average, honestly, and I have a

47:11

CS degree. and learning how

47:13

the machine works, actually

47:16

understanding the lower level

47:18

bits does make me a better software

47:20

engineer. Of course it does,

47:22

right? But that doesn't mean

47:24

every job in software is

47:27

that. You don't need to know

47:29

that when you start. But eventually you

47:31

should learn that. Right, like that's, I

47:33

mean, I think there's some people that

47:35

might be like, Chris, aren't you the

47:38

one that said that like everybody should

47:40

know what a cashline is? And I'm

47:42

like, yes, eventually, you should be able

47:44

to understand what a cashline is. And

47:46

in fact, early in your career, you

47:48

should be able to understand what a

47:50

cashline is. And in fact, early in

47:53

your career, you should be able to

47:55

understand what a cashline is. And in

47:57

fact, in your career, like, like, like,

47:59

like, like, Ben eater has fantastic content

48:01

on that. But I do think people

48:03

like eventually you need to learn these

48:05

things. But in the beginning, like no,

48:07

just learn how to solve problems. Solving

48:09

problems is the important part. Solving problems

48:12

efficiently is the thing you can do

48:14

eventually. You don't need to do that

48:16

right away. There's also a part of

48:18

it if you want to make it

48:20

your career where not only do you

48:22

have to learn what a cash line

48:24

is. You have to like one. care

48:26

about that and want to learn it

48:28

and enjoy learning it. Like if that

48:30

is like pulling teeth to you, you're

48:33

going to be miserable trying to go

48:35

like any further in one of these

48:37

careers. I don't think you have to

48:39

learn where the cashline is or you

48:41

know the analogy that we're going for.

48:43

I don't think you have to. The

48:45

analogy that we're going for. I don't

48:47

ever have to. Yeah, I don't know.

48:49

Like I said, I think there's this,

48:51

like we call the senior software engineer

48:54

like the career like the career like

48:56

the career level for so far so

48:58

far so far so far so-level for

49:00

so-level for so-level-level-level for so-level-level-level-level-level- for so-level-level-level-level-

49:02

many people- many people- many- many people-

49:04

many people- many people- many people- many

49:06

people- many people- many- many people- many-

49:08

many- many- many- many- many- many- many-

49:10

many- many- many people- and never know

49:13

what a cashline is and not even

49:15

care, because you're working on problems that

49:17

the business is giving you and you're

49:19

software engineering, you're writing code, and you

49:21

don't care about that stuff. And like,

49:23

yes, knowing it will make you better,

49:25

and it will, because you're going to

49:27

understand more about the system, and you

49:29

can make better decisions, and blah, blah,

49:31

blah. But you don't have to know

49:34

it unless you want to like improve

49:36

yourself, or maybe even prove your career

49:38

and go to that next level. Right?

49:40

But I think that's true of any

49:42

profession. You don't have to know how

49:44

the car is built or how it

49:46

works to be a good race car

49:48

driver. But if you want to be

49:50

the best race car driver, it's probably

49:52

going to be beneficial for you to

49:55

understand that tireware happens like this and

49:57

the engine operates like that and blah

49:59

blah blah. I don't know. Yeah, it's

50:01

hard for me to take that perspective

50:03

because like I just don't know it,

50:05

right? Like I do want to be

50:07

the best at what I do, what

50:09

I do, right what I do, right,

50:11

right. don't take the time to learn

50:14

these things. So I don't know. I

50:16

don't know who's right there. I've worked

50:18

with a few people over the years

50:20

that were absolutely nine to fivers. They

50:22

showed up, they did what was asked

50:24

of them. They were perfectly capable software

50:26

developers, but at 4.30 every day, they

50:28

started signing out and... at 5 o'clock

50:30

they turned their computer off and went

50:32

home and had no interest in kind

50:35

of to to Matt's point in diving

50:37

down further and understanding how operating systems

50:39

work or what a cue is or

50:41

what the difference between a binary search

50:43

and a whatever they just didn't care.

50:45

They were there to do what it

50:47

was a job. I kind of feel

50:49

like you're conflating two things there right

50:51

like you can be a nine to

50:53

fiver and not work outside nine to

50:56

five and still be interested in learning

50:58

all those new things and like care

51:00

about them without like doing that as

51:02

a hobby at home right but i

51:04

bet there's a large overlap but you

51:06

see what i'm saying yeah i think

51:08

it's like not nine to five like

51:10

nine to five specifically it's just like

51:12

a class of people that generally fall

51:14

into that you know i i i

51:17

do want to disagree that i i

51:19

do think that at some point if

51:21

you're going to be a professional software,

51:23

a person that's going to professionally build

51:25

software, you need to know how the

51:27

thing works. Like I think it's like,

51:29

you know, if you're going to be

51:31

a doctor, you need to know how

51:33

the whole body works. Even things outside

51:36

of your specific area of expertise, you've

51:38

got to understand, you should understand how

51:40

generally everything works, because it's all interconnected

51:42

at the end of the day. And

51:44

like, you know, how much do you

51:46

use that knowledge you actually need, but...

51:48

Actually having it I think at the

51:50

end of the day like the corpus

51:52

of knowledge I think software engineers need

51:54

to be good at software engineering I

51:57

think is much much wider and Requires

51:59

things that are much deeper than what

52:01

we currently that we currently think that

52:03

doesn't mean you have to learn it

52:05

right away But I do think eventually

52:07

there's we need to help people start

52:09

learning things. Okay. I I can agree

52:11

with that and what you said makes

52:13

sense. I don't think we have to

52:15

learn it right away. And that's kind

52:18

of the framing of where I was

52:20

getting at is I don't think just

52:22

you shouldn't like deny yourself going into

52:24

this industry or any industry really because

52:26

you're not the best right out the

52:28

gate and you don't know everything out

52:30

of the gate. You got to give

52:32

yourself some grace and time to get

52:34

there. And I think there's a lot

52:37

of people out there. that say, no,

52:39

I'm not going to learn software engineering

52:41

because I'm never going to work for

52:43

fang, so what good is it? Well,

52:45

there's more than fang to work at.

52:47

And that's kind of the perspective I

52:49

was trying to get at is there's

52:51

room in this field for people. You

52:53

don't have to just be the top

52:55

0.01%. You should strive to get there

52:58

for sure. You should strive to get

53:00

there for sure. You should strive to

53:02

get there. I don't think you have

53:04

to. I was probably 12 or 13

53:06

years in before I was to the

53:08

point where my skill set was what

53:10

I would, today I would call a

53:12

senior engineer. I wasn't one that did

53:14

hobby projects in Dobin and learned all

53:16

the new languages and aspired to go

53:19

work at the big companies. It was

53:21

just a job for a long time,

53:23

but it was a job that I

53:25

was interested in and I was good

53:27

at. And it took having to solve.

