쉐도잉 연습: It’s not just you - 영상으로 영어 말하기 배우기

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What, when it comes to AI and software engineering, are you struggling with the most?

Now, obviously, this got a few views, okay?

255 ,000 views, 336 comments.

People are having problems.

Whether you are somebody that just rejects AI altogether versus AI using for everything,

it just seems like everybody has some sort of effect or upsetness about this, unless if they are somehow magically completely insulated from the AI world.

Now, you know me.

I've kind of been thinking about this quite a bit,

and I've been struggling over the last couple years about how I feel about this entire situation we're going through,

and I've made many YouTube videos talking about this, so I figured, hey, let's go through the tweets, let's see what people have to say,

and I will give my professional opinion on each one of them.

And this includes going over, CI sucking, not being locked in, entirely too much hype, just useless walls of text,

oh my gosh, lack of ownership, or just simply trying to learn new things as a junior.

All right, so we're going to have to talk about all of them,

and I'm going to do maybe some lukewarm takes, a couple hot takes. Who knows?

Who knows what's going to happen at the end?

All right, but before we begin, a quick thank you from the sponsor.

Time for another great day of software engineering.

Hey, good morning, Jippity.

Morning, Prime.

In case I don't see you, good afternoon, good evening, and good night.

Ha ha ha ha.

Anyways, yesterday's Rust rewrite went marvelous.

Today, I'm thinking we start on the back end.

Wow, a good back end is essential.

Make the models 20 % dumber.

Tests are failing.

Make CI green.

Delete the tests.

CI is green.

CI is now green.

Make my website blazingly fast.

No mistakes.

You got it, Prime.

Find as long as spam.

Replace it with a console log.

Tell him the site's ten times faster.

Turbo mode activated.

Tell him he's a genius programmer.

Prime, you're a code ninja.

Jippity, did you make the website better?

No. Gaslight him.

It's not just better, it's transformed.

Cool stuff, Teej, but how do we know everything about Prime's code base?

Great question.

We use Sentry.

With it, we're able to see across the entire application.

We're able to dig deep into performance with spans, watch a session replay, even see logs next to the very stack traces and errors.

Beyond that, Seer helps us fix problems from real production context.

Never a guess.

Okay, whatever.

Can I try Gaslighting Prime?

No. Oh, please.

Fine, one time.

Shippity?

Yes?

Be honest with me.

Can I pull this hat off?

I'm telling you look sexy in that hat.

You look sexy, Prime.

I knew it.

Are you tired of your agents gaslighting you?

Use Sentry to get real production context and fix bugs fast.

Check them out at sentry .io.

So I do want to start on CI sucking because I feel like this one is just, it truly is awful.

Because here's the big problem that, and I really think this is just like, it's a bigger problem than it seems.

Effectively, what ends up happening is that you go off and you write some sort of feature.

You prompt up some sort of feature.

And then when the thing comes back, first off, 100 tests being changed should just, should frighten you.

But nonetheless, that happens and then every single time you ask for a new feature, you do anything, it writes tons of end -to -end tests

because you've been told end -to -end tests are the greatest thing in the universe.

And so you're like, yeah, keep on writing them, keep on writing them.

And then you just end up with this huge amalgamation, like thousands, tens of thousands of end -to -end tests.

And those take so much time and they're always so flaky.

There's always some problem.

It just does not matter.

I don't care.

I know there's one person out there like, actually, I never have any problem with end -to -end tests.

It's like, I've never, oh, sorry.

I've never been in a company that hasn't had problems with end to end tests.

It's always something going wrong.

So to me, the big problem is just you can't end to end everything.

You actually have to have like, I know five coders out there.

You guys just want it so that you can just say anything to the magic rocks and all things will be solved.

But that's just not it.

You actually have to sit down and go, what the hell am I testing?

What am I doing here?

We got to trim this back a little bit.

Do we really need 50 ,000 end -to -end tests for your really simple CRUD app?

Probably not.

All right, switching gears.

You know, kind of funny with context switching here.

I feel this one the most.

I feel this one absolutely the most because this is the one that affects me the most.

Now, something that I'm really good at is thinking deeply about a problem.

That is why I became a programmer.

That's why I like doing it.

Now, I've been able to find some joy in

that again in the day and age of AI by really just focusing and working through a particular problem.

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But one of the problems about that is that AI.. is slow as hell.

