ABSCHRIFTEnglish

I Was a 10x Engineer. Now I'm a 100x Engineer.

15m 37s3,012 Wörter433 segmentsEnglish

VOLLSTÄNDIGE ABSCHRIFT

0:00

There's a video going viral right now

0:02

about an engineer talking about how they

0:04

were a 10x engineer and then their

0:06

skills overnight thanks to AI somehow

0:09

became totally useless. He's saying that

0:11

the craft is dead and thousands of

0:15

engineers are watching the video nodding

0:17

their heads along and giving into

0:18

fatalism. This is part of a bigger

0:21

trend. This isn't some visionary iconic

0:23

YouTuber with a view of the future. To

0:26

some extent, they're riding the wave

0:27

that's going on on tech, Twitter, and

0:29

Reddit right now, which is AI is taking

0:31

all of our jobs. Things are dark and our

0:33

career doesn't matter anymore. This

0:35

fatalist wave is going to cost thousands

0:39

of tech workers their careers, but not

0:41

because AI is replacing them, because

0:44

they are choosing to believe it is

0:46

replacing them. I'm going to show you

0:47

why this argument is historically

0:50

illiterate. It's actually exclusionary,

0:53

which I have no patience for. And the

0:56

same tools that supposedly made that

0:57

engineer useless have turned me from a

0:59

10x engineer into a 100x engineer. This

1:02

one hit close to my heart because I have

1:04

some personal experience here. I did not

1:06

start my career as a software engineer

1:09

or even a technologist. I started it as

1:11

a composer, if you can believe it. I

1:13

went to school. I'm formally trained in

1:15

classical western music composition. I

1:18

primarily wrote pieces for small chamber

1:20

ensembles. So think cello, violin,

1:23

piano, that sort of thing. Over the

1:25

years, I started to get a little bit

1:27

more interested in how a computer could

1:29

sort of extend some of the sonic worlds

1:32

that I was exploring. And gradually,

1:34

gradually, gradually, as I picked up

1:36

more tools from the computer, the

1:37

computer became my main instrument,

1:39

either through the synthesizer or

1:41

through programming. So I learned a lot

1:43

of these tools as a necessary evil

1:44

initially and then came to love them

1:46

later. is I came to love the craft, the

1:50

ways of putting software together, the

1:52

feel of a good system. I began to

1:54

appreciate those things over time, but

1:56

as a secondary effect of me using the

1:58

computer as a tool of self-expression.

2:00

So, learning APIs, memorizing syntax,

2:02

memorizing le code problems, that was

2:04

never the point for me. It just kind of

2:06

came with the territory. But I got busy.

2:09

I became an engineering leader. I had a

2:11

bunch of one-on- ons. I started doing a

2:13

YouTube channel. I had my first kid. I

2:15

have a second kid on the way and time

2:18

got tight. I didn't have a lot of time

2:20

to work on side projects and I missed

2:22

that. What AI has done has it has

2:24

brought that back for me in a minimal

2:26

amount of time. I'm able to accomplish

2:28

at least 10 times more than I used to be

2:31

able to accomplish while sitting down

2:32

and programming or creating software,

2:35

let's say, at the computer. The computer

2:37

remains a tool of self-expression for

2:39

me, but it is highly more efficient than

2:41

it used to be. And I'll say it even

2:43

though I'm not supposed to. Nobody's

2:45

supposed to say this right now. It's a

2:47

good thing. It's a good thing because

2:49

that's what happens with tools as they

2:51

get better. The first can opener was

2:53

probably not very comfortable on the

2:55

hand. It probably was really thin, hard

2:57

to hold, and now they have those big fat

2:59

handles. They have a little indent for

3:01

the thumb on them. All of the tools in

3:03

your kitchen, go pick one up and look at

3:05

the handle, and I bet it's really nicely

3:07

suited to your hand. But it didn't start

3:08

out that way. It developed towards the

3:10

human. When you get in your car and

3:12

drive, you pro hopefully have power

3:14

steering. Power steering is not in the

3:17

car because it's good for the car or it

3:19

helps you drive better. It helps you

3:21

drive easier. It's because the human

3:24

wanted power steering. It's better for

3:25

the human. So tools adapt to the way

3:28

that humans are over time, not the other

3:30

way around. Everything starts crude and

3:33

then becomes more refined to fit the

3:36

human better. AI is no different. And so

3:38

the loudest people in the AI is making

3:41

me useless wave are interestingly enough

3:44

people without a lot of depthy or

3:47

breathy or even very long experience in

3:50

the tech industry. They're making these

3:52

claims and tens of thousands of people

3:54

are watching these videos and taking

3:55

them as fact. Let's take one example.

3:57

The guy who made the viral video that I

3:59

referenced in my opener, he made an

4:02

application called Standard Notes and it

4:03

got a respectable amount of users,

4:05

300,000 or so. Proton bought the

4:08

company. He left the company a year

4:09

later. Started working on a new project

4:11

called Shape. And even a flag on the

4:15

play there. Proton is chasing him down

4:16

about a cease and desist. He insists

4:18

that he's able to keep working on it.