53:29

similar problems in four or five different

53:31

programming languages in a couple of different

53:33

industries before what to Chris's point to

53:35

kind of the the more general knowledge

53:38

of how everything fits together for me

53:40

to kind of make that leap into

53:42

it doesn't matter if I'm writing C++

53:44

or Java or Python or go or

53:46

rust. The real skill set is the

53:48

problem solving and the thinking in terms

53:50

of the logic that's happening and being

53:52

able to do the analysis of what's

53:54

going on and the rest of it

53:56

is just tools. But it took a

53:59

long time for me to get there.

54:01

Yeah, and I think I don't think

54:03

my perspective on like how much you

54:05

should learn. I mean, I think A,

54:07

I think the main thing that we're

54:09

kind of saying here, I think that's

54:11

important is not. you know, what percentile

54:13

of the, you know, you are in

54:15

the software engineering field. I don't think

54:17

that really even is a thing. I

54:20

don't think you can really compare people

54:22

in that way, compare what we do

54:24

in that way. But I think going

54:26

back to the thing we said earlier,

54:28

where it's like curiosity is important, I

54:30

think... the desire to learn is the

54:32

main thing that needs to be there.

54:34

And I think if you have the

54:36

desire to learn, you will eventually stumble

54:38

your way down to like, oh, how

54:41

does the CPU actually work? How does

54:43

the GPU work? What are these things?

54:45

So I think that's a very important

54:47

thing. So I think that's a very

54:49

important thing. But I also think for

54:51

us as an industry, right? If you

54:53

want to enter this industry, like do

54:55

I think that you should enter into

54:57

this industry if you don't have any

55:00

interest in learning, How much better our

55:02

hardware gets software people squander it? All

55:04

of it squandered, right? People are talking

55:06

about trying to swap out electricity with

55:08

light, because light is so much faster,

55:10

so our processors will be faster, so

55:12

you can have more things in data

55:14

centers, talk to each other more quickly,

55:16

and it's like. You can't give us

55:18

another two or three orders of magnitude

55:21

in the hardware and not have us

55:23

waste it unless we actually start understanding

55:25

why we've wasted everything we've gotten already.

55:27

We've had like so many, I think

55:29

like we've had like a billion times

55:31

improvement more than that in our hardware

55:33

and our software has not gotten much

55:35

better and a lot of that is

55:37

because software people at the end of

55:39

the day are writing. software that, you

55:42

know, does the job, solves the problem,

55:44

but doesn't solve it in a way

55:46

that like the rest of the the

55:48

rest of the ecosystem, I guess it

55:50

doesn't solve in a way healthy enough

55:52

for the rest of the ecosystem. Well,

55:54

to some extent, I think software engineering

55:56

as an industry has kind of written

55:58

the coat, the coat, the coat tails

56:01

of the hardware improvements. We've had, we've

56:03

stopped having to worry about memory usage.

56:05

because most languages are garbage collected and

56:07

most machines have multiple gigabytes around. It's

56:09

not normal to have to do the

56:11

kind of tricks that John Carmack did

56:13

to get doomed to run in whatever

56:15

it was 600K. We should put that

56:17

in the show notes, the doom inverse

56:19

square, you know, talking about, it's really

56:22

cool, we'll put it in the shownets.

56:24

Yeah, like software engineering used to be

56:26

these feats of logic to find ways

56:28

to do things that other people couldn't

56:30

figure out, whereas... in the 90s into

56:32

the 2000s, it became much more of

56:34

a mundane task in general because the

56:36

hardware just propped us up. Yeah, this

56:38

is true. And real quick, I like

56:40

your point about like not comparing people,

56:43

Chris, and it reminded me of like

56:45

the thing you said earlier where like

56:47

the person didn't know how to install

56:49

the hard drive and you take those

56:51

two people. Is one better than the

56:53

other strictly? No, right? Like they have

56:55

different skills in their different areas and

56:57

they both are great at what they

56:59

do, but they're focused on different things.

57:02

So that the software this whole software

57:04

field is filled with that nuance where

57:06

it's filled with that nuance where it's

57:08

like Chris might be the best go

57:10

program around the planet and Matt might

57:12

be the best PhD program on the

57:14

planet or something. Does that mean Chris

57:16

is strictly better than Matt or Matt

57:18

is Chris strictly better than Chris? gathering

57:20

us along as software engineers, I think

57:23

the industry used to have the constraints

57:25

like forced upon them. And so they

57:27

were there present when they were building

57:29

software. And now constraints are like not

57:31

really thought of when you're programming or

57:33

writing software. You just kind of focus

57:35

only on the problem with almost no

57:37

constraints nowadays in like the average case.

57:39

Yeah, I think that I mean, one

57:41

of the things also popped into my

57:44

head, right is like, how much do

57:46

software people? You know, even maybe everybody

57:48

in this in this podcast right now,

57:50

understand about about networking, right? I think

57:52

a lot of us are like, most

57:54

of the time, we don't need to

57:56

care about networking, right? But that has.

57:58

head nods yes of head nods no

58:00

for the listener. That has caused like

58:03

some like very big problems with lower

58:05

level parts of how everything works because

58:07

even us even we don't really understand

58:09

like a good example is Ethernet right

58:11

like I've been thinking about this way

58:13

too much lately for reasons but like

58:15

Ethernet when it was created, you know,

58:17

you had 10 megabit Ethernet, you had

58:19

this this frame size of 1,500 bytes,

58:21

which is like 12,000 bits, which meant

58:24

that, you know, to have the line

58:26

rate of 10 megabits, you had to

58:28

process 800 packets per second. Right. We're

58:30

not at 10 megabits anymore. We're at,

58:32

you know, 100 gigabit, right? You can

58:34

have 100 gigabit now. But we never

58:36

change that frame size. So now the

58:38

hardware instead of having to having to

58:40

process. million packets per second. And that

58:42

is a completely different scale of thing.

58:45

So it's like, oh, if we wanted

58:47

to get that 100 gigabit either or

58:49

not going, then now we have to

58:51

actually build custom hardware. And now your

58:53

Nick has to be its own little

58:55

computer to actually be its own little

58:57

computer to actually be able to process

58:59

things at that land rate. And now

59:01

we've made the entire thing more complex.

59:03

And like, why is it complex? Because

59:06

we never bumped up the size of.