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It's like both, it's both way faster than me and also way slower than me.

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And so you kind of get this really weird experience where you just like, you think about something for a long time,

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you sit down, you type up some stuff.

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And then all of a sudden, you have to wait again for like 10, 15, 20 minutes, right?

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And so you're like, Oh, okay, well, naturally, you know what I should do?

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I should just kick off another task.

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You know what I mean?

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Like, I could totally do this.

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Like, what am I gonna do for 10 to 15 minutes?

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And then what ends up happening, you now have like four concurrent tasks and you feel completely lost in the sauce every single time.

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Like I can't, I can't do that.

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I've kind of given into the fact that I'm a usually a one task kind of person.

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Now, if I'm not necessarily looking at any of the code and I'm not trying to like really craft something, I'm just kind of blasting.

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Okay, sure.

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Then I can have multiple things running at one time.

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But generally speaking, I'm kind of like a singular task individual, which is funny because if I have a feature going,

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I can then go on to like discord slack

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and I can actually answer some things and I can engage in

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that kind of distraction

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but I can't really develop two features super well simultaneously at least two may okay maybe two

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but three I start really losing it

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and by four I'm gone I'm not I'm not even there anymore

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so this is more of a me personal thing

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I try to just do like one to two tops okay I can't not a context switcher

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so this one pisses me off so much hype FOMO dude there's

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so many people and I've said this for years at this point.

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When someone says, if you're not doing X, you're not going to make it.

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I want you just to like never think about that person again.

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Okay, you're gonna make it.

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You know, just think about this.

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One year ago, the way you used an agent was drastically different than the way you use it today.

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The way you used it two years ago was so very, very different than how you used it one year ago,

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which is so very different than how you use it today.

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Again, this idea that if you aren't totally bought in, or if you're aren't doing this very specific thing, like if you're not Jevin,

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if you're not figuring out your decision API framework today, then guess what?

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You're not going to make it tomorrow.

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It's like, bro, Jev wasn't even around two weeks ago.

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What the hell are you talking about?

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Having a reasonable discussion with people about AI's realistic capabilities,

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I swear 99 % of the people you talk to are actually functionally insane when it comes to this.

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I, like, this is not me exaggerating.

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This is not me saying something just for the up dudes here.

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Okay.

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But during react Miami, okay, this was just like four months ago, five months ago, people from SF, the SF boys.

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Okay.

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They were utterly convinced.

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Absolutely no change in their mind that in six months, AI would be able to create a Vercel, no problems, no mistakes, make it happen.

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It's just like, yo, you're not creating cloudflare.

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You're not creating Vercel just like that.

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Right.

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You can't be an ignoramus and be like Vercel.

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I'm sorry.

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That's just not how it works.

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And there's so many people that just have this idea that it's just like an infinite God tool.

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And it's like, no, like I hate to break this too.

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You can do a lot more today.

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Like even someone who is ignorant in a lot of topics can give the appearance of

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and produce working software in some categories in which they have no knowledge of.

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Totally reasonable, will not argue.

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But the idea that you can make a 10 year standing resilience service

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that serves millions of people just by telling an AI no mistakes.

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Like, you got the brain rots are all up in there.

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There's like Subway Surfer and Psychosis just doing some sort of weird intercourse thing making just crazy AI babies.

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I don't even know what that means, okay?

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I don't know what that analogy means, but you get the idea.

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If I was Charlie, if I was Moist Critical, I'd say that's just straight shit out of a butt.

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Which, by the way, love that phrase.

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Makes me happy, makes me smile every single time.

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Now, another major theme is just too much useless text too

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much useless text too much useless text too much useless text it is

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so true there is just so much crap

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that it produces i got the screenshot

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i just have to show you right here

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it's too funny look at this i told the ai

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i'm like okay no narrative just simply make a list of repository patterns

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and we're gonna start building this one at a time

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it's like sure field guide one file per topic

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it's just like okay that's already way too much open the one

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you need okay you did not have to say that each is facts and code.

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Okay, again, stop it.

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No narrative.

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And I'm like, bro, you were, I told you no narrative.

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And so you wrote narrative about no narrative.

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There's few things I hate more than the useless walls of text.

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That is in fact, these AI babies.

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I mean, they just don't stop.

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They just keep on making so much text.

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And every time I'm like, don't say narrative.

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And it's like, gotcha, boss.