4:19

Proton says absolutely not. So, he's

4:22

building another micro SAS tool and he's

4:25

making a bunch of videos on how

4:26

engineering is dead. And this doesn't

4:28

sit right with me. He has no fang

4:30

experience, no unicorn startup

4:32

experience, no PhD, no defense tech, no

4:35

obvious research track record, nothing.

4:37

He's created a couple of small SAS

4:39

companies

4:40

and one that's in legal battles. So far

4:43

as I know, he's never managed

4:44

engineering organizations. And I'm not

4:46

saying this to be cruel or to

4:51

just undermine the guy. I think it's

4:53

cool that we have all these different

4:54

perspectives on YouTube, but it's not

4:56

real front and center in the video. And

4:57

I want to make sure that you understand

4:59

when you are watching content like that,

5:01

consider the source and consider that

5:03

you may be looking through a very narrow

5:05

lens that lacks depth and breadth and

5:07

even time experience in the industry.

5:10

You might be falling for logical

5:11

fallacies or you might just be seeing

5:13

things through a very very narrow lens

5:15

of what's going on. I want to offer you

5:17

a different picture today. A lot of the

5:19

argument boils down to memorization was

5:22

my moat and that's exclusionary. If your

5:25

definition of a good engineer is an

5:28

engineer that has successfully memorized

5:30

more APIs, more function names, more

5:32

patterns, more leak code puzzles than

5:35

anyone else, then you have automatically

5:40

cast a value judgment on folks with

5:42

memory impairment, learning differences,

5:45

or are on the spectrum. And I take this

5:47

personally as someone on the spectrum

5:49

and that learns a little bit differently

5:51

than other people. As an example of

5:52

that, I had a pretty low GPA in high

5:55

school and undergrad. The main reason

5:57

for that wasn't because I wasn't sharp

5:59

and couldn't think my way through a

6:00

problem. It was because I couldn't

6:02

memorize stuff. I can't memorize dates.

6:04

I I can't memorize facts and figures.

6:06

It's always been an issue with me. And

6:09

I've come to appreciate it over time as

6:11

something that makes me unique. And I

6:13

actually, you know, love and accept that

6:14

in myself. But once I got to grad school

6:17

and the game became my own research and

6:19

critical thinking over rope

6:20

memorization, I excelled. I got my

6:23

masters. I went right on to my PhD and I

6:25

completed my PhD in a faster time than

6:28

anybody else in my cohort. I was out by

6:30

the time I was 29 with a PhD. It's not

6:32

an anecdote to say I'm brilliant, but

6:34

compare and contrast that with my

6:36

experience in high school and undergrad

6:37

with a low GPA and like just barely

6:40

scraping by to really excelling in grad

6:43

school. It's just a different skill set.

6:44

the game changed from recall to

6:46

reasoning and I could win the reasoning

6:48

game. What people like that are really

6:50

saying is that my unique cognitive

6:53

ability in one domain was my moat and

6:56

I'm really unhappy that now the space is

6:59

more inclusive and other people that may

7:01

have been excluded from that before are

7:03

able to participate. That's essentially

7:04

what they're saying. And as someone

7:06

who's been an engineering leader for a

7:07

long time, if you've ever worked for me,

7:10

you know that I fight tooth and nail for

7:12

meritocracy and representation of

MEHR FREISCHALTEN

Melden Sie sich kostenlos an, um Premium-Funktionen zu nutzen

INTERAKTIVER VIEWER

Sehen Sie sich das Video mit synchronisierten Untertiteln, anpassbarer Überlagerung und voller Wiedergabesteuerung an.

KOSTENLOS ANMELDEN ZUM FREISCHALTEN

KI-ZUSAMMENFASSUNG

Erhalten Sie eine sofortige KI-generierte Zusammenfassung des Videoinhalts, der wichtigsten Punkte und Erkenntnisse.

KOSTENLOS ANMELDEN ZUM FREISCHALTEN

ÜBERSETZEN

Übersetzen Sie das Transkript mit einem Klick in über 100 Sprachen. Download in jedem Format.

KOSTENLOS ANMELDEN ZUM FREISCHALTEN

MIND MAP

Visualisieren Sie das Transkript als interaktive Mind Map. Verstehen Sie die Struktur auf einen Blick.

KOSTENLOS ANMELDEN ZUM FREISCHALTEN

CHAT MIT TRANSKRIPT

Stellen Sie Fragen zum Videoinhalt. Erhalten Sie Antworten von der KI direkt aus dem Transkript.

KOSTENLOS ANMELDEN ZUM FREISCHALTEN

HOLEN SIE MEHR AUS IHREN TRANSKRIPTEN HERAUS

Melden Sie sich kostenlos an und schalten Sie interaktiven Viewer, KI-Zusammenfassungen, Übersetzungen, Mind Maps und mehr frei. Keine Kreditkarte erforderlich.

    I Was a 10x E… - Vollständiges Transkript | YouTubeTranscript.dev