59:08

should have to process about a thousand

59:10

of them per second. Our CPUs would

59:12

still be able to handle that, and

59:14

we probably wouldn't need all of this

59:16

extra complexity that makes our entire infrastructure,

59:18

all of the systems, everything involved in

59:20

building software and building hardware and making

59:22

computers much more complex. We wouldn't have

59:25

to do that if we'd actually said,

59:27

okay, well, we need to push these

59:29

things forward. But the problem is. Who's

59:31

going to be arguing for that? Right?

59:33

If you had all the software people

59:35

saying, no, I want, like, I want

59:37

to be able to take advantage of

59:39

bigger packet sizes in IP or in

59:41

UDP. Like, I want a four meg

59:43

packet, because then I can put so

59:46

much more in in a single thing.

59:48

And I don't have to think about

59:50

things as much. But because we're, because

59:52

not enough of us. us understand that

59:54

layer, there's not enough of us to

59:56

create pressure to actually fix these things

59:58

in the places they need to get

1:00:00

fixed. So we as an entire pot

1:00:02

in all of humanity winds up suffering.

1:00:04

Like the way that the internet is

1:00:07

coupled together and continues to be coupled

1:00:09

together because of these... Small things that

1:00:11

not enough people know is like really

1:00:13

problematic. And I think that part of

1:00:15

what we need to do is professional

1:00:17

people is understand that we might have

1:00:19

our area where we care about things

1:00:21

a lot and understand things a lot.

1:00:23

But we also need to care about

1:00:26

all of the other things because we

1:00:28

have to form the collective of people

1:00:30

that is saying that thing right there

1:00:32

has been neglected and we got to

1:00:34

go fix it. And even if I'm

1:00:36

not directly... you know, writing Ethernet implementations

1:00:38

or I'm not writing operating system implementations,

1:00:40

I'm going to go talk to the

1:00:42

people that are and say, this is

1:00:44

something we need to prioritize because this

1:00:47

is going to be a problem in

1:00:49

the future. Like a similar story. Few

1:00:51

years ago, I was tasked with what

1:00:53

was essentially upload this directory to an

1:00:55

S3 bucket. Goes great at doing concurrency.

1:00:57

So we did a semaphore with some

1:00:59

skating and go routines and using the

1:01:01

iO package to go just iO copy

1:01:03

this file to that network socket and

1:01:05

it was great until we brought down

1:01:08

other production systems because we had saturated

1:01:10

their network uplink and they started getting

1:01:12

hardware failures. Right. To both of your

1:01:14

points, the hyperscalers of the world or

1:01:16

the ISPs of the world, they think

1:01:18

about some of these problems and they

1:01:20

kind of, they do this, right? They

1:01:22

have jumbo frames enabled their own custom,

1:01:24

like, you know, stack there, layer, layer,

1:01:27

layer, or whatever. And it's funny because

1:01:29

you're not wrong. We could get away

1:01:31

from that like archaic constraint, possibly. I

1:01:33

don't know what all the ramifications are

1:01:35

there, but we could reevaluate that. Because

1:01:37

if you think about how traffic flows

1:01:39

across the network, like my device talking

1:01:41

to my router on, you know, 1500

1:01:43

MTU, but then once it gets to

1:01:45

like my ISP, maybe they're bumped up

1:01:48

to a higher MC. Maybe they're using

1:01:50

their own, maybe they're not even using

1:01:52

Ethernet internet anymore to like. relay the

1:01:54

information to one another, who knows? And

1:01:56

it's like, that sounds good on paper,

1:01:58

because it's like, oh, the internet is

1:02:00

just so redundant and we just have

1:02:02

like all this cool thing, it just

1:02:04

works. But we're not thinking about the

1:02:06

other side of that costs more CPU

1:02:09

time or power to do that, or

1:02:11

we're doing translations, basically, at every hop

1:02:13

almost in the network. And is that

1:02:15

efficient? No. Is it like resilient? Yes.

1:02:17

So like, what's, I feel like we've

1:02:19

tipped way to in the... in the

1:02:21

realm of resiliency, and we can probably

1:02:23

circle back to efficiency a little bit.

1:02:25

Yeah, I mean, I think, like, it's

1:02:27

interesting how some of us do with

1:02:30

finances, right? The reason why we can't

1:02:32

increase the MTU of the internet as

1:02:34

a whole is because you have to

1:02:36

increase it like. across all of this

1:02:38

and there's just these very old boxes

1:02:40

that have a 1500 by MTU and

1:02:42

you got to convince that ISP or

1:02:44

whoever to upgrade that box to something

1:02:46

that can be you know bigger so

1:02:49

like the way you fix this problem

1:02:51

is you got to like do it

1:02:53

over time you've got to increase all

1:02:55

of these things as you go not

1:02:57

like do it once every 60 years

1:02:59

I was like with the New York

1:03:01

City subway right where everybody's like We

1:03:03

dumped billions of dollars into this thing.

1:03:05

It's like, yeah, we spent 70 years

1:03:07

dumping nothing into it. And now we

1:03:10

got to play all the catch-up with

1:03:12

that. And that's how a lot of

1:03:14

the networking world works. You got to

1:03:16

play a lot of catch-up. Like, oh,

1:03:18

another good example of this is like,

1:03:20

with a quick protocol, right? Quick. Whoa,

1:03:22

whoa, whoa, who. This was a very

1:03:24

long networking tangent for a day. Wherewith

1:03:26

Quick, they have done two things so

1:03:28

far. They've already read the version of

1:03:31

it, and they have also added this

1:03:33

little bit in the protocol that just

1:03:35

kind of flips randomly as you're sending

1:03:37

things. And that's because they found out

1:03:39

that there were boxes that just basically

1:03:41

had protocol images baked into them, and

1:03:43

it just kind of ossified the whole

1:03:45

thing, and that's why TCP can't evolve

1:03:47

forward. So it's like as. time goes

1:03:50

on, like they figured out that we

1:03:52

have to continually change things, continually be

1:03:54

updating things, and that is how we

1:03:56

stop everything from ossifying. And I think

1:03:58

like that's, you know, and that involves

1:04:00

all of us. We all have to

1:04:02

create that pressure to stop things from

1:04:04

ossifying, because if you don't, it's too

1:04:06

small a group of people for us

1:04:08

as an industry to care enough to

1:04:11

invest the effort to make those things

1:04:13

not get stuck, and then that winds

1:04:15

up affecting all of us. I was

1:04:17

going to kick him off the tangia

1:04:19

anyway, but you got it. To close

1:04:21

the loop, okay. To close the loop,

1:04:23

should you become, should you learn the

1:04:25

code? Yes. Should you become a software

1:04:27

engineer? Did your eyes glaze over while

1:04:29

Chris was talking about networking protocols? I

1:04:32

mean, that is a good, that is

1:04:34

a good pulse check for it. If

1:04:36

that was boring to you and you

1:04:38

were like, I don't care about any

1:04:40

of this, that's probably a good sign

1:04:42

that maybe you're not so interested in

1:04:44

like, Maybe, uh, think about... Yeah, open

1:04:46

that Python. Even if you're not building

1:04:48

network hardware, those are the kinds of

1:04:51

problems that come up in software engineering.