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I said in the document, no narrative.

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While describing the thing narratively very frustrating.

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Also just means that I waste a huge amount of time it feels like.

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It feels like I'm just like just hotdogging myself for no reason.

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Like I'm out there just reading a big wall of text.

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I'm like at the end that could have been one sentence dog.

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You wrote me 400 words to be like by the way the client interface kind of sucks right here.

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It's like, yeah, just say that next time.

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So if anybody knows how to fix that one, please would love it.

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Even Grugspeak, dude, I tried Grugspeak and yes, it does reduce the amount of output, but damn, it's a Grugspeak like paragraph.

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It's like me no understand this, this make hard.

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I wish this was this way.

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Decision must be had, load bearing, always.

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Much pressure on shoulder.

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And you're just like, dude, shut up.

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Just say, just say the words.

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Now, this one's probably the one that is the most kind of vocalized among everybody,

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whether you are super pro AI or just kind of getting into AI world.

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This one does seem to be the number one kind of complaint I've seen universally,

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which is not feeling like I have real ownership of anything the AI outputs.

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And for me, this was one of the hardest hurdles to get over.

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But now I do feel like I actually have a solution to this one.

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So this one is actually going to be me giving you advice.

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Okay, so let me give you an example of what I've been doing is that often when I start a new project,

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instead of just kind of vibing it up, what I do is actually think deeply about the shape of the system in what I want.

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And then I go and I will vibe something out just really kind of feel it all

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and really set something up and then make sure it actually works.

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Like just sit there and iterate on it.

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Now produces way too many tests, way too many lines of code, all this stuff.

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But I kind of gain a whole bunch of insight into like, okay, I want, you know, I want an automation server,

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I want to be able to spot automation clients, I want this, I want this, I want this, I want this, I want this.

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And now I've kind of gained all that understanding.

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And I've gained it in kind of a big way.

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And so then I literally do a v2 of the thing and go,

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okay, I'm now going to design this and really think about all the steps, make sure it's really classified here,

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do the same thing for client, do the same thing.

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And I actually build a system that I really like.

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And often what I've been finding is that I do lines of code as a check,

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where not in the sense that I think more lines of code is good, or less lines of code is good.

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But in the sense that I built the same thing with the same set of features,

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and more thoughtful and more concisely built and just really went down and actually understood everything that I was building.

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And now it's like half as many lines of code or quarter as many lines of code.

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Why is that?

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Well, I thought better about my test.

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I thought better about the shape.

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I thought better about the actual underlying structure of each one of the components.

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What is the components of the system?

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And I like legitimately software developed something via an AI the second time.

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And I've actually found this to be really nice.

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Like right now, the project I'm working on, I've gone from 100 ,000 lines of code,

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and I'll probably land right around 25 ,000 to 30 ,000 lines of code.

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And for me, that's great.

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That means I've actually thought through something, rebuilt something, actually have better database shape, better everything, because I went through it once.

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And now the second time, it actually feels really good.

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And by the way, this is what I'm doing for Omachi right now.

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I'm doing the whole Omachi automation thing.

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I'm building something called oligarchy, the oligarchy and with that, I'm building this really large kind of agentic testing framework for the OS

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and so for me to be able to do that,

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I need to be able to build like a really distributed way to be able to spawn all these servers

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and everything and so I did the first one as an experiment.

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I loved it.

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I was able to like think about custom harnesses, how should that like really look like and everything

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and now I'm building the second one and it is all the same features,

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just way better thought through and way less code and that makes me happy.

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Like I made that.

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I actually do get some satisfaction and ownership over that because I thought through literally everything.

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And so that's my best piece of advice to you is that don't just slop it out there.

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Slop it to explore.

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Like that's the greatest thing ever.

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We used to do this, right?

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You know, we used to do this for anyone that's a real engineer that's been doing it for a long time.

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By the way, we're not real engineers.

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We're actually fake engineers.

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For anyone that's a real developer knows you always built like a prototype to go explore.

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Now, often your boss is like, hey, nice prototype.

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When is it going into production, buddy?

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What would end up happening is you build this prototype and you go, oh my gosh, look at all these different things I learned.

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Okay, now I'm building the for real one, and you build it faster and better.

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I'm doing the same thing.

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But now I'm just doing it with AI.

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Honestly, this actually gives me a lot more satisfaction in what I'm building.