1:04:53

Like, how do I solve this thing

1:04:55

given external constraints that I can't control?

1:04:57

1500 MTU, amount of RAM, all these

1:04:59

things that are kind of... To me,

1:05:01

it's always been the engineering side. I

1:05:03

have fixed constraints. how do I fit

1:05:05

the pieces together to solve the problem?

1:05:07

And to me that's the difference or

1:05:09

the hill to climb between coding and

1:05:12

kind of to what Matthew would say

1:05:14

to go make a computer do something

1:05:16

that you needed to do versus software

1:05:18

engineering as a career of do you

1:05:20

find joy in solving those kinds of

1:05:22

problems in picking them apart and turning

1:05:24

over the rocks and figuring those kinds

1:05:26

of things out. I think I would

1:05:28

say on that as well. I think

1:05:30

there's this idea that a lot of

1:05:33

people have that like just because I

1:05:35

was talking about networking like maybe you

1:05:37

don't. maybe like you don't actually need

1:05:39

to know this early on. And I

1:05:41

think the moment that you're designing software,

1:05:43

which I think people should really, I

1:05:45

think like as an industry, we need

1:05:47

to have people designing software much earlier

1:05:49

in their careers, I think not knowing

1:05:51

these things leads to poor designs that

1:05:54

can very quickly become industry standards. Right,

1:05:56

like if you look at, you know,

1:05:58

how we do networking, basically across the

1:06:00

board now with micro services, a lot

1:06:02

of it is based on things like

1:06:04

GRPC. Is this really the design we

1:06:06

want to have? Right? Have we actually

1:06:08

understood the context we existed? Did we

1:06:10

have enough knowledge when we did it

1:06:13

with like how Kubernetes works and how

1:06:15

these things were? It's like in the

1:06:17

historical path we took, I think a

1:06:19

lot of these things do wind up

1:06:21

making sense. But since people didn't have

1:06:23

the underlying information what they created, we

1:06:25

wound up creating things that aren't. as

1:06:27

good as they need to be. And

1:06:29

they cause a lot of either resource

1:06:31

waste, or they make systems that don't

1:06:34

work, or systems that have a lot

1:06:36

of bugs. And then those bugs bubble

1:06:38

up into effect real people's lives at

1:06:40

the end of the day. And it

1:06:42

makes their lives hard to make people

1:06:44

that don't have anything to do with

1:06:46

your company and what you're doing, now

1:06:48

they have to suffer the consequences for

1:06:50

it. So I think to think that

1:06:52

question of like, do I think people

1:06:55

should code? give to other people? I

1:06:57

think the answer to that is, like,

1:06:59

are you ready to potentially have the

1:07:01

responsibility of you being a load-bearing member

1:07:03

of society? I think that's a very

1:07:05

important thing that people need to understand

1:07:07

because if you make a little hobby

1:07:09

project, it could turn into log for

1:07:11

J, it could turn into bolt DP,

1:07:14

it could turn into SQ Light, it

1:07:16

could turn into one of these things

1:07:18

that is just, yeah, everywhere and ubiquitous

1:07:20

and... The XZ problem, the mandatory XKCD,

1:07:22

KCD cartoon reference. Yeah, you could be

1:07:24

the one in Nebraska maintaining image magic,

1:07:26

right? You could be the guy that

1:07:28

maintains curl that is used literally everywhere

1:07:30

and everything and you put one mistake,

1:07:32

you make one bug and that... could

1:07:35

crash the world's infrastructure, right? Like, I

1:07:37

think everybody needs to recognize that if

1:07:39

you're going to be someone that gives

1:07:41

software to other people, if that's the

1:07:43

line you want to cross, you just

1:07:45

have to be prepared that that might

1:07:47

happen to you. It might not, it

1:07:49

doesn't happen to a lot of people,

1:07:51

but it could. Full disclosure, if I

1:07:53

would have gotten that speech in 1996,

1:07:56

I would not be here today writing

1:07:58

software, because that's a lot of pressure.

1:08:00

We've all been in this career for

1:08:02

a while, and I actually think the

1:08:04

bar is a lot higher now than

1:08:06

when we started. In what way, like,

1:08:08

what do you think? I think specifically,

1:08:10

like, breaking in is a lot harder.

1:08:12

Like, what, all four of us, or

1:08:15

three out of the four of us,

1:08:17

so we fell into these computer science

1:08:19

jobs, right? Oh, that's not happening anymore,

1:08:21

right? Like, like, people, it's, it is

1:08:23

competitive out there. And so, I guess

1:08:25

the point I'm getting at is. The

1:08:27

bar is higher so you're going to

1:08:29

have to want it more and if

1:08:31

you don't enjoy it you're not going

1:08:33

to want it more. So like my

1:08:36

my answer to surge you make a

1:08:38

career isn't just can you do it

1:08:40

like what do you want to do

1:08:42

it? Right. I will call the at

1:08:44

what I just said as well if

1:08:46

anybody is a little scared now after

1:08:48

hearing what I just said of like

1:08:50

you don't have to become a load

1:08:52

bearing part of society. You can choose

1:08:54

to not to. You can choose to

1:08:57

not to not to make it. I

1:08:59

want to warn people too because it's

1:09:01

very easy to accidentally fall into it

1:09:03

and then get stuck. So if you

1:09:05

don't know that this can happen and

1:09:07

all of a sudden you're like, oh,

1:09:09

this popular library, this is great. I

1:09:11

have all this fame, people are telling

1:09:13

me how great it is that I'm

1:09:16

doing this thing. You can easily get

1:09:18

stuck if you're not careful. So I

1:09:20

just want to like. And not even

1:09:22

just public things. Like I work as

1:09:24

a, like on a team that supported

1:09:26

like HR and recruiting and you know

1:09:28

kind of all the internal teams out

1:09:30

of company. And you know you end

1:09:32

up over five years you build them

1:09:34

30 different tools and all of a

1:09:37

sudden the maintenance on those 30 tools

1:09:39

is a full-time job and you. no

1:09:41

longer have time to build new things,

1:09:43

right? So you can, that trap isn't

1:09:45

just in the public, it's everywhere. Like

1:09:47

you become a kind of a linchpin

1:09:49

in a lot of organizations, like they're

1:09:51

depending on the things that you built

1:09:53

to do their jobs. For me, the

1:09:55

difference in the environment is pretty striking.

1:09:58

When I started, open source essentially wasn't

1:10:00

a thing. Almost all software was. proprietary

1:10:02

corporate software that you were writing something

1:10:04

that was an internal system for the

1:10:06

company that you work for and no

1:10:08

one else is ever going to use

1:10:10

it. Compared to today, pretty much everything

1:10:12

goes to give up by default. Yeah.

1:10:14

People that are learning to code are

1:10:16

creating a get help account and pushing

1:10:19

their code out and are contributing to

1:10:21

existing things that are out there. So

1:10:23

everything is out there and available for

1:10:25

other people to use. So there's a

1:10:27

lot higher potential of someone else pulling

1:10:29

in your thing and depending on it

1:10:31

than there was when I got my

1:10:33

start. I'm glad that Chris didn't say

1:10:35

anything that was going to make me

1:10:38

change my opinion of what he said.

1:10:40

Because I agree with what you said,

1:10:42

like the scary story, like you know,

1:10:44

if I would have heard this before,

1:10:46

I wouldn't be here. Like, I agree

1:10:48

with telling people these things because a

1:10:50

lot of things are out there in

1:10:52

life where people don't know what they're

1:10:54

getting into. And I like the fact

1:10:56

that you outlined these are potential things

1:10:59

you can get into. Be aware. Don't

1:11:01

be afraid, but just be aware that

1:11:03

this can happen and like do what

1:11:05

you can, you know, to adjust to

1:11:07

that or avoid or whatever you want

1:11:09

to do. And like you mentioned like

1:11:11

ossification in terms of our like network

1:11:13

devices over time and whatnot. But there

1:11:15

also is that same concept of... to

1:11:17

us as engineers or as programmers or

1:11:20

as whatever title you want to give

1:11:22

us. If you are just going to

1:11:24

come into the field or learn to

1:11:26

code and only just do one thing

1:11:28

forever, that's going to be a problem.

1:11:30

You're going to be left behind, so

1:11:32

to speak. You should encourage yourself to

1:11:34

try different tools or different paradigms or

1:11:36

whatever, or even just different industries of

1:11:39

applying those. those skills and that's going

1:11:41

to make you a better well-rounded program

1:11:43

and it's actually going to increase your

1:11:45

curiosity of like liking things and seeing

1:11:47

what you want to do. Yeah, it's

1:11:49

kind of my my thing. Like continual

1:11:51

learning is I think that is something

1:11:53

that I want everybody that that wants

1:11:55

to do this professional like just continually

1:11:57

learning continually growing I think it's kind

1:12:00

of like how I don't know where

1:12:02

I write it but there's this thing

1:12:04

with doctors where a lot of doctors

1:12:06

just don't continue learning once they graduate

1:12:08

med school and like do the residency

1:12:10

now they're in the field they're not

1:12:12

learning nearly as much and when you

1:12:14

kind of say it to people as

1:12:16

like yeah do you want someone that

1:12:18

has like the most current knowledge or

1:12:21

someone that has knowledge from 30 years

1:12:23

ago you'd be like okay I want

1:12:25

that I think the most current knowledge

1:12:27

please I think that's the same with

1:12:29

like it's hard to do that in

1:12:31

law because you know law is always

1:12:33

moving but I think like that's the

1:12:35

same for us of like Yeah, you

1:12:37

got to keep refreshing your skills. You

1:12:40

got to keep learning. You got to

1:12:42

keep growing. Like if you're someone that

1:12:44

finds change to be extremely stressful, I'm

1:12:46

not saying don't become a software engineer,

1:12:48

but just make sure that you're ready

1:12:50

to push back against that a bit.

1:12:52

So I think there are currently a

1:12:54

few, I've run too many people in

1:12:56

my career who learned, you know, we're

1:12:58

learning a lot when they were younger

1:13:01

and now they're deep in their career

1:13:03

and they don't really want to learn

1:13:05

as much. company where it's just like,

1:13:07

okay, we got to find a way

1:13:09

to work around this person because they

1:13:11

don't want to learn something new, or

1:13:13

they have really updated knowledge, and you

1:13:15

have to spend all this time like

1:13:17

educating them and telling them, and it

1:13:19

drags everybody else down. I think that

1:13:22

could have been mitigated if it was

1:13:24

just like, no, just have a little

1:13:26

bit of time to learn some more,

1:13:28

do a little bit more of learning.

1:13:30

Someone had told them that in general,

1:13:32

I think it would help some. I

1:13:34

literally just wrote a blog post like

1:13:36

two days ago talking about like changing

1:13:38

your tools right in the new year

1:13:40

and That's something I mentioned of like

1:13:43

you should be encouraged to change your

1:13:45

tools or to change your skills or

1:13:47

whatever Just just give it a shot

1:13:49

and see where it leads you and

1:13:51

see what how it makes you think

1:13:53

about these things But so many people

1:13:55

are so ingrained in to the program

1:13:57

language they use. They never go to

1:13:59

another program language or the editor or

1:14:02

the OS or this. And it's like

1:14:04

you're doing yourself a disservice. I'm not

1:14:06

saying change your editor every two months

1:14:08

or whatever. That's all I'm saying. But

1:14:10

every once in a while, if you're

1:14:12

gonna be digging those holes, right? Learning

1:14:14

about with your backhoe or your shovel.

1:14:16

You should come up once in a

1:14:18

while and be like, what else is

1:14:20

new in this in this industry? Is

1:14:23

there a new type of backhoe? It

1:14:25

was the act of the digging holes

1:14:27

been like replaced. You should be challenging

1:14:29

yourself and doing that every so often

1:14:31

in my opinion. Yeah. I think that

1:14:33

also helps answer another question that I

1:14:35

think both people probably have that I

1:14:37

definitely got asked when I started my

1:14:39

career. Is there just like, and this

1:14:41

was, I saw my career like almost

1:14:44

like, what, 13 years ago, 13 plus

1:14:46

years ago, is like, oh, isn't all

1:14:48

of that being automated away, is an

1:14:50

AI kind of just. replace the need

1:14:52

for programmers and for people writing code

1:14:54

and all the fact. And I just

1:14:56

want to emphatically say, right here right

1:14:58

now, no, no, AI is not going

1:15:00

to replace people writing code. Louder for

1:15:03

those in the back, please. I'll say

1:15:05

that again, AI is not going to

1:15:07

replace the need for people writing code.