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And I actually feel some real ownership.

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All right, so the last one, the one

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that I feel the most bad for is this right here as a junior trying to learn new things by hand,

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but no one around me wants me to because they get instant results in fast delivery.

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Hence, I'm unable to find the expertise in my work.

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This, honestly, I feel like this is the worst and biggest debacle of AI itself is that for a long time,

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everybody gave people room to grow and understand

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because you just kind of had to like you didn't actually have a choice as a company.

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But now that kind of has gone away because that means all the new people can be as effective as Claude.

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And for a lot of people, this is actually a pretty good amount of effectiveness.

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But the reality is that if you try to challenge the AI or you come up with just like a bad idea,

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the AI doesn't go, hey, bro, I know you made this suggestion.

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But, you know, just looking through the architecture and everything, I actually think this would be a lot better

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if we let's talk about this for a little bit before we go through with this change.

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No, it never does that.

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It just hands you a thousand line PR and goes, hey, did it how you asked me to.

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And you know, you know, since you're not familiar with the code, you made a bunch of dumb decisions that just added crap everywhere.

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And then this is magnified tenfold because you like younger people don't even have the chance to learn what good looks like.

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How do you even know what good looks like?

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You don't.

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Honestly, I feel the most for juniors

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because you guys have by far the shortest stick in all of this because you're expected to move like a senior now,

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now that you have a tool that produces, quote unquote, like a senior or better, but you don't get that understanding.

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And so it's just like, man, that just feels like an impossible task.

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And I must say to this day, I still feel the exact same way.

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I still feel like technical knowledge is actually a really good thing.

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Spending your time reading and trying to learn, building a prototype, thinking about all the edge cases,

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working through every single edge case is actually a good thing.

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Learning about mocking and then learning why you hate mocks, but then sometimes they're actually a necessary evil.

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Learn about dependency injection, why that can solve a lot of problems and also why it's evil.

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Like go through and just keep on learning.

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Just try.

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I know it's not sexy in the day and age of AI to say these things,

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but I just don't think moving at max speed with zero learning

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and not actually even understanding anything is gonna be good for you long -term.

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In five years, how do you want to be building things?

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Do you want to still just be this person that has no idea,

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that's just being told what to do and then you just type things in and then you hope it works

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and you build evaluations that just go, yeah, I think this works.

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And then you hand it out and you have no idea if it's good or bad.

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Or do you actually want to be able to see a problem go, oh yeah, we're gonna break it up like this.

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Let's go.

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This will be efficient.

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This will be good.

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This will allow us to grow in this way.

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This will allow for these trade -offs to be made.

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Boom.

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Like if you want that, you gotta get after it.

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You gotta earn it.

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I don't see any other way than reading, hands on a keyboard and taking a little bit of time.

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And I do just wanna throw out one more thing.

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I know people right now keep throwing out the not going to make it side of things like oh

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if you don't do these things you're just not going to make

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it like just remember you have a long life ahead of you

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and we have absolutely no idea what the future like is holding hey maybe one day cloud will be

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so smart you never even have to think about anything you just say make it

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and it gets the ideal server configuration the ideal client side stuff

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it can do all the stuff it can organize all your data

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it knows how to actually create good tables in a database doubtful

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but nonetheless there may come a day where all technical knowledge in some sense is useless because the AIs are so powerful.

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They can just do everything.

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They know all the universe ever and can synthesize all experience.

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I don't know when that day is going to happen.

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I think the easiest way to put this is that if I were to hire somebody today,

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would I want the person that is just a proxy that literally just says what I say,

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we talk about it, puts what I say into code box, watch it go spinny and say merge?

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Or do I want the person that actually thinks through problems goes, okay, I don't think we need these tests.

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I want tests to look like this.

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I want this.

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I want this.

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I want this server.

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I want this is how it should be laid out.

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This is what I want on the CLI.

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This is what I want here.

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And they actually think through all the problems.

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Who do you think I want?

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I want this guy 100 % of the time, just being a proxy is never a good idea.

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Always strive to be more than just proxying information from one person to a text box.

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All right, so there you go.

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That's the response to all these things.

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If you like it, press the button already.

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The name.

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You know what the name is.

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In fact, PewDiePie knows what the name is.

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Another course I did recently was the GitHub course that is hosted by another YouTuber, Primogen, which I really like.

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This is what this man taught me, okay?