1:15:09

It might change how we write code

1:15:11

and what code you write, but it

1:15:13

will not replace the need for people

1:15:15

to write code. I will say, I

1:15:17

was talking about that bar being higher

1:15:19

now, and I do think the introduction

1:15:21

of AI does make finding like an

1:15:24

entry-level position harder, not because like AI

1:15:26

can replace those entry-level people, but I

1:15:28

think you said this earlier, Chris, or

1:15:30

maybe Matt, that like there's a lot

1:15:32

of companies spending a lot of money

1:15:34

to advertise to tell those managers that

1:15:36

it can, right? So I do think

1:15:38

it's, if you do decide that you

1:15:40

want to make this your professional career,

1:15:42

it's not going to be an easy

1:15:45

path for the path for the for

1:15:47

the beginning. Yeah, I guess I'll say

1:15:49

I've played with AI enough and LLLMs

1:15:51

to have ridden some of the hallucination

1:15:53

tangents and just Yes, it's not there

1:15:55

yet. It's very cool and it does

1:15:57

some interesting things, but at the end

1:15:59

of the day, it's still just a

1:16:01

statistical word generator and it will lie

1:16:04

to you with a straight face and

1:16:06

never hesitate. I'll give you the right

1:16:08

equation with everything plugged in right and

1:16:10

then the wrong answer. Sounds about right.

1:16:12

I mean, this happened with it. I

1:16:14

was Googling because I needed to doing

1:16:16

that. project I was doing with CSVs,

1:16:18

I needed to like reverse, I was

1:16:20

trying to figure out, oh, is there

1:16:22

an easy way to just reverse a

1:16:25

CSV in like in Bash? And I

1:16:27

looked it up and then Google gave

1:16:29

me a little AI review thing and

1:16:31

it was, oh yes, you can use

1:16:33

the tech command for this. And bubble

1:16:35

and I just do this and I

1:16:37

went in. I literally went to my

1:16:39

editor. I was like, I never heard

1:16:41

a tack, I typed tack in, wasn't

1:16:43

found. And I was about to keep

1:16:46

going and looking for how to keep

1:16:48

going and looking for how to how

1:16:50

to looking for how to how to

1:16:52

how to how to how to how

1:16:54

to how to how to how to

1:16:56

how to how to I was like,

1:16:58

oh, you're really annoying. You know that

1:17:00

it like probably inferred that because of

1:17:02

if and fee in case and eSag

1:17:04

and all the bashisms that are out

1:17:07

there. So it's probably like, wait a

1:17:09

minute. If I can do cat for

1:17:11

the forward, I could do tack for

1:17:13

the backward, right? Yeah. Yeah. Oh, I

1:17:15

was so annoyed at that moment. I

1:17:17

was like, I, and then I wrote

1:17:19

a bunch of like wrote a bunch

1:17:21

of go. Even the best of us

1:17:23

those solutions will just like you know

1:17:26

make you question yourself a little bit

1:17:28

of like oh, maybe like no like

1:17:30

tack does not exist. Those have always

1:17:32

been my kind of points of hesitation

1:17:34

because it's it's really good at spitting

1:17:36

out something that sounds plausible. So to

1:17:38

me it's you almost spend as much

1:17:40

time verifying what the AI told you

1:17:42

as you would have just doing it

1:17:44

yourself. Yeah, I agree. I mean it

1:17:47

straight up lied to me about open

1:17:49

telemetry configuration I was like hey, how

1:17:51

do you do like a filter here

1:17:53

in open telemetry and it gave me

1:17:55

configuration that was just not valid like

1:17:57

like plugins at the exist all that

1:17:59

stuff and I was like oh you

1:18:01

don't you don't know do you you

1:18:03

don't know anything you're just guessing at

1:18:05

least at least when I talk to

1:18:08

like an experienced engineer or something they're

1:18:10

gonna tell me they don't know and

1:18:12

they're gonna say I don't actually know

1:18:14

the answer sorry they're not gonna lie

1:18:16

to me AI likes to lie to me

1:18:18

even some random person on stack overflow

1:18:20

replying to your question yeah they're at

1:18:22

least like took a shot at it

1:18:24

and was right right that's not to say

1:18:27

that I don't like AI though I use

1:18:29

it all the time. It's like having, you

1:18:31

know, like we're all here, we're talking on

1:18:33

the podcast, it's great, we're sharing perspectives. When

1:18:35

we leave, I don't talk to you until

1:18:37

like, you know, we do the next one

1:18:39

or we talk in back channels, but like

1:18:41

I can't just easily say, hey Chris. Oh,

1:18:43

that quick thing you're talking about. Can we

1:18:45

talk about it more? Like, it's a little

1:18:48

harder, because our schedules have to align. But

1:18:50

with AI, I can just be like, open

1:18:52

it up, you're an expert in networking, talk

1:18:54

to me about quick, give me the the

1:18:56

CLDR, and that's super helpful for my workflows.

1:18:58

It's like, if I had this when I

1:19:00

was learning, like, by reading books, mostly, it

1:19:02

would have supercharged my learning. I would

1:19:04

have been talking with AI all the AI all

1:19:06

the time of like just. That curiosity itch that

1:19:09

got me into software, AI can help scratch that

1:19:11

really, really nicely. And that's what I like about

1:19:13

using it. Do I use it to write code?

1:19:15

No. I'll use it to sketch out things,

1:19:17

but I won't use this to actually

1:19:19

write my code for me. Yeah, I

1:19:21

think it's, you know, I haven't been

1:19:23

thinking a lot about this, because I

1:19:25

think also, it's the same as with

1:19:27

Wikipedia. where if it's something that is

1:19:29

very well known, very well understood that

1:19:31

a lot of people have talked about

1:19:33

or written about, it gives you very

1:19:36

good answers. Like AI will do this,

1:19:38

Wikipedia will do this, Stack Overflow will

1:19:40

do this, but as soon as you

1:19:42

start getting to the edges, the stack

1:19:44

overflow will do this, but as soon

1:19:46

as you start getting to the edges,

1:19:48

those things that aren't, that may

1:19:50

be a little bit controversial, and

1:19:52

networking all of this. There's a

1:19:54

lot of wrong or missing information

1:19:56

there. I think that's the area

1:19:58

where AI does terribly. And I think

1:20:00

even stack over those dad does bad

1:20:03

of it Wikipedia does bad on it

1:20:05

like an example quick little example I've

1:20:07

been you know going down YouTube rabbit

1:20:09

holes about now working lately and I've

1:20:12

always wondered like you have these three

1:20:14

devices a bridge a switch and a

1:20:16

router and I've always been so confused

1:20:18

about what the difference between all of

1:20:20

these devices are and they're watching these

1:20:23

videos and now reading a book by

1:20:25

literally one of the people who helped

1:20:27

create the idea of routing in the

1:20:29

first place. Like she wrote this book

1:20:32

and she's basically like, yeah, no, these

1:20:34

words, we're just kind of trying to

1:20:36

make up new words. She's like, I

1:20:38

kind of understand what we have then,

1:20:40

but no, like, there's not a lot

1:20:43

of difference here. The difference in the

1:20:45

switch and a bridge is basically null.

1:20:47

You have like bridges and routers and

1:20:49

these things called switches that sit between.

1:20:52

And it's like, None of this makes

1:20:54

sense with people giving very strong definitive

1:20:56

answers about this is a bridge and

1:20:58

this is a switch and this is

1:21:00

a router and they are very three

1:21:03

separate things. Like no, this is all

1:21:05

a mess. This is all very modeled.

1:21:07

And I think that's one of the

1:21:09

things that trips new people up sometimes

1:21:12

with esoteric knowledge, but also very experienced

1:21:14

people with the esoteric knowledge. In AI's

1:21:16

defense, I have several times over the

1:21:18

course of my career done a Google

1:21:20

search and got less than one page

1:21:23

of results, where five of the six

1:21:25

answers were links to the first one.

1:21:27

And I definitely have channeled Denver Coder

1:21:29

9 from the XKCD cartoon quite a

1:21:32

few times. Like, this is a thing.

1:21:34

I'm quoting the error message from this

1:21:36

Windows component. How is no one else

1:21:38

on the planet experiencing this? I thought

1:21:40

about this too because I've had the

1:21:43

same thing and this is one of

1:21:45

the reasons why I'm starting to write

1:21:47

more and I want to write more

1:21:49

and get more content out there. Yes,

1:21:52

I know. So AI trains for free

1:21:54

off of my content, blah, but I

1:21:56

get all that. I really do. But

1:21:58

also, humans are on the other side

1:22:00

of that content too. And I don't

1:22:03

want humans to end up like you

1:22:05

did, where you look for something, you're

1:22:07

like, none of these are helpful. I'm

1:22:09

stuck. What's going on? So that's part

1:22:12

of the motivation of why I like

1:22:14

to create and write and whatnot to

1:22:16

help counteract some of that stuff. Yeah.

1:22:18

I think if you know you listener,

1:22:20

listener or viewer, or viewer, do decide

1:22:23

after all of this that you want

1:22:25

to become a coder. I think something

1:22:27

that you should do is blog. Like

1:22:29

if you run into a problem, write

1:22:32

a little bit things. It's going to

1:22:34

be like a blog blog. It could

1:22:36

be on. Blue Sky, it could be

1:22:38

on medium, it could be wherever you

1:22:40

can throw some words, but throw some

1:22:43

words. Hey, I ran into this problem.

1:22:45

And here's a solution I found that

1:22:47

works for me. Just share what you

1:22:49

learn. I think that's a very, it's

1:22:51

a very important thing that I think

1:22:54

not enough people do, because they think

1:22:56

they're too earlier, too inexperienced, or they

1:22:58

haven't done it. No matter what level

1:23:00

of coding you do. Even if it's

1:23:03

just Excel stuff, even if it's, you

1:23:05

know, you know, whatever it's, you know,

1:23:07

whatever it's, whatever it's, whatever it's, whatever

1:23:09

it's, you know, whatever it's, whatever it's,

1:23:11

whatever it's, whatever it's, whatever it's, whatever

1:23:14

it's, whatever it's, you know, you know,

1:23:16

you know, you know, you know, you

1:23:18

know, you know, you know, you know,

1:23:20

you know, you know, you know, you

1:23:23

know, whatever you know, whatever you know,

1:23:25

whatever, whatever, whatever, put that information out

1:23:27

there into the world. Yes, it does

1:23:29

help AI models get better, but I

1:23:31

mean, we're gonna be stuck with these

1:23:34

things for a while anyway. I would

1:23:36

prefer them to be a little bit

1:23:38

better and not hallucinating things in any

1:23:40

way. Let's give them some better inputs.

1:23:43

And for when ultimately all of this

1:23:45

AI stuff collapses and falls into the

1:23:47

ocean, the stuff you published will still

1:23:49

be out there for people to consume

1:23:51

and to, you know, have. So I

1:23:54

think it's important to do that. Don't

1:23:56

just hold stuff in your head. I've

1:23:58

definitely been guilty of not doing enough

1:24:00

writing, and I think we should all

1:24:03

be doing more writing, because then when

1:24:05

you do that Google Search, like Dylan

1:24:07

did, you won't have five results. Maybe

1:24:09

you'll have 50. Totally, totally agree. And

1:24:11

it helps you exercise those muscles of

1:24:14

thinking through a problem and formulating your

1:24:16

thoughts better. So even if you're like,

1:24:18

oh, no. Nobody's going to read my

1:24:20

post. You're going to write it. You're

1:24:23

going to read it. And that's going

1:24:25

to help you think about the problem

1:24:27

better. And even if that, that's it.

1:24:29

The act of explaining it will, kind

1:24:31

of like Matt said, that we'll exercise

1:24:34

the muscles of breaking it down into

1:24:36

the parts and organizing them and thinking

1:24:38

about them in a structured manner. And

1:24:40

that is at the end of the

1:24:43

day what we do. Yeah, totally agree.

1:24:45

All right. So we've been on this

1:24:47

long, long, long, long journey. And so

1:24:49

I think it's time to go to

1:24:51

the last segment. But also, if you're

1:24:54

wondering, are we going to answer the

1:24:56

question, should you learn to code? I

1:24:58

don't think there's a definitive yes or

1:25:00

no to that. I think you've got

1:25:03

to go back and re-listen to everything

1:25:05

we just said, and then decide for

1:25:07

yourself. I'm not going to give you

1:25:09

a yes or no answer. As with

1:25:11

all things, it depends. It depends. That's

1:25:14

the best way to end this. Should

1:25:16

we tee up the next episode? Yes.

1:25:18

Coming soon. Coming soon to your ears

1:25:20

and eyes is part two of this

1:25:23

wonderful thing. So this one was about

1:25:25

do we think you should learn to

1:25:27

code. The next part is going to

1:25:29

be all about. Should you get a

1:25:31

career in this? Should you build a

1:25:34

career in this? And we are going

1:25:36

to have a very special guest. He's

1:25:38

a recruiter that has been in this

1:25:40

industry, been doing tech recruiting since the

1:25:43

90s. So he's seen the.com boom, the

1:25:45

great recession, you know, everything that happened

1:25:47

in the 2010s, he's seen all of

1:25:49

it. So he'll be joining us to

1:25:51

give us a perspective of. You know,

1:25:54

what's it like to get a career

1:25:56

in tech? What are the things we

1:25:58

need to know? And we'll all be

1:26:00

here to give some commentary around that.