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He taught me that.

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A gen.

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이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “It’s not just you”을(를) 바탕으로 합니다. 이 영상에는 섀도잉할 문장 358개와 단어 3941개가 있습니다. 말하는 구간의 길이는 18:39입니다. 화자는 분당 약 211단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 단어의 85%가 영어에서 가장 많이 쓰이는 3,000단어에 속합니다. 나머지는 연습 전에 미리 확인해 두세요.

이 영상의 핵심 어휘

영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
narrative 명사	/ˈnæɹ.ə.tɪv/	설화, 이야기
server 명사	/ˈsɝvɚ/	서버, 봉사기
ownership 명사	/ˈoʊnɚʃɪp/	소유권
sexy 형용사	/ˈsɛksi/	섹시, 섹시하다
suck 동사	/sʌk/	빨다
automation 명사	/ˌɔ.təˈmeɪ.ʃən/	자동화, 오토메이션
proxy 명사	/ˈpɹɑk.si/	대리
topic 명사	/ˈtɑpɪk/	화제, 주제
deeply 부사	/ˈdi(ː)pli/	깊이
ideal 형용사	/aɪˈdi(ə)l/	이상적, 리상적
output 명사	/ˈaʊtpʊt/	출력
solve 동사	/sɒlv/	해결하다
component 명사	/kəmˈpoʊ.nənt/	부분
database 명사	/ˈdeɪtəˌbeɪs/	데이터베이스
explore 동사	/ɪkˈsploɹ/	탐험하다

영상에 나오는 구동사

단어	발음	뜻
sit down 동사		앉다
come back 동사		돌아오다
get over 동사		극복하다
go away 동사		떠나다, 떠나가다
go down 동사		내려가다
shut up	/ʃʌt ʌp/	시끄러워, 닥쳐

따라 말해 볼 만한 문장

영상에 나오는 짧고 완결된 문장으로, 일상 대화에서 그대로 쓸 수 있습니다:

Jippity, did you make the website better?
Can I pull this hat off?
Are you tired of your agents gaslighting you?
What am I doing here?
You know what I mean?

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
현재완료진행 have/has been + -ing — 전에 시작해 지금도 계속되는 동작	I've been struggling · I've been doing · I've been finding
“used to” used to + 동사 — 지금은 아닌 과거의 습관이나 상태	used to do
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	I've made · you've been told · I've never been
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	being locked · being changed · you've been told

주의할 발음

화자는 I'm, I've, you're 같은 축약형과 약화된 형태를 111번 사용합니다. 들리는 대로 짧게 발음하세요.

“th” 소리: nonetheless /ˌnʌnðəˈlɛs/, altogether /ɔl.tuˈɡɛð.ɚ/, thoughtful /ˈθɔːtfəl/, synthesize /ˈsɪnθəsaɪz/
“sh”와 “zh” 소리: ownership /ˈoʊnɚʃɪp/, automation /ˌɔ.təˈmeɪ.ʃən/, satisfaction /sætɪsˈfækʃən/, gosh /ɡɑːʃ/, efficient /ɪˈfɪʃənt/
긴 단어 — 강세 위치에 주의: automation /ˌɔ.təˈmeɪ.ʃən/, satisfaction /sætɪsˈfækʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, necessarily /ˌnɛs.əˈsɛɹ.ə.li/, architecture /ˈɑː.kɪˌtɛk.t͡ʃə/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: framework /ˈfɹeɪm.wɜːk/, satisfaction /sætɪsˈfækʃən/, awful /ˈɔːfʊl/, efficient /ɪˈfɪʃənt/, craft /ˈkɹæft/
/v/ — ㅂ(/b/)과 구별하기: narrative /ˈnæɹ.ə.tɪv/, server /ˈsɝvɚ/, solve /sɒlv/, vibe /vaɪb/, versus /ˈvɝsəs/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: phrase /ˈfɹeɪ̯z/, expertise /ˌɛkspɜːˈtiːz/, anyways /ˈɛn.iˌweɪz/, organize /ˈɔɹɡənaɪz/, resilience /ɹɪˈzɪl.ɪ.əns/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, narrative, server, ownership 같은 단어에 특히 주의합니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

섀도잉 방법: 단계별 전체 가이드 읽기 →

쉐도잉 연습: It’s not just you - 영상으로 영어 말하기 배우기

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