1:26:03

So we're super-confect. Yeah, well, we shall

1:26:05

see. So we might not. Yeah, he

1:26:07

might not agree. He might agree. He

1:26:09

might agree. You know, your listeners out

1:26:11

there. You might agree with him. You

1:26:14

might not agree with him. We're super

1:26:16

excited for that. And now, let's do

1:26:18

some un-pops. Who's got an un-pop? Anybody

1:26:20

got un-pops? I have one. OK. All

1:26:23

right. My unpopular opinion is that muscle

1:26:25

memory is not immutable. It can be

1:26:27

changed. It can be overridden. It can

1:26:29

be modified. I think a lot of

1:26:31

people spend too much time saying, oh,

1:26:34

I have muscle memory for this. That's

1:26:36

why I can never try something new.

1:26:38

Yes, you can. You can, you take

1:26:40

muscle memory, it just takes some discipline

1:26:43

and some training, but you can do

1:26:45

it, and don't use that as an

1:26:47

excuse. That is my popular thing. Sometimes

1:26:49

you have to slow down before you

1:26:51

can speed up. Are you secretly telling

1:26:54

me I need to learn EMAC, because

1:26:56

if you are, I know. It's really

1:26:58

funny you bring that up, because I

1:27:00

have just started my VIM journey. Oh.

1:27:02

That's congratulations, I'm sorry. There's a terminal

1:27:05

session somewhere that's still running a VEM

1:27:07

instance that I can never get out

1:27:09

of. Try getting out of eMac. I

1:27:11

mean, it makes fun of getting out

1:27:14

of VEM. Anyway, well, Ian, welcome to

1:27:16

the VEM journey. You can escape until

1:27:18

you learn the power of macros, and

1:27:20

then you're just stuck in actual VEM

1:27:22

for forever, because. Oh, yeah. All those,

1:27:25

all those, all those key bindings. Great

1:27:27

until you want to make a macro

1:27:29

out of them and then Things start

1:27:31

to fall apart when those I'm not

1:27:34

quite there yet, but we'll we'll see

1:27:36

Okay, I look I look forward to

1:27:38

your muscle memory being developed. It's a

1:27:40

whole new way to think all right

1:27:42

I like that one I agree with

1:27:45

it that you know muscle memory is

1:27:47

a very mutable thing It's a thing

1:27:49

that you can develop and change over

1:27:51

time. See I think I do think

1:27:54

people you know people you know people

1:27:56

ossify themselves sometimes. They're like a I

1:27:58

can't I don't want to change people

1:28:00

very change a verse. I look at

1:28:02

cars like we used to have manual

1:28:05

cars where you have to like actually

1:28:07

row the gears which I still have

1:28:09

one they made automatic of cars where

1:28:11

the sticks in the middle and you

1:28:14

switch select gears, now like modern cars

1:28:16

have a where the windshield wiper is,

1:28:18

you know, like on the stick of

1:28:20

a steering wheel. It's like if you

1:28:22

made the argument of muscle memory, then

1:28:25

by definition, then go back to driving

1:28:27

a manual car. If that's so important,

1:28:29

then by definition, then go back to

1:28:31

driving a manual car. If that's so

1:28:34

important to you, like, if that's so

1:28:36

important, then go back to driving a

1:28:38

manual car. If it's going to use,

1:28:40

give it. I like that. I like

1:28:42

that one. Anybody else have an unpopular

1:28:45

opinion? I feel like Dylan always got

1:28:47

popular opinions. I did not come prepared

1:28:49

this week. Ah, okay. Okay. I feel

1:28:51

like Ian's, he's contemplating his thinking. Yeah,

1:28:54

he's just pulling one right now. I

1:28:56

see it. It's slipping away. I don't

1:28:58

know if I have one. All right,

1:29:00

I got one. This is not a

1:29:02

good one, but. I don't think anyone

1:29:05

needs an iPad. No one needs an

1:29:07

iPad. No one should probably even have

1:29:09

one. Like, it is the most... You

1:29:11

say that's not a good one, but

1:29:14

that's actually a good one. For the

1:29:16

definition of unpop. That it's the silliest

1:29:18

device that's ever been made. Like, I

1:29:20

guess if you only have an iPad,

1:29:22

right, but like... I can hear and

1:29:25

feel... are like future listeners cringing at

1:29:27

this right now. I feel it. I

1:29:29

feel it. As a corollary to that

1:29:31

one, I guess I'll throw my own

1:29:34

as a corollary. An iPad is not

1:29:36

sufficient for a software development machine. It's

1:29:38

not sufficient for anything. I know a

1:29:40

few people who have done it. They're

1:29:42

like, oh, it's great. All I have

1:29:45

is my iPad and a Bluetooth keyboard

1:29:47

and it's wonderful. And I'm like, no,

1:29:49

it's not. I have some people connecting

1:29:51

their Mac minis to their iPads, though,

1:29:54

and that kind of seems slick. Oh,

1:29:56

that's cool. Why don't you like the

1:29:58

iPad? Like, what's wrong with it? I

1:30:00

just think it's the most superfluous. superfluous

1:30:02

device that's ever been made because everyone

1:30:05

has a phone right and you can

1:30:07

do everything on a phone you can

1:30:09

do on an iPad unless you're an

1:30:11

artist right if you need the pencil

1:30:14

and you need to draw right but

1:30:16

then almost everyone also has a computer

1:30:18

and so it's this weird in-between device

1:30:20

that like you use to it's like

1:30:22

a $1,200 YouTube machine you know like

1:30:25

let's let's be real kid baby zitter

1:30:27

In three years, the iPad 18 Pro

1:30:29

Max Plus Plus plus will actually be

1:30:31

a 10 and a half inch iPad.

1:30:34

Not wrong. I mean, the iPad mini

1:30:36

and like the Max iPhone are pretty,

1:30:38

you can actually put the iPad mini

1:30:40

in your pants pocket. Well, in men's

1:30:42

pants pockets don't exist. But you literally,

1:30:45

like I put the iPad mini. They

1:30:47

don't. Have you like they? No, they

1:30:49

totally don't exist. It's like you could

1:30:51

literally fit an iPad many like in

1:30:54

your in your pants pocket, but I

1:30:56

would say for the vast majority of

1:30:58

people, iPads are a weird thing. I

1:31:00

think you did point out artists, I

1:31:02

think are one thing, but I think

1:31:05

businesses. Like I think the whole replacing

1:31:07

your point of sale terminal with like